Molecular signatures to assess cancer responsiveness to mitochondria-targeted antioxidants

Abstract

The present invention relates to the use of expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 as a molecular signature to identify individuals with cancer, particularly breast cancer, as likely to respond to treatment with mitochondrial targeted antioxidants.

Description

[Technical field]

[0001] The present invention relates to the field of personalized medicine, in particular to molecular signatures that allow the identification of individuals with cancer who are likely to respond to treatment. [Background technology]

[0002] Breast cancer is the second leading cause of death in women. According to the World Health Organization (WHO), 2.09 million cases were detected in 2018, of which 627,000 died. To date, metastasis remains the main cause of death in breast cancer patients, and despite major clinical advances, there are no effective drugs that can prevent it.

[0003] It has been demonstrated that metastatic cells are metabolically different from other cancer cells. Depending on the cancer type, cancer cell invasion can be promoted by increased glucose and lactate metabolism, increased fatty acid metabolism and / or altered mitochondrial metabolism. For example, increased mitochondrial reactive oxygen species (mtROS) production and downstream activation of the SRC / PYK2 pathway promotes cancer cell migration, invasion and metastasis (Porporato et al., 2014). mtROS-induced metastasis is accompanied by mitochondrial superoxide production, superoxide-mediated activation of SRC kinases that activate downstream parts of the transforming growth factor-β (TGF-β) pathway, and ultimately, activation of the focal adhesion kinase (FAK) family member, PYK2, which remodels the cell cytoskeleton during cancer metastasis (Porporato et al., 2014).

[0004] The role of enhancing reactive oxygen species (ROS) levels in solid tumor metastasis was also demonstrated in cancer stem cells (CSCs). More specifically, ROS signaling was shown to promote CSC self-renewal and enhance epithelial-mesenchymal transition (EMT) and invasiveness of cancer cells. CSCs or tumor-initiating cells (TICs) are a highly tumorigenic subpopulation. These cells play a key role in tumor growth and cancer metastasis due to their quiescent properties as well as their self-renewal and differentiation potential.

[0005] Some antioxidants, such as muscadine grape skin extract (MSKE), have been demonstrated to be effective in reducing ROS levels in prostate cancer models, as well as attenuating cell migration and EMT marker expression (Burton et al., 2014). However, common antioxidants cannot be used in cancer therapy, as they produce variable effects, sometimes promoting tumor growth and interfering with immunity. Preferentially, the use of mitochondrial-targeted antioxidants, such as MitoQ and MitoTEMPO, has proven to be a good strategy to inhibit the migration, invasion and metastatic phenotype of cancer cells (Porporato et al., 2014). Interestingly, MitoQ has successfully passed phase I clinical trials and is currently being tested in phase II and III trials in pathologies other than cancer (see, for example, ClinicalTrials.gov Identifiers: NCT 04267926). SKQ1, which belongs to the SkQ class of mitochondrial-targeted antioxidants, is also currently being tested in clinical trials, albeit for applications other than cancer therapy.

[0006] MitoQ consists of a lipophilic cation (tetraphenylphosphonium [TPP]) linked to an antioxidant moiety (quinone) by a 10-carbon alkyl chain, which can rapidly cross biological membranes and become concentrated up to 100-fold in mitochondria (Murphy and Smith, 2007). It can access the mitochondrial membrane core where it acts as a chain-breaking antioxidant, which can further regenerate MitoQ to its ubiquinol form via reduction by the electron transport chain (ETC) complex II. MitoQ is currently mainly used as a food supplement, but MitoQ has also been tested and proven safe in humans, as its promising protective effects were observed in in vivo experiments in mitochondrial-related diseases such as Parkinson's disease or Alzheimer's disease (NCT00329056, NCT02597023).

[0007] There is a need to provide the state of the art with means to identify individuals with cancer who are likely to respond to treatment with mitochondrially targeted antioxidants, such as MitoQ and SKQ1.

[0008] There is also a need to provide the state of the art with means to identify individuals with metastatic cancer who are likely to respond to treatment with mitochondrially targeted antioxidants, such as MitoQ and SKQ1. [Prior art documents] [Non-patent literature]

[0009] [Non-Patent Document 1] Porporato et al., 2014 [Non-Patent Document 2] Burton et al., 2014 [Non-Patent Document 3] ClinicalTrials.gov Identifiers:NCT04267926 [Non-Patent Document 4] Murphy and Smith, 2007 [Non-Patent Document 5] NCT00329056 [Non-Patent Document 6] NCT02597023 Summary of the Invention

[0010] 1. A method for identifying an individual having cancer, particularly breast cancer, who is susceptible to treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or a functional derivative thereof (e.g., SKQ1), the method comprising: a) assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 in a sample obtained from the individual before and after treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof; and b) comparing the expression levels of at least three biomarkers in a sample obtained after treatment with a mitochondrial targeted antioxidant with their respective reference levels in a sample obtained before treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, A significant variation in the expression levels of at least three biomarkers compared to their respective reference levels represents a molecular signature indicating that an individual with cancer, particularly breast cancer, is likely to respond to treatment with at least one mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0011] In some embodiments, significant variation comprises at least a 1.2-fold variation in expression levels of at least three biomarkers compared to their respective reference levels, and optionally a statistical association of P<0.05. In one embodiment, the statistical association is determined by a Student's t-test, a Mann-Whitney U test, or another suitable statistical test, preferably a Student's t-test.

[0012] In a particular embodiment, the at least three biomarkers include SLC7A11, and / or SERPINE1 and / or PSAT1, preferably SLC7A11, SERPINE1 and PSAT1.

[0013] In some embodiments, the at least three biomarkers include SLC7A11, and / or SERPINE1, and / or PSAT1, and / or PHGDH-1 and / or TXNRD1, preferably SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1.

[0014] In certain embodiments, the biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0015] In some embodiments, assessing the expression levels of the at least three biomarkers is performed at the nucleic acid level, preferably at the RNA level, more preferably at the mRNA level.

[0016] In certain embodiments, the cancer is a metastatic cancer or a cancer prone to metastasis, in particular a metastatic breast cancer or a breast cancer prone to metastasis.

[0017] A further aspect of the present invention relates to the use of expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 as a molecular signature for identifying individuals with cancer, in particular breast cancer, as likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0018] In some embodiments, the molecular signature comprises: - at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1, preferably the biomarkers SLC7A11, SERPINE1 and PSAT1; or - at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1 and / or PHGDH-1 and / or TXNRD1, preferably the biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1; or Biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0019] In certain embodiments, the expression levels of at least three biomarkers are compared to their respective reference levels, and a significant variation in the expression levels of the at least three biomarkers compared to their respective reference levels indicates that the individual with cancer is likely to respond to treatment with at least one mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0020] In some embodiments, the cancer is a metastatic cancer or a cancer prone to metastasis, particularly a metastatic breast cancer or a breast cancer prone to metastasis.

[0021] The present invention also relates to a mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating cancer, in particular breast cancer, in an individual identified by the methods defined herein.

[0022] In another aspect, the present invention relates to a mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating metastasis of cancer, in particular breast cancer, in an individual identified by the methods defined herein.

[0023] The present invention further relates to a mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating cancer recurrence, in particular breast cancer recurrence, in an individual identified by the methods defined herein, before, simultaneously with or after surgery intended to remove all or part of the tumor.

[0024] In some embodiments, the antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, is further combined with another cancer treatment, preferably selected from the group consisting of chemotherapy, radiation therapy, hormonal therapy, immunotherapy, antiangiogenic therapy, surgery intended to remove all or part of a tumor, in particular a breast tumor, at least one other mitochondrially targeted antioxidant, and any combination thereof.

[0025] Another aspect of the present invention relates to a kit for identifying individuals with cancer, in particular breast cancer, likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, comprising means for determining the expression level of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0026] definition In the present invention, the following terms have the following meanings.

[0027] The term "about" preceding a number includes up to plus or minus 10% of the value of the number. It is to be understood that the value to which the term "about" refers is itself specifically and preferably disclosed.

[0028] "Comprise" is intended to mean "contain," "encompass," and "include." In some embodiments, the term "comprise" also encompasses the term "consist of."

[0029] "Mitochondria-targeted antioxidant" refers to an antioxidant that accumulates inside mitochondria and can scavenge and / or inactivate one or more reactive oxygen species (ROS). Non-limiting examples of mitochondria-targeted antioxidants suitable for carrying out the present invention are disclosed, for example, by Jiang et al. (2020) and Fock and Parnova (2021).

[0030] "Functional derivatives", when referring to the mitochondrial targeted antioxidant according to the present invention, are intended to refer to derivatives of the mitochondrial targeted antioxidant that have a similar structure and share the same biological physiological function. The term "having a similar structure" is intended to mean that the derivative of the mitochondrial targeted antioxidant differs from the reference mitochondrial targeted antioxidant in that it has one or more substituents.

[0031] "Expression level" refers to the synthesis of a significant detectable level of a biomarker of interest at the nucleic acid (RNA) level and / or polypeptide level. By extension, "express" or "expression" also refers to the level itself.

[0032] "Biomarker" refers to a molecule, preferably a DNA sequence, RNA sequence, protein, glycoprotein or lipoprotein, that is expressed or not expressed by a given cell or cell population, in particular a differentially expressed or not differentially expressed molecule, the expression level of which can be measured by a suitable technique (e.g., RT-PCR, RNA sequencing, ELISA, FACS, Western blot, proteomics, immunofluorescence staining, protein activity) to characterize the cell or cell population. In some embodiments, the cell or cell population is derived from an individual's sample, in particular a blood sample or biopsy.

[0033] "Molecular signature" refers to a combination of DNA, RNA, proteins, genetic variants and / or other variables that exhibit differential levels of expression in a particular context and provide an indication of biological behavior relative to the context. Thus, as used herein, a "molecular signature" is indicative of a biological state, a particular prognosis, or a particular response of an individual to a treatment.

[0034] "Metastasis" refers to the process by which cancer cells spread from where the cancer first began (called the "primary cancer") to other parts of the body. In practice, metastasis can be the result of pleural effusion; colonization of lymph nodes or blood vessels; as well as the spread of cancer cells from the primary cancer site / localization to any other site / localization to, for example, but not limited to, the liver, brain, bone, lung, skin, eye, peritoneum and / or peritoneal cavity.

[0035] "Treating" or "treatment" or "palliation" refers to both therapeutic treatment and preventative or preventive measures, the purpose being to prevent or slow down (alleviate) cancer, particularly breast cancer. Those in need of treatment include those who already have cancer, particularly breast cancer, as well as those who are prone to develop cancer or those whose cancer must be prevented. An individual is successfully "treated" with cancer, particularly breast cancer, if, after receiving a therapeutic amount of a mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or their functional derivatives, alone or in combination with another treatment, the individual shows one or more observable and / or measurable reduction or absence of symptoms associated with cancer, particularly breast cancer; reduced morbidity and mortality, and improved quality of life issues. The above parameters for evaluating the successful treatment and improvement of cancer, particularly breast cancer, are easily measurable by routine procedures well known to physicians or authorities.

[0036] "Preventing" refers to averting the occurrence of and / or reducing the likelihood of development of at least one adverse effect or symptom of cancer, particularly breast cancer, and / or a disorder or condition associated with the lack or absence of an organ, tissue or cell function.

[0037] "Therapeutically effective amount" refers to a level or amount of an active agent, particularly a mitochondrial targeted antioxidant, more particularly MitoQ or SKQ1 or a functional derivative thereof, which is intended to (1) delay or prevent the onset of cancer, particularly breast cancer; (2) delay or prevent the recurrence or regression of cancer, particularly breast cancer; (3) slow or stop the progression, progression or worsening of one or more symptoms of cancer, particularly breast cancer; (4) bring about an improvement in the symptoms of cancer, particularly breast cancer; (5) reduce the severity or incidence of cancer, particularly breast cancer; or (6) cure cancer, particularly breast cancer, without causing significant negative or unacceptable adverse side effects to the target. The therapeutically effective amount may be administered prior to the onset of cancer, particularly breast cancer, in the case of prophylactic or preventative treatment. Alternatively or additionally, the therapeutically effective amount may be administered after the onset of cancer, particularly breast cancer, in the case of therapeutic treatment. In one embodiment, the therapeutically effective amount of the composition is an amount effective to reduce at least one symptom of cancer, particularly breast cancer.

[0038] "Pharmaceutically acceptable carrier" refers to a carrier or vehicle that does not produce or produces any acceptable adverse, allergic or other undesirable reactions when administered to an animal individual, preferably a human individual. This includes any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like. For human administration, preparations must meet sterility, pyrogenicity, general safety, quality and purity standards as required by regulatory authorities, such as the Food and Drug Administration (FDA) of the United States or the European Medicines Agency (EMA) of the European Union.

[0039] "Individual" is intended to refer to an animal individual, preferably a mammalian individual, more preferably a human individual. Among non-human mammalian individuals of interest, there may be mentioned, but are not limited to, pets such as dogs, cats, guinea pigs; economically important animals such as cows, sheep, goats, horses, monkeys, etc. In one embodiment, the individual may be a "patient", i.e. a warm-blooded animal, more preferably a human, waiting to receive or receiving medical care, or has been / is / will be the subject of medical care, or is being monitored for the development of a disease, disorder, or condition. In one embodiment, the individual is an adult (e.g., a human subject over 18 years of age). In another embodiment, the individual is a child (e.g., a human subject under 18 years of age). In one embodiment, the individual is a male. In another embodiment, the individual is a female. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0040] We have identified a set of specific biomarkers that are differentially expressed in tumors when individuals with breast cancer are treated with the mitochondrial-targeted antioxidant MitoQ and the MitoQ analog SKQ1. By determining a molecular signature based on these biomarkers, it is possible to identify individuals with breast cancer who are likely to respond positively to treatment.

[0041] The present invention relates to a method for identifying individuals with cancer, in particular breast cancer, who are likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, the method comprising: a) assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 in a sample obtained from the individual before and after treatment with at least one mitochondrial-targeted antioxidant; and b) comparing the expression levels of at least three biomarkers in a sample obtained after treatment with a mitochondrial-targeted antioxidant to their respective reference levels in a sample obtained before treatment with at least one mitochondrial-targeted antioxidant; A significant variation in the expression levels of at least three biomarkers compared to their respective reference levels represents a molecular signature indicating that an individual with cancer, particularly breast cancer, is likely to respond to treatment with at least one mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0042] As used herein, the term "treatment with at least one mitochondrial targeted antioxidant" includes treatment with one mitochondrial targeted antioxidant, simultaneous treatment with two mitochondrial targeted antioxidants or more (i.e., two mitochondrial targeted antioxidants or more are administered simultaneously), and sequential treatment with two mitochondrial targeted antioxidants or more (i.e., two mitochondrial targeted antioxidants or more are administered sequentially).

[0043] In some embodiments, the method comprises: a) assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1 in a sample obtained from the individual before and after treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof; and b) comparing the expression levels of at least three biomarkers in a sample obtained after treatment with at least one mitochondrial targeted antioxidant with their respective reference levels in a sample obtained before treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, A significant variation in the expression levels of at least three biomarkers compared to their respective reference levels represents a molecular signature indicating that an individual with cancer, particularly breast cancer, is likely to respond to treatment with at least one mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0044] In certain embodiments, the method is performed in vitro or ex vivo.

[0045] In some embodiments, the method of the present invention is for helping to identify individuals with cancer, particularly breast cancer, as being susceptible to treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1.In practice, the method disclosed herein is for predicting the responsiveness of individuals with cancer, particularly breast cancer, to treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or its functional derivatives.

[0046] As used herein, a "mitochondrial targeted antioxidant" refers to an antioxidant that accumulates inside mitochondria and is capable of scavenging and / or inactivating and / or preventing the production of one or more reactive oxygen species (ROS).

[0047] As used herein, "reactive oxygen species" or "ROS" is intended to refer to highly reactive molecules that are derived from oxygen (O2) and can be produced by cells. ROS include, among others, the superoxide ion (O2· - ), hydroxyl radical (HO·) and hydrogen peroxide (H2O2).

[0048] Non-limiting examples of mitochondrial targeted antioxidants suitable for the present invention are disclosed, for example, by Jiang et al. (2020) and Fock and Parnova (2021).

[0049] In some embodiments, the mitochondrial targeted antioxidant is selected from the group consisting of MitoQ, MitoTEMPO, MitoTEMPOL, MitoE, MitoVitE, MitoSOD, MitoSNO, SKQ1, SKQR1, SKQ2, SKQ3, SKQ4, SKQ5, SKQBerb, SKQPalm, C12TPP, melatonin, dimethyl malonate, methylene blue, Mn-porphyrin-oligopeptide conjugate, M40401, SS20, SS31, XJB-5-125, XJB-5-131 and XJB-5-197. In some embodiments, the mitochondrial targeted antioxidant is a SKQ compound.

[0050] In certain embodiments, the mitochondrial targeted antioxidant is selected from the group consisting of MitoQ, SKQ1, and MitoTEMPO. In certain embodiments, the mitochondrial targeted antioxidant is MitoQ or SKQ1. In some embodiments, the mitochondrial targeted antioxidant is MitoQ. In some embodiments, the mitochondrial targeted antioxidant is SKQ1.

[0051] Indeed, certain mitochondrially targeted antioxidants may be substituted with one or more chemical groups to generate functional derivatives thereof. In some embodiments, the one or more chemical groups include O, S, N, F, Cl or Br atoms. In certain embodiments, the one or more chemical groups include C1-C 10 Alkyl groups, C1-C 10 These include aryl groups, carboxyl groups, amine groups, amide groups, sulfide groups, sulfoxide groups, and ester groups, ether groups, and the like.

[0052] As used herein, the phrase "at least three biomarkers" encompasses 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15 biomarkers.

[0053] In some embodiments, step a) comprises assessing the expression levels of 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9. In certain embodiments, step a) comprises assessing the expression levels of the biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0054] In some embodiments, step a) comprises assessing the expression levels of 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, and NUPR1. In certain embodiments, step a) comprises assessing the expression levels of the biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, and NUPR1.

[0055] In practice, SLC7A11 has the Entrez Gene ID No. 23657, and further refers, without limitation, to solute carrier family 7 member 11, XCT, solute carrier family 7 (anionic amino acid transporter light chain, Xc-system) member 11, calcium channel blocker resistance protein CCBR1, amino acid transporter system Xc-, cystine / glutamate transporter, solute carrier family 7 (cationic amino acid transporter, Y+system) member 11, and CCBR1.

[0056] SERPINE1 has Entrez Gene ID No. 5054 and includes, but is not limited to, Serpin family A member 1, alpha-1-antitrypsin, AAT, Serpin peptidase inhibitor clade A (alpha-1 antiproteinase, antitrypsin) member 1, protease inhibitor 1 (anti-elastase) alpha-1-antitrypsin, alpha-1 protease inhibitor, alpha-1-antiproteinase, Serpin Also referred to as A1, alpha 1 AT, A1AT, A1A, PI1, PI, serine (or cysteine) proteinase inhibitor clade A (alpha-1 antiproteinase, antitrypsin) member 1, alpha-1-antitrypsin short transcript variant 1C4, alpha-1-antitrypsin short transcript variant 1C5, Serpin peptidase inhibitor clade A member 1, epididymal secretory sperm-binding protein, alpha-1-antitrypsin Null, PRO2275, and NNIF.

[0057] PSAT1 has the Entrez Gene ID No. 29968, and also refers to, without limitation, phosphoserine aminotransferase 1, PSA, phosphohydroxythreonine aminotransferase, phosphoserine aminotransferase, EC 2.6.1.52, PSAT, endometrial progesterone-induced protein, PSATD, EPIP, and NLS2.

[0058] PHGDH-1 has Entrez Gene ID No. 26227, and is also referred to, without limitation, as phosphoglycerate dehydrogenase-1, Inc-PHGDH-1, NONHSAG002595.2, HSALNG0006501, and Lnc-PHGDH-1.

[0059] TXNRD 1 has Entrez Gene ID No. 7296 and also refers to, but is not limited to, Thioredoxin reductase 1, GRIM-12, Gene Associated With Retinoic And Interferon-Induced Mortality 12 Protein, Cytoplasmic Thioredoxin Reductase 1, Reductase-Like Factor From KM-102, Thioredoxin Reductase TR1, EC 1.8.1.9, TXNR, TR, Testicular Tissue Sperm Binding Protein Li 46a, Thioredoxin Reductase GRIM-12, Oxidoreductase, EC 1.8.1, TRXR1, KDRF, and TR1.

[0060] VIM has the Entrez Gene ID No. 7431 and also refers, without limitation, to vimentin, and epididymal secretory sperm-binding protein.

[0061] SNAI1 has Entrez Gene ID No. 6615, and also refers to, without limitation, Snail family transcriptional repressor 1, SNAH, Snail family zinc finger 1, zinc finger protein SNAI1, protein Snail homolog 1, protein Sna, SLUGH2, SNAIL1, SNAIL, SNA, Snail 1 (Drosophila homolog) zinc finger protein, Snail homolog 1 (Drosophila), Snail 1 zinc finger protein, Snail 1 homolog, Snail homolog 1, and DJ710H13.1.

[0062] ZEB 1 has Entrez Gene ID No. 6935, and also refers to, but is not limited to, zinc finger E-box binding homeobox 1, AREB6, transcription factor 8 (represses interleukin 2 expression), posterior polymorphic corneal dystrophy 3, negative regulator of IL2, FECD6, TCF8, BZP, zinc finger homeodomain enhancer binding protein, delta-crystallin enhancer binding factor 1, NIL-2-A zinc finger protein, transcription factor 8, DELTAEF1, NIL-2-A, ZFHX1A, PPCD3, ZFHEP, TCF-8, and ZEB.

[0063] NANOG has the Entrez Gene ID No. 79923, and also refers, without limitation, to Nanog homeobox, homeobox transcription factor Nanog, homeobox protein NANOG, homeobox transcription factor Nanog-delta 48, FLJ12581, FLJ40451, and HNanog.

[0064] SOX2 has the Entrez Gene ID No. 6657, and also refers to, without limitation, SRY-box transcription factor 2, SRY (sex determining region Y)-box 2, transcription factor SOX-2, SRY-related HMG-box gene 2, transcription factor SOX2, MCOPS3, ANOP3.

