Cancer Diagnosis and Treatment

Abstract

The present invention relates to compositions and methods for cancer therapy, including but not limited to therapy utilizing cancer biomarkers. In particular, the present invention relates to compositions and methods for predicting a subject's response to cancer therapy.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to and the benefit of U.S. Provisional Application No. 62 / 524,116, filed on June 23, 2017, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to cancer markers. In particular, the present invention relates to compositions and methods for predicting a subject's response to cancer therapy. Background Art

[0004] The growing interest in personalized medicine, coupled with our continued understanding of cancer biology, has revealed the great potential of biomarkers in cancer treatment. A variety of different biomarkers have been introduced into clinical practice to predict patient survival, evaluate treatment efficacy, or monitor disease progression (Bailey et al, Discovery Medicine, 2014, 17: 101-114). The high cost of targeted cancer therapies is a strong motivation for the development of biomarkers in order to select those patients who are most likely to benefit from treatment. To this end, regulators are increasingly requiring the inclusion of predictive biomarkers for new therapies in clinical evaluations (Marton & Weiner, Biomed Res Int. 2013;2013:891391.

[0005] Breast cancer is the second most common form of cancer among women in the United States and the second leading cause of cancer death among women. The number of new cases of breast cancer increased dramatically in the 1980s, but now the numbers appear to have stabilized. The decline in breast cancer mortality may be due to the fact that more women are getting mammograms. If breast cancer is detected early, the chances of successfully treating it are greatly improved.

[0006] When detected early, breast cancer is most often curable with treatment options such as surgery, radiation therapy, chemotherapy, and hormone therapy. Mammography is the most important screening test for early detection of breast cancer. Breast cancer is classified into many subtypes, but only a few of these are known to affect prognosis or treatment selection. Patient management after breast cancer is initially suspected usually includes confirmation of the diagnosis, assessment of the stage of disease, and selection of treatment. The diagnosis can be confirmed by needle aspiration cytology, core needle biopsy using stereotactic or ultrasound techniques for lesions that cannot be palpated, or incisional or excisional biopsy.

[0007] Prognosis is influenced by the patient's age, disease stage, pathological characteristics of the primary tumor, including the presence of tumor necrosis, estrogen receptor (ER) and progesterone receptor (PR) levels in tumor tissue, HER2 overexpression status and measures of proliferation capacity, as well as by menopausal status and overall health. Overweight patients may have a worse prognosis (Bastarrachea et al., Annals of Internal Medicine, 120: 18

[1994] ). Prognosis also varies with race, with blacks and, to a lesser extent, Hispanics having a worse prognosis than whites (Elledge et al., Journal of the National Cancer Institute 86: 705

[1994] ; Edwards et al., Journal of Clinical Oncology 16: 2693

[1998] ).

[0008] The three main treatments for breast cancer are surgery, radiation, and drug therapy. No treatment is right for every patient, and two or more treatments are often needed. The choice depends on many factors, including the patient's age and her menopausal status, the type of cancer (ductal or lobular, for example), the stage of the cancer, whether the tumor is hormone-responsive, and how aggressive it is.

[0009] The treatment of breast cancer is limited to local or systemic. Surgery and radiation are considered to be local therapy because they directly treat tumors, breasts, lymph nodes or other specific areas. Drug therapy is called systemic therapy because it works extensively. Drug therapy includes classical chemotherapy drugs, hormone blocking therapy (for example, aromatase inhibitors, selective estrogen receptor modulators and estrogen receptor down-regulators) and monoclonal antibody therapy (for example, for HER2). They can be used alone, or most commonly used in different combinations.

[0010] HER2 (ERBB2) is a validated biomarker in breast cancer, and HER2 gene amplification or protein overexpression is found in ~20% of newly diagnosed breast cancer patients (Slamon, et al., Science, 1989, 244, 707-712; Hernandez-Blanquisett, et al, Breast (Edinburgh, Scotland), 2016, 29, 170-177). HER2 is used as a therapeutic biomarker for treatment with monoclonal antibodies (mAbs) targeting HER2 (trastuzumab and pertuzumab) and tyrosine kinase inhibitors (TKI) (lapatinib and afatinib) (Hernandez-Blanquisett, et al, Breast (Edinburgh, Scotland), 2016, 29, 170-177). The pharmacological effects of mAbs and TKIs targeting HER2 are the direct result of drug-target interactions and include antibody-mediated cytotoxicity (ADCC) (mAb), HER2 downregulation, and inhibition of growth-promoting signaling (Rimawi, et al, Annual review of medicine, 2015, 66, 111-128; Clynes, et al, Nature medicine, 2000, 6, 443-446; Harbeck, et al, Breast care, 2013, 8, 49-55). The ability of HER2 to undergo receptor-mediated endocytosis also makes this transmembrane protein a candidate for delivering cytotoxic agents to cancer cells. This has indeed been exemplified by the antibody-drug conjugate (ADC) trastuzumab emtasine (T-DM1) (Lewis Phillips, et al, Cancer research, 2008, 68, 9280-9290; Verma, et al, The New England journal of medicine, 2012, 367, 1783-1791; Barok, et al, Breast cancer research, 2011, 13, R46), which received FDA approval in 2013 for the treatment of metastatic breast cancer.

[0011] T-DM1 consists of trastuzumab connected to DM-1, a drug derived from maytansine, via a thioether (cyclohexane-1-carboxylic acid N-maleimidomethyl ester (MCC)) (Baron, et al, Journal of oncologypharmacy practice, 2015, 21, 132-142). After administration, T-DM1 binds to HER2 and is brought into cells by HER2-mediated endocytosis. Proteolytic degradation of trastuzumab-components in the endosomal / lysosomal pathway is speculated to be a mechanism for cytosolic release of DM1, which subsequently induces microtubule destabilization and cell death (Erickson, et al, Cancer research, 2006, 66, 4426-4433; Martinez, et al, Critical reviews in oncology / hematology, 2016, 97, 96-106). Thus, in addition to the pharmacological effects exerted by its trastuzumab-component, T-DM1 also induces intracellular cytotoxic mechanisms of action.

[0012] Another experimental approach to using HER2 as a drug transporter is by using a fusion toxin targeting HER2, such as MH3-B1 / rGel, which consists of a single-chain variable fragment MH3-B1 that binds to HER2 and is genetically fused to the type I ribosome inactivating protein toxin gelonin (Cao, et al, Cancer Res., 2009, 69, 8987-8995; Cao, et al, Mol. Cancer Ther., 2012, 11, 143-153). MH3-B1 / rGel is taken up by HER2-mediated endocytosis and subsequently released into the cytosol, where it binds to ribosomes and inhibits translation (Stirpe, et al, J Biol. Chem., 1980, 255, 6947-6953). Therefore, in addition to its binding effect on HER2, MH3-B1 / rGel also induces cytotoxic effects in cells.

[0013] Compared to mAbs and TKIs targeting HER2, the mechanisms of drugs that bind to HER2 with intracellular sites of action are clearly more complex, and this should be reflected in biomarkers used to predict drug-response (Ritchie, et al, mAbs, 2013, 5, 13-21). However, the evaluation of biomarkers for the efficacy of T-DM1 has focused on HER2 and its downstream signaling in addition to HER3 (Baselga, et al, Clinical cancer research, 2016, 22, 3755-3763; Kim, et al, Int J Cancer, 2016, 139, 2336-2342), while little is known about the effects of proteins involved in endocytosis, endocytic vesicle transport, and exocytosis. Additional biomarkers are needed to improve the predictive value of antibody drug conjugates and immunotoxins targeting HER2 and other target receptors. This study aimed to evaluate proteins in the Rab GTPase family (Stenmark, Nature reviews. Molecular cell biology, 2009, 10, 513-525), as well as proteins specifically involved in HER2 endocytosis, as possible biomarkers of the therapeutic efficacy of ADCs and immunotoxins targeting HER2. Summary of the invention

[0014] The present invention relates to compositions and methods for cancer therapy, including but not limited to therapies utilizing cancer biomarkers. In particular, the present invention relates to compositions and methods for predicting a subject's response to cancer therapy.

[0015] Targeted therapies rely heavily on validated biomarkers in order to select patients who are most likely to benefit from treatment. HER2 has been used as a therapeutic biomarker for a variety of tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) against HER2. However, HER2 can also be used as a transport gate to deliver cytotoxic agents to the cell cytosol, such as by antibody-drug conjugates (ADCs) and antibody-toxin conjugates (immunotoxins) targeting HER2. Compared with biomarkers for TKIs and mAbs, therapeutic biomarkers for such drugs may be more complex because they not only act as targets, but may also reflect the mechanism of drug uptake and intracellular action.

[0016] In this study, the sensitivity of a panel of HER2-positive breast and ovarian cancer cell lines to two drugs targeting HER2 was evaluated; the ADC trastuzumab-emtansine (T-DM1) and the antibody-toxin conjugate MH3-B1 / rGel. Drug sensitivity was associated with the expression levels of HER2 binding to HER3 and EGFR, which may affect the pharmacology of the targeting portion of the drug, as well as Rab4, Rab5, Rab11, and HSP90 involved in endocytic trafficking, which may affect the pharmacology of the toxic portion. Early endosomal marker Rab5 and early recycling marker Rab4 were indicated as possible therapeutic biomarkers for both T-DM1 and MH3-B1 / rGel. In addition, the toxicity of MH3-B1 / rGel was also shown to depend on HSP90 and Rab11 (reverse). The present results provide a first overview of proteins involved in endocytic trafficking that are commonly used as possible biomarkers for ADCs and antibody-toxin conjugates targeting HER2, as well as ADCs and targeted antibody-toxin conjugates. In addition, a mathematical method is provided to validate the combination of biomarkers with different contribution factors.

[0017] Therefore, in some embodiments, the present invention provides a method for treating a patient diagnosed with cancer with an antibody drug conjugate or an antibody toxin conjugate, comprising: a) determining the normalized protein expression level of a receptor of the antibody component of the antibody drug or toxin conjugate and at least one additional protein marker selected from Rab5, Rab4, Rab11 and HSP90 in a biological sample from the patient; b) generating a composite expression index of the protein expression levels of the receptor and the marker; and c) based on the composite expression index, treating the patient with the antibody drug or toxin conjugate. In some embodiments, the receptor is HER2, HER3 or EGFR.

[0018] In some embodiments, the method includes when determining that the protein expression level of HER2 in addition to RAB5 also increases the expression index, administering antibody drug conjugates or antibody toxin conjugates. In some embodiments, the method includes when determining that the protein expression level of HER2 in addition to Rab5 and Rab4 also increases the expression index, administering antibody drug conjugates or antibody toxin conjugates. In some embodiments, the method includes when determining that the protein expression level of HER2 in addition to Rab5 and Rab4 also increases the expression index, administering antibody drug conjugates or antibody toxin conjugates. In some embodiments, the method includes when determining that the protein expression level of HER2 in addition to RAB5, RAB4 and HSP90 also increases the expression index, administering antibody drug conjugates or antibody toxin conjugates.