[0065] PCK2 has the Entrez Gene ID No. 5106, and also refers, without limitation, to mitochondrial phosphoenolpyruvate carboxykinase 2, PEPCK2, mitochondrial phosphoenolpyruvate carboxykinase [GTP], EC 4.1.1.32, PEPCK-M, PEPCK, epididymal secretory sperm-binding protein, phosphopyruvate carboxylase, and PEP carboxykinase.

[0066] G6PD has the Entrez Gene ID No. 2539 and also refers, without limitation, to glucose-6-phosphate dehydrogenase, glucose-6-phosphate 1-dehydrogenase, EC 1.1.1.49, G6PD1 and epididymal secretory sperm-binding protein.

[0067] ASNS has Entrez Gene ID No. 440, and is also referred to, without limitation, as glutamine hydrolyzing asparagine synthetase, glutamine-dependent asparagine synthetase, EC 6.3.5.4, TS11, TS11 cell cycle control protein, cell cycle control protein TS11, asparagine synthetase, and ASNSD.

[0068] NUPR1 has Entrez Gene ID No. 26471, and is also referred to, without limitation, as nuclear protein 1, transcriptional regulator, Candidate of Metastasis 1, COM1, nuclear protein 1, protein P8, and P8.

[0069] SLC6A9 has the Entrez Gene ID No. 6536 and also refers, without limitation, to solute carrier family 6 member 9, sodium- and chloride-dependent glycine transporter 1, GlyT1.

[0070] In certain embodiments, the biomarkers are human biomarkers.

[0071] In a particular embodiment, the at least three biomarkers include SLC7A11, and / or SERPINE1 and / or PSAT1, preferably SLC7A11, SERPINE1 and PSAT1.

[0072] In some embodiments, the at least three biomarkers include SLC7A11, and / or SERPINE1, and / or PSAT1, and / or PHGDH-1, and / or TXNRD1, preferably SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1.

[0073] In some embodiments, the at least three biomarkers include SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1, and further include VIM, and / or SNAI1, and / or ZEB1, and / or NANOG, and / or SOX2, and / or PCK2, and / or G6PD, and / or ASNS, and / or NUPR1 and / or SLC6A9.

[0074] In some embodiments, the at least three biomarkers include SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1, and further include VIM, and / or SNAI1, and / or ZEB1, and / or NANOG, and / or SOX2, and / or PCK2, and / or G6PD, and / or ASNS, and / or NUPR1.

[0075] In certain embodiments, the biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0076] In certain embodiments, the biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1.

[0077] In practice, step a) comprises the assessment of the expression levels of at least three biomarkers in samples obtained from the individual before and after treatment with at least one mitochondrially targeted antioxidant.

[0078] As used herein, the term "pre-treatment" means that the sample may be collected about 6 hours to about 10 days, preferably about 12 hours to 72 hours, before the start of treatment. Within the scope of the present invention, the term "about 6 hours to about 10 days" includes 6 hours, 12 hours, 24 hours (1 day), 48 hours (2 days), 72 hours (3 days), 4 days, 5 days, 6 days, 7 days, 8 days, 9 days and 10 days. In practice, the start of treatment encompasses the time course preceding the initial uptake of at least one mitochondrial-targeted antioxidant.

[0079] Illustratively, the treatment may consist of administering a dose of the mitochondrial targeted antioxidant in the range of about 50 mg to about 100 mg per day, preferably about 80 mg per day. In practice, the daily dose of the mitochondrial targeted antioxidant may be administered as a single dose or divided into two or more doses. Illustratively, a daily dose of 80 mg / day may be administered as two doses of 40 mg (40 mg, bid). Within the scope of the present invention, the expression "about 50 mg to about 100 mg" includes 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 and 100 mg.

[0080] In practice, the treatment may last from about 5 days to about 30 days, preferably from about 10 days to about 21 days. Within the scope of the present invention, the expression "from about 5 days to about 30 days" includes 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 and 30 days. In some embodiments, the treatment may be or should be performed once, or repeated two, three, four or more times, if applicable. In certain embodiments, the treatment may or should be performed for life.

[0081] As used herein, the term "after treatment" means that samples may be collected about 6 hours to about 10 days, preferably about 12 hours to 72 hours, after the end of treatment. Within the scope of the present invention, the term "about 6 hours to about 10 days" includes 6 hours, 12 hours, 24 hours (1 day), 48 hours (2 days), 72 hours (3 days), 4 days, 5 days, 6 days, 7 days, 8 days, 9 days and 10 days. In practice, the end of treatment encompasses the time course after the first or last intake of the mitochondrial targeted antioxidant. In one embodiment, the treatment consists of a single ingestion (i.e., a single dose) of at least one mitochondrial targeted antioxidant.

[0082] Indeed, assessing the expression levels of the at least three biomarkers may be performed at the nucleic acid level and / or at the protein level.

[0083] In some embodiments, assessing the expression levels of the at least three biomarkers is performed at the nucleic acid level, preferably at the RNA level, more preferably at the mRNA level.

[0084] Exemplarily, the assessment of the expression level of the at least three biomarkers at the mRNA level can be carried out by any suitable method known from the state of the art or an adaptation thereof, such as RT-PCR, RT-qPCR, Northern blot, hybridization techniques, etc. In practice, total RNA can be extracted from the sample by any suitable method known from the state of the art or an adaptation thereof, or by commercially available kits, such as the mammalian RNA isolation kit from BioVision®, the RNeasy Mini Kit from Qiagen®, etc.

[0085] In certain embodiments, the expression levels of the biomarkers can be assessed by PCR or qPCR primers specific for the biomarkers disclosed above.

[0086] By way of illustration, non-limiting examples of suitable PCR or qPCR primers specific for biomarkers according to the invention are shown in Tables 1 and 2 below.

[0087] [Table 1]

[0088] [Table 2]

[0089] In a particular embodiment, the evaluation of the expression level of at least three biomarkers is carried out at the protein level. Illustratively, the evaluation of the expression level of at least three biomarkers at the polypeptide level can be carried out by any suitable method known from the state of the art or an adaptation thereof, such as immunohistochemical staining, immunofluorescence, FACS, ELISA, enzymatic assay, etc.

[0090] In some embodiments, the expression level of a biomarker may be assessed by an antibody that specifically binds to the biomarker.

[0091] By way of illustration, non-limiting examples of suitable antibodies that specifically bind to biomarkers according to the invention are shown in Table 3 below.

[0092] [Table 3]

[0093] Significant variation

[0094] In some embodiments, significant variation comprises at least about a 1.2-fold variation in expression levels of at least three biomarkers compared to their respective reference levels, and optionally a statistical association of P<0.05. In some embodiments, the statistical association is determined by a Student's t-test or a Mann-Whitney U test or any other suitable statistical test, preferably a Student's t-test.

[0095] Within the scope of the present invention, the expression "at least about 1.2 fold" encompasses at least about 1.2, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.6, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, or more.

[0096] In some embodiments, significant variation comprises at least about a 1.5-fold variation in expression levels of at least three biomarkers compared to their respective reference levels, and optionally a statistical association of P<0.05.

[0097] In some embodiments, significant variation comprises at least about a 2.0-fold variation in expression levels of at least three biomarkers compared to their respective reference levels, and optionally a statistical association of P<0.05.

[0098] In practice, the expression levels of the at least three biomarkers following treatment with at least one mitochondrial targeted antioxidant are compared to their respective reference levels following treatment with at least one mitochondrial targeted antioxidant.

[0099] In some embodiments, the variation comprises an increase in the expression level of biomarkers compared to corresponding reference levels.In practice, the expression levels of biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 increase compared to corresponding reference levels.In certain embodiments, the expression levels of biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 are upregulated compared to corresponding reference levels.

[0100] In some embodiments, the variation comprises an increase in the expression level of biomarkers compared to corresponding reference levels.In fact, the expression levels of biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, PCK2, G6PD, ASNS and NUPR1 are increased compared to corresponding reference levels.In certain embodiments, the expression levels of biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, PCK2, G6PD, ASNS and NUPR1 are upregulated compared to corresponding reference levels.

[0101] In some embodiments, the expression level of SLC7A11 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of SLC7A11 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0102] In certain embodiments, the expression level of SERPINE1 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of SERPINE1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0103] In certain embodiments, the expression level of PSAT1 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of PSAT1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0104] In certain embodiments, the expression level of PHGDH-1 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of PHGDH-1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0105] In some embodiments, the expression level of TXNRD1 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the TXNRD1 expression level in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0106] In some embodiments, the expression level of PCK2 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of PCK2 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0107] In certain embodiments, the expression level of G6PD in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of G6PD in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0108] In some embodiments, the expression level of ASNS in a sample obtained from the individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of ASNS in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0109] In certain embodiments, the expression level of NUPR1 in a sample obtained from the individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of NUPR1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0110] In certain embodiments, the expression level of SLC6A9 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is upregulated compared to a reference level represented by the expression level of SLC6A9 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0111] In some embodiments, the fluctuation comprises a decrease in the expression level of biomarkers compared to corresponding reference levels.In fact, the expression levels of biomarkers VIM, SNAI1, ZEB1, NANOG and SOX2 are decreased compared to corresponding reference levels.In certain embodiments, biomarkers VIM, SNAI1, ZEB1, NANOG and SOX2 are downregulated compared to corresponding reference levels.

[0112] In some embodiments, the expression level of VIM in a sample obtained from an individual after treatment with at least one mitochondrial targeted antioxidant is down-regulated compared to a reference level represented by the expression level of VIM in a sample obtained from the individual before treatment with at least one mitochondrial targeted antioxidant.

[0113] In certain embodiments, the expression level of SNAI1 in a sample obtained from an individual after treatment with at least one mitochondrial-targeted antioxidant is down-regulated compared to a reference level represented by the expression level of SNAI1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0114] In some embodiments, the expression level of ZEB1 in a sample obtained from the individual after treatment with at least one mitochondrial-targeted antioxidant is down-regulated compared to a reference level represented by the expression level of ZEB1 in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0115] In certain embodiments, the expression level of NANOG in a sample obtained from the individual after treatment with at least one mitochondrial-targeted antioxidant is down-regulated compared to a reference level represented by the NANOG expression level in a sample obtained from the individual before treatment with at least one mitochondrial-targeted antioxidant.

[0116] In some embodiments, the expression level of SOX2 in a sample obtained from an individual after treatment with at least one mitochondria-targeted antioxidant is down-regulated compared to a reference level represented by the expression level of SOX2 in a sample obtained from the individual before treatment with at least one mitochondria-targeted antioxidant.

[0117] In some embodiments, the sample obtained from an individual is a biological sample. As used herein, the term "biological sample" includes biopsies, blood samples, stool samples, urine samples, saliva samples, and the like.

[0118] In certain embodiments, the sample is a blood sample. In some embodiments, the sample is a biopsy, particularly a biopsy of the organ affected by cancer to be treated, more particularly a biopsy of the breast cancer to be treated. In certain embodiments, the sample comprises cancer cells from the cancer to be treated, more particularly the breast cancer to be treated.

[0119] In certain embodiments, the sample is a fresh sample. In some embodiments, the sample is stored frozen, particularly at a temperature ranging from about -80°C to about 4°C. Within the scope of the present invention, the expression "about -80°C to about 4°C" includes about -80°C, -70°C, -60°C, -50°C, -40°C, -30°C, -20°C, -10°C, -5°C, 0°C, 1°C, 2°C, 3°C and 4°C. In some embodiments, the sample is maintained in paraffin or the like. In some embodiments, the sample is stored in formaldehyde or the like.

[0120] In practice, samples are collected within the bounds of good practice in veterinary or human medicine.

[0121] In some embodiments, the sample is previously collected from an individual. In other words, the method of the present invention does not include a step of obtaining a sample from an individual. In certain embodiments, the method of the present invention is a non-invasive method. In some embodiments, the method of the present invention is performed in vivo or ex vivo.

[0122] In certain embodiments, the individual with cancer is a mammal. In some embodiments, the mammalian individual is a non-human mammalian individual, in particular selected from the group consisting of dogs, cats, rats, mice, horses, cows, sheep, goats, pigs, etc. In some embodiments, the mammalian individual is a human individual. In certain embodiments, the human individual is a female. In some embodiments, the human individual is a male.

[0123] Indeed, an individual with cancer may have previously been diagnosed with cancer by one of skill in the art.

[0124] In some embodiments, the individual with cancer is or may be undergoing treatment for cancer.

[0125] In some embodiments, the cancer is a hematological cancer or a solid cancer.

[0126] In certain embodiments, the cancer is a blood cancer. As used herein, the term "blood cancer" is also referred to as "hematological cancer" and includes any cancer involving uncontrolled proliferation of blood cells, particularly white blood cells. Blood cancers include leukemia, lymphoma (Hodgkin's lymphoma and non-Hodgkin's lymphoma) and myeloma.

[0127] In some embodiments, the cancer is a hematological cancer selected from the group including or consisting of Hodgkin's disease, immunoblastic lymphadenopathy, lymphoma, chronic lymphocytic leukemia, acute leukemia, myeloma, and the like.

[0128] In certain embodiments, the cancer is a solid cancer. As used herein, the term "solid cancer" includes any cancer (also called a "malignant tumor" or "tumor") that forms a discrete tumor mass, as opposed to a blood cancer.

[0129] In some embodiments, the solid cancer comprises or is selected from the group consisting of bladder cancer, bone cancer, brain cancer, breast cancer, cancer of the central nervous system, cervical cancer, cancer of the upper aerodigestive tract, colorectal cancer, endometrial cancer, germ cell cancer, glioblastoma, kidney cancer, laryngeal cancer, liver cancer, lung cancer, nephroblastoma (Wilms' tumor), neuroblastoma, esophageal cancer, osteosarcoma, ovarian cancer, pancreatic cancer, pleural cancer, prostate cancer, retinoblastoma, skin cancer (including melanoma), small intestine cancer, soft tissue sarcoma, gastric cancer, testicular cancer, and thyroid cancer.

[0130] In certain embodiments, the solid cancer is breast cancer. As used herein, the term "breast cancer" refers to histologically or cytologically confirmed cancer of the breast. In some embodiments, the breast cancer is a carcinoma. In some embodiments, the breast cancer is an adenocarcinoma. In some embodiments, the breast cancer is a sarcoma. In some embodiments, the breast cancer is a hormone receptor positive (HR+) breast cancer. In some embodiments, the HR+ breast cancer is an estrogen receptor positive (ER+) breast cancer. In some embodiments, the ER+ breast cancer is a luminal A breast cancer. In some embodiments, the ER+ breast cancer is a luminal B breast cancer.

[0131] In some embodiments, the breast cancer is non-invasive breast cancer, particularly ductal carcinoma in situ or lobular carcinoma in situ. In certain embodiments, the breast cancer is invasive breast cancer, particularly selected from the group including or consisting of invasive ductal carcinoma, invasive lobular carcinoma, Paget's disease of the nipple, inflammatory breast cancer, Phyllodes tumor of the breast, locally advanced breast cancer, and metastatic breast cancer.

[0132] In certain embodiments, the breast cancer is HR+ breast cancer or hormone receptor negative (HR-) breast cancer. In one embodiment, the hormone receptor positive breast cancer is ER+ breast cancer and / or progesterone receptor positive (PR+) breast cancer. In one embodiment, the hormone receptor negative breast cancer is triple negative breast cancer (TNBC).

[0133] In some embodiments, the breast cancer is human epidermal growth factor receptor 2 positive (HER2+) breast cancer. In some embodiments, the breast cancer is human epidermal growth factor receptor 2 negative (HER2-) breast cancer.

[0134] In some embodiments, the breast cancer is a cancer with combined receptor expression, eg, hormone receptor positive and HER2 negative (HR+HER2-).

[0135] In some embodiments, the breast cancer is a Group 1 (luminal A), Group 2 (luminal B), Group 3 (HER2+) or Group 4 (basal-like) cancer. Group 1 includes tumors that are ER+, progesterone receptor positive (PR+) but HER2 negative (HR+HER2-). Group 2 includes tumors that are ER+, PR- and HER2+. Group 3 includes tumors that are ER-, PR- but HER2+. Group 4, also referred to as TNBC, includes tumors that are ER-, PR- and HER2+.

[0136] In some embodiments, the breast cancer is HER2+ breast cancer or TNBC. In some embodiments, the breast cancer is HER2+ breast cancer, preferably HER2+ breast adenocarcinoma. In some embodiments, the breast cancer is TNBC.

[0137] In some embodiments, the tissue type in which breast cancer arises is the milk duct, milk producing lobule, or connective tissue.

[0138] In some embodiments, the breast cancer is metastatic or locally advanced breast cancer. The term "locally advanced breast cancer" refers to cancer that has spread from where it began in the breast to nearby tissues or lymph nodes, but has not spread to other parts of the body.

[0139] In certain embodiments, the cancer is a metastatic cancer or a cancer prone to metastasis, in particular a metastatic breast cancer or a breast cancer prone to metastasis.

[0140] The term "metastatic breast cancer" refers to cancer that has spread from the breast to other parts of the body, such as the bone, liver, lungs, or brain. Metastatic breast cancer is sometimes referred to as stage IV breast cancer. As used herein, the term "cancer susceptible to metastasis" refers to invasive cancers in which cancer cells can detach from the primary tumor and grow in other organs, where they can grow and form secondary tumors, also called metastases.

[0141] In one aspect, the present invention also relates to the use of expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 as a molecular signature for identifying individuals with cancer, in particular breast cancer, as likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0142] In one aspect, the present invention also relates to the use of expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1 as a molecular signature for identifying individuals with cancer, in particular breast cancer, as likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0143] In some embodiments, the molecular signature comprises: a. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1, preferably the biomarkers SLC7A11, SERPINE1 and PSAT1; or b. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1 and / or PHGDH-1 and / or TXNRD1, preferably the biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1; or c. Biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0144] In some embodiments, the molecular signature comprises: a. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1, preferably the biomarkers SLC7A11, SERPINE1 and PSAT1; or b. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1 and / or PHGDH-1 and / or TXNRD1, preferably the biomarkers SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1; or c. Biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1.

[0145] In some embodiments, the use is performed in vitro or ex vivo.

[0146] In certain embodiments, the expression levels of at least three biomarkers are compared to their respective reference levels, and a significant variation in the expression levels of the at least three biomarkers compared to their respective reference levels indicates that the individual with cancer is likely to respond to treatment with at least one mitochondrial-targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0147] In some embodiments, the expression levels of at least three biomarkers are assessed before and after treatment of the individual with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0148] In a particular embodiment, the reference levels are represented by the expression levels of at least three biomarkers assessed before treatment of the individual with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0149] In some embodiments, the cancer is a metastatic cancer or a cancer prone to metastasis, particularly a metastatic breast cancer or a breast cancer prone to metastasis.

[0150] In some embodiments, the present invention further relates to a method for identifying and treating an individual having cancer, particularly breast cancer, susceptible to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, the method comprising: a) assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 in a sample obtained from the individual before and after treatment with at least one mitochondrial-targeted antioxidant; and b) comparing the expression levels of at least three biomarkers in a sample obtained after treatment with the mitochondrial-targeted antioxidant to their respective reference levels in a sample obtained before treatment with at least one mitochondrial-targeted antioxidant; c) identifying a patient with cancer, in particular breast cancer, as likely to respond to treatment with at least one mitochondrial-targeted antioxidant if a significant variation in the expression levels of at least three biomarkers compared to their respective reference levels is observed in step b); d) treating an individual susceptible to treatment with at least one mitochondrial targeted antioxidant identified in step c) by administering a therapeutically effective amount of at least one mitochondrial targeted antioxidant.

[0151] In some embodiments, the present invention further relates to a method for identifying and treating an individual having cancer, particularly breast cancer, susceptible to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, the method comprising: a) assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1 in a sample obtained from the individual before and after treatment with at least one mitochondrial-targeted antioxidant; and b) comparing the expression levels of at least three biomarkers in a sample obtained after treatment with at least one mitochondrial-targeted antioxidant with their respective reference levels in a sample obtained before treatment with the mitochondrial-targeted antioxidant; c) identifying a patient with cancer, in particular breast cancer, as likely to respond to treatment with at least one mitochondrial-targeted antioxidant if a significant variation in the expression levels of at least three biomarkers compared to their respective reference levels is observed in step b); d) treating an individual susceptible to treatment with a mitochondrial targeted antioxidant identified in step c) by administering a therapeutically effective amount of at least one mitochondrial targeted antioxidant.

[0152] Another aspect of the present invention relates to a mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating cancer, particularly breast cancer, in an individual identified by a method according to the present invention.Another aspect of the present invention relates to at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating cancer, particularly breast cancer, in an individual identified by a method according to the present invention.

[0153] A further aspect of the present invention relates to the use of at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for preventing and / or treating cancer, in particular breast cancer, in an individual identified by the method according to the present invention.

[0154] One aspect of the present invention relates to a method for preventing and / or treating cancer, in particular breast cancer, in an individual identified by a method according to the present invention, comprising administering a therapeutically effective amount of at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0155] A further aspect of the present invention relates to at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating metastasis of cancer, in particular breast cancer, in an individual identified by a method according to the present invention.

[0156] In some embodiments, at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, is for use in a method for preventing metastasis of cancer, particularly breast cancer, in an individual identified by a method according to the present invention.

[0157] One aspect of the present invention relates to the use of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for preventing and / or treating metastasis of cancer, in particular breast cancer, in an individual identified by the method according to the present invention.

[0158] In some embodiments, the use of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, is for use in preventing metastasis of cancer, particularly breast cancer, in an individual identified by the method according to the present invention.

[0159] Another aspect of the present invention relates to a method for preventing and / or treating metastasis of cancer, particularly breast cancer, in an individual identified by the method according to the present invention, comprising administering a therapeutically effective amount of at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof. In some embodiments, the method is for preventing metastasis of cancer, particularly breast cancer, in an individual identified by the method according to the present invention.

[0160] In one aspect, the present invention relates to at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for use in a method for preventing and / or treating cancer recurrence, in particular breast cancer recurrence, in an individual identified by a method according to the present invention, before, simultaneously with or after surgery intended to remove all or part of the tumor.

[0161] The present invention also relates to the use of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, for preventing and / or treating cancer recurrence, in particular breast cancer recurrence, in an individual identified by the method according to the present invention, before, simultaneously with or after surgery intended to remove all or part of the tumor.

[0162] In one aspect, the present invention relates to a method for use in preventing and / or treating cancer recurrence, in particular breast cancer recurrence, in an individual identified by a method according to the invention, before, simultaneously with or after surgery intended to remove all or part of the tumor, comprising administering a therapeutically effective amount of at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof.

[0163] As used herein, the term "recurrence" (also called "relapse") is intended to refer to the process by which cancer is discovered after treatment and after a period during which the cancer was not detected.

[0164] In some embodiments, at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, may be formulated as a pharmaceutical composition.

[0165] In a particular embodiment, the pharmaceutical composition is to be administered to an individual with a cancer, particularly breast cancer, identified by the methods according to the invention.

[0166] A further aspect of the present invention relates to a pharmaceutical composition for use in a method for preventing and / or treating cancer, in particular breast cancer, in an individual identified by a method according to the present invention, comprising (i) at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, and (ii) a pharma- ceutically acceptable carrier.

[0167] In some embodiments, suitable pharma- ceutically acceptable carriers according to the present invention include any and all conventional solvents, dispersion media, fillers, solid carriers, aqueous solutions, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, etc. In certain embodiments, suitable pharma-ceutically acceptable carriers may include water, saline, phosphate buffered saline, dextrose, glycerol, ethanol, and mixtures thereof. In some embodiments, pharma-ceutically acceptable carriers may contain small amounts of auxiliary substances, such as wetting or emulsifying agents, preservatives or buffers, which improve the shelf life or effectiveness of cells. The preparation and use of pharma-ceutically acceptable carriers are well known in the art.

[0168] In some embodiments, at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or its functional derivative, or pharmaceutical composition can be administered to an individual in need thereof by any suitable route, i.e., by oral administration, topical administration, or parenteral administration, including, for example, by injection, subcutaneous administration, intravenous administration, intraarterial administration, intramuscular administration, intraocular administration, and intraauricular administration.In certain embodiments, at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or its functional derivative, or pharmaceutical composition can be administered to an individual in need thereof by oral administration.

[0169] In some embodiments, administration of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, or a pharmaceutical composition by injection may be performed directly into the target tissue of interest, particularly to avoid diffusion of the mitochondrial targeted antioxidant.

[0170] Within the scope of the present invention, the therapeutically effective amount of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or its functional derivatives to be administered can be determined by a physician or authorized practitioner and can be appropriately adjusted within the time course of treatment.

[0171] In certain embodiments, the therapeutically effective amount administered may depend on a variety of parameters, including the material selected for administration, whether the administration is a single dose or multiple doses, and individual parameters including age, physical condition, size, weight, sex, and the severity of the cancer being treated.

[0172] In certain embodiments, the therapeutically effective amount of at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, may range from about 0.001 mg to about 3,000 mg per dosage unit, preferably from about 0.05 mg to about 100 mg per dosage unit.

[0173] Within the scope of the present invention, the expression "about 0.001 mg to about 3,000 mg" means a range of about 0.001 mg to about 0.002 mg, 0.003 mg, 0.004 mg, 0.005 mg, 0.006 mg, 0.007 mg, 0.008 mg, 0.009 mg, 0.01 mg, 0.02 mg, 0.03 mg, 0.04 mg, 0.05 mg, 0.06 mg, 0.07 mg, 0.08 mg, 0.09 mg, 0.1 mg , 0.2mg, 0.3mg, 0.4mg, 0.5mg, 0.6mg, 0.7mg, 0.8mg, 0.9mg, 1mg, 2mg, 3mg, 4mg, 5mg, 6mg, 7mg, 8mg, 9mg, 10mg, 20 mg, 30mg, 40mg, 50mg, 60mg, 70mg, 80mg, 90mg, 100mg, 150mg, 200mg, 250mg, 300mg, 350mg, 400mg, 450mg, 500mg, 5 50mg, 600mg, 650mg, 700mg, 750mg, 800mg, 850mg, 900mg, 950mg, 1,000mg, 1,100mg, 1,150mg, 1,200mg, 1,250mg , 1,300mg, 1,350mg, 1,400mg, 1,450mg, 1,500mg, 1,550mg, 1,600mg, 1,650mg, 1,700mg, 1,750mg, 1,800mg, 1,85 Includes 0mg, 1,900mg, 1,950mg, 2,000mg, 2,100mg, 2,150mg, 2,200mg, 2,250mg, 2,300mg, 2,350mg, 2,400mg, 2,450mg, 2,500mg, 2,550mg, 2,600mg, 2,650mg, 2,700mg, 2,750mg, 2,800mg, 2,850mg, 2,900mg, 2,950mg and 3,000mg.

[0174] In certain embodiments, at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, may be at a dosage level sufficient to deliver about 0.001 mg / kg to about 100 mg / kg, about 0.01 mg / kg to about 50 mg / kg, preferably about 0.1 mg / kg to about 40 mg / kg, preferably about 0.5 mg / kg to about 30 mg / kg, about 0.01 mg / kg to about 10 mg / kg, about 0.1 mg / kg to about 10 mg / kg, more preferably about 1 mg / kg to about 25 mg / kg of subject body weight per day. Within the scope of the present invention, the expression "about 0.001 mg / kg to about 100 mg / kg" means about 0.001 mg / kg, 0.002 mg / kg, 0.003 mg / kg, 0.004 mg / kg, 0.005 mg / kg, 0.006 mg / kg, 0.007 mg / kg, 0.008 mg / kg, 0.009 mg / kg, 0.01 mg / kg, 0.02 mg / kg, 0.03 mg / kg, 0.04 mg / kg, 0.05 mg / kg, 0.06 mg / kg, 0.07 mg / kg, 0.08 mg / kg, 0.09 mg / kg, Includes 0.1mg / kg, 0.2mg / kg, 0.3mg / kg, 0.4mg / kg, 0.5mg / kg, 0.6mg / kg, 0.7mg / kg, 0.8mg / kg, 0.9mg / kg, 1mg / kg, 2mg / kg, 3mg / kg, 4mg / kg, 5mg / kg, 6mg / kg, 7mg / kg, 8mg / kg, 9mg / kg, 10mg / kg, 20mg / kg, 30mg / kg, 40mg / kg, 50mg / kg, 60mg / kg, 70mg / kg, 80mg / kg, 90mg / kg and 100mg / kg.

[0175] In some embodiments, at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, is further combined with another cancer treatment, preferably selected from the group consisting of chemotherapy, radiation therapy, hormonal therapy, immunotherapy, antiangiogenic therapy, surgery intended to remove all or part of a tumor, in particular a breast tumor, and another mitochondrial targeted antioxidant, and any combination thereof.

[0176] As used herein, the term "chemotherapy" refers to drug treatment that uses chemicals to kill rapidly growing cells, especially cancer cells.

[0177] Non-limiting examples of chemotherapeutic agents include acalabrutinib, alectinib, alemtuzumab, anastrozole, avapritinib, avelumab, belinostat, bevacizumab, bleomycin, blinatumomab, bosutinib, brigatinib, carboplatin, carmustine, cetuximab, chlorambucil, cisplatin, copanlisib, cytarabine, daunorubicin, decitabine, dexamethasone, docetaxel, doxorubicin, encorafenib, epirubicin, erdafitinib, etoposide, and everolimus. , exemestane, fludarabine, 5-fluorouracil (5-FU), gemcitabine, ifosfamide, imatinib mesylate, leuprolide, lomustine, mechlorethamine, melphalan, methotrexate, mitomycin, nelabine, paclitaxel, pamidronate, panobinostat, pralatrexate, prednisolone, ofatumumab, rituximab, temozolomide, topotecan, tositumomab, trastuzumab, vandetanib, vincristine, vorinostat, zanubrutinib, and the like.

[0178] In certain embodiments, the chemotherapeutic agent is selected from the group consisting of doxorubicin, 5-FU, cisplatin, paclitaxel, gemcitabine, epirubicin, and the like.

[0179] In one embodiment, the chemotherapeutic agent is doxorubicin.In one embodiment, the chemotherapeutic agent is cisplatin.

[0180] Without wishing to be bound by theory, the inventors have observed that an antioxidant as defined herein, preferably MitoQ or SKQ1 or a functional derivative thereof, can prevent cancer cell migration and invasion (pro-metastatic properties) that can occur with certain pro-metastatic chemotherapeutic agents, such as anthracycline drugs, in particular doxorubicin.

[0181] As used herein, the term "radiotherapy" refers to treatment that uses radiation to kill cancer cells or reduce the size / volume of a tumor.

[0182] In some embodiments, radiation therapy relies on external beam radiation or internal beam radiation used in the field.

[0183] As used herein, the term "hormonal therapy" refers to therapy that uses drugs to stop or slow the growth of tumors, primarily by blocking the body's ability to produce hormones or by interfering with the effects of hormones on cancer cells.

[0184] Illustrative, non-limiting examples of hormone therapies include luteinizing hormone releasing hormone (LHRH) agonists such as truprolide, goserelin, triptorelin and histrelin; androgen receptor antagonists such as flutamide, enzalutamide, apalutamide, bicalutamide and nilutamide; other androgen blockers such as abiraterone, prednisone and ketoconazole; estrogen receptor modulators such as tamoxifen, toremifene and fulvestrant; drugs that reduce estrogen action such as the aromatase inhibitors letrozole, anastrozole and exemestane; progesterone-like drugs such as megestrol acetate; testosterone-like drugs such as androgens; estrogen-like drugs such as estradiol.

[0185] As used herein, the term "immunotherapy" refers to therapy aimed at inducing and / or enhancing an immune response against specific targets, particularly cancer cells.

[0186] As used herein, examples of immunotherapy include, but are not limited to, vaccination, e.g., prophylactic and therapeutic vaccination; adoptive transfer of immune cells, particularly T cells (such as alpha beta (αβ) T cells or gamma delta T cells) or natural killer (NK) cells; checkpoint inhibitors; checkpoint agonists; and antibodies.

[0187] In some embodiments, the immunotherapy is cancer immunotherapy. As used herein, the term "cancer immunotherapy" refers to immunotherapy used to treat cancer, where the immunotherapy modulates the subject's immune response with the aim of inducing and / or stimulating the subject's immune response against cancer cells. In some embodiments, the cancer immunotherapy comprises or consists of adoptive transfer (ACT) of immune cells, particularly T cells (such as αβ T cells or γδ T cells), NK cells or NK T cells. In some embodiments, the cancer immunotherapy comprises or consists of administration of a checkpoint inhibitor.

[0188] In certain aspects, immunotherapy includes ACT, checkpoint inhibitors, vaccinations, and the like, and combinations thereof.

[0189] As used herein, adoptive transfer of cells or adoptive cell therapy (or ACT) is defined as the transfer, for example, injection, of immune cells into a subject.As cancer treatment, adoptive transfer of immune cells into a subject aims to enhance the subject's immune response against cancer cells.

[0190] In certain embodiments, the transferred immune cells are T cells or natural killer (NK) cells. In some embodiments, the transferred immune cells are T cells, particularly CD8+ T cells, and / or NK cells.

[0191] In one embodiment, the transferred immune cells are T cells, particularly effector T cells. Examples of effector T cells include CD4+ T cells and CD8+ T cells. In one embodiment, the transferred immune cells are αβ T cells. In another embodiment, the transferred immune cells are γδ T cells. In one embodiment, the transferred immune cells are CD4+ T cells, CD8+ T cells, or NKT cells, and preferably, the transferred T cells are CD8+ T cells.

[0192] In a particular embodiment, the transferred immune cells are antigen-specific immune cells.In one embodiment, the transferred immune cells are tumor-specific immune cells, in other words, the transferred immune cells specifically recognize cancer cells or tumor cells through the antigen that is specifically and / or abundantly expressed by cancer cells or tumor cells.In one embodiment, the transferred immune cells are tumor-specific effector T cells, particularly tumor-specific CD8+ effector T cells, more particularly tumor-specific cytotoxic CD8+ T cells; or tumor-specific NK cells.

[0193] Examples of tumor-specific antigens, i.e., antigens that are specifically and / or abundantly expressed by cancer cells, include, but are not limited to, neoantigens (also called new antigens or mutated antigens), 9D7, ART4, β-catenin, BING-4, Bcr-abl, BRCA1 / 2, calcium-activated chloride channel 2, CDK4, CEA (carcinoembryonic antigen), CML66, cyclin B1, CypB, EBV (Epstein-Barr virus)-associated antigens (e.g., LMP-1, LMP-2, EBNA1 and BARF1), EGFRvIII, Ep-CAM, EphA3, fibronectin, Gp100 / pmel17, Her2 / neu, HPV (human papillomavirus) E6, HPV These include E7, hTERT, IDH1, IDH2, immature laminin receptor, MC1R, Melan-A / MART-1, MART-2, mesothelin, MUC1, MUC2, MUM-1, MUM-2, MUM-3, NY-ESO-1 / LAGE-2, p53, PRAME, prostate specific antigen (PSA), PSMA (prostate specific membrane antigen), Ras, SAP-1, SART-I, SART-2, SART-3, SSX-2, survivin, TAG-72, telomerase, TGF-βRII, TRP-1 / -2, tyrosinase, WT1, antigens of the BAGE family, antigens of the CAGE family, antigens of the GAGE ​​family, antigens of the MAGE family, antigens of the SAGE family, and antigens of the XAGE family.

[0194] As used herein, neoantigens (also called new antigens or mutant antigens) correspond to antigens derived from proteins that are affected by somatic mutations or gene rearrangements acquired by tumors. Neoantigens can be specific to each individual subject, and therefore can provide targets for developing personalized immunotherapy. Examples of neoantigens include, but are not limited to, for example, the R24C mutant of CDK4, the R24L mutant of CDK4, KRAS mutated at codon 12, mutated p53, the V600E mutant of BRAF, and the R132H mutant of IDH1.

[0195] In one embodiment, the transferred immune cells are specific for a tumor antigen selected from the group including or consisting of the CTA (cancer / testis antigens, also known as MAGE type antigens) class, the neoantigen class and the viral antigen class.

[0196] As used herein, the class of CTAs corresponds to antigens encoded by genes that are expressed in tumor cells but not in normal tissues other than cells of the male germ line.

[0197] Examples of CTAs include, but are not limited to, MAGE-A1, MAGE-A3, MAGE-A4, MAGE-C2, NY-ESO-1, PRAME and SSX-2.

[0198] As used herein, the class of viral antigens corresponds to antigens derived from viral oncogenic proteins. Examples of viral antigens include, but are not limited to, HPV (human papillomavirus)-associated antigens, such as E6 and E7.

[0199] In one embodiment, the transferred immune cells are autologous immune cells, particularly autologous T cells. In another embodiment, the transferred immune cells are allogeneic (or allogeneic) immune cells, particularly allogeneic NK cells.

[0200] For example, autologous T cells can be generated ex vivo, either by expansion of antigen-specific T cells isolated from a subject, or by redirection of the subject's T cells by genetic manipulation.

[0201] In one embodiment, the immune cells to be infused are modified ex vivo, particularly with RNA interference (also known as RNAi), prior to infusion into the subject.

[0202] In some embodiments, the immune cells are selected from the group including T cells, particularly CD8+ T cells and chimeric antigen receptor (CAR) T cells; NK cells, particularly CAR NK cells, etc.; and combinations thereof.

[0203] CAR is a synthetic receptor that consists of a targeting moiety associated with one or more signaling domains in a single fusion molecule or several molecules. In general, the binding moiety of CAR consists of the antigen-binding domain of a single chain antibody (scFv), which comprises the light variable fragment of a monoclonal antibody linked by a flexible linker. Binding moieties based on receptor or ligand domains have also been successfully used. The signaling domain of first generation CARs is usually derived from the cytoplasmic region of CD3 zeta or Fc receptor gamma chain.

[0204] Thus, in one embodiment, the above-described transferred T cells are CAR T cells.The expression of CAR allows T cells to be redirected to selected antigens, such as antigens expressed on the surface of cancer cells.In one embodiment, the transferred CAR T cells recognize tumor-specific antigens.

[0205] In another embodiment, the above-described transferred NK cells are CAR NK cells. The expression of CAR allows the NK cells to be redirected to a selected antigen, for example, an antigen expressed on the surface of cancer cells. In one embodiment, the transferred CAR NK cells recognize tumor-specific antigens.

[0206] Examples of tumor-specific antigens are mentioned hereinabove.

[0207] In one embodiment, said CAR immune cells are autologous CAR immune cells, in particular autologous CAR T cells. In another embodiment, said CAR immune cells are allogeneic (or allogeneic) CAR immune cells, in particular allogeneic CAR NK cells.

[0208] As used herein, checkpoint inhibitor therapy is defined as the administration of at least one checkpoint inhibitor to a subject.

[0209] Checkpoint inhibitors (CPIs, also called immune checkpoint inhibitors or ICIs) block the interaction between inhibitory receptors expressed on T cells and their ligands.As cancer treatment, checkpoint inhibitor therapy aims to prevent the activation of inhibitory receptors expressed on T cells by ligands expressed by tumor cells.Therefore, checkpoint inhibitor therapy aims to prevent the inhibition of T cells present in tumors, i.e., tumor-infiltrating T cells, and thus enhance the subject's immune response to tumor cells.

[0210] Examples of checkpoint inhibitors include, but are not limited to, inhibitors of the cell surface receptor PD-1 (programmed cell death protein 1), also known as CD279 (cluster of differentiation 279); inhibitors of the ligand PD-L1 (programmed death ligand 1), also known as CD274 (cluster of differentiation 274) or B7-H1 (B7 homolog 1); inhibitors of the cell surface receptor CTLA4 or CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), also known as CD152 (cluster of differentiation 152); inhibitors of IDO (indoleamine 2,3-dioxygenase) and inhibitors of TDO (tryptophan 2,3-dioxygenase); LAG-3 (lymphocyte activation inhibitor), also known as CD223 (cluster of differentiation 223) inhibitors of TIM-3 (T cell immunoglobulin and mucin domain containing 3), also known as HAVCR2 (Hepatitis A virus cellular receptor 2) or CD366 (cluster of differentiation 366); inhibitors of TIGIT (T cell immunoreceptor with Ig and ITIM domains), also known as VSIG9 (V-set and immunoglobulin domain containing protein 9) or VSTM3 (V-set and transmembrane domain containing protein 3); inhibitors of BTLA (B and T lymphocyte attenuator), also known as CD272 (cluster of differentiation 272); and inhibitors of CEACAM-1 (carcinoembryonic antigen-related cell adhesion molecule 1), also known as CD66a (cluster of differentiation 66a).

[0211] In one embodiment, the at least one checkpoint inhibitor comprises or is selected from the group consisting of an inhibitor of PD-1, an inhibitor of PD-L1, an inhibitor of CTLA-4, and any mixture thereof.

[0212] In one embodiment, the at least one checkpoint inhibitor is selected from the group including or consisting of pembrolizumab, nivolumab, cemiplimab, tislelizumab, spartalizumab, ABBV-181, JNJ-63723283, BI 754091, MAG012, TSR-042, AGEN2034, avelumab, atezolizumab, durvalumab, LY3300054, ipilimumab, tremelimumab, and any mixture thereof.

[0213] In one embodiment, at least one checkpoint inhibitor is an inhibitor of PD-1, also called anti-PD-1.The inhibitor of PD-1 can include antibodies, particularly monoclonal antibodies, that target PD-1, and non-antibody inhibitors, such as small molecule inhibitors.Examples of inhibitors of PD-1 include, but are not limited to, pembrolizumab, nivolumab, cemiplimab, tislelizumab, spartalizumab, ABBV-181, JNJ-63723283, BI 754091, MAG012, TSR-042 and AGEN2034.

[0214] In one embodiment, at least one checkpoint inhibitor is an inhibitor of PD-L1, also called anti-PD-L1. PD-L1 inhibitors can include antibodies, particularly monoclonal antibodies, that target PD-L1, and non-antibody inhibitors, such as small molecule inhibitors. Examples of PD-L1 inhibitors include, but are not limited to, avelumab, atezolizumab, durvalumab, and LY3300054.

[0215] In one embodiment, at least one checkpoint inhibitor is an inhibitor of CTLA-4, also called anti-CTLA-4.The inhibitor of CTLA-4 can include antibodies, particularly monoclonal antibodies, that target CTLA-4, and non-antibody inhibitors, such as small molecule inhibitors.The examples of inhibitors of CTLA-4 include, but are not limited to, ipilimumab and tremelimumab.

[0216] In one embodiment, at least one checkpoint inhibitor is an inhibitor of IDO or an inhibitor of TDO, also called anti-IDO or anti-TDO, respectively.Examples of inhibitors of IDO include but are not limited to 1-methyl-D-tryptophan (also known as indoximod), epacadostat (also known as INCB24360), navoximide (also known as IDO-IN-7 or GDC-0919), linrodostat (also known as BMS-986205), PF-06840003 (also known as EOS200271), TPST-8844 and LY3381916.

[0217] As used herein, antibody therapy is defined as the administration of at least one antibody to a subject.

[0218] As used herein, "antibody therapy" can include the administration of monoclonal antibodies, polyclonal antibodies, multi-chain antibodies, single-chain antibodies, single domain antibodies, antibody fragments, antibody domains, antibody mimetics, or multispecific antibodies such as bispecific antibodies.

[0219] Examples of antibodies include, but are not limited to, tumor-specific antibodies, particularly tumor-specific monoclonal antibodies (e.g., antibodies that target cell surface markers of cancer or tumor cells, antibodies that target proteins involved in the growth or spread of cancer or tumor cells, etc.).

[0220] Exemplary antibodies include anti-CD137 and anti-OX40 antibodies as described hereinabove; anti-PD-1 antibodies (e.g., pembrolizumab, nivolumab, cemiplimab, tislelizumab, and spartalizumab), anti-PD-L1 antibodies (e.g., avelumab, atezolizumab, and durvalumab) and anti-CTLA-4 antibodies (e.g., ipilimumab and tremelimumab) as described hereinabove; and anti-HER2 antibodies (such as trastuzumab).