[0019] In some embodiments, the biological sample from the patient is a surgical tumor sample, a biopsy sample, or a blood sample. In some embodiments, the cancer is breast cancer, colorectal cancer, lung cancer, prostate cancer, melanoma, glioblastoma, pancreatic cancer, renal cell carcinoma, ovarian cancer, bladder cancer, gastrointestinal cancer, mesothelioma, multiple myeloma, acute myeloid leukemia, acute lymphoblastic leukemia, and non-Hodgkin's lymphoma.

[0020] In some embodiments, the antibody drug conjugate is Trastuzumab vedotin (T-DM1, Kadcyla), Brentuximab vedotin (SGN-35), Inotuzumab ozogamicin (CMC-544), Pinatuzumab vedotin (RG-7593), Polatuzumab vedotin (RG-7596), Lifastuzumab vedotin (DNIB0600A, RG-7599), Glembatuzumab vedotin (CDX-011), Coltuximab ravtansine (SAR3419), Lorvotuzumabmertansine (IMGN-901), Indatuximab ravtansine (BT-062), Sacitizumab govitican (IMMU-132), Labetuzumab govitican (IMMU-130), Milatuzumab doxorubicin (IMMU-110), Indusatumab vedotin (MLN-0264), Vadastuximab talirine (SGN-CD33A), Denintuzumabmafodotin (SGN-CD19A), Enfortumab vedotin (ASG-22ME), Rovalpituzumab tesirine (SC16LD6.5), Vandortuzumab vedotin (DSTP3086S, RG7450), Mirvetuximab soravtansine (IMGN853), ABT-414, IMGN289 or AMG595.

[0021] In some embodiments, the antibody toxin conjugate is MH3-B1 / rGel, denileukindiftitox (DAB389IL2), moxetumomab pasudotox (CAT-8015), oportuzumab monotox (VB4-845), Resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE or D2C7-IT. In some embodiments, determining comprises an immunoassay.

[0022] Additional embodiments provide methods for determining a course of therapeutic action, the method comprising: a) determining the normalized protein expression level of a receptor for the antibody component of an antibody drug conjugate or an antibody toxin conjugate and at least one additional marker selected from RAB5, RAB4, RAB11 and HSP90 in a biological sample from the patient; b) generating a composite expression index of the protein expression levels of the receptor and the marker; and c) recommending a course of therapeutic action based on the composite expression index.

[0023] Additional embodiments provide methods for determining a composite expression index in a biological sample from a patient diagnosed with cancer, the method comprising: a) determining the normalized protein expression level of a ligand of the antibody component of an antibody drug conjugate or an antibody toxin conjugate and at least one additional marker selected from, for example, RAB5, RAB4, RAB11 and HSP90 in the biological sample from the patient; and b) generating a composite expression index of the protein expression levels of the ligand and the marker.

[0024] Yet another embodiment provides a kit comprising: at least one first reagent for detecting the protein expression level of at least one first marker selected from, for example, HER2, HER3, and EGFR, and at least one second reagent for detecting the expression level of at least one second marker selected from, for example, RAB5, RAB4, RAB11, or HSP90. In some embodiments, the reagent is an antibody.

[0025] Still other embodiments provide systems comprising: a) at least one first reagent for detecting the expression level of at least one first marker selected from, for example, HER2, HER3, and EGFR, and at least one second reagent for detecting the expression level of at least one second marker selected from, for example, RAB5, RAB4, RAB11, or HSP90; b) a computer processor and computer software for calculating a composite expression index based on the expression levels.

[0026] In still other embodiments, the present invention provides a method for treating cancer in a patient, comprising: obtaining a sample comprising cancer cells from the patient; measuring the expression level of RAB5 in the cancer cells by an in vitro assay; and administering an effective amount of an immunoconjugate targeting a cancer cell surface antigen if the expression level of RAB5 in the cancer cell sample is increased compared to a predetermined reference level; or administering an antigen binding protein that does not comprise a drug or toxin if the expression level of RAB5 in the cancer cell sample is decreased compared to a predetermined reference level.

[0027] In some preferred embodiments, measuring the expression level of RAB5 in cancer cells includes measuring the level of RAB5 mRNA. In some preferred embodiments, measuring the expression level of RAB5 in cancer cells includes measuring the level of RAB5 protein. In some preferred embodiments, RAB5 is RAB5A. In some preferred embodiments, RAB5 is RAB5B. In some preferred embodiments, RAB5 is RAB5C.

[0028] In some preferred embodiments, the method further comprises the step of determining the expression level of one or more of RAB4, RAB11 or HSP90. In some preferred embodiments, the method further comprises the step of incorporating the expression level of one or more of RAB4, RAB11 or HSP90 into an expression index having an expression level of RAB5, and administering an effective amount of an immunoconjugate targeting a cancer cell surface antigen if the expression index increases compared to a predetermined reference level.

[0029] In some preferred embodiments, the cancer cells are obtained from a surgical tumor sample, a biopsy sample, or a blood sample.

[0030] In some preferred embodiments, the immunoconjugate binds to an antigen selected from the group consisting of HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA (CD66e), CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM and MSLN. In some preferred embodiments, the immunoconjugate is an antibody drug conjugate selected from the group consisting of trastuzumab emtansine, vetin-brentuximab, inotuzumab, pinatuzumab vedotin, polatuzumab vedotin, lifastuzumab vedotin, glembatuzumab vedotin, coltuximab ravtansine, lorvotuzumabmertansine, indatuximab ravtansine, sacitizumab govitican, labetuzumab govitican, milatuzumab doxorubicin, indusatumab vedotin, vadastuximab talirine, denintuzumab mafodotin, enfortumab vedotin, rovalpituzumab tesirine, vandortuzumab vedotin, mirvetuximab soravtansine, ABT-414, IMGN289 and AMG595. In some preferred embodiments, the immunoconjugate is an immunotoxin selected from the group consisting of MH3-B1 / rGel, denileukin, moxetumomab pasudotox, oportuzumab monotox, resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE, and D2C7-IT.

[0031] In some preferred embodiments, the cancer cells are selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

[0032] In some preferred embodiments, the method further comprises the step of determining the expression of surface antigens on cancer cells.

[0033] In some particularly preferred embodiments, the cancer cell is a breast cancer cell. In some preferred embodiments, the surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor (HER1), HER2, HER3 and a combination thereof, and the immunoconjugate targets the surface antigen. In some preferred embodiments, the antibody drug conjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine (T-DM1), ABT-414, IMGN289, AMG595 and AMG595. In some preferred embodiments, the surface antigen is HER2. In some preferred embodiments, the immunoconjugate is trastuzumab-emtansine (T-DM1).

[0034] In some preferred embodiments, the present invention provides an immunoconjugate targeting a surface antigen for use in a method of treating cancer in a patient, wherein cancer cells from the patient express the antigen and exhibit an increased level of RAB5 expression compared to a predetermined reference level, as determined by an in vitro expression assay. In other preferred embodiments, the present invention provides an antigen binding protein not conjugated to a drug or toxin for use in a method of treating cancer in a patient, wherein cancer cells from the patient express the antigen and exhibit a decreased level of RAB5 expression compared to a predetermined reference level, as determined by an in vitro expression assay.

[0035] In some preferred embodiments, the in vitro expression assay is a RAB5 mRNA assay. In some preferred embodiments, the in vitro expression assay is a RAB5 protein assay. In some preferred embodiments, RAB5 is RAB5A. In some preferred embodiments, RAB5 is RAB5B. In some preferred embodiments, RAB5 is RAB5C.

[0036] In some preferred embodiments, the immunoconjugate binds to an antigen selected from the group consisting of HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA (CD66e), CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM and MSLN. In some preferred embodiments, the immunoconjugate is an antibody drug conjugate selected from the group consisting of trastuzumab emtansine, vetin-brentuximab, inotuzumab, pinatuzumab vedotin, polatuzumab vedotin, lifastuzumab vedotin, glembatuzumab vedotin, coltuximab ravtansine, lorvotuzumabmertansine, indatuximab ravtansine, sacitizumab govitican, labetuzumab govitican, milatuzumab doxorubicin, indusatumab vedotin, vadastuximab talirine, denintuzumab mafodotin, enfortumab vedotin, rovalpituzumab tesirine, vandortuzumab vedotin, mirvetuximab soravtansine, ABT-414, IMGN289 and AMG595. In some preferred embodiments, the immunoconjugate is an immunotoxin selected from the group consisting of MH3-B1 / rGel, denileukin, moxetumomab pasudotox, oportuzumab monotox, resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE, and D2C7-IT.

[0037] In some preferred embodiments, the cancer cells are selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

[0038] In some preferred embodiments, the cancer cell is a breast cancer cell. In some preferred embodiments, the surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor (HER1), HER2, HER3 and a combination thereof, and the antibody drug conjugate or immunotoxin targets the surface antigen. In some preferred embodiments, the antibody drug conjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine (T-DM1), ABT-414, IMGN289, AMG595 and AMG595. In some preferred embodiments, the surface antigen is HER2. In some preferred embodiments, the immunoconjugate is trastuzumab-emtansine (T-DM1).

[0039] In yet another preferred embodiment, the present invention provides an in vitro method for determining whether human cancer cells are responsive to an immunoconjugate targeting a surface antigen on a cancer cell, comprising: obtaining a sample containing cancer cells from a patient; and measuring the expression level of RAB5 in the cancer cells by an in vitro assay, wherein an increase in the expression level of RAB5 compared to a predetermined reference level indicates reactivity to the immunoconjugate.

[0040] In some preferred embodiments, the in vitro expression assay is a RAB5 mRNA assay. In some preferred embodiments, the in vitro expression assay is a RAB5 protein assay. In some preferred embodiments, RAB5 is RAB5A. In some preferred embodiments, RAB5 is RAB5B. In some preferred embodiments, RAB5 is RAB5C. In some preferred embodiments, the method further comprises the step of determining the expression level of one or more of RAB4, RAB11 or HSP90. In some preferred embodiments, the method further comprises the step of incorporating the expression level of one or more of RAB4, RAB11 or HSP90 into an expression index with RAB5 expression level.

[0041] In some preferred embodiments, the cancer cells are obtained from a surgical tumor sample, a biopsy sample, or a blood sample. In some preferred embodiments, the cancer cells are selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells, and non-Hodgkin's lymphoma.

[0042] In some preferred embodiments, the cancer cell is a breast cancer cell. In some preferred embodiments, the method further comprises the step of measuring the expression of a surface antigen on the cancer cell. In some preferred embodiments, the surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor (HER1), HER2, HER3 and a combination thereof, and the antibody drug conjugate or immunotoxin targets one of epidermal growth factor receptor (HER1), HER2 and HER3. In some particularly preferred embodiments, the surface antigen is HER2.

[0043] In some preferred embodiments, the method further comprises the step of administering an immunoconjugate to the subject when the expression level of RAB5 is increased compared to a reference RAB5 expression level.

[0044] In some preferred embodiments, the method further comprises the step of administering an antibody that does not comprise a drug or a toxin to the subject when the expression level of RAB5 is decreased compared to a reference RAB5 expression level.

[0045] Additional implementations are described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1: A: Western blot of HER2 and γ-tubulin expression in SK-BR-3, SKOV-3, HCC1954, AU-565, MDA-MB-435 and MDA-MB-231 cells. B: Relative viability (MTT) of SK-BR-3, SKOV-3, AU-565, HCC1954 and MDA-MB-435 after 72 hours of treatment with the indicated drugs. A sigmoidal curve fitting model a / (1+exp(-(x-x0) / b) was used for T-DM1. Data points represent the mean of three independent experiments (trastuzumab, error bars: SE) or one representative value of at least three independent experiments (T-DM1 and MH3-B1 / rGel, error bars: SD).