[0221] As used herein, the term "vaccination" refers to the use of a preparation that includes a substance or group of substances (i.e., a vaccine) that is intended to induce and / or enhance a targeted immune response against cancer cells in a subject. Preventive vaccination is used to prevent a subject from having a particular disease, or simply to alleviate the symptoms of a disease. Therapeutic vaccination is intended to treat a particular disease, such as cancer, in a subject. For example, a therapeutic anti-cancer vaccine may include one or more tumor-associated antigens and is intended to induce and / or enhance a cell-mediated immune response, particularly a T-cell immune response, directed against cancer cells that express the tumor-associated antigen.

[0222] As used herein, a "therapeutic vaccine" is defined as the administration of at least one tumor-specific antigen (e.g., synthetic long peptide or SLP) or a nucleic acid encoding a tumor-specific antigen; the administration of a recombinant viral vector that selectively enters and / or replicates in tumor cells; the administration of tumor cells; and / or the administration of immune cells (e.g., dendritic cells) that have been engineered to present tumor-specific antigens and elicit an immune response against these antigens.

[0223] As a cancer treatment, therapeutic vaccines aim to boost a subject's immune response against tumor cells.

[0224] Examples of therapeutic vaccines aimed at enhancing a subject's immune response against tumor cells include, but are not limited to, viral vector-based therapeutic vaccines, such as adenoviruses (e.g., oncolytic adenoviruses), vaccinia viruses (e.g., Modified Vaccinia Ankara (MVA)), alphaviruses (e.g., Semliki Forest virus (SFV)), measles viruses, herpes simplex viruses (HSV) and coxsackie viruses; synthetic long peptide (SLP) vaccines; RNA-based vaccines, and dendritic cell vaccines.

[0225] As used herein, the term "anti-angiogenic therapy" refers to therapy that uses anti-angiogenic drugs to inhibit the growth of new blood vessels, particularly blood vessels from tumors.

[0226] Non-limiting examples of antiangiogenic agents include bevacizumab (marketed as Avastin®), lenalidomide, sunitinib, axitinib, cabozantinib, everolimus, lenvatinib mesylate, pazopanib, regorafenib, sorafenib, thalidomide, ramucirumab, vandetanib, and dib-aflibercept.

[0227] In one embodiment, the mitochondrial targeted antioxidant of the present invention is further combined with at least one other mitochondrial targeted antioxidant.

[0228] In certain embodiments, chemotherapy, radiotherapy, hormonal therapy, immunotherapy, antiangiogenic therapy, surgery or other mitochondrial targeted antioxidant should be administered separately or simultaneously with mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or its functional derivative.In certain embodiments, mitochondrial targeted antioxidant of the present invention, preferably MitoQ or SKQ1 or its functional derivative, should be administered separately or simultaneously with at least one other mitochondrial targeted antioxidant.

[0229] One aspect of the present invention relates to a kit for identifying individuals with cancer, in particular breast cancer, likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, comprising means for determining the expression level of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

[0230] One aspect of the present invention relates to a kit for identifying individuals with cancer, in particular breast cancer, likely to respond to treatment with at least one mitochondrially targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, comprising means for determining the expression level of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS and NUPR1.

[0231] In some embodiments, the means for determining the expression level of a biomarker include an antibody that specifically binds to the biomarker and / or PCR or qPCR primers that specifically hybridize to the mRNA of the biomarker.

[0232] Another aspect of the present invention relates to the use of a kit for identifying individuals with cancer, in particular breast cancer, that are likely to respond to treatment with at least one mitochondrial targeted antioxidant, preferably MitoQ or SKQ1 or a functional derivative thereof, the kit comprising means for determining the expression level of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1, and optionally SLC6A9. [Brief description of the drawings]

[0233] [Figure 1A] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by MDA-MB-231 human breast cancer cells. (A-C) MDA-MB-231 human breast cancer cells were treated with ± MitoQ 100 nM for 48 h. (A) Basal, (B) Maximal and (C) ATP-coupled mitochondrial oxygen consumption rates (mtOCR) measured using Seahorse Oximetry (n=17-18). (D) Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=16). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 1B] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by MDA-MB-231 human breast cancer cells. (A-C) MDA-MB-231 human breast cancer cells were treated with ± MitoQ 100 nM for 48 h. (A) Basal, (B) Maximal and (C) ATP-coupled mitochondrial oxygen consumption rates (mtOCR) measured using Seahorse Oximetry (n=17-18). (D) Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=16). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 1C]A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by MDA-MB-231 human breast cancer cells. (A-C) MDA-MB-231 human breast cancer cells were treated with ± MitoQ 100 nM for 48 h. (A) Basal, (B) Maximal and (C) ATP-coupled mitochondrial oxygen consumption rates (mtOCR) measured using Seahorse Oximetry (n=17-18). (D) Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=16). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 1D] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by MDA-MB-231 human breast cancer cells. (A-C) MDA-MB-231 human breast cancer cells were treated with ± MitoQ 100 nM for 48 h. (A) Basal, (B) Maximal and (C) ATP-coupled mitochondrial oxygen consumption rates (mtOCR) measured using Seahorse Oximetry (n=17-18). (D) Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=16). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 1E]A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by MDA-MB-231 human breast cancer cells. (A-C) MDA-MB-231 human breast cancer cells were treated with ± MitoQ 100 nM for 48 h. (A) Basal, (B) Maximal and (C) ATP-coupled mitochondrial oxygen consumption rates (mtOCR) measured using Seahorse Oximetry (n=17-18). (D) Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=16). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test.

[0234] [Figure 2A] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by SkBr3 human breast cancer cells. SkBr3 human breast cancer cells were treated with MitoQ ± 100 nM for 48 h. (A-C) As in Figure 1A-C (n=36-41). (D) As in Figure 1D (n=16). (E) As in Figure 1E (n=6). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 2B] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by SkBr3 human breast cancer cells. SkBr3 human breast cancer cells were treated with MitoQ ± 100 nM for 48 h. (A-C) As in Figure 1A-C (n=36-41). (D) As in Figure 1D (n=16). (E) As in Figure 1E (n=6). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 2C]A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by SkBr3 human breast cancer cells. SkBr3 human breast cancer cells were treated with MitoQ ± 100 nM for 48 h. (A-C) As in Figure 1A-C (n=36-41). (D) As in Figure 1D (n=16). (E) As in Figure 1E (n=6). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 2D] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by SkBr3 human breast cancer cells. SkBr3 human breast cancer cells were treated with MitoQ ± 100 nM for 48 h. (A-C) As in Figure 1A-C (n=36-41). (D) As in Figure 1D (n=16). (E) As in Figure 1E (n=6). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test. [Figure 2E] A set of graphs showing that MitoQ selectively inhibits mitochondrial superoxide production by SkBr3 human breast cancer cells. SkBr3 human breast cancer cells were treated with MitoQ ± 100 nM for 48 h. (A-C) As in Figure 1A-C (n=36-41). (D) As in Figure 1D (n=16). (E) As in Figure 1E (n=6). All data are shown as mean ± SEM. * P<0.05, *** P<0.001 compared to control; by Student's t-test.

[0235] [Figure 3A] A set of graphs showing that MitoQ has no effect on mitochondrial potential (Δψ) in MCF10A normal breast epithelial cells. (A-C) MCF10A normal breast epithelial cells were treated with ±MitoQ 100 nM for 48 h. (A-C) As in Figure 1A-C (n=19-23). ​​(D) As in Figure 1D (n=8). (E) As in Figure 1E (n=3). All data shown as mean ± SEM. *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 3B] A set of graphs showing that MitoQ has no effect on mitochondrial potential (Δψ) in MCF10A normal breast epithelial cells. (A-C) MCF10A normal breast epithelial cells were treated with ±MitoQ 100 nM for 48 h. (A-C) As in Figure 1A-C (n=19-23). ​​(D) As in Figure 1D (n=8). (E) As in Figure 1E (n=3). All data shown as mean ± SEM. *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 3C] A set of graphs showing that MitoQ has no effect on mitochondrial potential (Δψ) in MCF10A normal breast epithelial cells. (A-C) MCF10A normal breast epithelial cells were treated with ±MitoQ 100 nM for 48 h. (A-C) As in Figure 1A-C (n=19-23). ​​(D) As in Figure 1D (n=8). (E) As in Figure 1E (n=3). All data shown as mean ± SEM. *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 3D] A set of graphs showing that MitoQ has no effect on mitochondrial potential (Δψ) in MCF10A normal breast epithelial cells. (A-C) MCF10A normal breast epithelial cells were treated with ±MitoQ 100 nM for 48 h. (A-C) As in Figure 1A-C (n=19-23). ​​(D) As in Figure 1D (n=8). (E) As in Figure 1E (n=3). All data shown as mean ± SEM. *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 3E] A set of graphs showing that MitoQ has no effect on mitochondrial potential (Δψ) in MCF10A normal breast epithelial cells. (A-C) MCF10A normal breast epithelial cells were treated with ±MitoQ 100 nM for 48 h. (A-C) As in Figure 1A-C (n=19-23). ​​(D) As in Figure 1D (n=8). (E) As in Figure 1E (n=3). All data shown as mean ± SEM. *** P<0.001, ns=not significant compared to control; by Student's t-test.

[0236] [Figure 4A] A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 4B]A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 4C] A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 4D] A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 4E]A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 4F] A set of graphs showing that MitoQ selectively inhibits ATP production by MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were treated with ±100 nM mitoQ for 48 h. (A) Representative Western blots of phospho-Thr172-AMPK (P-T172-AMPK) / total AMPK (n=4). (B) Glucose consumption, (C) lactate production determined using enzymatic assays on a CMA600 analyzer (all n=3). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in MDA-MB-231 cells by flow cytometry using propidium iodide (n=3-4) (10,000 events analyzed per experiment). (F) Direct MDA-MB-231 cell counts on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses of MitoQ (0 nM-500 nM) (n=4). All data are shown as mean ± SEM. *P<0.05, ***P<0.001 compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F).

[0237] [Figure 5A] A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 5B] A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 5C]A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 5D] A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 5E]A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F). [Figure 5F] A set of graphs showing that MitoQ selectively inhibited ATP production by SkBr3 human breast cancer cells. SkBr3 cells were treated for 48 h with ±MitoQ 100 nM. (A) As in Figure 4A (n=10). (B) As in Figure 4B-C (n=3-6). (D) Total ATP cellular content (n=8). (E) Cell cycle analysis in SkBr3 cells by flow cytometry using propidium iodide (right, n=2) (10,000 events analyzed per experiment). (F) As in Figure 4F (n=6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test (A-E) or 2-way ANOVA with Tukey's post-hoc test (F).

[0238] [Figure 6A] FIG. 1 is a set of graphs showing that MitoQ dose-dependently depolarizes mitochondria in human breast cancer cells. Human breast cancer cells were treated with the indicated doses of MitoQ for 48 hours. Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer in MDA-MB-231 (A) and SkBr3 (B) cells (all n=16). All data are shown as mean±SEM. ***P<0.001 compared to control; by 2-way ANOVA with Tukey's post-hoc test. [Figure 6B] FIG. 1 is a set of graphs showing that MitoQ dose-dependently depolarizes mitochondria in human breast cancer cells. Human breast cancer cells were treated with the indicated doses of MitoQ for 48 hours. Mitochondrial potential (Δψ) measured using a JC-10 on a SpectraMax i3 spectrophotometer in MDA-MB-231 (A) and SkBr3 (B) cells (all n=16). All data are shown as mean±SEM. ***P<0.001 compared to control; by 2-way ANOVA with Tukey's post-hoc test.

[0239] [Figure 7A] FIG. 1 is a set of graphs showing that MitoQ induces the glycolytic switch in human breast cancer cells in a dose-dependent manner. Human breast cancer cells were treated with the indicated doses of MitoQ for 48 h. Glucose consumption, lactate production and lactate / glucose ratio were measured in MDA-MB-231 (A) (n=3) and SkBr3 (B) (n=5-6) cells using enzymatic assays on a CMA600 analyzer. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by 2-way ANOVA with Tukey's post-hoc test. [Figure 7B] FIG. 1 is a set of graphs showing that MitoQ induces the glycolytic switch in human breast cancer cells in a dose-dependent manner. Human breast cancer cells were treated with the indicated doses of MitoQ for 48 h. Glucose consumption, lactate production and lactate / glucose ratio were measured in MDA-MB-231 (A) (n=3) and SkBr3 (B) (n=5-6) cells using enzymatic assays on a CMA600 analyzer. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by 2-way ANOVA with Tukey's post-hoc test.

[0240] [Figure 8A]A set of graphs showing that MitoQ partially reverses EMT in human breast cancer cells. MDA-MB-231 cells (A-B) and SkBr3 cells (C-D) were treated with ±500 nM MitoQ for 48 h. (A / C) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in MDA-MB-231 cancer cells (n=6-9) and SkBr3 cells (n=3-9). (B / D) Representative western blots of corresponding proteins with β-actin as a loading control. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 8B] A set of graphs showing that MitoQ partially reverses EMT in human breast cancer cells. MDA-MB-231 cells (A-B) and SkBr3 cells (C-D) were treated with ±500 nM MitoQ for 48 h. (A / C) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in MDA-MB-231 cancer cells (n=6-9) and SkBr3 cells (n=3-9). (B / D) Representative western blots of corresponding proteins with β-actin as a loading control. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 8C]A set of graphs showing that MitoQ partially reverses EMT in human breast cancer cells. MDA-MB-231 cells (A-B) and SkBr3 cells (C-D) were treated with ±500 nM MitoQ for 48 h. (A / C) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in MDA-MB-231 cancer cells (n=6-9) and SkBr3 cells (n=3-9). (B / D) Representative western blots of corresponding proteins with β-actin as a loading control. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 8D] A set of graphs showing that MitoQ partially reverses EMT in human breast cancer cells. MDA-MB-231 cells (A-B) and SkBr3 cells (C-D) were treated with ±500 nM MitoQ for 48 h. (A / C) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in MDA-MB-231 cancer cells (n=6-9) and SkBr3 cells (n=3-9). (B / D) Representative western blots of corresponding proteins with β-actin as a loading control. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test.

[0241] [Figure 9A]A set of graphs showing that MitoQ inhibits in vitro migration and invasion of human breast cancer cells. MDA-MB-231 cells (A / C) and SkBr3 cells (B / D) were treated with MitoQ (100 nM) for 48 h ±. MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=3–8) cancer cell migration in scratch test assays. MDA-MB-231 (C) and SkBr3 (D) cell invasion in Boyden chamber assays. All data are shown as mean ± SEM. *** P<0.001, compared to control; by Student's t-test (C–D) or 2-way ANOVA (A–B). [Figure 9B] A set of graphs showing that MitoQ inhibits in vitro migration and invasion of human breast cancer cells. MDA-MB-231 cells (A / C) and SkBr3 cells (B / D) were treated with MitoQ (100 nM) for 48 h ±. MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=3–8) cancer cell migration in scratch test assays. MDA-MB-231 (C) and SkBr3 (D) cell invasion in Boyden chamber assays. All data are shown as mean ± SEM. *** P<0.001, compared to control; by Student's t-test (C–D) or 2-way ANOVA (A–B). [Figure 9C] A set of graphs showing that MitoQ inhibits in vitro migration and invasion of human breast cancer cells. MDA-MB-231 cells (A / C) and SkBr3 cells (B / D) were treated with MitoQ (100 nM) for 48 h ±. MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=3–8) cancer cell migration in scratch test assays. MDA-MB-231 (C) and SkBr3 (D) cell invasion in Boyden chamber assays. All data are shown as mean ± SEM. *** P<0.001, compared to control; by Student's t-test (C–D) or 2-way ANOVA (A–B). [Figure 9D]A set of graphs showing that MitoQ inhibits in vitro migration and invasion of human breast cancer cells. MDA-MB-231 cells (A / C) and SkBr3 cells (B / D) were treated with MitoQ (100 nM) for 48 h ±. MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=3–8) cancer cell migration in scratch test assays. MDA-MB-231 (C) and SkBr3 (D) cell invasion in Boyden chamber assays. All data are shown as mean ± SEM. *** P<0.001, compared to control; by Student's t-test (C–D) or 2-way ANOVA (A–B).

[0242] [Figure 10A] 1 is a set of graphs showing that MitoQ inhibits breast cancer clonogenicity. Cells were pretreated for 48 h with the indicated doses of mitoQ. (A-B) Clonogenic assays with adherent MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=9) cells. (C) Clonogenic assays on soft agar using MDA-MB-231 and SkBr3 cells (all n=16). All data are shown as mean ± SEM. ** P<0.01, *** P<0.001 compared to control; by Student's t-test (A-B) or 2-way ANOVA (C). [Figure 10B] 1 is a set of graphs showing that MitoQ inhibits breast cancer clonogenicity. Cells were pretreated for 48 h with the indicated doses of mitoQ. (A-B) Clonogenic assays with adherent MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=9) cells. (C) Clonogenic assays on soft agar using MDA-MB-231 and SkBr3 cells (all n=16). All data are shown as mean ± SEM. ** P<0.01, *** P<0.001 compared to control; by Student's t-test (A-B) or 2-way ANOVA (C). [Figure 10C]1 is a set of graphs showing that MitoQ inhibits breast cancer clonogenicity. Cells were pretreated for 48 h with the indicated doses of mitoQ. (A-B) Clonogenic assays with adherent MDA-MB-231 (A) (n=6) and SkBr3 (B) (n=9) cells. (C) Clonogenic assays on soft agar using MDA-MB-231 and SkBr3 cells (all n=16). All data are shown as mean ± SEM. ** P<0.01, *** P<0.001 compared to control; by Student's t-test (A-B) or 2-way ANOVA (C).

[0243] [Figure 11A] FIG. 1 is a set of graphs showing that MitoQ partially suppresses breast cancer stemness. Cells were pretreated with the indicated doses of MitoQ for 48 h. mRNA expression of cancer stem cell markers MYC, POU5F1 / (Oct4), NANOG and SOX2 in (A) MDA-MB-231 spheroids (n=3–7) and (B) SkBr3 spheroids (n=4–6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test. [Figure 11B] FIG. 1 is a set of graphs showing that MitoQ partially suppresses breast cancer stemness. Cells were pretreated with the indicated doses of MitoQ for 48 h. mRNA expression of cancer stem cell markers MYC, POU5F1 / (Oct4), NANOG and SOX2 in (A) MDA-MB-231 spheroids (n=3–7) and (B) SkBr3 spheroids (n=4–6). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns=not significant compared to control; by Student's t-test.

[0244] [Figure 12A]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12B]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12C]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12D]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12E]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12F]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12G]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12H]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12I]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12J]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12K]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12L]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test. [Figure 12M]A set of graphs showing that MitoQ regulates transcription of metabolic genes in human breast cancer cells. (A-M) MDA-MB-231 (left panel) and SkBR3 (right panel) cells were treated with ±500 nM MitoQ for 48 h, after which mRNA transcripts were analyzed using RNAseq. The threshold was |log2 fold change|>1, and P<0.01 for all analyses. (A) EID1 expression (all n=3). (B) PEG10 expression (all n=3). (C) PHGDH-1 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (D) SLC7A11 expression (n=12 for MDA-MB-231, n=9 for SkBR3). (E) SERPINE1 expression (n=10-12 for MDA-MB-231, n=6-9 for SkBR3). (F) FTH1 expression (all n=3). (G) TXNRD1 expression (all n=3). (H) PSAT1 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (I) PCK2 expression (n=12 in MDA-MB-231, n=9 in SkBR3). (J) G6PD expression (all n=3). (K) ASNS expression (n=12 in MDA-MB-231, n=9 in SkBR3). (L) SCL6A9 expression (all n=3). (M) NUPR1 expression (n=3 in MDA-MB-231, n=3–6 in SkBR3). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.001, ns P>0.05 by Student's t-test.

[0245] [Figure 13A] A set of graphs showing that MitoQ inhibits metastatic uptake of triple-negative human breast cancer cells in mice. (A) Experimental protocol for tumor uptake assay, where breast cancer cells were pretreated with ±1 μM MitoQ for 6 h, and then viable cells were injected into the tail vein of female NMRI nude mice. (B) Metastatic uptake in lungs of MDA-MB-231 human breast cancer cells (control group n=18; MitoQ group n=11). All data are shown as mean ± SEM. *P<0.05 compared to vehicle by Mann-Whitney test (B). [Figure 13B]A set of graphs showing that MitoQ inhibits metastatic uptake of triple-negative human breast cancer cells in mice. (A) Experimental protocol for tumor uptake assay, where breast cancer cells were pretreated with ±1 μM MitoQ for 6 h, and then viable cells were injected into the tail vein of female NMRI nude mice. (B) Metastatic uptake in lungs of MDA-MB-231 human breast cancer cells (control group n=18; MitoQ group n=11). All data are shown as mean ± SEM. *P<0.05 compared to vehicle by Mann-Whitney test (B).

[0246] [Figure 14A]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14B]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14C]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14D]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14E]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14F]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14G]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14H]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14I]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14J]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H). [Figure 14K]A set of graphs and photographs showing that MitoQ reduces the pro-metastatic properties of human MDA-MB-436 breast cancer cells in vitro. (A-E) Human MDA-MB-436 breast cancer cells were treated with the indicated doses ± MitoQ for 48 hours. (A) Basal, (B) Maximal and (C) ATP-bound oxygen consumption rates (OCR) were measured using Seahorse oximetry (n=14-16). (D) Mitochondrial potential (Δψ) was measured using a JC-10 on a SpectraMax i3 spectrophotometer (n=8). (E) Mitochondrial superoxide production was measured using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide sensor (n=4). (F) Direct MDA-MB-436 cell counting on a SpectraMax i3 spectrophotometer at the indicated time points after treatment with increasing doses (0-500 nM) of MitoQ (n=7). (G) MDA-MB-436 cells were treated with ±500 nM MitoQ for 48 h and gene expression profiles of VIM, SNAI1, SNAI2, ZEB1 and TWIST were assessed (expressed as fold change). (H) mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), SLUG (SNAI2), ZEB1 and TWIST1 in ±500 nM MitoQ treated cells (n=6-9). (I) Cell migration in scratch assay (n=6). (J) Clonogenic assay on soft agar (n=3). (K) Spheroid formation over a week using cells treated with increasing doses of MitoQ. All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to control; by Student's t-test (A-E,F,I) or two-way ANOVA with Tukey's post-hoc test (E,H).

[0247] [Figure 15A]A set of schemes and graphs showing that MitoQ prevents primary tumor recurrence and metastatic spread of human triple-negative breast cancer in mice. (A) Experimental protocol of spontaneous MDA-MB-231 metastasis after orthotopic injection into the mammary fat pad of female NMRI nude mice. (B-C) Primary tumor growth in mice using the protocol shown in (A) (n=10 per group until the day of surgery; n=7 in vehicle-treated group and n=8 in MitoQ-treated group after surgery). (D) Kaplan-Meier graph showing recurrence-free mouse survival after surgery. All mice were from (B-C) (n=7 in vehicle-treated group and n=8 in MitoQ-treated group). (E) At the end of the protocol shown in (A), mouse lungs were removed, sliced, stained for cytokeratin 19 (CK19), counterstained with hematoxylin and eosin, and analyzed for the presence of metastases and quantification of metastases. Data are from two independent experiments including mice from (B–C) (n=21 in control group, n=19 in MitoQ group). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to vehicle; by two-way ANOVA with Sidak's multiple comparison test post-hoc test (B–C), log-rank (Mantel-Cox) test (D), or Student's t-test (E). [Figure 15B]A set of schemes and graphs showing that MitoQ prevents primary tumor recurrence and metastatic spread of human triple-negative breast cancer in mice. (A) Experimental protocol of spontaneous MDA-MB-231 metastasis after orthotopic injection into the mammary fat pad of female NMRI nude mice. (B-C) Primary tumor growth in mice using the protocol shown in (A) (n=10 per group until the day of surgery; n=7 in vehicle-treated group and n=8 in MitoQ-treated group after surgery). (D) Kaplan-Meier graph showing recurrence-free mouse survival after surgery. All mice were from (B-C) (n=7 in vehicle-treated group and n=8 in MitoQ-treated group). (E) At the end of the protocol shown in (A), mouse lungs were removed, sliced, stained for cytokeratin 19 (CK19), counterstained with hematoxylin and eosin, and analyzed for the presence of metastases and quantification of metastases. Data are from two independent experiments including mice from (B–C) (n=21 in control group, n=19 in MitoQ group). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to vehicle; by two-way ANOVA with Sidak's multiple comparison test post-hoc test (B–C), log-rank (Mantel-Cox) test (D), or Student's t-test (E). [Figure 15C]A set of schemes and graphs showing that MitoQ prevents primary tumor recurrence and metastatic spread of human triple-negative breast cancer in mice. (A) Experimental protocol of spontaneous MDA-MB-231 metastasis after orthotopic injection into the mammary fat pad of female NMRI nude mice. (B-C) Primary tumor growth in mice using the protocol shown in (A) (n=10 per group until the day of surgery; n=7 in vehicle-treated group and n=8 in MitoQ-treated group after surgery). (D) Kaplan-Meier graph showing recurrence-free mouse survival after surgery. All mice were from (B-C) (n=7 in vehicle-treated group and n=8 in MitoQ-treated group). (E) At the end of the protocol shown in (A), mouse lungs were removed, sliced, stained for cytokeratin 19 (CK19), counterstained with hematoxylin and eosin, and analyzed for the presence of metastases and quantification of metastases. Data are from two independent experiments including mice from (B–C) (n=21 in control group, n=19 in MitoQ group). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to vehicle; by two-way ANOVA with Sidak's multiple comparison test post-hoc test (B–C), log-rank (Mantel-Cox) test (D), or Student's t-test (E). [Figure 15D]A set of schemes and graphs showing that MitoQ prevents primary tumor recurrence and metastatic spread of human triple-negative breast cancer in mice. (A) Experimental protocol of spontaneous MDA-MB-231 metastasis after orthotopic injection into the mammary fat pad of female NMRI nude mice. (B-C) Primary tumor growth in mice using the protocol shown in (A) (n=10 per group until the day of surgery; n=7 in vehicle-treated group and n=8 in MitoQ-treated group after surgery). (D) Kaplan-Meier graph showing recurrence-free mouse survival after surgery. All mice were from (B-C) (n=7 in vehicle-treated group and n=8 in MitoQ-treated group). (E) At the end of the protocol shown in (A), mouse lungs were removed, sliced, stained for cytokeratin 19 (CK19), counterstained with hematoxylin and eosin, and analyzed for the presence of metastases and quantification of metastases. Data are from two independent experiments including mice from (B–C) (n=21 in control group, n=19 in MitoQ group). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to vehicle; by two-way ANOVA with Sidak's multiple comparison test post-hoc test (B–C), log-rank (Mantel-Cox) test (D), or Student's t-test (E). [Figure 15E]A set of schemes and graphs showing that MitoQ prevents primary tumor recurrence and metastatic spread of human triple-negative breast cancer in mice. (A) Experimental protocol of spontaneous MDA-MB-231 metastasis after orthotopic injection into the mammary fat pad of female NMRI nude mice. (B-C) Primary tumor growth in mice using the protocol shown in (A) (n=10 per group until the day of surgery; n=7 in vehicle-treated group and n=8 in MitoQ-treated group after surgery). (D) Kaplan-Meier graph showing recurrence-free mouse survival after surgery. All mice were from (B-C) (n=7 in vehicle-treated group and n=8 in MitoQ-treated group). (E) At the end of the protocol shown in (A), mouse lungs were removed, sliced, stained for cytokeratin 19 (CK19), counterstained with hematoxylin and eosin, and analyzed for the presence of metastases and quantification of metastases. Data are from two independent experiments including mice from (B–C) (n=21 in control group, n=19 in MitoQ group). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.001, ns=not significant compared to vehicle; by two-way ANOVA with Sidak's multiple comparison test post-hoc test (B–C), log-rank (Mantel-Cox) test (D), or Student's t-test (E).

[0248] [Figure 16A]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16B] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16C]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16D] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16E]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16F] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16G]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16H] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16I]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16J] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16K]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16L] 1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test. [Figure 16M]1 is a set of graphs showing in vitro validation of a potential mRNA signature of human breast cancer cells responsive to mitoQ. Bulk primary human MDA-MB-231 tumors resected on day +32 with the protocol shown in Figure 16A were analyzed for mRNA expression of (A) EID1 (n=28-30), (B) PEG10 (n=30), (C) PHGDH-1 (n=29), (D) SLC7A11 (n=29-30), (E) SERPINE1 (n=29-30), (F) FTH1 (n=29-30), (G) TXNRD1 (n=30), (H) PSAT1 (n=29-30), (I) G6PD (n=28-30), (J) ASNS (n=29), (K) SLC6A9 (n=30), (L) NUPR1 (n=30) and (M) PCK2 (n=30) using RT-qPCR. All data are presented as mean ± SEM. * P<0.05, *** P<0.001, ns P>0.05 compared with control by Student's t test.

[0249] [Figure 17A]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17B]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17C]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17D]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17E]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17F]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17G]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17H]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17I]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17J]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17K]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3). [Figure 17L]A set of graphs showing that MitoQ does not interfere with conventional chemotherapy used to treat breast cancer. (A-F) MDA-MB-231 human breast cancer cells treated with increasing doses of chemotherapy are counted directly on a SpectraMax i3 spectrophotometer. (A) Cells treated with doxorubicin ± 100 nM mitoQ for 48 hours (n=3). (B) Cells treated with epirubicin ± 100 nM mitoQ for 24 hours (n=3). (C) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 hours (n=3). (D) Cells treated with cisplatin ± 100 nM mitoQ for 48 hours (n=3). (E) Cells treated with paclitaxel ± 100 nM mitoQ for 48 hours (n=3). (F) Cells treated with gemcitabine ± 100 nM mitoQ for 72 hours (n=3). (G-L) Direct counting of SkBr3 human breast cancer cells treated with increasing doses of chemotherapy. (G) Cells treated with doxorubicin ± 100 nM mitoQ for 48 h (n=3). (H) Cells treated with epirubicin ± 100 nM mitoQ for 24 h (n=3). (I) Cells treated with 5-fluorouracil (5-FU) ± 100 nM mitoQ for 48 h (n=3). (J) Cells treated with cisplatin ± 100 nM mitoQ for 48 h (n=3). (K) Cells treated with paclitaxel ± 100 nM mitoQ for 48 h (n=3-4). (L) Cells treated with gemcitabine ± 100 nM mitoQ for 72 h (n=3).

[0250] [Figure 18A]A set of schemes and graphs showing that MitoQ prevents metastatic spread in MMTV-PyMT mice that spontaneously develop metastatic breast cancer. (A) Experimental protocol for MMTV-PyMT mice treatment. Note that all mice were treated with FEC chemotherapy. (B) Total weight of primary tumors collected on the day of sacrifice of MMTV-PyMT mice treated as shown in (A) (n=11–17). (C) Number of surface lung metastases in MMTV-PyMT mice treated as shown in (A) (n=15–21). All data are shown as mean ± SEM. *P<0.05, ns=not significant, compared to vehicle, by Mann-Whitney test (B–C). [Figure 18B] A set of schemes and graphs showing that MitoQ prevents metastatic spread in MMTV-PyMT mice that spontaneously develop metastatic breast cancer. (A) Experimental protocol for MMTV-PyMT mice treatment. Note that all mice were treated with FEC chemotherapy. (B) Total weight of primary tumors collected on the day of sacrifice of MMTV-PyMT mice treated as shown in (A) (n=11–17). (C) Number of surface lung metastases in MMTV-PyMT mice treated as shown in (A) (n=15–21). All data are shown as mean ± SEM. *P<0.05, ns=not significant, compared to vehicle, by Mann-Whitney test (B–C). [Figure 18C] A set of schemes and graphs showing that MitoQ prevents metastatic spread in MMTV-PyMT mice that spontaneously develop metastatic breast cancer. (A) Experimental protocol for MMTV-PyMT mice treatment. Note that all mice were treated with FEC chemotherapy. (B) Total weight of primary tumors collected on the day of sacrifice of MMTV-PyMT mice treated as shown in (A) (n=11–17). (C) Number of surface lung metastases in MMTV-PyMT mice treated as shown in (A) (n=15–21). All data are shown as mean ± SEM. *P<0.05, ns=not significant, compared to vehicle, by Mann-Whitney test (B–C).

[0251] [Figure 19] 18A-B are graphs showing validation of a biomarker signature in MMTV-PyMT mice of MitoQ response in primary breast cancer. Spontaneously developing primary breast tumors in MMTV-PyMT mice were collected at the end of the experiment shown in FIG. 18A. They were analyzed for expression of mouse transcripts of PHGDH-1, SLC7A11, SERPINE1, PSAT1 and TXNRD1 using RT-qPCR (n=24-33). All data are shown as mean±SEM. **P<0.01, ***P<0.001, nsP>0.05 compared to control by Student's t-test.

[0252] [Figure 20A] A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) Human MCF7 breast cancer cells were treated with increasing doses of doxorubicin (DXR) for 24 h, after which oxygen consumption rate (OCR) was measured on a Seahorse XF 96 bioanalyzer. Representative Seahorse OCR traces are shown on the left, and graphs on the right report on mitochondrial and non-mitochondrial OCR normalized by total protein content (n=7). (B-C) MCF7 cells were treated with 0.1 μg / mL of DXR for 24 h, after which glucose uptake and lactate release were measured enzymatically. Data were normalized by total protein content (n=5-6). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.005, ns:P<0.05 compared with control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t test (C). [Figure 20B]A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) Human MCF7 breast cancer cells were treated with increasing doses of doxorubicin (DXR) for 24 h, after which oxygen consumption rate (OCR) was measured on a Seahorse XF 96 bioanalyzer. Representative Seahorse OCR traces are shown on the left, and graphs on the right report on mitochondrial and non-mitochondrial OCR normalized by total protein content (n=7). (B-C) MCF7 cells were treated with 0.1 μg / mL of DXR for 24 h, after which glucose uptake and lactate release were measured enzymatically. Data were normalized by total protein content (n=5-6). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.005, ns:P<0.05 compared with control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t test (C). [Figure 20C] A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) Human MCF7 breast cancer cells were treated with increasing doses of doxorubicin (DXR) for 24 h, after which oxygen consumption rate (OCR) was measured on a Seahorse XF 96 bioanalyzer. Representative Seahorse OCR traces are shown on the left, and graphs on the right report on mitochondrial and non-mitochondrial OCR normalized by total protein content (n=7). (B-C) MCF7 cells were treated with 0.1 μg / mL of DXR for 24 h, after which glucose uptake and lactate release were measured enzymatically. Data were normalized by total protein content (n=5-6). All data are shown as mean ± SEM. *P<0.05, **P<0.01, ***P<0.005, ns:P<0.05 compared with control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t test (C).

[0253] [Figure 21A]A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) As in FIG. 20A, but using mouse 4T1 breast cancer cells (n=7). (B-C) As in FIG. 20B-C, but using 4T1 cells (n=5). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t-test (C). [Figure 21B] A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) As in FIG. 20A, but using mouse 4T1 breast cancer cells (n=7). (B-C) As in FIG. 20B-C, but using 4T1 cells (n=5). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t-test (C). [Figure 21C] A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. (A) As in FIG. 20A, but using mouse 4T1 breast cancer cells (n=7). (B-C) As in FIG. 20B-C, but using 4T1 cells (n=5). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by one-way ANOVA with Dunnett's post-hoc test (A, B) or Student's t-test (C).

[0254] [Figure 22A]A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. Cells were treated with increasing doses of DXR for 24 hours, after which proton leak in the electron transport chain of (A) MCF7 (n=8) and (B) 4T1 (n=5-7) cells was measured with a Seahorse XF 96 bioanalyzer. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by one-way ANOVA with Dunnett's post-hoc test (A, B). [Figure 22B] A set of graphs showing that low doses of doxorubicin induce proton leak and mitochondrial superoxide production in breast cancer cells. Cells were treated with increasing doses of DXR for 24 hours, after which proton leak in the electron transport chain of (A) MCF7 (n=8) and (B) 4T1 (n=5-7) cells was measured with a Seahorse XF 96 bioanalyzer. All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by one-way ANOVA with Dunnett's post-hoc test (A, B).

[0255] [Figure 23A] A set of graphs showing mitochondrial superoxide levels in breast cancer cells after treatment with doxorubicin (DXR). (A) MCF7 (n=5) and (B) 4T1 (n=3) cells were treated with 0.1 μg / mL DXR for 24 h, after which mitochondrial superoxide levels were measured by FACS analysis using the mitochondrially targeted fluorescent probe mitoSOX. Representative graphs on the left show data plotted as population distributions, while graphs on the right show mean fluorescence intensity (MFI) normalized to vehicle-treated cells (control). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by Student's t-test (A, B). [Figure 23B]A set of graphs showing mitochondrial superoxide levels in breast cancer cells after treatment with doxorubicin (DXR). (A) MCF7 (n=5) and (B) 4T1 (n=3) cells were treated with 0.1 μg / mL DXR for 24 h, after which mitochondrial superoxide levels were measured by FACS analysis using the mitochondrially targeted fluorescent probe mitoSOX. Representative graphs on the left show data plotted as population distributions, while graphs on the right show mean fluorescence intensity (MFI) normalized to vehicle-treated cells (control). All data are shown as mean ± SEM. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; by Student's t-test (A, B).

[0256] [Figure 24A] A set of graphs showing that MitoQ inhibits doxorubicin-induced cancer cell migration and invasion. (A) Human MCF7 (n=11–24) and (B) murine 4T1 (n=11–12) breast cancer cells were treated with increasing doses of DXR ± MitoQ 100 nM for 48 h, after which cell viability was determined using the CellTiter-Glo Luminescent Cell Viability assay. (C–E) Cells were pretreated with the indicated amounts of drug for 16 h and allowed to recover for 6 h. (C) Migration of MCF7 (n=6) and (D) 4T1 (n=5–6) towards 0.5% serum after treatment with 0.1 μg / mL of DXR ± MitoQ 100 nM. (E) As in (C-D), but reporting invasion (4T1, n=5–8). All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; # P<0.05, ## P<0.01, ### P<0.005 compared to DXR treatment alone; by 2-way ANOVA (A–B) or 1-way ANOVA with Dunnett's post-hoc test (C–E). [Figure 24B]A set of graphs showing that MitoQ inhibits doxorubicin-induced cancer cell migration and invasion. (A) Human MCF7 (n=11–24) and (B) murine 4T1 (n=11–12) breast cancer cells were treated with increasing doses of DXR ± MitoQ 100 nM for 48 h, after which cell viability was determined using the CellTiter-Glo Luminescent Cell Viability assay. (C–E) Cells were pretreated with the indicated amounts of drug for 16 h and allowed to recover for 6 h. (C) Migration of MCF7 (n=6) and (D) 4T1 (n=5–6) towards 0.5% serum after treatment with 0.1 μg / mL of DXR ± MitoQ 100 nM. (E) As in (C-D), but reporting invasion (4T1, n=5–8). All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; # P<0.05, ## P<0.01, ### P<0.005 compared to DXR treatment alone; by 2-way ANOVA (A–B) or 1-way ANOVA with Dunnett's post-hoc test (C–E). [Figure 24C]A set of graphs showing that MitoQ inhibits doxorubicin-induced cancer cell migration and invasion. (A) Human MCF7 (n=11–24) and (B) murine 4T1 (n=11–12) breast cancer cells were treated with increasing doses of DXR ± MitoQ 100 nM for 48 h, after which cell viability was determined using the CellTiter-Glo Luminescent Cell Viability assay. (C–E) Cells were pretreated with the indicated amounts of drug for 16 h and allowed to recover for 6 h. (C) Migration of MCF7 (n=6) and (D) 4T1 (n=5–6) towards 0.5% serum after treatment with 0.1 μg / mL of DXR ± MitoQ 100 nM. (E) As in (C-D), but reporting invasion (4T1, n=5–8). All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; # P<0.05, ## P<0.01, ### P<0.005 compared to DXR treatment alone; by 2-way ANOVA (A–B) or 1-way ANOVA with Dunnett's post-hoc test (C–E). [Figure 24D]A set of graphs showing that MitoQ inhibits doxorubicin-induced cancer cell migration and invasion. (A) Human MCF7 (n=11–24) and (B) murine 4T1 (n=11–12) breast cancer cells were treated with increasing doses of DXR ± MitoQ 100 nM for 48 h, after which cell viability was determined using the CellTiter-Glo Luminescent Cell Viability assay. (C–E) Cells were pretreated with the indicated amounts of drug for 16 h and allowed to recover for 6 h. (C) Migration of MCF7 (n=6) and (D) 4T1 (n=5–6) towards 0.5% serum after treatment with 0.1 μg / mL of DXR ± MitoQ 100 nM. (E) As in (C-D), but reporting invasion (4T1, n=5–8). All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; # P<0.05, ## P<0.01, ### P<0.005 compared to DXR treatment alone; by 2-way ANOVA (A–B) or 1-way ANOVA with Dunnett's post-hoc test (C–E). [Figure 24E]A set of graphs showing that MitoQ inhibits doxorubicin-induced cancer cell migration and invasion. (A) Human MCF7 (n=11–24) and (B) murine 4T1 (n=11–12) breast cancer cells were treated with increasing doses of DXR ± MitoQ 100 nM for 48 h, after which cell viability was determined using the CellTiter-Glo Luminescent Cell Viability assay. (C–E) Cells were pretreated with the indicated amounts of drug for 16 h and allowed to recover for 6 h. (C) Migration of MCF7 (n=6) and (D) 4T1 (n=5–6) towards 0.5% serum after treatment with 0.1 μg / mL of DXR ± MitoQ 100 nM. (E) As in (C-D), but reporting invasion (4T1, n=5–8). All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; # P<0.05, ## P<0.01, ### P<0.005 compared to DXR treatment alone; by 2-way ANOVA (A–B) or 1-way ANOVA with Dunnett's post-hoc test (C–E).

[0257] [Figure 25A] A set of schemes and graphs showing that mitochondrial superoxide scavenging acts synergistically with doxorubicin to delay breast tumor growth. (A) Scheme showing treatment of mice bearing 4T1. (B) Primary tumor growth rate shown as fold change in volume starting from day 0 (n=12–16 mice / group). (C) Photograph of a representative H&E stained lung section (left). Bar=500 μm. (D) Determination of metastasis positive areas normalized to the total analyzed area from (C) using a Leica SCN400 slide scanner (n=5–30 mice / group). All data are shown as mean ± SEM. * P<0.05, *** P<0.005, ns: P<0.05 compared to control; # P<0.05 compared to DXR alone treatment; by 2-way ANOVA (B) or Kruskal-Wallis test with Dunn's post-hoc test (D). [Figure 25B]A set of schemes and graphs showing that mitochondrial superoxide scavenging acts synergistically with doxorubicin to delay breast tumor growth. (A) Scheme showing treatment of mice bearing 4T1. (B) Primary tumor growth rate shown as fold change in volume starting from day 0 (n=12–16 mice / group). (C) Photograph of a representative H&E stained lung section (left). Bar=500 μm. (D) Determination of metastasis positive areas normalized to the total analyzed area from (C) using a Leica SCN400 slide scanner (n=5–30 mice / group). All data are shown as mean ± SEM. * P<0.05, *** P<0.005, ns: P<0.05 compared to control; # P<0.05 compared to DXR alone treatment; by 2-way ANOVA (B) or Kruskal-Wallis test with Dunn's post-hoc test (D). [Figure 25C] A set of schemes and graphs showing that mitochondrial superoxide scavenging acts synergistically with doxorubicin to delay breast tumor growth. (A) Scheme showing treatment of mice bearing 4T1. (B) Primary tumor growth rate shown as fold change in volume starting from day 0 (n=12–16 mice / group). (C) Photograph of a representative H&E stained lung section (left). Bar=500 μm. (D) Determination of metastasis positive areas normalized to the total analyzed area from (C) using a Leica SCN400 slide scanner (n=5–30 mice / group). All data are shown as mean ± SEM. * P<0.05, *** P<0.005, ns: P<0.05 compared to control; # P<0.05 compared to DXR alone treatment; by 2-way ANOVA (B) or Kruskal-Wallis test with Dunn's post-hoc test (D). [Figure 25D]A set of schemes and graphs showing that mitochondrial superoxide scavenging acts synergistically with doxorubicin to delay breast tumor growth. (A) Scheme showing treatment of mice bearing 4T1. (B) Primary tumor growth rate shown as fold change in volume starting from day 0 (n=12–16 mice / group). (C) Photograph of a representative H&E stained lung section (left). Bar=500 μm. (D) Determination of metastasis positive areas normalized to the total analyzed area from (C) using a Leica SCN400 slide scanner (n=5–30 mice / group). All data are shown as mean ± SEM. * P<0.05, *** P<0.005, ns: P<0.05 compared to control; # P<0.05 compared to DXR alone treatment; by 2-way ANOVA (B) or Kruskal-Wallis test with Dunn's post-hoc test (D).