[0047] Figure 2: A: Schematic representation of cell sensitivity to trastuzumab and intracellularly acting therapeutic agents targeting HER2. B: Cell sensitivity of SK-BR-3, SKOV-3, AU-565, HCC1954, and MDA-MB-435 cells to trastuzumab, T-DM1, and MH3-B1 / rGel. 50 : Drug concentration that inhibits 50% cell viability. TI:IC 50 (rGel) / IC 50(MH3-B1 / rGel). Representative (C) and quantitative (D) Western blots of HER2 (D1), HER3 (D2), EGFR (D3), and γ-tubulin expression in SK-BR-3, SKOV-3, AU-565, HCC1954, and MDA-MB-435 cells (n=2). HER2 and T-DM1 sensitivity (1 / IC 50 Linear regression analysis curves between (T-DM1) (E1) or MH3-B1 / rGel sensitivity (TI) (E2).

[0048] Figure 3 : The effect of HER3 and EGFR expression together with HER2 on T-DM1 (A and B) and MH3-B1 / rGel (C, D and E) sensitivity. A and B: The left panel shows the linear regression analysis curve between HER3 (A1) or EGFR (B1) expression and T-DM1 sensitivity in five cell lines. The middle panel shows the R of the linear regression. 2 Values, which are functions of the contribution factors of HER3 (A2) or EGFR (B2) expression to T-DM1 sensitivity in addition to the contribution of HER2 expression in the five cell lines. A3 represents the optimized linear regression analysis curve, in which T-DM1 sensitivity is linearly correlated with both HER2 and HER3 expression (contribution factor: 0.2). B3 shows the R of the linear regression 2 Values, which are functions of the factors of the effect of EGFR expression on T-DM1 sensitivity in addition to the effects of HER2 expression and HER3 expression (contribution factor: 0.2) in the five cell lines. C and D: The left panel shows the linear regression analysis curves between HER3 (C1) or EGFR (D1) expression and MH3-B1 / rGel sensitivity in the five cell lines. The middle panel shows the R of the linear regression. 2 Values, which are functions of the contribution of HER3 (A2) or EGFR (B2) expression to MH3-B1 / rGel sensitivity in addition to the contribution of HER2 expression in the five cell lines. The right panel represents the optimized linear regression analysis curves, where MH3-B1 / rGel sensitivity is linearly correlated with both HER2 and HER3 expression (contribution factor: 0.4) (C3) or HER2 and EGFR expression (contribution factor: 0.3) (D3). E1 shows the R of the linear regression 2 Values, which are functions of factors for the effect of HER3 expression on MH3-B1 / rGel sensitivity in addition to the effects of HER2 and EGFR expression (contribution factor: 0.3) in the five cell lines. E2 represents the optimized linear regression analysis curve, in which MH3-B1 / rGel sensitivity is linearly correlated with HER2, EGFR (contribution factor: 0.3) and HER3 expression (contribution factor: 0.4).

[0049] Figure 4: Representative (A) and quantitative (BE) Western blots of Rab5, Rab4, HSP90, Rabl 1 and γ-tubulin expression in SK-BR-3, SKOV-3, AU-565, HCC1954 and MDA-MB-435 cells (n=2).

[0050] Figure 5 : The effect of Rab5, Rab4, HSP90 and Rab11 expression on T-DM1 sensitivity together with HER2. The left panel shows the linear regression analysis curves between Rab5 (A1), Rab4 (B1), HSP90 (C1) or Rab11 (D1) expression and T-DM1 sensitivity in five cell lines. The middle panel shows the R 2 Values, which are functions of the factors of the effect of Rab5 (A2), Rab4 (B2), HSP90 (C2) or 1 / Rab11 (D2) expression on T-DM1 sensitivity in addition to the effect of HER2 expression in the five cell lines. The right panel represents the optimized linear regression analysis curve, in which T-DM1 sensitivity is linearly correlated with both HER2 and Rab5 (contribution factor: 0.3) (A3), Rab4 (contribution factor: 0.4) (B3) or 1 / Rab11 (contribution factor: 0.2) (D3) expression.

[0051] Figure 6 : The effect of Rab5, Rab4, HSP90 and Rab11 expression on MH3-B1 / rGel sensitivity together with HER2. The left panel shows the linear regression analysis curves between Rab5 (A1), Rab4 (B1), HSP90 (C1) or Rab11 (D1) expression and MH3-B1 / rGel sensitivity in five cell lines. The middle panel shows the R 2 Values, which are functions of the factors of the effect of Rab5 (A2), Rab4 (B2), HSP90 (C2) or 1 / Rab11 (D2) expression on MH3-B1 / rGel sensitivity in addition to the effect of HER2 expression in the five cell lines. The right panel represents the optimized linear regression analysis curve, in which MH3-B1 / rGel sensitivity is linearly correlated with both HER2 and Rab5 (contribution factor: 0.3) (A3), Rab4 (contribution factor: 0.6) (B3), HSP90 (contribution factor: 1) (C3) or 1 / Rab11 (contribution factor: 1) (D3) expression.

[0052] Figure 7 : Effect of Rab5, Rab4 and HSP90 or 1 / Rab11 expression in combination with HER2 on MH3-B1 / rGel sensitivity. A1 shows the R of the linear regression2 Values, which are functions of the factors of the effect of Rab4 expression on MH3-B1 / rGel sensitivity in addition to the effect of HER2 and Rab5 expression (contribution factor 0.3) in the five cell lines. A2 represents the optimized linear regression analysis curve, in which MH3-B1 / rGel sensitivity is linearly correlated with HER2, Rab5 (contribution factor: 0.3) and Rab4 expression (contribution factor: 0.6). B1 shows the R of the linear regression 2 Values, which are functions of the factors of the effect of HSP90 expression on MH3-B1 / rGel sensitivity in addition to the effects of HER2, Rab5 (contribution factor 0.3) and Rab4 (contribution factor 0.6) in the five cell lines. B2 represents the optimized linear regression analysis curve, in which MH3-B1 / rGel sensitivity is linearly correlated with HER2, Rab5 (contribution factor 0.3), Rab4 expression (contribution factor 0.6) and HSP90 expression (contribution factor 0.8). C1 shows the R of the linear regression 2 Values, which are functions of the factors of the effect of 1 / Rab11 expression on MH3-B1 / rGel sensitivity in five cell lines in addition to the effects of HER2, Rab5 (contribution factor: 0.3), Rab4 (contribution factor: 0.6) and HSP90 (contribution factor: 0.8). C2 represents the optimized linear regression analysis curve, in which MH3-B1 / rGel sensitivity is linearly correlated with HER2, Rab5 (contribution factor 0.3), Rab4 expression (contribution factor 0.6), HSP90 expression (contribution factor 0.8) and 1 / Rab11 expression (contribution factor 0.4).

[0053] Figure 8 : Effect of the combination of HER3 and EGFR (A1, B1) or Rab5, Rab4, HSP90 and 1 / Rab11 expression (A2, B2) together with HER2 on T-DM1 (A) or MH3-B1 / rGel sensitivity (B). The results presented are similar to Figure 5 , Figure 6 and Figure 7 The same as reported in , and here combined in the same figure. In this report (C) is a schematic diagram of biomarkers indicating sensitivity to T-DM1 and MH3-B1 / rGel. The arrows indicate the drugs recommended for the current biomarker, and the width of the arrows indicates the effect of the protein on drug sensitivity. The circles indicate two libraries of biomarkers that are recommended for combination.

[0054] Fig. 9 : Results of a Monte-Carlo 2-fold cross-validation procedure to determine the threshold that minimizes the p-value for the biomarker x treatment interaction.

[0055] Fig.10 : Bayesian pCR probability curves related to RAB5A expression.

[0056] definition

[0057] To facilitate understanding of the present invention, a number of terms and phrases are defined below:

[0058] As used herein, the term "antigen binding protein" refers to a protein comprising a portion that binds to an antigen and optionally a scaffold or framework portion that allows the antigen binding portion to adopt a conformation that promotes the binding of the antigen binding protein to the antigen. Examples of antigen binding proteins include antibodies, antibody fragments (e.g., antigen binding portions of antibodies), antibody derivatives, and antibody analogs. Antigen binding proteins may include, for example, alternative protein scaffolds or artificial scaffolds with grafted CDRs or CDR derivatives. Such scaffolds include, but are not limited to, antibody-derived scaffolds comprising mutations introduced to, for example, stabilize the three-dimensional structure of the antigen binding protein, and fully synthetic scaffolds including, for example, biocompatible polymers. Examples of antigen binding proteins include, but are not limited to, polyclonal antibodies, monoclonal antibodies, chimeric antibodies, single-chain antibodies, humanized antibodies, mini antibodies, Fab fragments, F(ab')2 fragments, Fv fragments, single-chain Fv fragments, etc.

[0059] As used herein, the term "immunoconjugate" refers to a molecule comprising an antigen binding protein that is connected or combined with another agent (such as a drug or toxin) such as by a chemical bond or a peptide linker. The term "immunoconjugate" encompasses antibody drug conjugates, immunotoxins and affinity toxins. The antigen binding protein portion of the molecule can be an immunoglobulin or an antigen binding fragment or its antigen binding derivative, such as a polyclonal antibody, a monoclonal antibody, a chimeric antibody, a single-chain antibody, a humanized antibody, a mini antibody, a Fab fragment, a F(ab')2 fragment, a Fv fragment, a single-chain Fv fragment, etc. The antigen binding protein portion can also be a protein ligand that can bind to a cell surface antigen. For example, EGF can target the EGF receptor expressed on the cell surface.

[0060] As used herein, the term "antibody drug conjugate (ADC)" refers to a molecule comprising an antigen binding protein linked or otherwise associated with a drug molecule, typically via a chemical bond.

[0061] As used herein, the term "immunotoxin" refers to a molecule comprising an antigen binding protein linked or otherwise associated with a toxin molecule, typically via a peptide linker.

[0062] As used herein, the term "affinity toxin" refers to a molecule comprising a protein ligand capable of binding a cell surface antigen, wherein the protein ligand is typically linked or otherwise associated with the toxin molecule via a peptide linker.

[0063] As used herein, a cancer cell is "responsive" to an immunoconjugate when a measurable toxic response is detected when the cell is contacted with the immunoconjugate.

[0064] As used herein, the terms "detect," "detecting," or "detection" may describe either the general action of finding or discerning or the specific observation of a component.