[0258] [Figure 26A] A set of graphs showing that low doses of cisplatin stimulate mitochondrial superoxide production. (A) Human MDA-MB-231 (n=2-3) and (B) murine 4T1 (n=2-3) breast cancer cells were treated with increasing doses of cisplatin for 48 h, after which mitochondrial superoxide levels were measured by FACS analysis using the mitochondrially targeted fluorescent probe mitoSOX. Representative graphs on the left show data plotted as population distributions, while graphs on the right show mean fluorescence intensity (MFI) normalized to vehicle-treated cells (control). All data are shown as mean ± SEM normalized to control. [Figure 26B]A set of graphs showing that low doses of cisplatin stimulate mitochondrial superoxide production. (A) Human MDA-MB-231 (n=2-3) and (B) murine 4T1 (n=2-3) breast cancer cells were treated with increasing doses of cisplatin for 48 h, after which mitochondrial superoxide levels were measured by FACS analysis using the mitochondrially targeted fluorescent probe mitoSOX. Representative graphs on the left show data plotted as population distributions, while graphs on the right show mean fluorescence intensity (MFI) normalized to vehicle-treated cells (control). All data are shown as mean ± SEM normalized to control.

[0259] [Figure 27A] A set of graphs showing that MitoQ inhibits cisplatin-induced cancer cell migration. (A) Human MDA-MB-231 (n=18-20) and (B) murine 4T1 (n=20) breast cancer cells were treated with increasing doses of cisplatin ± MitoQ 100 nM for 48 h, after which cell viability was determined using the Crystal Violet Cell Viability assay. (C-D) Cells were pretreated with the indicated amounts of drugs for 16 h and allowed to recover for 6 h. Migration of MDA-MB-231 (C, n=6) and 4T1 (D, n=8-18) towards 0.5% serum after treatment with the indicated doses of cisplatin ± MitoQ 100 nM. All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; ### P<0.005 compared to cisplatin 6.23 μM alone; by 2-way ANOVA (A) or 1-way ANOVA with Dunnett's post-hoc test (B). [Figure 27B]A set of graphs showing that MitoQ inhibits cisplatin-induced cancer cell migration. (A) Human MDA-MB-231 (n=18-20) and (B) murine 4T1 (n=20) breast cancer cells were treated with increasing doses of cisplatin ± MitoQ 100 nM for 48 h, after which cell viability was determined using the Crystal Violet Cell Viability assay. (C-D) Cells were pretreated with the indicated amounts of drugs for 16 h and allowed to recover for 6 h. Migration of MDA-MB-231 (C, n=6) and 4T1 (D, n=8-18) towards 0.5% serum after treatment with the indicated doses of cisplatin ± MitoQ 100 nM. All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; ### P<0.005 compared to cisplatin 6.23 μM alone; by 2-way ANOVA (A) or 1-way ANOVA with Dunnett's post-hoc test (B). [Figure 27C] A set of graphs showing that MitoQ inhibits cisplatin-induced cancer cell migration. (A) Human MDA-MB-231 (n=18-20) and (B) murine 4T1 (n=20) breast cancer cells were treated with increasing doses of cisplatin ± MitoQ 100 nM for 48 h, after which cell viability was determined using the Crystal Violet Cell Viability assay. (C-D) Cells were pretreated with the indicated amounts of drugs for 16 h and allowed to recover for 6 h. Migration of MDA-MB-231 (C, n=6) and 4T1 (D, n=8-18) towards 0.5% serum after treatment with the indicated doses of cisplatin ± MitoQ 100 nM. All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; ### P<0.005 compared to cisplatin 6.23 μM alone; by 2-way ANOVA (A) or 1-way ANOVA with Dunnett's post-hoc test (B). [Figure 27D]A set of graphs showing that MitoQ inhibits cisplatin-induced cancer cell migration. (A) Human MDA-MB-231 (n=18-20) and (B) murine 4T1 (n=20) breast cancer cells were treated with increasing doses of cisplatin ± MitoQ 100 nM for 48 h, after which cell viability was determined using the Crystal Violet Cell Viability assay. (C-D) Cells were pretreated with the indicated amounts of drugs for 16 h and allowed to recover for 6 h. Migration of MDA-MB-231 (C, n=6) and 4T1 (D, n=8-18) towards 0.5% serum after treatment with the indicated doses of cisplatin ± MitoQ 100 nM. All data are shown as mean ± SEM normalized to control. * P<0.05, ** P<0.01, *** P<0.005, ns: P<0.05 compared to control; ### P<0.005 compared to cisplatin 6.23 μM alone; by 2-way ANOVA (A) or 1-way ANOVA with Dunnett's post-hoc test (B).

[0260] [Figure 28A]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28B]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28C]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28D]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28E]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28F]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28G]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Fig. 28H]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28I]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28J]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28K]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28L]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28M]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28N]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test. [Figure 28O]A set of graphs showing that SKQ1 regulates EMT-related genes and stemness-related transcription in human breast cancer cells. (AO) MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with SKQ1 ± 500 nM for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (AC) Vimentin (VIM) expression (n=4-6 in MDA-MB-231, n=7 in SkBR3, n=6 in MDA-MB-436). (DF) SNAIL (SNAI1) (n=6 in MDA-MB-231, n=5 in SkBR3, n=6 in MDA-MB-436). (GI) ZEB1 (n=6 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (JL) NANOG (n=5 in MDA-MB-231, n=5-6 in SkBR3, n=5-6 in MDA-MB-436). (MO) SOX2 (n=5 in MDA-MB-231, n=5 in SkBR3, n=5-6 in MDA-MB-436). *P<0.05, **P<0.01, ***P<0.005 compared to control; by Student's t-test.

[0261] [Figure 29A]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29B]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29C]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29D]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29E]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29F]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29G]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Fig. 29H]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29I]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29J]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29K]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29L]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29M]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29N]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 29O]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30A]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30B]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30C]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30D]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30E]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30F]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30G]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30H]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30I]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30J]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30K]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30L]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30M]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30N]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. [Figure 30O]SKQ1 is a set of graphs showing that SkQ1 regulates transcription of metabolic genes in human breast cancer cells. MDA-MB-231 (top panel), SkBR3 (middle panel) and MDA-MB-436 (bottom panel) cells were treated with ±500 nM SKQ1 for 48 h, after which mRNA transcripts were analyzed using RT-qPCR. (29A-29B) PHGDH-1 expression (n=5-6 for MDA-MB-231, n=5-6 for SkBR3, n=3 for MDA-MB-436). (29D-29F) SLC7A11 expression (n=3 for MDA-MB-231, n=6 for SkBR3, n=3 for MDA-MB-436). (29G-29I) SERPINE1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29J-29L) TXNRD1 expression (n=3 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (29M-29O) PSAT1 expression (n=5-6 in MDA-MB-231, n=6 in SkBR3, n=3 in MDA-MB-436). (30A-30C) PCK2 expression (all n=3). (30D-30F) G6PD expression (n=5-6 in MDA-MB-231, n=2 in SkBR3, n=3 in MDA-MB-436). (30G-30I) ASNS expression (all n=3). (30J-30L) SLC6A9 expression (all n=3). (30M-30O) NUPR1 expression (all n=3). * P<0.05, ** P<0.01, *** P<0.005 compared to control; by Student's t-test. EXAMPLES

[0262] The disclosure and invention are further illustrated by the following examples.

[0263] Example 1 1. Materials and Methods 1.1. Chemicals Mitoquinol methanesulfonate (mitoQ) was dissolved in DMSO at a stock concentration of 10 mM. Doxorubicin (2 mg / mL), epirubicin (2 mg / mL), 5-fluorouracil (5-FU; 50 mg / mL), cisplatin (1 mg / mL), gemcitabine (38 mg / mL), paclitaxel (1 mg / mL) and cyclophosphamide (20 mg / ml) were kindly provided by the Central Pharmacy of the Cliniques Universitaires Saint-Luc (Brussels, Belgium). All other chemicals were from Sigma-Aldrich® unless otherwise stated. An equal volume of solvent (DMSO) was used in control experiments.

[0264] 1.2. Cells and cell culture Human triple-negative MDA-MB-231 breast adenocarcinoma cells were obtained from Caliper® (catalog number 119369). Human HER2+ SkBr3 breast adenocarcinoma cells (ATCC® HTB-30™), human triple-negative MDA-MB-436 breast adenocarcinoma cells (ATCC® HTB-130™) and human MCF10A non-malignant breast epithelial cells were obtained from ATCC (ATCC® CRL-10317™). All cancer cell lines were originally derived from pleural effusions. MDA-MB-231 and SkBr3 cells were routinely cultured in DMEM containing 4.5 g / L glucose and GlutaMax™ (Gibco®, Catalog No. 10566016) with 10% FBS, MDA-MB-436 in IMDM containing GlutaMax™ (Gibco®, Catalog No. 31980030) with 20% FBS, and MCF10A in DMEM:F-12 (Gibco®, Catalog No. 11320033) with 5% horse serum, 1 mM CaCl2, 10 mM HEPES, 10 μg / mL insulin, 20 ng / mL epidermal growth factor (EGF) and 0.5 μg / mL hydrocortisone. All cell cultures were routinely maintained in a subconfluent state in a humidified atmosphere (air) of 5% CO2 at 37°C. The authenticity of cells was routinely verified by short tandem repeat (STR) testing (Eurofins Genomics).

[0265] 1.3.Metabolic Assays Oxygen consumption rate (OCR) was determined on a Seahorse XF96 Bioenergy Analyzer using the XF cell Mito Stress Kit (Agilent Technologies®) according to the manufacturer's recommendations. 4 cells / well), SkBr3 (10 4 cells / well), MDA-MB-436 (10 4 cells / well) or MCF10A (10 5Cells / well) were plated in XF96 culture plates 16 h prior to the experiment in DMEM containing 10% FBS and treated with MitoQ for 48 h. On the day of analysis, the culture medium was replaced with DMEM containing 10 mM glucose, 2 mM glutamine, 1.85 g / L NaCl, 3 mg / L phenol red, pH 7.4. Cells were incubated for 1 h in a CO2-free incubator and then analyzed. Sequentially, basal OCR without treatment; ATP-bound OCR after addition of 1 μM of the ATP synthase inhibitor oligomycin; maximum OCR after disruption of mitochondrial potential using 1 μM of the ionophore carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone (FCCP); and non-mitochondrial OCR after addition of 0.5 μM of the complex I inhibitor rotenone together with 0.5 μM of the complex III inhibitor antimycin A were obtained. All data were normalized by total protein content (Bio-Rad® Protein Assay; Cat. No. 5000006) measured immediately after oxygen measurement. Mitochondrial OCR (mtOCR) was calculated by subtracting non-mitochondrial OCR to the corresponding basal OCR, maximum OCR and ATP-bound OCR.

[0266] Mitochondrial superoxide levels were determined using electron paramagnetic resonance (EPR) with MitoTEMPO-H ± PEG-SOD2 as a specific mitochondrial superoxide probe to specifically assign the signal to mitochondrial superoxide. EPR measurements were performed using a Bruker EMX-Plus spectrometer operating at X-band (9.85 GHz) and equipped with a PremiumX ultra-low noise microwave bridge and a SHQ high sensitivity resonator. Typical settings were as follows: microwave power: 20 mW; attenuation: 10 dB; modulation frequency: 100 kHz; modulation amplitude: 0.1 mT; time constant: 20.48 ms; conversion time: 22.58 ms; sweep width: 0.15 mT. Briefly, MDA-MB-231, SkBr3, MCF10A or MDA-MB-436 cells were treated with ± MitoQ for 48 h, harvested and 2 × 10 6The cells were resuspended in PBS at 1000 cells / mL. The experimental mixture was prepared with the cell suspension, 1 mM DTPA and 150 μM MitoTEMPO-H. This was then aspirated into a gas-permeable polytetrafluoroethylene (PTFE) tube and placed into a quartz tube open at both ends. During all experiments, the tube was directly inserted inside the EPR cavity heated at 310 °K with air. EPR measurements were performed 3 min after the probe was incorporated into the cell mixture and collection continued up to 15 min. To specifically measure the superoxide contribution to the EPR signal, each experiment was repeated replacing 2.5 μL of PBS with 2.5 μL of PEG-SOD2 (2,000 U / mL). Computer simulations were performed using the Bruker Xenon spinfit program. All data were normalized by cell number (trypan blue assay). Net superoxide production was calculated by subtracting the double integral value of the CMH spectrum with PEG-SOD2 against the control value at the 15 min time point.

[0267] Glucose and lactate concentrations were measured in cell supernatants collected after 48 hours of culture ± MitoQ using specific enzyme assays on a CMA600 analyzer (Aurora Borealis®) as previously described by Sonveaux et al. (J Clin Invest; 2008; 118, 3930-3942). All data were normalized by total protein content (Bio-Rad® protein assay).

[0268] Intracellular ATP levels were measured after 48 hours ± MitoQ treatment using the CellTiter-Glo Luminescent Viability Assay (Promega®) in a Glomax 96 microplate luminometer (Promega®) according to the manufacturer's instructions. Results were normalized to cell number.

[0269] 1.4.Mitochondrial potential Mitochondrial potential (ΔΨ) was measured using the JC-10 Mitochondrial Membrane Potential Assay Kit (Abcam®, #ab112134) according to the manufacturer's recommendations. 4 cells / well), SkBr3 (10 4 cells / well), MDA-MB-436 (10 4 cells / well) or MCF10A (10 5 Cells were seeded in 96-well plates and treated with MitoQ for 48 hours. Cells were then washed twice and incubated with JC-10 (1× solution) for 45 minutes. Fluorescence intensity was measured at absorbances of 490 / 525 nm and 540 / 525 nm using a SpectraMax i3 spectrophotometer equipped with a MiniMax imaging cytometer (Molecular Devices®).

[0270] 1.5.Western Blotting For Western blotting (WB), total protein extracts from MDA-MB-231, SkBr3 and MDA-MB-436 cells were prepared using RIPA buffer (50 mM Tris pH 7.4, 150 mM NaCl, 1% Triton-X-100, 0.05% sodium deoxycholate, 1 mM EDTA, 0.1% SDS, protease inhibitor cocktail and PhosSTOP phosphatase inhibitor cocktail (Roche®)), centrifuged at 10,000 × g for 10 min and quantified using the Bio-Rad® protein assay. Protein (50 μg for MDA-MB-231 cells and 100 μg for SkBr3 and MDA-MB-436 cells) was loaded into each lane of a 10-12% polyacrylamide gel in the presence of SDS and separated at 120 V for 90 min. Protein transfer to nitrocellulose membranes was performed using an iBlot 2 dry blotting system (Thermo Fisher Scientific®) with a 7 min P0 program. The membranes were then blocked for 1 h using 5% (w / v) milk powder and incubated overnight at 4 °C with primary antibodies (Table 4).

[0271] [Table 4]

[0272] β-actin served as a loading control. Immunodetection was performed using goat anti-rabbit (Jackson®, Cat. No. 111-035-003) and goat anti-mouse (Jackson®, Cat. No. 115-035-003) conjugated to horseradish peroxidase as secondary antibodies in PBS-Tween containing 5% (w / v) milk or BSA for 1 h at room temperature. Detection was performed with ECL reagents (Amersham®, Cat. No. RPN2209) and protein bands were visualized and captured using an ECL Imager 600 (Amersham®). They were analyzed using Image J software (Java).

[0273] 1.6.Cell number To examine the effect of MitoQ alone on cell number, MDA-MB-231, SkBr3, MDA-MB-436 or MCF10A (2,500-10,000 cells / well) cells were plated in 96-well plates and treated with increasing concentrations of MitoQ. At each time point, the number of cells per well was measured using a SpectraMax i3 spectrophotometer equipped with a MiniMax™ Imaging Cytometer.

[0274] To test the effect of combination treatment on cell number, MDA-MB-231 or SkBr3 cancer cells were plated in 96-well plates and treated with increasing concentrations of chemotherapy drugs ± MitoQ for 24 hours (epirubicin), 48 hours (doxorubicin, 5-FU, cisplatin, paclitaxel) or 72 hours (gemcitabine). Cells were then fixed with 11% glutaraldehyde and stained with crystal violet. The dye retained by the cells was solubilized in 10% acetic acid and the optical density (570 nm) was measured using a SpectraMax i3 spectrophotometer equipped with a MiniMax™ imaging cytometer.

[0275] 1.7.Cell cycle Cells were plated in 6-well plates at a density of 500,000 cells / well and allowed to adhere overnight. Cells were then starved for 24 hours in 0.1% FBS medium and treated with MitoQ for 48 hours. They were then detached with Trypsin-EDTA (0.05%) (Gibco®, Cat. No. 25300054) and centrifuged at 1,200 rpm for 5 minutes. The culture medium was discarded and the pellet was washed. Cells were fixed by adding 700 μL of ice-cold ethanol 100% in 300 μL of cell suspension in PBS. Cells were then washed twice with 1 mL of Tris buffer containing 0.2% (v / v) Triton X-100 and finally resuspended in 300 μL of PBS containing RNase (0.2 mg / mL) and propidium iodide (5 μg / mL). Cells were analyzed for at least 10 min using a FACSCalibur™ flow cytometer (Becton Dickinson®). 4 events were acquired and the data were analyzed according to DNA content using the FlowJo cell cycle analysis tool.

[0276] 1.8. Electron Microscopy Electron microscopy images of MDA-MB-231 and SkBr3 cells treated with MitoQ for 48 h were obtained using a previously published protocol (Piret et al.; Nanotoxicology, 2012; 6, 789-803) as described by TECNAI G. 220 Acquired with a LaB6 transmission microscope.

[0277] 1.9. Immunocytochemistry To visualize cell morphology, MDA-MB-231, SkBr3 and MDA-MB-436 cells were seeded in 24-well plates, treated with MitoQ for 48 h, fixed in 100% methanol for 10 min, stained with hematoxylin and eosin (H&E) for 10 min each, washed with water and dried. Photographs were taken with an Axiovert 40 CFL microscope (Zeiss®) equipped with an MRC camera (Zeiss®).

[0278] 1.10. Real-time quantitative PCR Total mRNA from MDA-MB-231, SkBr3 and MDA-MB-436 cells treated with ±MitoQ for 48 hours was extracted using NucleoSpin RNA Kit (Macherey-Nagel®). Total mRNA from primary tumors was extracted with Tri reagent (Molecular Research Center®, Catalog No. TR118). mRNA was quantified by Qubit BR dsRNA Assay Kit (Thermo Fisher Scientific®) and mRNA integrity was assessed on an Agilent® 2100 Bioanalyzer with an RNA 6000 Nano Kit (Agilent®). This was reverse transcribed into complementary DNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems®, Catalog No. 4368814) according to the manufacturer's protocol. Complementary DNA (500 ng) was amplified by real-time quantitative PCR (RT-qPCR) on a ViiA 7 Real-Time PCR System (Thermo Fisher Scientific®) using low ROX SYBR Master Mix dTTP Blue (Eurogentec®) and the primers listed in Tables 5 and 6. Gene expression was normalized to β-actin gene expression.

[0279] [Table 5]

[0280] [Table 6]

[0281] 1.11. Cell migration Scratch tests were performed on cells treated with ±MitoQ for 48 hours (Tamura et al.; Science, 1998; 280, 1614-1617). For each condition and each time point, pictures were taken of the same field of view, and the distance between the wound edges was analyzed using Image J software (Java®). The percentage of scratch closure was calculated relative to the wound area at 0 hours.

[0282] 1.12.Cell Infiltration Cell chemotaxis was assayed in 48-well microchemotaxis chambers (Neuroprobe® AP48) equipped with a polycarbonate porous membrane (8 μm diameter, Neuroprobe® PFB8) coated with 5 μg / mL fibronectin according to the manufacturer's instructions. Briefly, MDA-MB-231 (20,000 cells / well), SkBr3 (40,000 cells / well) or MDA-MB-436 (80,000 cells / well) cells were seeded in the upper compartment in culture medium without FBS, and 0.2% (v / v) FBS-containing medium (for MDA-MB-231 and MDA-MB-436 cells) or 10% (v / v) FBS-containing medium (for SkBr3 cells) supplemented with 10 ng / mL human EGF (PrepoTech®, catalogue no. AF-100-15) was used as a chemoattractant. Cells were allowed to infiltrate the membrane overnight. The membrane was then washed with PBS, fixed with methanol and stained with crystal violet (0.23% v / v). Photographs were taken under an Axiovert™ 40 CFL microscope (Zeiss®) equipped with an MRC camera (Zeiss®). Quantification was performed using Image J software.

[0283] 1.13. Clonogenic Assay For adhesion assays, MDA-MB-231 and SKBR3 cells were pretreated with MitoQ for 48 h ± 10 and seeded in 6-well plates (1,000–2,000 cells / well). After colony formation (2 weeks), cells were fixed and stained with 0.5% crystal violet in 10% ethanol solution for 30 min. Colonies were washed with water and counted. Results are expressed as survival fraction (SF), where SF = # colonies / colony formation fraction (PE).