[0065] As used herein, the term "nucleic acid molecule" refers to any molecule comprising nucleic acid, including but not limited to DNA or RNA. The sequences encompassed by the term include any known base analogs of DNA and RNA, including but not limited to 4-acetylcytosine, 8-hydroxy-N6-methyladenosine, aziridinylcytosine, pseudoisocytosine, 5-(carboxyhydroxymethyl)uracil, 5-fluorouracil, 5-bromouracil, 5-carboxymethylaminomethyl-2-thiouracil, 5-carboxymethylaminomethyluracil, dihydrouracil, inosine, N6-isopentenyladenine, 1-methyladenine, 1-methylpseudouracil, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, N6-methyladenine, 7-methylguanine, 5-methylaminomethyluracil, 5-methoxyaminomethyl-2-thiouracil, β-D-mannosylqueosine, 5'-methoxycarbonylmethyluracil, 5-methoxyuracil, 2-methylthio-N6-isopentenyl adenine, uracil-5-oxyacetate methyl ester, uracil-5-oxyacetic acid, oxybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, N-uracil-5-oxyacetate methyl ester, uracil-5-oxyacetic acid, pseudouracil, queosine, 2-thiocytosine and 2,6-diaminopurine.

[0066] As used herein, the term "amplification oligonucleotide" refers to an oligonucleotide that hybridizes with a target nucleic acid or its complementary sequence and participates in a nucleic acid amplification reaction. An example of an amplification oligonucleotide is a "primer", which hybridizes with a template nucleic acid and is included in a 3'OH end extended by a polymerase during the amplification process. Another example of an amplification oligonucleotide is an oligonucleotide that is not extended by a polymerase (for example, because it has a 3' closed end), but participates in or promotes amplification. The amplification oligonucleotide may optionally include modified nucleotides or analogs, or participate in the amplification reaction but is not complementary to the target nucleic acid or other nucleotides not included in the target nucleic acid. The amplification oligonucleotide may include a sequence that is not complementary to the target or template sequence. For example, the 5' region of the primer may include a promoter sequence (referred to as "promoter-primer") that is not complementary to the target nucleic acid. It will be appreciated by those skilled in the art that the amplification oligonucleotide that acts as a primer may be modified to include a 5' promoter sequence, and therefore acts as a promoter-primer. Similarly, promoter-primers may be modified by removing a promoter sequence or synthesizing in the absence of a promoter sequence, and still act as primers. The 3' blocked amplification oligonucleotide can provide a promoter sequence and serve as a template for polymerization (referred to as a "promoter-provider").

[0067] As used herein, the term "primer" refers to an oligonucleotide, whether it exists naturally as a purified restriction digest or is produced by synthesis, when placed under conditions that induce the synthesis of a primer extension product complementary to a nucleic acid chain (e.g., in the presence of nucleotides and an inducing agent such as a DNA polymerase and at a suitable temperature and pH), the oligonucleotide can serve as a starting point for synthesis. For maximum amplification efficiency, the primer is preferably single-stranded, but alternatively may also be double-stranded. If double-stranded, then before being used to prepare an extension product, the primer is first treated to separate its chain. Preferably, the primer is an oligodeoxyribonucleotide. The primer should be long enough to initiate the synthesis of an extension product in the presence of an inducing agent. The exact length of the primer will depend on many factors, including the use of temperature, primer source, and method.

[0068] As used herein, the term "probe" refers to an oligonucleotide (i.e., a nucleotide sequence), whether naturally present as a purified restriction digest or produced by synthesis, recombination, or by PCR amplification, which is capable of hybridizing with at least a portion of another oligonucleotide of interest. The probe can be single-stranded or double-stranded. The probe can be used to detect, identify, and separate specific gene sequences. It is contemplated that any probe used in the present invention will be labeled by any "reporter molecule" so that it can be detected in any detection system, including but not limited to enzymes (e.g., ELISA, and enzyme-based histochemical assays), fluorescence, radioactivity, and luminescent systems. It is not intended that the present invention be limited to any specific detection system or labeling. In some embodiments, the reporter molecule is an "exogenous reporter molecule."

[0069] The term "exogenous reporter molecule" refers to a reporter molecule or label that is not found in nature attached to a detection reagent (eg, a probe, nucleic acid, or antibody). Examples include, but are not limited to, enzymatic, fluorescent, radioactive, or luminescent reporter molecules.

[0070] The term "isolated", as in "isolated oligonucleotide" or "isolated polynucleotide", when used in connection with nucleic acids, refers to a nucleic acid sequence that has been identified and separated from at least one component or contaminant to which it is normally associated in the natural source. An isolated nucleic acid is present in a form or arrangement different from that in which the nucleic acid is found in the natural state. In contrast, non-isolated nucleic acids, such as nucleic acids of DNA and RNA, are found in their naturally occurring state. For example, a given DNA sequence (e.g., a gene) is found on a host cell chromosome close to neighboring genes; an RNA sequence (such as a specific mRNA sequence encoding a specific protein) is found in a cell as a mixture with many other mRNAs encoding multiple proteins. However, for example, an isolated nucleic acid encoding a given protein includes such nucleic acids in cells that normally express a given protein, wherein the nucleic acid is in a different chromosomal position than in the natural cell, or is flanked by nucleic acid sequences that are different from those in the naturally occurring state. An isolated nucleic acid, oligonucleotide, or polynucleotide may exist in single-stranded or double-stranded form. When an isolated nucleic acid, oligonucleotide or polynucleotide is used to express a protein, the oligonucleotide or polynucleotide will contain at least the sense or coding strand (i.e., the oligonucleotide or polynucleotide may be single-stranded), but may contain both sense and antisense strands (i.e., the oligonucleotide or polynucleotide may be double-stranded).

[0071] As used herein, the term "purified" or "purification" refers to the removal of components (e.g., contaminants) from a sample. For example, antibodies are purified by removing contaminating non-immunoglobulins; they are also purified by removing immunoglobulins that do not bind to the target molecule. Removal of non-immunoglobulins and / or removal of immunoglobulins that do not bind to the target molecule results in an increase in the percentage of target-reactive immunoglobulins in the sample. In other examples, recombinant polypeptides are expressed in bacterial host cells, and the polypeptides are purified by removing host cell proteins; therefore, the percentage of recombinant polypeptides in the sample is increased.

[0072] As used herein, the term "sample" is used in its broadest sense. In a sense, this means including samples or cultures obtained from any source, as well as biological and environmental samples. Biological samples can be obtained from animals (including humans) and include fluids, solids, tissues and gases. Biological samples include blood products, such as plasma, serum, etc. Environmental samples include environmental materials, such as surface materials, soil, water, crystals and industrial samples. However, these examples should not be construed as limiting the sample types applicable to the present invention. DETAILED DESCRIPTION

[0073] The present invention relates to compositions and methods for cancer treatment, including but not limited to therapies utilizing cancer biomarkers. In particular, the present invention relates to compositions and methods for predicting a subject's response to cancer therapy.

[0074] The growing focus on personalized medicine, combined with our increasing understanding of cancer biology, has revealed great potential for the use of biomarkers in cancer treatment. A range of different biomarkers have been incorporated into clinical practice to predict patient survival, assess treatment efficacy or monitor disease progression. 1 Predictive biomarkers enable the careful selection of patients most likely to benefit from a specific treatment, and such knowledge is therefore critical for the rational utilization of current and future high-cost targeted cancer therapies.

[0075] Therefore, provided herein are systems and methods for determining the treatment of a subject suffering from cancer (e.g., breast cancer) based on the expression of one or more protein markers, recommending treatment thereto, and / or giving treatment thereto. The present invention is not limited to specific markers. In some embodiments, the combination of an antigen (e.g., HER2, HER3, EGFR) and one or more other markers (e.g., RAB5 (preferably RAB5A), RAB4, RAB11 and HSP90 or HER3 and EGFR) of an antibody is detected alone or in combination. In some embodiments, the expression level of the combination or marker is combined to produce a composite expression index.

[0076] In some preferred embodiments, the present invention provides a method for treating cancer in a patient, comprising: obtaining a sample containing cancer cells from a patient; measuring the expression level of RAB5 in cancer cells by in vitro assay; and if the expression level of RAB5 in the cancer cell sample is increased compared to a predetermined reference level, administering an effective amount of an immunoconjugate targeting a cancer cell surface antigen; or if the expression level of RAB5 in the cancer cell sample is decreased compared to a predetermined reference level, administering an antigen binding protein that does not contain a drug or toxin. The expression of any one or a combination of RAB5A, RAB5B or RAB5C can be determined. In some particularly preferred embodiments, the expression of RAB5A is determined.

[0077] As described, in some preferred embodiments, the decision of administering immunoconjugates or administering antigen-binding proteins that are not conjugated to toxins or drugs is based on comparing the expression of RAB5 (preferably RAB5A) in the measured patient sample with a predetermined reference level or threshold level. It will be appreciated by those skilled in the art that reference levels or threshold levels can be determined by statistical programs applied to expression data obtained from a suitable patient population. Suitable statistical methods are provided in the embodiments, but it will be appreciated by those skilled in the art that other statistical programs can also be utilized. It will also be appreciated that different statistical programs or the same program run different or extended data sets, and different reference levels or threshold levels may be produced. Therefore, the present invention is not limited to any specific reference level or threshold level used for the expression of any specific marker (e.g., RAB5A) or a combination of markers. In this regard, in some embodiments, the method of the present invention also includes determining the expression level of one or more of RAB4, RAB11 or HSP90. In some preferred embodiments, the expression level in a sample of one or more of RAB4, RAB11 or HSP90 is incorporated into an expression index having an expression level of RAB5 (preferably an expression level of RAB5A), and if the expression index is increased compared to a predetermined reference level, an effective amount of an immunoconjugate targeting a cancer cell surface antigen is administered.

[0078] In some preferred embodiments, the patient sample used for the method of the present invention comprises cancer cells. Suitable cell-containing samples can be obtained by a variety of methods, including but not limited to biopsy, surgical samples and blood samples. In some preferred embodiments, the presence of one or more cell surface antigens in the sample has been determined previously. In some embodiments, the method also includes if the sample is not characterized previously, then the expression of one or more cell surface antigens in the sample is determined. The present invention is not limited to the determination of any specific cell surface antigen, but the cell surface antigen that is easy to internalize (e.g., by endocytosis) is preferred. Exemplary cell surface antigens that are easy to internalize include but are not limited to HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA (CD66e), CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM and MSLN.

[0079] In some particularly preferred embodiments, the sample comprises breast cancer cells. In these embodiments, the expression of epidermal growth factor receptor (HER1), HER2 and / or HER3 of breast cancer cells is preferably characterized. In even more preferred embodiments, the sample is determined as, or has previously been determined and identified as having a HER2 receptor.

[0080] As described above, in some embodiments, a composite expression index is used in the methods of the present invention. The present invention is not limited to the use of any particular composite expression index. Examples of suitable composite expression indexes are as follows.

[0081] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB5 expression) x 0.3) x (1-(1-relative RAB4 expression) x 0.6) x (1-(1-relative HSP90 expression) x 0.8) / (1-(1-(1 / relative RAB11 expression)) x 0.4).

[0082] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB4 expression) x 0.6) x (1-(1-relative RAB5 expression) x 0.3) x (1-(1-relative HSP90 expression) x 0.8).

[0083] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB4 expression) x 0.6) x (1-(1-relative RAB5 expression) x 0.2) x (1-(1-relative HSP90 expression) x 0.6).

[0084] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB4 expression) x 0.4) x (1-(1-relative RAB5 expression) x 0.2).

[0085] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB5 expression) x 0.3) x (1-(1-relative RAB4 expression) x 0.6).

[0086] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB5 expression) x 0.3).

[0087] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB4 expression) x 0.4).

[0088] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB4 expression) x 0.6).

[0089] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative RAB11 expression) x 0.2).

[0090] In some embodiments, the composite expression index is: relative HER2 expression x (1-(1-relative HSP90 expression).

[0091] In some embodiments, the expression is protein expression. In some embodiments, the determining step comprises an immunoassay. In some embodiments, the expression is mRNA expression. In some embodiments, the determining step comprises reverse transcription of mRNA to provide cDNA, and amplifying the cDNA with specific primers for the biomarker. In some embodiments, the detection technique is RT-PCR.

[0092] The expression assays used in the present invention can utilize a single biomarker, such as RAB5A, or a panel of biomarkers (e.g., RAB5A and one or more of RAB4, RAB11, or HSP90; RAB5A and HER2; or RAB5A, HER2, and one or more of RAB4, RAB11, or HSP90). In some embodiments, the panels or assays of the present invention include less than 100, 75, 50, 25, 20, 15, 10, or five biomarkers, or in other preferred embodiments, up to a total of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 20 biomarkers.

[0093] In some embodiments, the protein expression level in a sample from a subject is detected. In some embodiments, the subject has been diagnosed with cancer (e.g., breast cancer). In some embodiments, the sample is tissue (e.g., biopsy tissue), blood, serum, urine, etc.

[0094] Exemplary methods for detecting protein markers are provided below. However, any suitable method for detecting tumor marker proteins may be used.

[0095] Illustrative, non-limiting examples of immunoassays include, but are not limited to, immunoprecipitation; Western blot; ELISA; immunohistochemistry; immunocytochemistry; flow cytometry; and immuno-PCR. Polyclonal or monoclonal antibodies detectably labeled using various techniques known to those of ordinary skill in the art (e.g., colorimetric, fluorescent, chemiluminescent, or radioactive) are suitable for use in immunoassays.

[0096] Immunoprecipitation is a technique for precipitating an antigen from a solution using an antibody specific for the antigen. This method can be used to identify protein complexes present in cell extracts by targeting proteins that are thought to exist as complexes. The complex is taken out of solution by insoluble antibody-bound proteins (such as protein A and protein G) that were initially isolated from bacteria. These antibodies can also be connected to agarose beads that can be easily isolated from solution. After washing, the precipitate can be analyzed using mass spectrometry, Western blotting or any of a variety of other methods to identify the components in the complex.

[0097] Western blotting, or immunoblotting, is a method for detecting proteins in a given sample of tissue homogenate or extract. It uses gel electrophoresis to separate denatured proteins by mass. The proteins are then transferred from the gel and onto a membrane, usually polyvinyl difluoride or nitrocellulose, where they are probed using antibodies specific for the protein of interest. As a result, researchers can examine the amount of protein in a given sample and compare levels between several groups.

[0098] ELISA, short for enzyme-linked immunosorbent assay, is a biochemical technique used to detect the presence of antibodies or antigens in a sample. It utilizes at least two antibodies, one of which is specific for the antigen and the other is linked to an enzyme. The second antibody will cause a chromogenic or fluorogenic substrate to produce a signal. Variations of ELISA include sandwich ELISA, competitive ELISA, and ELISPOT. Because ELISA can be performed to assess the presence of either an antigen or an antibody in a sample, it is a useful tool for determining serum antibody concentrations as well as for detecting the presence of an antigen.

[0099] Immunohistochemistry and immunocytochemistry refer to methods for localizing proteins in tissue sections or cells, respectively, by binding the principle of their respective antibodies to antigens in tissues or cells. Visualization can be achieved by labeling antibodies with labels that produce color or emit fluorescence. Typical examples of colored labels include, but are not limited to, horseradish peroxidase and alkaline phosphatase. Typical examples of fluorophore labels include, but are not limited to, fluorescein isothiocyanate (FITC) or phycoerythrin (PE).

[0100] Flow cytometry is a technique used to count, examine, and classify microscopic particles suspended in a fluid stream. It allows for simultaneous multi-parameter analysis of the physical and / or chemical properties of individual cells flowing through an optical / electronic detection device. A beam of light (e.g., a laser) of a single frequency or color is directed onto a hydrodynamically focused fluid stream. Multiple detectors are aimed at the point where the stream passes through the beam; one in line with the beam (forward scatter, or FSC), and several perpendicular to the beam (side scatter (SSC) and one or more fluorescence detectors). Each suspended particle that passes through the beam scatters the light in some way, and fluorescent chemicals in the particle may be excited to emit light at a lower frequency than the light source. The combination of scattered light and fluorescence is picked up by detectors, and by analyzing the brightness fluctuations of each detector (one for each fluorescence emission peak), various facts about the physical and chemical structure of each individual particle can be inferred. FSC is related to cell volume, while SSC is related to the density or internal complexity of the particle (e.g., the shape of the nucleus, the number and type of cytoplasmic particles, or the roughness of the membrane).

[0101] Immunopolymerase chain reaction (IPCR) utilizes nucleic acid amplification technology to increase signal generation in antibody-based immunoassays. Because there is no protein equivalent to PCR, that is, proteins cannot be replicated in the same way as nucleic acids are replicated during PCR, the only way to increase detection sensitivity is through signal amplification. The target protein is bound to an antibody directly or indirectly conjugated to an oligonucleotide. Unbound antibodies are washed away, and the remaining antibody-bound oligonucleotides are amplified. Protein detection is performed by detecting the amplified oligonucleotides using standard nucleic acid detection methods (including real-time methods).

[0102] In some embodiments, immunomagnetic detection is utilized. In some embodiments, detection is automated. Exemplary immunomagnetic detection methods include, but are not limited to, those commercially available from Veridex (Raritan, NJ).

[0103] In some embodiments, computer-based analysis programs are used to convert the raw data (e.g., the presence, absence or quantity of marker expression) generated by the detection assay into data (e.g., the selection of cancer therapy or a composite expression index) with predictive value to clinicians. Clinicians can use the predicted data in any suitable manner. Therefore, in some preferred embodiments, the invention provides additional benefits, i.e., clinicians who are unlikely to receive genetics or molecular biology training do not need to understand the raw data. Data are directly presented to clinicians in their most useful form. Then, clinicians can immediately use this information to optimize the care of the subject.

[0104] The present invention contemplates any method of receiving, processing and transmitting information between the laboratory, information provider, medical staff and subject being measured. For example, in some embodiments of the present invention, the sample (such as biopsy or blood or serum sample) is obtained from the subject and submitted to the analysis service party (such as, clinical laboratory of medical institution, genome analysis enterprise etc.) located in any place in the world (such as, different country from the country where the subject lives or the country where the information is finally used) to generate raw data. If the sample comprises tissue or other biological samples, the subject can go to the medical center so that the sample is collected and sent to the analysis center, or the subject can collect the sample (such as urine sample) by himself and send it directly to the analysis center. If the sample comprises previously determined biological information, the information can be directly sent to the analysis service party (such as, the information card comprising the information can be scanned by a computer, and the data is transferred to the computer of the analysis center using an electronic communication system) by the subject. Once received by the analysis service party, the sample is processed and the analysis overview (i.e., expression data) of the diagnosis or prognosis information required for the subject is generated.

[0105] The analysis overview data are then prepared in a format suitable for being interpreted by the attending clinician. For example, rather than providing raw data, the preparation format can represent the diagnosis or risk assessment (for example, the probability of successful cancer treatment or a composite expression index) of the experimenter, and the advice selected for a specific treatment. Data can be displayed to the clinician by any suitable method. For example, in some embodiments, the analysis service party generates a report, which can be printed to the clinician (for example, when nursing) or displayed to the clinician on a computer monitor.

[0106] In some embodiments, the information is first analyzed at the point of care or regional device. The raw data is then sent to a central processing device for further analysis and / or conversion of the raw data into useful information for the clinician or patient. The central processing device provides the following advantages: privacy (all data is stored in the central device using a unified security protocol), speed, and consistency of data analysis. The central processing device can then control the fate of the data after the subject has been treated. For example, using an electronic communication system, the central device can provide the data to a clinician, subject, or researcher.

[0107] In some embodiments, the subject can directly access the data using an electronic communication system. The subject can choose further intervention or consultation based on the results. In some embodiments, the data is used for research purposes. For example, the data can be used to further optimize the inclusion or removal of markers as useful indicators of a particular condition or stage of a disease.

[0108] Compositions used in the diagnostic, prognostic and therapeutic methods of the present invention include, but are not limited to, probes, amplification oligonucleotides and antibodies. Particularly preferred compositions detect the presence of marker expression levels in a sample.

[0109] Any of these compositions can be provided in the form of a kit, either alone or in combination with other compositions of the invention. For example, a single labeled probe and paired amplification oligonucleotides or antibodies and immunoassay components can be provided in a kit for amplifying and detecting markers. The kit can also include appropriate controls and / or detection reagents.

[0110] The probe and antibody compositions of the invention may also be provided in the form of array assays or panel assays.

[0111] In some embodiments, the invention provides systems, kits, and methods for determining and administering a course of therapeutic action.

[0112] The method of the present invention can be used to treat a variety of cancers. Cancers that can be treated according to the present invention include, but are not limited to, breast cancer, colorectal cancer, lung cancer, prostate cancer, melanoma, glioblastoma, pancreatic cancer, renal cell carcinoma, ovarian cancer, bladder cancer, endometrial cancer, gastrointestinal cancer, mesothelioma, multiple myeloma, acute myeloid leukemia, acute lymphocytic leukemia, and non-Hodgkin's lymphoma. As described above, in a preferred embodiment, when compared with a reference or threshold expression level or a composite expression index, the expression level of a combination of biomarkers or biomarkers in a patient sample increases, and it is required to administer an immunoconjugate to the patient. Similarly, in other preferred embodiments, if compared with a reference or threshold expression level or a composite expression index, the expression level of a combination of biomarkers or biomarkers in a patient sample decreases, it is required to administer an antigen-binding protein that is not conjugated to a drug or toxin to the patient. In an embodiment, if it is required to administer an immunoconjugate, an immunoconjugate that is bound to a surface antigen expressed by a patient's tumor or cancer cell is selected. Suitable surface antigens to which the immunoconjugates may be directed include, but are not limited to, HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA (CD66e), CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM, and MSLN.

[0113] In some embodiments, the immunoconjugate is an antibody drug conjugate. Suitable antibody drug conjugates include, but are not limited to, trastuzumab-mertansine (T-DM1, Kadcyla), vetin-brentuximab (SGN-35), inotuzumab (CMC-544), pinatuzumab vedotin (RG-7593), polatuzumab vedotin (RG-7596), Lifastuzumab vedotin (DNIB0600A, RG-7599), Glembatuzumab vedotin (CDX-011), coltuximab ravtansine (SAR3419), lorvotuzumab mertansine (IMGN-901), indatuximabravtansine (BT-062), sacitizumab govitican (IMMU-132), labetuzumab govitican (IMMU-130), milatuzumab doxorubicin(IMMU-110), Indusatumab vedotin(MLN-0264), Vadastuximab talirine(SGN-CD33A), Denintuzumab mafodotin(SGN-CD19A), Enfortumabvedotin(ASG-22ME), Rovalpituzumab tesirine(SC16LD6.5), Vandortuzumab vedotin (DSTP3086S, RG7450), Mirvetuximab soravtansine (IMGN853), ABT-414, IMGN289 or AMG595. In some embodiments, the antibody toxin conjugate is MH3-B1 / rGel, denileukin (DAB389IL2), moxetumomab pasudotox (CAT-8015), oportuzumab monotox (VB4-845), Resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE or D2C7-IT. As described above, the choice of which antibody drug conjugate to use in the methods of the invention will depend on which specific surface antigens are expressed by the cancer cells in the subject.