[0284] For the soft agar colony formation assay, 0.4% Seaplaque soft agar (Lonza®) was diluted with DMEM containing 10% FBS and covered with a second 0.3% soft agar layer in which 500 MDA-MB-231 or SKBR3 cells were embedded. Complete DMEM culture medium ± MitoQ was added at twice the final concentration. After 20 days, colonies were counted using an Axiovert™ 40 CFL microscope equipped with an MRC camera.

[0285] 1.14.Sphere Using the 3D model, we obtained an enriched population of stem cells. 4 MDA-MB-231, SkBr3 or MDA-MB-436 cancer cells were grown in suspension in stem cell medium: DMEM / F-12 (Gibco®, catalog number 11320033) supplemented with 100 units / mL penicillin, 100 μg / mL streptomycin, 20 μL / mL B27 (Gibco®, catalog number 17504044), 20 ng / mL human recombinant epidermal growth factor (EGF) (Peprotech®, catalog number AF-100-15), 10 ng / mL basic fibroblast growth factor (bFGF; Peprotech®, catalog number 100-18B) and 2.5 mg / mL insulin using Polyhema-coated 10 cm dishes. When the spheres reached a diameter of approximately 100 μm, they were washed with PBS and dissociated with accutase (Stem Cell Technology®, Cat. No. 07920) to obtain single cells again. At the third passage, the dissociated spheres were treated with ±MitoQ for 96 hours. Images were acquired with an Axiovert™ 40 CFL microscope equipped with an MRC camera. At the end of the treatment, viable cells were collected for RNA extraction.

[0286] Stem-like spheroids were prepared by seeding 5,000 MDA-MB-231, SkBr3 or MDA-MB-436 dissociated spheres per well in ultra-low attachment 96-well plates (Corning®, Cat. No. 7007) in stem cell medium supplemented as described above. After overnight formation, spheroids were treated with ±MitoQ for 96 hours. Spheroid growth was monitored using an Axio Observer live-cell phase contrast microscope (Zeiss®).

[0287] RNA Sequencing MDA-MB-231 and SkBr3 cancer cells were treated with ±MitoQ for 48 hours. Total mRNA was then extracted using the NucleoSpin RNA kit (Macherey-Nagel®) (including DNAse treatment at the intermediate step). mRNA was quantified using the Qubit BR dsRNA Assay Kit (Thermo Fisher Scientific®) and mRNA integrity was assessed on an Agilent 2100 Bioanalyzer using the RNA 6000 Nano Kit (Agilent®). RNA integrity numbers for all samples were 7.5 or higher. Libraries from control and treated samples were prepared starting from 150 ng of total mRNA using the KAPA RNA HyperPrep Kit with RiboErase (HMR) kit (KAPA Biosystems®) according to the manufacturer's recommendations (KR1351-v1.16). Libraries were equimolarly pooled and sequenced in a single lane on an Illumina® NovaSeq 6000 platform. All libraries were sequenced to a depth of more than 50 million paired-end reads (2 × 100 bp reads) per sample. All sequencing data were analyzed using the Automated Reproducible Modular Workflow for Preprocessing and Differential Analysis of RNAseq Data (ARMOR) pipeline. In this pipeline, reads were quality checked using FastQC. Quantification and quality control results were summarized in a MultiQC report before being mapped using Salmon to a transcriptome index built using all Ensembl cDNA sequences obtained in the Homo_sapiens.GRCh38.cdna.all.fa file. Estimated transcript abundance from Salmon was then imported into R using the tximeta package and analyzed for differential gene expression using edgeR. To obtain strong signatures, only genes with |log2 fold change|>1 and P<0.01 were retained.

[0288] 1.16. In vivo experiments All in vivo experiments were carried out with the approval of UCLouvain Comite d'Ethique pour l'Experimentation Animale (approval IDs: 2016 / UCL / MD / 018, and 2020 / UCL / MD / 033) and in accordance with national and European animal care regulations.

[0289] For metastatic uptake assays, cancer cells were pretreated with MitoQ for 6 h and then incubated for 10 min at 4 °C for 1 h. 6 Viable cells were injected into the tail vein of 5-week-old female Rj:NMRI-Foxn1 nu / nu mice (Janvier). After 4 weeks, the mice were sacrificed and the lungs were injected with 3 mL of India ink (15% in ddH2O). The lungs of the mice were removed, washed with PBS, and incubated overnight in Fekete's solution (700 mL / L 100% ethanol, 32 mL / L 37% formalin, 40 mL / L glacial acetic acid, diluted with ddH2O). The following morning, the lungs were transferred to a 70% ethanol solution and further examined under a Stemi 2000-C dissecting stereomicroscope (Zeiss®) to count the number of metastases per lung.

[0290] For spontaneous metastasis assays using human breast cancer cells, MDA-MB-231, SkBr3 or MDA-MB-436 cells were prepared in medium containing 10% growth factor-reduced Matrigel (Corning®, Catalog No. 734-11-01). Five-week-old female Rj:NMRI-Foxn1 nu / nu mice (Janvier) were inoculated with 10 6 Cancer cells were injected into the second mammary fat pad on the left side. After tumor acquisition (72 hours), mice were treated daily with ±20mg / Kg MitoQ by oral gavage. Tumor size was measured once a week with electronic calipers. Four weeks after treatment initiation, primary tumors were surgically removed and processed for RT-qPCR. Tumor recurrence was determined when recurrent tumors in the vehicle group grew to approximately 200cm. 3 , i.e., 24 days after surgery, at which point the mice were sacrificed and their lungs were harvested and fixed in PFA 4% for immunocytochemistry.

[0291] Female FVB / N-Tg(MMTV-PyMT)634Mul / J (MMTV-PyMT) mice expressing polyomavirus middle T antigen spontaneously develop orthotopic multifocal mammary adenocarcinomas that spontaneously propagate metastases to the lungs during the life of the mice. For spontaneous metastasis assays, female MMTV-PyMT mice (The Jackson Laboratory) were observed daily for signs of spontaneous primary tumors starting at 6 weeks of age. Once tumors were palpable, an additional 4 weeks were waited to mimic the clinical time frame between first tumor signs and treatment initiation. Ten-week-old mice bearing primary tumors measuring approximately 0.8 cm in diameter were administered a single dose of FEC chemotherapy (5-FU 100mg / Kg, epirubicin 5mg / Kg, cyclophosphamide 100mg / Kg), clinically relevant neoadjuvant chemotherapy or adjuvant chemotherapy combinations. Animals were then randomly assigned to receive daily oral gavage of 18 mg / Kg MitoQ or the same volume of vehicle. They were sacrificed at 16 weeks of age and the lungs were injected with India ink for metastasis quantification as described above. Primary tumors were collected, weighed, and processed for RT-qPCR.

[0292] 1.17. Immunohistochemistry Harvested lungs were processed for immunohistochemistry as previously shown. They were stained for cytokeratin 19 (CK19) using a primary rabbit recombinant anti-CK19 antibody (Abcam®, Cat. No. ab76539) and a secondary Envision anti-rabbit antibody coupled to HRP (Dako®, Cat. No. K4003), and counterstained with H&E. Images of whole lung slides were acquired with an SCN400 slide scanner (Leica®) and analyzed with QuPath software (0.1.2). Quantification was performed according to Chang and Erler (Adv Exp Med Biol, 2016;899,245-251), and the number of lung metastases was proportional to the positive area of ​​CK19 staining.

[0293] 1.18. Statistics All results are expressed as the mean ± standard error of the mean (SEM) for n independent observations. Error bars may be smaller than the symbol. Dixon's Q test was used to identify outliers. Data were analyzed using GraphPad Prism 8.4.3. Student's t test, Mann-Whitney test, one-way ANOVA with Tukey post-hoc test, and two-way ANOVA were used as appropriate. Kaplan-Meier graphs were analyzed using the log-rank (Mantel-Cox) test. P < 0.05 was considered statistically significant.

[0294] 2.Results 2.1.MitoQ suppresses pro-metastatic mitochondrial ROS signaling in human breast cancer cells To test whether MitoQ can prevent metastasis in breast cancer, we selected human triple-negative MDA-MB-231 breast adenocarcinoma cancer cells and human HER2+ SkBr3 breast adenocarcinoma cancer cells as our primary models. Both cell lines were originally derived from pleural effusion and have demonstrated their metastatic potential.

[0295] In MDA-MB-231 cells, metabolic characterization showed that MitoQ at low concentrations (100 nM, 48 h) reduced basal, maximal and ATP-bound oxygen consumption rates (OCR) (Figure 1A-C), as well as mitochondrial potential (Δψ) (Figure 1D). This was associated with a reduction in mitochondrial superoxide and mitochondrial H2O2 production, measured using electron paramagnetic resonance (EPR) (Figure 1E). Similar effects were observed when these assays were repeated with SkBr3 cancer cells (Figure 2A-E). Comparatively, even though MitoQ reduced OCR in human MCF10A normal epithelial breast cells (Figure 3A-C), Δψ was not affected (Figure 3D), nor was mitochondrial superoxide production affected (Figure 3E), revealing a selective effect of MitoQ on cancer cells.

[0296] Despite activation of 5' AMP-activated protein kinase (AMPK) (Figure 4A) and metabolic compensation by increasing their glycolytic rate (Figure 4B-C), MDA-MB-231 cells treated with MitoQ (100 nM, 48 h) underwent an overall decrease in ATP production (Figure 4D). At this dose, the cell cycle was not altered (Figure 4E), but MitoQ eventually started to reduce MDA-MB-231 cell numbers from 500 nM (Figure 4F). MitoQ did not significantly activate AMPK in SkBr3 cells (Figure 5A). However, similar effects on OCR, ATP production and cell numbers were observed in SkBr3 cells, except that SkBr3 cell numbers started to decrease from a dose of 250 nM MitoQ (Figure 5B-F). A dose-dependent decrease in cell number coincided with a dose-dependent decrease in Δψ (Figures 6A-6B), while glycolytic compensation was saturated in both cancer cell lines (Figures 7A-7B).

[0297] 2.2. MitoQ induced mesenchymal-epithelial transition (MET) and inhibited in vitro migration and invasion of human breast cancer cells As adenocarcinomas, both MDA-MB-231 and SkBr3 are of epithelial origin, but as expected from metastatic breast cancer cells isolated from patient pleural effusions, they have a mesenchymal phenotype. We therefore tested whether MitoQ could reverse the epithelial-mesenchymal transition (EMT) acquired in patients. Morphological changes induced by 100 nM–500 nM MitoQ for 48 h were not evident in either MDA-MB-231 or SkBr3 cancer cells. However, MitoQ (500 nM, 48 h) reduced the mRNA expression of EMT markers, vimentin (VIM), SNAIL (SNAI1), ZEB1 and TWIST1 in MDA-MB-231 cells (Figure 8A), whereas SLUG / SNAI2 transcription was not significantly altered. At the same time point, SNAIL, ZEB1, Twist1 and E-cadherin protein expression was reduced (Figure 8B). In SkBr3 cells, MitoQ (500 nM, 48 h) suppressed the mRNA expression of all EMT inducers analyzed (Figure 8C). At the same time point, SNAIL protein expression was reduced (Figure 8D). Based on these data, it was concluded that MitoQ has the ability to induce partial MET in mesenchymal human breast cancer cells that have undergone EMT in patients.

[0298] After EMT, metastatic cancer cells must acquire migration and invasion capabilities to metastasize. MDA-MB-231 and SkBr3 cells possess these capabilities, which were greatly reduced when the cells were treated with MitoQ (100 nM, 48 h) (Figures 9A-D).

[0299] 2.3.MitoQ suppresses breast cancer clonogenic and stemness To establish secondary tumors in distant organs, mesenchymal, migratory and invasive cancer cells must additionally possess stem cell properties. Assays in Petri dishes allowing adhesion showed that MDA-MB-231 and SkBr3 cells were equally clonogenic, which was largely inhibited following treatment with MitoQ (100 nM, 48 h) (Figure 10A-B). In suspension on soft agar, MDA-MB-231 were more clonogenic than SkBr3 cells, reducing their sensitivity to MitoQ (Figure 10C). However, a 250 nM concentration of MitoQ completely abolished the clonogenicity of both cell lines. This dose also inhibited MDA-MB-231 spheroid formation, which was associated with a significant decrease in the mRNA expression of stem cell markers POU5F1 / (Oct4), NANOG and SOX2 in MDA-MB-231 spheroids (Figure 11A). Furthermore, a dose of 100 nM MitoQ was sufficient to destabilize already formed MDA-MB-231 spheroids. Using SkBr3 cells, neither inhibition of spheroid formation nor spheroid destabilization was observed, even though the mRNA expression of NANOG and SOX2 was reduced in SkBr3 spheroids (Figure 11B). Therefore, it was concluded that MitoQ has the ability to at least partially inhibit all major metastatic properties (i.e., EMT, migration, invasion, clonogenicity and stemness) in breast cancer cells in vitro.

[0300] 2.4. Identifying markers of breast cancer cell response to MitoQ Although EMT and stemness markers are generally suspect when testing anti-metastatic strategies, we decided to further our understanding of the molecular effects of MitoQ and performed unbiased RNA sequencing (RNAseq) with cells treated for 48 h ± MitoQ (500 nM). Principal component analysis showed strong clustering of gene transcripts between treated and untreated MDA-MB-231 cells, and between treated and untreated SkBr3 cells. Setting the threshold at |log2 fold change|>1 and P<0.01 to retain only highly significantly regulated transcripts, 1,943 and 5 downregulated transcripts in MDA-MB-231 and SkBr3 cells, respectively, of which 2 were commonly repressed; 2,153 and 20 upregulated transcripts in MDA-MB-231 and SkBr3 cells, respectively, of which 11 were commonly induced. As shown in Figure 12A-M, the downregulated gene transcripts were EID1 and PEG10, and the upregulated gene transcripts were PHGDH-1, SLC7A11, SERPINE1, FTH1, TXNRD1, PSAT1, PCK2, G6PD, ASNS, SLC6A9, and NUPR1. The downregulated transcripts encoded proteins normally required for cell differentiation, whereas most of the upregulated transcripts encoded metabolic enzymes and transporters (Table 7). In independent samples under the same conditions (including |log2 fold change|>1 and P<0.01), all genes were validated as potential biomarkers of human breast cancer cell response to MitoQ by RT-qPCR on the two cell lines, except for EID1, PEG10, FTH1, and NUPR1 (Figure 12A-M and Table 7).

[0301] [Table 7]

[0302] 2.5. MitoQ inhibits recurrence and metastasis of human breast cancer in mice Overall, the in vitro results indicate that MDA-MB-231 and SkBr3 cells are sufficiently competent to induce MitoQ-sensitive metastasis, and this hypothesis was tested in vivo in mice. The metastatic uptake assay used the protocol shown in Figure 13A, where cancer cells were pretreated with MitoQ 1 μM for 6 h prior to tail vein injection. 6 Four weeks after injection of viable MDA-MB-231 cells, mice receiving MitoQ-treated cells had significantly fewer metastases than mice receiving vehicle-treated cells (Figure 13B). In the control group, 11.1% of mice were metastasis-free, and 88.9% had more than two lung metastases at necropsy. In the MitoQ group, 36.4% of mice were metastasis-free, 27.2% had two or fewer metastases, and 36.4% had more than two lung metastases.

[0303] Since SkBr3 did not generate metastases in mice up to 6 weeks after tail vein injection, it was envisioned to use triple-negative MDA-MB-436 breast adenocarcinoma cancer cells, initially recovered from pleural effusion, as a third model. MDA-MB-436 responded in vitro similarly to MDA-MB-231 and SkBr3 to MitoQ. Thus, MitoQ (100 nM, 48 h) suppressed basal, maximal and ATP-bound OCR (Figure 14A-C) as well as Δψ (Figure 14D) in MDA-MB-436 cells. It dose-dependently reduced cell number (Figure 14E). MitoQ (100 nM, 48 h) further downregulated mRNA expression of EMT markers VIM (vimentin), SNAI1, SNAI2 and TWIST1 (Figure 14F). A higher dose, 500 nM, at 48 h was required to reveal a decrease in the protein expression of vimentin, SNAI1, SNAI2 (SLUG), ZEB1 and TWIST1 (Figure 14G). At the phenotypic level, MitoQ (100 nM, 48 h) inhibited the migration (Figure 14H) and invasion (Figure 14I) of MDA-MB-436 cells. It delayed spheroid formation in a dose-dependent manner (Figure 14J). These factors were therefore considered sufficient to validate the model in vitro. However, similar to SkBr3, MDA-MB-436 was found to be unable to form metastases in a metastatic uptake assay following the protocol of Figure 13A (not shown).

[0304] The ability of MitoQ to prevent tumor metastasis was tested in an orthotopic model of MDA-MB-231-bearing mice using the protocol shown in Figure 15A. The protocol included a 3-day time lapse from tumor implantation to treatment initiation, and daily oral administration of 20 mg / kg MitoQ (or an equivalent volume of vehicle) to avoid interfering with primary tumor uptake. Direct measurements revealed that primary tumor growth was not significantly affected (P=0.3150) (Figures 15B-C).

[0305] Removal of primary tumors was performed on day +32 to reveal metastatic growth, as previously reported. Three animals in the control group and two in the MitoQ group died on the day of surgery. After surgery, primary tumors recurred in 100% of animals in the control group but only in 25% of the MitoQ group (Figure 15D). Thus, MitoQ significantly improved recurrence-free survival.

[0306] After sacrificing the mice on day 56, microscopic lung examination revealed that MitoQ very significantly prevented metastatic spread (Figure S15E). In the MitoQ group, 75.0% (2 / 16) of the mice were metastasis-free, whereas only 9.5% (2 / 21) of the mice in the control group were metastasis-free.

[0307] Primary tumor samples were assayed to test the validity of the biomarkers identified above. Of these, PHGDH-1, SLC7A11, SERPINE1, TXNRD1 and PSAT1 were each independently qualified with fold induction > 2-fold and P < 0.01 (Figure 16A-M and Table 7). Taken individually, PSAT1 (Figure 16H) was the most robust as its expression was induced in 100% of tumor samples.

[0308] 2.6. MitoQ is compatible with common breast cancer chemotherapy and prevents metastasis in spontaneously metastatic breast cancer in MMTV-PyMT mice For final validation of MitoQ's antimetastatic activity in mice, we selected the MMTV-PyMT mouse model of spontaneous breast cancer, known to metastasize spontaneously. To set the grounds for future clinical trials, we compared standard of care + vehicle vs. standard of care + MitoQ. However, some chemotherapies are known to increase ROS production in cancer cells, which may be involved in their anticancer activity. It was therefore important to first test whether MitoQ interferes with these treatments. To do so, we counted cells treated in vitro with increasing doses of chemotherapy ± 100 nM MitoQ. Treatment times were adapted to drug activity. In MDA-MB-231 and SkBr3 cells, MitoQ did not alter the cytostatic / cytotoxic effects of doxorubicin, epirubicin, 5-fluorouracil (5-FU), cisplatin, paclitaxel and gemcitabine (Figure 17A-L).

[0309] To test the benefit of combining MitoQ with chemotherapy in a spontaneous model of metastatic breast cancer, hemizygous female MMTV-PyMT mice were treated using daily oral administration of FEC (5-FU 100 mg / kg, epirubicin 5 mg / kg, cyclophosphamide 100 mg / kg) ± MitoQ (18 mg / kg) as standard treatment, as shown in Figure 18A. After 6 weeks of treatment, total primary tumor weight (number of tumors per animal) was unchanged in animals receiving FEC+MitoQ compared to FEC+vehicle (P=0.1395) (Figure 18B). However, MitoQ significantly suppressed the number of surface lung metastases (Figure 18C). In the FEC+control group, all 15 mice had metastases, whereas 4 of 21 mice in the FEC+MitoQ group were metastasis-free. Primary tumor samples were used to test the validity of the biomarkers reserved thus far. Of these, SLC7A11, SERPINE1 and TXNRD1 were each independently potent with fold induction > 2-fold and P < 0.01 (Figure 19).

[0310] 3. Conclusion In this study, it was verified for the first time that MitoQ can be used to prevent metastasis of human breast cancer cells in immunodeficient mice. Furthermore, it was discovered that MitoQ can prevent recurrence of human breast cancer after surgery. MitoQ was also found not to interfere with the cytotoxic effects of all common chemotherapy used to treat breast cancer. Using in vitro and in vivo assays, we finally verified the molecular mRNA signature of the response of human breast cancer cells to MitoQ. The signature consists of the following changes in expression in response to MitoQ treatment: mRNA: decreases in VIM, SNAI1, ZEB1, NANOG, SOX2; increases in PHGDH-1, SLC7A11, SERPINE1, TXNRD1, PSAT1, PCK2, G6PD, ASNS, NUPR1 and SLC6A9. Of this signature, the strongest biomarkers, also verified in vivo, were increases in PHGDH-1, SLC7A11, SERPINE1, TXNRD1 and PSAT1. Among these, the strongest biomarkers, also validated in all in vitro and in vivo assays, were increases in SLC7A11, SERPINE1 and PSAT1. This signature can be used as a biomarker of breast tumor response to MitoQ therapy to early define patients who respond to treatment versus those who do not. This is advantageous for initial phase II clinical trials as surrogates for metastasis-free survival and recurrence-free survival, which usually occur months to years after surgery. Subsequent phase II and III clinical trials could also use the biomarkers to select patients at enrollment, thus continuing MitoQ treatment for patients with a positive biomarker response and discontinuing treatment for those without a positive biomarker response.

[0311] Example 2 1. Materials and Methods 1.1. Cells and cell culture Human MCF7 breast cancer cells (ATCC®, Catalog No. HTB-22), human MDA-MB-231 breast cancer cells (Caliper®, Catalog No. 119369), and mouse 4T1 breast cancer cells (kindly provided by Prof. Fred R. Miller, Karmanos Cancer Institute, Detroit, MI) were routinely grown in DMEM containing GlutaMax® and 4.5 g / L glucose supplemented with 10% FBS (Gibco®, #11965092) in a humidified atmosphere (air) with 5% CO2 at 37°C. All in vitro assays were performed in this medium unless otherwise stated.

[0312] 1.2.Metabolic measurements Cellular oxygen consumption rate (OCR) was assessed on a Seahorse XF96® Bioenergy Analyzer using the Mito Stress® kit according to the manufacturer's instructions (Agilent Technologies®). Briefly, 40,000 cells were plated and allowed to attach for 24 h before being treated with the indicated doses of DXR. Basal mitochondrial oxygen consumption (mtOCR) was determined to be the portion of OCR sensitive to 0.5 μM of the complex I inhibitor rotenone together with 0.5 μM of the complex III inhibitor antimycin A. Proton leak corresponded to the portion of mtOCR resistant to 1 μM of the ATP synthase inhibitor oligomycin. The highest OCR was determined after mitochondrial potential disruption using 1 μM of the ionophore carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone (FCCP). At the end of the experiment, cells were lysed in 30 μl of NaOH 0.5 M and protein was quantified by the Bradford method to normalize data by total protein content. Lactate and glucose concentrations were measured in deproteinized cell supernatants using an ISCUSflex CMA 600™ analyzer (Aurora Borealis®) as previously described (Sonveaux et al.; PLoS.One 2012;7,e33418).

[0313] 1.3. Mitochondrial superoxide measurement Mitochondrial superoxide was measured in cells loaded with 3 μM MitoSOX (Invitrogen®, Catalog No. M36008) for 10 min at 37° C. Cells were gently detached with Accutase® (Thermo Fisher Scientific®, Catalog No. A1110501), resuspended in PBS containing 10 mM D-glucose and 2% FBS, and immediately analyzed by flow cytometry using a FACSCantoII flow cytometer (BD Biosciences®).

[0314] 1.4. Cell viability Cells were plated in 96-well plates and allowed to adhere for 16 hours. To avoid reaching full confluence at the end point, the starting cell number was defined according to the doubling time and duration of the experiment. After adhesion, cells were treated with the indicated compounds for 48 hours, and then stained with the CellTiter-Glo Luminescent Cell Viability assay (Promega®, Cat. No. G7570) according to the supplier's instructions. This method is based on the quantification of intracellular ATP levels.

[0315] Alternatively, after adhesion, cells were treated with the indicated compounds for 24 hours and stained with 100 μl of 0.23% crystal violet solution (Sigma-Aldrich®, #C0775) for 10 minutes. The solution was carefully removed and the plates were washed twice with water. After drying protected from light, cells were resuspended in 50 μl DMSO and plates were read on a Victor X4 plate reader (Perkin®).

[0316] 1.5. Cell Migration and Invasion Prior to migration and invasion assays, cells were pretreated with the indicated amounts of drugs for 16 h and allowed to recover in complete culture medium for 6 h. Migration assays were performed in NeuroProbe® standard 48-well chemotaxis chambers according to the manufacturer's instructions. Briefly, the bottom chamber was filled with DMEM containing 0.5% serum as a chemoattractant. 50,000 cells were seeded in the top chamber in the same medium but without the indicated serum ± MitoQ and allowed to migrate overnight through a polycarbonate membrane with 8 μm pore size. A similar stimulation protocol was used for the invasion assay, except that Matrigel-coated transwells (Corning®) were used. With MCF7 cells, the membrane was preincubated with a solution of vitronectin 10 μg / ml (Sigma-Aldrich®, #SRP3186) for 30 min. Migrated / invaded cells were fixed and stained with 100 μl of 0.23% crystal violet solution (Sigma-Aldrich®, #C0775) for 10 min, then counted on a SpectraMax™ i3 spectrophotometer equipped with a MiniMax imaging cytometer using SoftMax Pro software. Data were normalized to vehicle-treated cells (control).

[0317] 1.6. In vivo assays In vivo experiments were performed in accordance with national animal care regulations and with the approval of the Université Catholique de Leuven (UCL) authorities (Comite d'Ethique Facultaire pour l'Experimentation Animale). The unique approval IDs for this study were UCL / MD / 2010 / 11 and 2016 / UCL / MD / 018.

[0318] On day -8, 9-week-old female Balb / cJRj mice (Janvier®) were injected with 200,000 viable 4T1 cells into the fourth mammary fat pad. When tumors reached a mean diameter of 4 mm (day 0) and were palpable in all mice, intravenous injections of doxorubicin (4 mg / kg) were administered once a week for 3 weeks (30), ± intraperitoneal injections of MitoTEMPO (0.7 mg / kg) or the same volume of vehicle (DMSO) were administered daily until the end of the experiment. Tumor volumes were measured three times a week using electronic calipers and normalized to tumor volumes on day 0. At the endpoint (day +21), mice were sacrificed and lungs were fixed in formalin. Tissues were stained with hematoxylin and eosin (H&E). Photographs of whole lung slides were taken with a slide scanner (SCN400, Leica®) and analyzed with Digital Image Hub software (DIH, Leica®). The area occupied by metastases was normalized to the analyzed lung area.

[0319] 1.7. Statistics All data are presented as mean ± SEM of n independent observations. Error bars may be smaller than the symbols. Dixon's Q test was used to identify outliers. Data were analyzed using GraphPad Prism. One-way ANOVA with Dunnett's post-hoc test and two-way ANOVA with Sidak's post-hoc test were used as indicated. P<0.05 was considered statistically significant.

[0320] 2.Results In the previous examples, it was shown that MitoQ can prevent cell migration, invasion and metastasis that are dependent on mitochondrial superoxide. Here, it was further hypothesized that chemotherapy can induce these phenotypic characteristics. Thus, doxorubicin (DXR), a chemotherapeutic agent used in the clinic to treat breast cancer, was observed to increase the mitochondrial oxygen consumption rate (mtOCR) of human MCF7 breast cancer cells when used at low doses (0.1-0.01 μg / mL, Figures 20A-B). Within this range, DXR had little effect on glycolysis, yet significantly increased glucose uptake (Figure 20C). Low-dose DXR also increased mtOCR in mouse 4T1 cells (Figures 21A-B). At 0.1 μg / mL, DXR had little effect on glycolysis, yet significantly decreased lactate release (Figure 21C).

[0321] Interestingly, DXR also induced a dose-dependent proton leak in the electron transport chain (ETC) of both human MCF and murine 4T1 cancer cell lines (Figures 22A-B). At a dose of 0.1 μg / mL DXR, this was accompanied by increased production of mitochondrial superoxide in the ETC of both cancer cell lines, as measured using the mitochondrially targeted superoxide-selective probe mitoSOX in a FACS assay (Figures 23A-B).

[0322] In cell viability assays using the CellTiter-Glo reporter, MitoQ did not interfere with DXR-induced cell killing (Figures 24A-B). At low doses, DXR stimulated MCF7 and 4T1 cell migration (Figures 24C-D) and 4T1 cell invasion (Figure 24E), and these phenotypes were inhibited by 100 nM MitoQ (Figures 24C-E).

[0323] Taken together, these results demonstrate that increased cancer cell migration and invasion are side effects of DXR chemotherapy and that these deleterious side effects can be inhibited by MitoQ. Therefore, it was hypothesized that MitoQ could inhibit cancer metastasis in breast cancer-bearing animals treated with DXR, which was demonstrated in Figures 25A-D using another mitochondria-targeted superoxide scavenger, MitoTEMPO.

[0324] We then hypothesized that the above observations could be shared with other types of chemotherapy. For demonstration, we chose cisplatin, another chemotherapeutic agent used in breast cancer treatment. Similar to DXR, it was found that cisplatin could induce mitochondrial superoxide production in the ETC of human MDA-MB-231 breast cancer cell line and mouse 4T1 breast cancer cell line (Figure 26A-Figure 26B). The combination of cisplatin with MitoQ did not interfere with the cancer cell killing activity of MitoQ using a cell viability assay based on crystal violet uptake (Figure 27A-Figure 27B). Interestingly, cisplatin induced cancer cell migration at a dose of 77.76 μM, for example, in 4T1 cells (Figure 27D). In the presence of cisplatin, MitoQ inhibited breast cancer cell migration (Figure 27C-Figure 27D).

[0325] Taken together, these results indicate that increased cancer cell migration, invasion and metastasis may be expected to be a common side effect of various types of chemotherapeutic drugs, and that these side effects may also be counteracted by using MitoQ or its analogues.

[0326] Example 3 1. Materials and Methods 1.1. Chemicals [10-(4,5-Dimethyl-3,6-dioxo-1,4-cyclohexadien-1-yl)decyl]triphenyl-phosphonium, monobromide (SKQ1 bromide; also known as Visomitin®) (Selleck Chemicals®, catalog number S9729) was dissolved in DMSO at a stock concentration of 10 mM. All other chemicals were from Sigma-Aldrich® unless otherwise stated. An equal volume of solvent (DMSO) was used in control experiments.

[0327] 1.2. Cells and cell culture Human triple-negative MDA-MB-231 breast adenocarcinoma cells were obtained from Caliper® (catalog number 119369). Human HER2+ SkBr3 breast adenocarcinoma cells (ATCC® HTB-30™), human triple-negative MDA-MB-436 breast adenocarcinoma cells (ATCC® HTB-130™) and human MCF10A non-malignant breast epithelial cells were obtained from ATCC (ATCC® CRL-10317™). All cancer cell lines were originally derived from pleural effusions. MDA-MB-231 and SkBr3 cells were routinely cultured in DMEM containing 4.5 g / L glucose and GlutaMax™ (Gibco®, Catalog No. 10566016) with 10% FBS, MDA-MB-436 in IMDM containing GlutaMax™ (Gibco®, Catalog No. 31980030) with 20% FBS, and MCF10A in DMEM:F-12 (Gibco®, Catalog No. 11320033) with 5% horse serum, 1 mM CaCl2, 10 mM HEPES, 10 μg / mL insulin, 20 ng / mL epidermal growth factor 25 (EGF) and 0.5 μg / mL hydrocortisone. All cell cultures were routinely maintained in a subconfluent state in a humidified atmosphere (air) of 5% CO2 at 37°C. The authenticity of cells was routinely verified by short tandem repeat (STR) testing (Eurofins Genomics).

[0328] 1.3. Real-time quantitative PCR Total mRNA from MDA-MB-231 or SkBr-3 human breast cancer cells treated with SKQ1 for 48 hours ±500 nM (Alexandr V. et al. Int. J. Cancer 2016;139,130-139) was extracted using Tri reagent (Brunschwig Chemie®, Catalog No. TR118). mRNA was quantified by NanoDrop TM 1000® (Thermo Fisher Scientific®) and reverse transcribed to complementary DNA using High Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific®, Catalog No. 4368814) according to the manufacturer's protocol. Complementary DNA (500 ng per sample) was amplified by RT-qPCR on a CFX96 Real-Time PCR System (BioRad®) using ROX SYBR Master Mix dTTP Blue (Eurogentec®) and the primers listed in Tables 5 and 6. Gene expression was normalized to β-actin gene expression.

[0329] 1.4. Statistics All data are presented as the mean ± SEM of n independent observations. Error bars may be smaller than the symbols. Dixon's Q test was used to identify outliers. Data were analyzed using GraphPad Prism. Student's t test was used in all experiments. P < 0.05 was considered statistically significant.

[0330] 2.Results Finally, we tested whether the biomarker signature of response to MitoQ identified above could be used to assess the response of human breast cancer cells MDA-MB-231, SkBR3 and MDAMB-436 to other mitochondrially targeted antioxidants. We chose SKQ1, an analogue of MitoQ.

[0331] Like MitoQ, SKQ1 contains an antioxidant moiety (in this case plastoquinone) linked to a mitochondrially targeted triphenylphosphonium cation with a decane linker. It was used at a concentration of 500 nM according to Alexandr V et al. (Alexandr V.et al. Int. J.Cancer 2016;139,130-139) and, like MitoQ, the cellular response was detected by using RT-qPCR after 48 hours of treatment.

[0332] Figures 28A-O report on the expression of EMT-related genes (VIM, SNAI1, ZEB1; Figures 28A-I) and stemness-related genes (NANOG, SOX2; Figures 28J-O), where a decrease in gene expression was expected in response to SKQ1. Figures 29A-O and 30A-O report on the expression of other genes (PHGDH-1, SLC7A11, SERPINE1, TXNRD1, PSAT1, PCK2, G6PD, ASNS, SLC6A9, and NUPR1). As with the MitoQ assay, expression of this second panel of genes was expected to increase in response to SKQ1.

[0333] The core biomarker signature determined using MitoQ included SLC7A11, SERPINE1, and PSAT1. As expected, expression of all three genes increased in all three cell lines after 48 h treatment with 500 nM SKQ1 (Figures 29D-F, 29G-I, and 29M-O). In MDA-MB-231 cells, SLC7A11 expression increased 2.35-fold (P<0.005), SERPINE1 expression increased 1.63-fold (P<0.01), and PSAT1 expression increased 3.43-fold (P<0.005). In SkBR3 cells, SLC7A11 expression increased 6.65-fold (P<0.005), SERPINE1 expression increased 1.45-fold (P=0.0732), and PSAT1 expression increased 2.26-fold (P<0.01). In MDA-MB-436 cells, SLC7A11 expression increased 3.60-fold (P<0.01), SERPINE1 expression increased 1.46-fold (P<0.01), and PSAT1 expression increased 2.53-fold (P<0.005). These changes demonstrated the ability of this gene set to demonstrate molecular responses to SKQ1 in human breast cancer cells.

[0334] The extended biomarker signature determined using MitoQ included SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1. As expected, expression of both PHGDH-1, PHGDH1 and TXNRD1 increased in all three cell lines after 48 h treatment with 500 nM SKQ1 (Figures 29A-C and 29J-L). Expression of PHGDH-1, PHGDH1, and TXNRD1 increased 5.36-fold (P<0.005) and 1.69-fold (P<0.005), respectively, in MDA-MB-231 cells; 2.26-fold (P<0.01) and 3.20-fold (P<0.005), respectively, in SkBR3 cells; and 2.51-fold (P<0.005) and 2.11-fold (P<0.005), respectively, in MDA-MB-436 cells. These changes demonstrated the ability of this expanded gene set to demonstrate molecular responses to SKQ1 in human breast cancer cells.

[0335] The complete biomarker signature determined using MitoQ included SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9. In addition to the results above, among the expected responses, decreased gene expression was detected for SNAI1 (not significant, P=0.4575) (Figures 28D-28F), SOX2 (P<0.005) (Figures 28M-28O), as well as increased gene expression was detected for PCK2 (P<0.005) (Figures 30A-30C), G6PD (P<0.005) (Figures 30D-30F), ASNS (P<0.005) (Figures 29G-29I), SLC6A9 (P<0.005) (Figures 29J-29L), and NUPR1 (P<0.005) (Figures 29M-29O) in MDA-MB-231 cells. In SkBR3 cells, decreased gene expression was detected for VIM (not significant, P=0.3557) (Figures 28A-29B), ZEB1 (P<0.05) (Figures 28G-I), NANOG (not significant, P=0.1539) (Figures 28J-L) and SOX2 (P<0.005), in addition to increased gene expression detected for PCK2 (P<0.005), G6PD, ASNS (P<0.01) and NUPR1 (not significant, P=0.2615). In MDA-MB-436 cells, decreased gene expression was detected for SNAI1 (not significant, P = 0.6013), ZEB1 (not significant, P = 0.6890), NANOG (not significant, P = 0.5663) and SOX2 (P < 0.05), in addition to increased gene expression detected for PCK2 (P < 0.005), G6PD (not significant, P = 0.0974), ASNS (P < 0.005), SLC6A9 (P < 0.005) and NUPR1 (P < 0.005).

[0336] 3. Conclusion Overall, the series of experiments in Example 3 demonstrates that a biomarker signature comprising gene expression of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 is effective in determining the response of human breast cancer cells to SKQ1, a mitochondrial targeted antioxidant other than MitoQ.

[0337] Therefore, this example allows one to predict that this biomarker signature will be valid for any other mitochondria-targeted antioxidants other than MitoQ and SKQ1.

[0338] In support of this conclusion, for MDA-MB-231 cells, SKQ1 induced expected gene expression changes in 12 of the 15 genes in the complete biomarker signature. Among the expected changes in expression of these 12 genes, 11 were statistically significant. For the 12 genes, the amplitude of change ranged from -21% (SNAI1) to -52% (SOX2) for genes expected to decrease expression and +63% (SERPIN1) to +676% (NUPR1) for genes expected to increase expression.

[0339] In further support of this conclusion, for SkBR3 cells, SKQ1 induced expected gene expression changes in 13 of the 15 genes in the complete biomarker signature. Among the expected changes in expression of these 13 genes, 8 were statistically significant and 1 (G6PD) contained only two replicates, preventing a definitive conclusion regarding statistics. For the 13 genes, the amplitude of change ranged from -19% (VIM) to -95% (SOX2) for genes expected to decrease expression and +25% (NUPR1) to +565% (SLC7A11) for genes expected to increase expression.

[0340] In further support of this conclusion, for MDA-MB-436, SKQ1 induced expected gene expression changes in 14 of the 15 genes in the complete biomarker signature. Among the expected changes in expression of these 14 genes, 10 were statistically significant. For the 14 genes, the amplitude of change ranged from -12% (SNAI1) to -67% (SOX2) for genes expected to have decreased expression and +22% (G6PD) to +526% (ASNS) for genes expected to have increased expression.

[0341] The core version of the biomarker signature (SLC7A11, SERPIN1 and PSAT1) was highly robust, providing 100% of expected outcomes, with eight of nine tests providing statistically significant data.

[0342] The expanded version of the biomarker signature (SLC7A11, SERPINE1, PSAT1, PHGDH-1 and TXNRD1) was also highly robust, providing 100% of expected results, with 14 of 15 tests providing statistically significant data.

[0343] The complete biomarker signature (SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1, and SLC6A9) was less robust, providing 87% (39 / 45) of expected results, with 29 of 39 successful tests (74%) providing statistically significant data.

[0344] Importantly, the complete biomarker signature had significant added value, since gene expression changes did not always affect the same panel of genes in the three tested human breast cancer cell lines, and the leading edge in terms of the amplitude of changes most frequently affected different genes in different cell lines.

[0345] Overall, based on the results of Example 3, it can be reasonably concluded that in the efficacy and usefulness of a complete biomarker signature for detecting the response of human breast cancer cells to mitochondrial-targeted antioxidants.

Claims

1. 1. A method for identifying an individual having cancer who is likely to respond to treatment with at least one mitochondrial targeted antioxidant, comprising: a. assessing the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1, and SLC6A9 in a sample obtained from the individual before and after treatment with the at least one mitochondrial-targeted antioxidant; and b. comparing the expression levels of the at least three biomarkers in the sample obtained after treatment with the at least one mitochondrial targeted antioxidant to their respective reference levels in the sample obtained before treatment with the at least one mitochondrial targeted antioxidant; A method wherein a significant variation in the expression levels of at least three biomarkers compared to their respective reference levels represents a molecular signature indicative of the individual having cancer being likely to respond to treatment with the at least one mitochondrial targeted antioxidant.

2. 2. The method of claim 1, wherein the significant variation comprises at least a 1.2-fold variation in the expression levels of at least three biomarkers compared to their respective reference levels.

3. The method of claim 1 , wherein the at least three biomarkers include SLC7A11, and / or SERPINE1, and / or PSAT1.

4. 2. The method of claim 1, wherein the at least three biomarkers include SLC7A11, and / or SERPINE1, and / or PSAT1, and / or PHGDH-1, and / or TXNRD1.

5. 2. The method of claim 1, wherein the biomarkers are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

6. 2. The method of claim 1, wherein assessing the expression levels of the at least three biomarkers is performed at the nucleic acid level.

7. 2. The method of claim 1, wherein the cancer is a metastatic cancer or a cancer prone to metastasis.

8. 2. The method of claim 1, wherein the at least one mitochondrial targeted antioxidant is selected from the group consisting of MitoQ, MitoTEMPO, MitoTEMPOL, MitoE, MitoVitE, MitoSOD, MitoSNO, SKQ1, SKQR1, SKQ2, SKQ3, SKQ4, SKQ5, SKQBerb, SKQPalm, C12TPP, melatonin, dimethyl malonate, methylene blue, Mn-porphyrin-oligopeptide conjugates, M40401, SS20, SS31, XJB-5-125, XJB-5-131, and XJB-5-197.

9. Use of the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9 as a molecular signature to identify individuals with cancer as likely to respond to treatment with at least one mitochondrial targeted antioxidant.

10. The use of claim 9 , wherein the molecular signature comprises: a. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1; or b. at least three biomarkers including SLC7A11, and / or SERPINE1, and / or PSAT1, and / or PHGDH-1, and / or TXNRD1; or c. Biomarkers that are SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

11. 10. The use of claim 9, wherein the expression levels of the at least three biomarkers are compared to their respective reference levels, and a significant variation in the expression levels of the at least three biomarkers compared to their respective reference levels indicates that the individual with cancer is likely to respond to treatment with the at least one mitochondrial targeted antioxidant.

12. 10. The use according to claim 9, wherein the cancer is a metastatic cancer or a cancer prone to metastasis.

13. A pharmaceutical composition comprising a mitochondrial targeted antioxidant for use in the prevention and / or treatment of cancer in an individual identified by the method of claim 1.

14. A pharmaceutical composition comprising a mitochondrial targeted antioxidant for use in the prevention and / or treatment of cancer metastasis in an individual identified by the method of claim 1.

15. A pharmaceutical composition comprising a mitochondrial targeted antioxidant for use in preventing and / or treating cancer recurrence prior to, concurrent with or following surgery intended to remove all or part of a tumor in an individual identified by the method of claim 1.

16. The pharmaceutical composition of any one of claims 13 to 15, wherein the mitochondrial targeted antioxidant is further combined with another cancer treatment selected from the group consisting of chemotherapy, radiation therapy, hormonal therapy, immunotherapy, anti-angiogenic therapy, surgery intended to remove all or part of the tumor, at least one other mitochondrial targeted antioxidant, and any combination thereof.

17. A kit for identifying individuals having cancer as likely to respond to treatment with at least one mitochondrial targeted antioxidant, comprising a means for determining the expression levels of at least three biomarkers selected from the group consisting of SLC7A11, SERPINE1, PSAT1, PHGDH-1, TXNRD1, VIM, SNAI1, ZEB1, NANOG, SOX2, PCK2, G6PD, ASNS, NUPR1 and SLC6A9.

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