[0114] In some embodiments, the immunoconjugate is an immunotoxin. Suitable immunotoxins include, but are not limited to, MH3-B1 / rGel, denileukin (DAB389IL2), moxetumomab pasudotox (CAT-8015), oportuzumab monotox (VB4-845), Resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE, or D2C7-IT. Moreover, as described above, the selection of which immunotoxin to use in the method of the present invention will depend on which specific surface antigen is expressed by the cancer cells in the subject.

[0115] experiment

[0116] The following examples are provided to illustrate and further illustrate certain embodiments of the present invention and should not be construed as limiting the scope thereof.

[0117] Example 1

[0118] Materials and methods

[0119] Cells and Culture. Five human cell lines expressing HER2 were used in this study; breast cancer cell lines SK-BR-3, AU-565 (CRL-2351), HCC1954 (CRL-2338), and MDA-MB-453 (HTB-131) and ovarian cancer cell line SKOV-3 (HTB-77). The HER2-negative human breast cancer cell line MDA-MB-231 was used as a negative control for HER2 expression. All cell lines except SK-BR-3 were obtained from the American Type Culture Collection (Manassas, VA, USA); SK-BR-3 was kindly provided by the Department of Biochemistry, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway. All cell lines used were between passages 3 and 25 to avoid changes in cell line properties over time, and cells were routinely checked for mycoplasma infection. SK-BR-3 and SKOV-3 cells were cultured in McCoy's 5A medium, AU-565, HCC1954, and MDA-MB-231 cells were cultured in RPMI-1640 medium (both obtained from Sigma-Aldrich, St. Louis, MO, USA), and MDA-MB-453 was cultured in Leibovitz's L-15 medium (Lonza, Verviers, Belgium). All media were supplemented as described previously. 19 .

[0120] Cytotoxicity assay. Cells were plated at 8x10 3 (SK-BR-3), 1.8x10 3 (SKOV-3), 6x10 3 (AU-565), 4x10 3 (HCC1954) or 1x10 4 Cells / well (MDA-MB-453) were seeded in 96-well plates (Nunc, Roskilde, Denmark) and allowed to adhere overnight. The cells were then incubated with trastuzumab ( Roche, Basel, Switzerland), T-DM1 (ado-trastuzumab-emtansine, Genentech, San Francisco, CA, USA), MH3-B1 / rGel or rGel (expressed and purified as described previously 13,20 ) were incubated at increasing concentrations for 72 h, and cell viability was assessed by MTT assay as described previously. 21 Calculating IC from S-curve 50 Value (fitting model: a / (1+exp(-(x-x0) / b)).

[0121] Western blot analysis. Total cell extracts were obtained and analyzed by Western blot as described previously. 19 .use Turbo TM Western blot transfer system (Bio-Rad Laboratories, CA, USA) was used for western blot transfer. Cellular protein expression was detected using EGFR (#4267), HER2 (#2165), HER3 (#12708), HSP90 (#4877) antibodies from Cell Signaling Technology (Danvers, MA, USA), Rab5 (610281) and Rab11 (610656) antibodies from BD Biosciences (San Jose, CA, USA), and Rab4 (R5780) antibody from Sigma-Aldrich. Protein expression was associated with γ-tubulin as detected by antibody (#T6557) from Sigma-Aldrich. Supersignal West Dura Extended duration Substrate (Thermo Scientific, Rockford, IL, USA) and ChemiDoc were used. TM Protein bands on the membrane were detected by a densitometer (Bio-Rad). Protein expression was quantified using ImageLab 4.1 (Bio-Rad) (software). The expression of each protein was calculated relative to the highest expressing cell line.

[0122] Correlation analysis. The relative expression of HER2, HER3, EGFR, Rab4, Rab5, Rab11 and HSP90 in the cell lines was compared with that of 1 / IC 50The sensitivity of the cell lines to two HER2-targeted therapies as measured by the HER2-targeted (T-DM1) or targeted index (TI) (MH3-B1 / rGel) was plotted and linear regression was evaluated. Several proteins can affect T-DM1 or MH3-B1 / rGel toxicity together with HER2. However, the magnitude of the effect may be different compared to HER2. It was evaluated whether the 1 / IC linear correlation with HER2 could be improved by incorporating the relative expression of other proteins (HER3, EGFR, Rab4, Rab5, Rab11, and HSP90) into the regression. 50 R obtained by (T-DM1) or TI (MH3-B1 / rGel) 2 The contribution factor of each protein together with HER2 was gradually reduced from 1 to 0, and the following formula was used to establish these regression curves:

[0123] For a curve with a positive slope, HER2 x (1-(1-protein) x F), and

[0124] For a curve with a negative slope, HER2 / (1-(1-protein) x F)

[0125] where HER2 is the relative expression of HER2, Protein is the relative expression of the protein of interest, and F is the contribution factor ranging from 1 to 0.

[0126] R 2 The R values ​​were plotted as a function of the contribution factor of each protein. 2 Compared with the above, the contribution factor leads to R 2 The increased proteins were incorporated into the final regression curve for T-DM1 and MH3-B1 / rGel sensitivity in order to set the highest correlation with T-DM1 and MH3-B1 / rGel sensitivity (by R 2 A combination of expression parameters (measure).

[0127] result

[0128] The efficacy of T-DM1 and MH3-B1 / rGel was independent of trastuzumab sensitivity. In contrast to the low expression reported in HER2-negative MDA-MB-231, strong expression of HER2 was documented in the five HER2-expressing cell lines used in this study ( Figure 1A ) 22 The antiproliferative effects of the HER2-targeting mAb trastuzumab and the intracellularly acting HER2-targeting therapeutic agents T-DM1 and MH3-B1 / rGel in five HER2-positive cell lines were established ( Figure 1B). After 72 h of treatment with trastuzumab, T-DM1, or MH3-B1 / rGel, SK-BR-3 and AU-565 cells were found to be highly sensitive to all three therapeutic agents, whereas SKOV-3 cells were found to be unresponsive to trastuzumab and to exhibit low sensitivity to T-DM1 and MH3-B1 / rGel, as indicated by the relatively high IC values ​​of 1.2 μg / ml, respectively. 50 and a low TI of 2.4 50 As demonstrated (Fig. 1 and 2B). It was found that HCC1954 and MDA-MB-453 cells all had low to moderate sensitivity to trastuzumab treatment, but the responses to the therapeutic agents targeting HER2 acting in the cells were different, HCC1954 cells all showed high sensitivity to both T-DM1 and MH3-B1 / rGel, while MDA-MB-453 cells showed low sensitivity to these two drugs (Fig. 1 and 2B). Therefore, there was no clear connection between the sensitivity to trastuzumab and the sensitivity to T-DM1 and MH3-B1 / rGel in five cell lines (Fig. 1 and 2B). Even though T-DM1 and MH3-B1 / rGel had significantly different action points in the cells, consistency was still shown between the sensitivity to these two therapeutic agents in the cell lines, wherein the high / low response to one of the two therapeutic agents seemed to predict a similar high / low response to the other.

[0129] Based on these findings, the cell lines were divided into three categories; (i) highly sensitive to trastuzumab, T-DM1, and MH3-B1 / rGel (SK-BR-3 and AU-565), (ii) low / moderately sensitive to trastuzumab, T-DM1, and MH3-B1 / rGel (SKOV-3 and MDA-MB-453), and (iii) low / moderately sensitive to trastuzumab but highly sensitive to T-DM1 and MH3-B1 / rGel (HCC1954) ( Figure 2A ).

[0130] HER2 expression was more strongly correlated with T-DM1 toxicity than with MH3-B1 / rGel toxicity. HER2 expression is critical for both T-DM1 and MH3-B1 / rGel toxicity. However, due to differences in drug processing between cells (e.g., uptake, intracellular transport, and interaction with intracellular drug targets), expression levels may not necessarily correlate directly with drug sensitivity. Quantification of HER2 expression in the five cell lines showed that AU-565 had the highest HER2 expression level, followed by HCC1954 (0.9) and SK-BR-3 (0.8) ( Figure 2Cand D1). HER2 expression in SKOV-3 cells was reduced by 50% compared with AU-565, and MDA-MB-453 was found to be the cell line with the lowest HER2 expression in this group (0.4) ( Figure 2C and D1). The HER2 expression levels reported here are consistent with recent reports 22,23 In addition, a linear relationship was found between HER2 expression and sensitivity to T-DM1 and MH3-B1 / rGel among the cell lines, resulting in an R 2 The value was 0.926, and the R 2 The value was 0.800 (Figure 2E1 and E2).

[0131] HER3 can serve as an additional biomarker to HER2 for T-DM1 sensitivity. HER2 is known to complex with other members of the EGFR family. Therefore, HER3 and EGFR were quantified to examine the relationship between T-DM1 and MH3-B1 / rGel toxicity and the expression of these two members of the EGFR family. The selected panel of cell lines was found to differ greatly in their HER3 and EGFR expression levels ( Figure 2C , 2D2, and 2D3). However, the levels of HER3 or EGFR were not significantly correlated with the response to T-DM1 ( Figure 3 A1 and B1) or MH3-B1 / rGel( Figure 3 No significant correlation was found between the sensitivity of C1 and D1). We further evaluated whether EGFR and HER3, together with HER2, could be associated with T-DM1 and MH3-B1 / rGel sensitivity. 50 The R of linear regression of (T-DM1) and HER2 and HER3 with increasing contribution 2 The values ​​showed that compared with HER2 alone (R 2 =0.926, Figure 2E1), when HER3 expression was included in the correlation analysis with a contribution factor of 0.2, R 2 Higher, 0.953( Figure 3 A2 and 3A3). By incorporating the increasing influence factor EGFR into the regression analysis between T-DM1 sensitivity and HER2 expression, no increase in linear correlation was found ( Figure 3 B2). The effect of EGFR expression in the regression between T-DM1 and HER2 x HER3 (contribution factor 0.2) was also evaluated. Here again, it was found that R 2 The values ​​were smaller than the R observed using only HER2 and HER3 (contribution factor 0.2). 2 value( Figure 3 B3).

[0132] For MH3-B1 / rGel sensitivity, HER3 and EGFR can serve as additional biomarkers to HER2. Incorporating the contribution of EGFR and HER3 into the regression analysis between MH3-B1 / rGel sensitivity and HER2 expression resulted in R 2 The value increased (HER2 x HER3 with a contribution factor of 0.4 R 2 = 0.970, and the R of EGFR with a contribution factor of 0.3 for HER2 x 2 =0.826) (Figures 2E2, 3C2, 3C3, 3D2, and 3D3). Incorporating the effect of HER3 expression with increasing contribution factors into the regression between HER2 and EGFR (contribution factor 0.3) and MH3-B1 / rGel sensitivity showed an increased correlation, as indicated by the increased R 2 The maximum value (R 2 =0.997, Figure 3 E1 and 3E2).

[0133] Cell lines expressing HER2 differ in their expression levels of proteins involved in endocytic trafficking. Since T-DM1 and MH3B1 / rGel rely on internalization and intracellular trafficking in order to exert their intracellular mechanisms of action, proteins involved in the endocytic machinery were quantified in this panel of cell lines. These proteins include Rab5 ( Figure 4A and B); involved in the delivery of cargo from the plasma membrane to early endosomes and endosomal fusion, Rab4; involved in the recycling of cargo from early endosomes ( Figure 4A and C), HSP90( Figure 4A and D), reported to regulate HER2 recycling, as well as Rab11; involved in recycling via perinuclear recycling endosomes and plasma membrane-Golgi transport ( Figure 4A and E) 24,25 The expression levels of these proteins showed great variation between cell lines, and no simple correlation was found between the expression levels.

[0134] Rab5 and Rab4 can be used as additional biomarkers to HER2 to predict T-DM1 sensitivity. We further evaluated whether the proteins involved in the endocytic machinery studied (Figure 4) had an impact on T-DM1 sensitivity in these cell lines. Rab5 expression levels were found to be 2.5-3 times higher in the highly T-DM1-sensitive SK-BR-3 and AU-565 cells than in the other cell lines in this group ( Figure 4A A relatively weak correlation was found between T-DM1 toxicity and Rab5 expression (R 2 =0.643)( Figure 5 A1). A linear regression curve was established between T-DM1 toxicity and HER2 expression and the increasing contribution factor Rab5 expression, indicating that Rab5 and HER2 together affect T-DM1 toxicity ( Figure 5 A2) When the contribution factor of added Rab5 was 0.3, the maximum R of HER2 and Rab5 was found. 2 value( Figure 5 A2), by including a 30% contribution from Rab5, R 2 Increased from 0.926 to 0.986 ( Figure 5 A3). No linear correlation was found between Rab4 expression and T-DM1 sensitivity (R2 = 0.088, Figure 5 B1) When T-DM1 sensitivity was associated with HER2 at a contribution factor of 0.4 for Rab4, R 2 The value increased slightly ( Figure 5 B2 and 5B3). We also investigated whether Rab4, together with HER2, was negatively correlated with T-DM1 sensitivity. However, the R 2 Compared with the values, no R was found when 1 / Rab4 expression was incorporated into the regression formula. 2 The linear regression of HSP90 expression and T-DM1 sensitivity also showed that R 2 A poor correlation of 0.266 ( Figure 5 C1) and compared with R obtained with HER2 alone 2 Compared with the values, no R 2 Value increase ( Figure 5 C2). It was found that there was a negative linear correlation between Rab11 expression and T-DM1 sensitivity (R 2 =0.459)( Figure 5 D1). Compared with the R obtained with HER2 alone 2 Compared with the values, linear regression between T-DM1 sensitivity and increasing expression of HER2 and contributing factor 1 / Rab11 showed R 2 The values ​​barely increased (0.929 and 0.926, Figure 5 D2 and 5D3).

[0135] like Figure 5As shown in Figure 2, the expression levels of Rab5 and Rab4 were indicated individually along with HER2 as possible biomarkers for T-DM1 sensitivity. It was then evaluated whether combining Rab5 and Rab4 with HER2 further increased the correlation with T-DM1 sensitivity. However, compared to the results observed with HER2 x 0.3 Rab5, no R was found when the effect of Rab4 was incorporated into the regression formula. 2 In summary, the best linear correlation with T-DM1 sensitivity was found when HER2 was combined only with Rab5 with an impact factor of 0.3 (R 2 =0.986, Figure 5 A3).

[0136] For MH3-B1 / rGel sensitivity, Rab5, Rab4, HSP90, and Rab11 can all be used as additional biomarkers for HER2. The cellular expression levels of Rab5, Rab4, HSP90, and Rab11 (Figure 4) were also plotted against MH3-B1 / rGel sensitivity (measured by TI) ( Figure 6 A linear correlation between Rab5 and TI was detected between the cell lines (R 2 =0.486, Figure 6 A1). Incorporating the increasing contribution factor of Rab5 into the established linear regression curve of HER2 and MH3-B1 / rGel toxicity indicates that Rab5 and HER2 together affect MH3-B1 / rGel toxicity ( Figure 6 A2), as compared with regression using HER2 alone (R 2 =0.800, Figure 2E2), R 2 By including a 30% contribution of Rab5, the highest R 2 The value is 0.856( Figure 6 A2 and 6A3), as also observed for T-DM1 association ( Figure 5 A3). No correlation was found between Rab4 expression and MH3B1 / rGel sensitivity (R 2 =0.024, Figure 6 B1). However, using Rab4 expression with increasing impact factor as an additional biomarker to HER2 enhanced the linear correlation with TI compared to HER2 alone. The largest R was obtained by adding Rab4 with an impact factor of 0.6 to the regression analysis of HER2 and TI. 2 The value is 0.930( Figure 6B1 and 6B2). HSP90 and 1 / Rab11 were also shown to be correlated with MH3B1 / rGel sensitivity, although not strongly (R2 = 0.552 for HSP90 and R2 = 0.406 for 1 / Rab11, Figure 6 C1 and D1). It further shows that HSP90 and 1 / Rab11 increase the correlation between HER2 expression and MH3B1 / rGel sensitivity one by one, and both proteins obtain the maximum R when the contribution factor is 1. 2 value( Figure 6 C2, C3, D2 and D3).

[0137] like Figure 6 As shown, Rab5, Rab4, HSP90 and 1 / Rab11 were all indicated as possible biomarkers of MH3B1 / rGel sensitivity one by one along with HER2. It was further investigated whether the combination of these 4 biomarkers together with HER2 would further increase the correlation with MH3B1 / rGel sensitivity. The order in which the different proteins were combined into the regression formula was based on the pathways of endocytosis and transport, starting with Rab5 (endocytosis) and then adding Rab4 (early recycling), HSP90 (early recycling) and 1 / Rab11 (late recycling). As Figure 6 As shown in A3, Rab5 (impact factor 0.3) and HER2 were well correlated with MH3B1 / rGel sensitivity (R 2 =0.856). However, adding the increasing influence factor Rab4 expression to the regression analysis increased the R 2 When Rab4 was added to HER2 and 0.3x Rab5 with a contribution factor of 0.6, the maximum R 2 The value is 0.938( Figure 7 A1 and A2). HSP90 expression was further incorporated into the regression analysis of HER2, Rab5, and Rab4. The maximum R was obtained by incorporating 80% contribution of HSP90 into the regression analysis between MH3B1 / rGel sensitivity and HER2, Rab5 (contribution factor 0.3), and Rab4 (contribution factor 0.6). 2 The value is 0.974( Figure 7 B) Figure 6 As shown in D, 1 / Rab11 and HER2 together correlated well with MH3B1 / rGel sensitivity (R 2 =0.894). Adding the effect of 1 / Rab11 expression to the regression analysis between MH3B1 / rGel sensitivity and HER2, Rab5, Rab4, and HSP90 expression also increased the R 2 Values, such as Figure 7When MH3B1 / rGel sensitivity was associated with HER2, Rab5 (contribution factor 0.3), Rab4 (contribution factor 0.6), and HSP90 (contribution factor 0.8), the best correlation between 1 / Rab11 expression and other proteins and MH3B1 / rGel sensitivity was found at an impact factor of 0.4 ( Figure 7 C2), producing the maximum R 2 The value is 0.993( Figure 7 C2). A regression analysis was also performed by adding the contribution of the different proteins in a non-biological order, without affecting the R obtained when correlated with MH3B1 / rGel sensitivity. 2 Overall, the best correlation between MH3-B1 / rGel toxicity and protein expression levels was found when the contributions of the different proteins were added in a biologically logical order, when TI was plotted against (R 2 =0.993)( Figure 7 C2):

[0138] Relative HER2 expression x

[0139] (1-(1-relative Rab5 expression) x 0.3) x

[0140] (1-(1-relative Rab4 expression) x 0.6) x

[0141] (1-(1-relative HSP90 expression) x 0.8) /

[0142] (1-(1-(1 / relative Rab11 expression)) x 0.4)

[0143] The field of biomarker-driven personalized cancer therapy is rapidly evolving with the growing number of clinically approved targeted anticancer treatments. Overall, the efficacy of drug-based personalized cancer therapies depends on the reliability of the selected biomarkers in predicting prognosis, response, and / or resistance. The development of the HER2-targeting mAb trastuzumab represents a success story in the field of biomarker-driven personalized cancer therapy, as breast cancer patients classified as HER2-positive (~20% of all breast cancers) routinely receive trastuzumab as part of their treatment. 26 Another example is the evaluation of BCR-ABL fusion in chronic myeloid leukemia (CML) for the use of imatinib, or the evaluation of EGFR and RAS wild-type expression for the use of cetuximab in colorectal cancer. 27 .

[0144] Most targeted drugs currently approved for the treatment of cancer are mAbs or small molecule inhibitors whose drug targets also represent the targets of the mechanism of action. The targets themselves represent clear biomarkers for treatment with these drugs, even though additional biomarkers may be needed to deselect patients who may experience resistance or low tolerance. However, drug development in cancer therapy is currently moving towards more complex targeted therapeutics composed of both a targeting moiety and a cytotoxic component, such as cytostatic drugs (ADCs) or toxins (targeted toxins). For these multifunctional therapeutics, additional biomarkers related to intracellular transport and / or cytotoxic mechanism of action may influence the therapeutic effect. 15 This is demonstrated herein by the lack of concordance between trastuzumab and T-DM1 / MH3-B1 / rGel sensitivity in a selected panel of HER2-positive cell lines.

[0145] We report here a strong linear correlation between cellular HER2 expression and response to T-DM1 (Figure 2E1). This is consistent with several clinical studies showing that the response rate to T-DM1 was higher in patients with HER2 mRNA levels above the median compared with the subgroup below the median. 16,17,28 This paper shows that for T-DM1, the relationship between drug activity and HER2 expression is better than that of MH3-B1 / rGel. 2 The correlation measured by the R values ​​was stronger and may be caused by differences in the cytotoxic components of these drugs. The cytotoxic component of T-DM1 (DM1) is a relatively small lipophilic drug that, once released from the trastuzumab component in endocytic vesicles, is able to diffuse across the endocytic membrane and enter the cytosol where it exerts its effects on microtubules. This is in stark contrast to the cytotoxic portion of MH3-B1 / rGel, which is a 28 kDa hydrophilic type I ribosome-inactivating protein toxin (gelonin) that lacks an efficient transport mechanism into the cytosol but enters the cytosol to some extent through an unknown mechanism. The higher R values ​​obtained by correlation analysis of T-DM1 and HER2 expression compared with MH3-B1 / rGel and HER2 expression 2 The values ​​may reflect differences in the endocytic escape mechanisms between the two drugs, with more obstacles indicative of the gelonin pathway. The intracellular release pathway of gelonin is more complex compared to DM1, which is also reflected in the number of proteins investigated for their effect on MH3-B1 / rGel sensitivity (Rab5, Rab4, HSP90, and Rab11), compared to only Rab5 and Rab4 for T-DM1.

[0146] This paper shows that the sensitivity of cells to both T-DM1 and MH3-B1 / rGel is associated with HER3 in addition to HER2. It has been previously reported that the therapeutic effect of T-DM1 in a phase III clinical trial was similar to that in the HER3 expression subgroup 17 This is consistent with the data presented here, where no correlation was found between HER3 expression alone and T-DM1 sensitivity ( Figure 3 A1). However, this report focuses on mathematical methods to combine biomarkers with different contributing factors. These calculations suggest that the combination of HER3 and HER2 could serve as a better biomarker for T-DM1 response than HER2 alone. HER3 is considered the preferred dimerization partner of HER2, and heterodimers are reported to induce highly active tyrosine kinase signaling. 29 . Therefore, the correlation between T-DM1 and MH3-B1 / rGel sensitivity and HER3 expression and HER2 together may reflect the indirect inhibition of these heterodimers by trastuzumab and MH3-B1 after binding to HER2. In contrast to the full-length antibody trastuzumab in T-DM1, MH3-B1 / rGel consists of a single-chain fv fragment. Therefore, binding of MH3-B1 to HER2 as part of a heterodimer (both HER2 / HER3 and HER2 / EGFR) cannot be excluded. This is also shown by the following results: compared with T-DM1 (R 2 From 0.926 to 0.953, Figure 8 A1), Correlation between MH-3B1 / rGel sensitivity and HER3 expression in addition to HER2 ( Figure 8 B1) is significantly stronger (R 2 When MH3-B1 / rGel sensitivity was correlated with EGFR in addition to HER2 and HER3, R 2 There was a slight increase in the values ​​for T-DM1, but no such correlation was found for T-DM1 ( Figure 8 A1 and B1).

[0147] Rab5 localizes to early endosomes and regulates endocytosis of clathrin-coated vesicles and endosomal fusion 18 This paper shows that the sensitivity of T-DM1 and MH3-B1 / rGel depends on Rab5 ( Figure 5 A3 and 6A3). Rab5 and HER2 together have similar effects on two HER2-targeting therapeutic agents ( Figure 8A2 and B2) may be related to the early function of Rab5 in endocytosis and subsequent endocytic trafficking, where both drugs likely follow the same HER2-mediated endocytic pathway. Rab4 also plays a role early in the endocytic pathway by controlling recycling from early endosomes. 30 , and are shown here to be associated with T-DM1 and MH3-B1 / rGel sensitivity together with HER2 ( Figure 5 B3 and 6B3). Rapid recycling of HER2 can increase drug uptake into cells, but also passively localize the drug to early endosomes within the cell.

[0148] When incorporated with Rab4 and HER2, R 2 Increased from 0.830 to 0.930 ( Figure 8 B2), indicating that cytosolic translocation from early endosomes is the mechanism of cytosolic release of MH3-B1 / rGel. Rab4 other than HER2 contributes little to T-DM1 sensitivity (R 2 From 0.926 to 0.944, Figure 8 A2), indicating that a certain amount of -emtansine was also released from early endosomes, suggesting that the cytosolic translocation of -emtansine is not entirely dependent on the lysosomal sequestration of the trastuzumab portion of T-DM1 as previously reported. 7,10 It has been previously demonstrated that Rab5 expression predicts poor outcome in breast cancer patients and that Rab5 / Rab4 recycling promotes extracellular matrix invasion and metastasis 31 Therefore, the present results may indicate that patients with Rab5 / Rab4 and HER2-positive breast cancer are promising candidates for T-DM1- and MH3-B1 / rGel-based therapies.

[0149] HSP90 is a HER2 chaperone and is thought to inhibit HER2 degradation through multiple mechanisms, including rapid recycling 32,33 . This article shows that HSP90 and HER2 are associated with MH3-B1 / rGel toxicity ( Figure 8 B2), whereas no such correlation was found for T-DM1 ( Figure 8 A2). As commented on the differences in Rab4 dependency, the differences in the cytotoxic effects of HSP90 on these drugs may reflect differences in the cytosolic translocation mechanisms. The differences may also be due to the different HER2-targeting moieties between these drugs. On the other hand, Rab11 localizes to the endocytic recycling compartment (ERC) and then acts by recycling cargo back to the plasma membrane during endocytosis. 34 Here, we found a negative correlation between MH3-B1 / rGel efficacy and Rab11 expression ( Figure 6B), indicating that recycling and subsequent exocytosis inhibits MH3-B1 / rGel efficacy. Lack of effect of Rab11 and HER2 together on T-DM1 toxicity ( Figure 5 D) This may indicate that T-DM1 and MH3-B1 / rGel follow different intracellular pathways, consistent with the chemical nature of their cytotoxic moieties. For example, DM1 may plausibly escape endocytic vesicles before accumulating in Rab11-positive recycling endosomes.

[0150] In total, six proteins were tested here along with HER2 as potential biomarkers for MH3-B1 / rGel and T-DM1 response. The biomarkers tested here were divided into two groups reflecting either the targeting moiety of the drug targeting HER2 (EGFR and HER3) or the intracellular trafficking component of the drug (Rab5, Rab4, HSP90, and Rab11) ( Figure 8 The best correlation with drug sensitivity was obtained by combining the biomarkers in these groups, and no increase in correlation with drug sensitivity was shown by combining the two groups of biomarkers (data not shown). These results suggest that the proteins in the two groups are not completely independent, which is not surprising, as endocytic trafficking of drugs obviously depends on cellular binding and endocytosis. Therefore, HER2 as a biomarker should be combined with HER3 and EGFR, or Rab4, Rab5, HSP90, and 1 / Rab11 to predict cellular sensitivity to T-DM1 and MH3-B1 / rGel ( Figure 8 ). Figure 3 , 5 , 6 and 7 illustrate the impact of adding these six proteins as biomarkers with increasing contribution factors relative to HER2. However, the importance of different proteins can be compared, e.g. Figure 8 A and 8B, where the R2 correlation data for both sets of biomarkers are included in the same figure. By adding the expression of the extracellular protein HER3 or the intracellular proteins Rab5 and Rab4 to the expression of HER2 as biomarkers, it was found that the correlation of drug sensitivity was improved for both drugs targeting HER2, but the R 2 The impact of different values, such as Figure 8 A, B, and C. MH3-B1 / rGel sensitivity was also shown to be dependent to some extent on EGFR expression in addition to HER2 and HER3, and on HSP90 and 1 / Rab11 expression in addition to HER2, Rab5, and Rab4. The more complex repertoire of biomarkers associated with MH3-B1 / rGel sensitivity compared with T-DM1 may be due to a greater barrier to cytosolic translocation of MH3-B1 / rGel compared with T-DM1, and may also reflect differences in the HER2-targeting moieties between these drugs.

[0151] In summary, this report shows for the first time that, in addition to HER2, proteins involved in endocytic trafficking can be used to predict responses to therapeutic agents targeting HER2 with intracellular sites of action. However, the effects of different proteins appear to be related to both the HER2-targeting portion of the drug and the intracellular active component, as well as the subsequent endocytic trafficking and cytosolic release mechanisms. Future development of ADCs and other targeted drugs with intracellular mechanisms of action should include a library of drug-dependent biomarkers, and in addition to the most commonly used targeting and resistance markers, markers of uptake and cellular transport should also be included. As used herein, mathematical methods can be used to establish a library of biomarkers with different contribution factors for prognosis and treatment.

[0152] The general inventive concepts described herein are applicable to all antibody drug conjugates (ADCs) and antibody toxin conjugates (immunotoxins). Some preferred drugs that can be administered according to this method are listed in Table 1 (ADCs) and Table 2 (immunotoxins).

[0153] Table 1 - Leading clinical stage ADCs

[0154]

[0155] Table 2 - Leading Clinical Stage Immunotoxins

[0156]

[0157] Example 2

[0158] Patient Population. Pretreatment expression and pathological complete response (pCR) data were available for 52 patients in the T-DM1+pertuzumab (TDM1+P) group and 31 patients in the trastuzumab control (TH) group. For this analysis, patients who progressed, withdrew consent, left the treatment facility, or received non-protocol treatment before surgery were considered non-pCR. The following table shows the pCR rate for the HR subtype in each cohort:

[0159] HR-HER2+ HR+HER2+ TDM1+P 12 / 17 18 / 35 TH 5 / 12 3 / 19

[0160] Expression data. All I-SPY 2 samples were analyzed on one of two Agilent custom arrays (15746 and 32627 designs). All samples in the TDM1+P cohort were analyzed on the 32627 array, while the TH cohort was split between platforms, with 22 samples on the older 15746 platform and 9 samples on the 32627 array. To combine data from both designs, we updated the probe annotations for the 15746 platform (September 2016); and for each platform, expression data were fold-normalized by averaging, so that genes represented by multiple probes were calculated as the average of the probes. The ComBat algorithm was then applied to adjust for platform bias, and data from both platforms were merged. This procedure was performed on pre-treatment data for the first 880 I-SPY 2 patients, regardless of experimental cohort. Combined platform-adjusted data for the TH and TDM1+P cohorts, as well as annotation files for the 32627 and updated 15746 array designs, are included in this delivery.

[0161] Qualified Biomarker Analysis. Normalized platform-corrected pre-treatment expression levels of RAB5A, RAB4A, RAB11A, and HSP90AA1 were first tested individually as specific biomarkers of response to TDM1+P according to the Qualified Biomarker Evaluation (QBE) program.

[0162] Step 1: Evaluation of biomarkers as specific predictors of response to TDM1+P

[0163] Model 1A: pCR in the TDM1+P group Biomarkers

[0164] Model 1B: pCR in the TH cohort Biomarkers

[0165] Model 1C: pCR Treatment + Biomarker + Treatment x Biomarker

[0166] Model 1D: pCR Treatment + Biomarker + Treatment x Biomarker + HR Status

[0167] Of the biomarkers evaluated, only RAB5A was associated with response in the TDM1+P group (likelihood ratio (LR) test p=0.012), but not in the control group (LR test p=0.242). The p value for the interaction between RAB5A expression and treatment was 0.024, which remained <0.05 after adjusting for HR status. The following table summarizes the results of the four biomarkers evaluated.

[0168]

[0169] RAB5A successfully serves as a continuing qualified biomarker and will be evaluated in QBE step 2.

[0170] Step 2: Determine the dichotomy threshold

[0171] We used a Monte Carlo 2-fold cross-validation procedure to determine the threshold that minimized the p-value for the biomarker x treatment interaction. Specifically, for 100 iterations, we randomly selected half of the cases to serve as the training set, balanced across treatment cohort and pCR status. We considered each value between the 10th and 90th percentiles as a potential threshold to dichotomize the training set into “high” vs. “low” RAB5A expression groups; and fitted a series of logistic regression models to assess the biomarker x treatment interaction (Model 1C). We selected the threshold that minimized the LR test p-value for the interaction term in the training set, used it to dichotomize the test set, and assessed the significance of the biomarker x treatment interaction in the test set. We then pooled the LR p-values ​​from the 100 test sets using the logit method; and then selected the threshold that produced the minimum combined LR test p-value.

[0172] Using this procedure, a threshold of 9.76 was selected. Fig. 9 As a dichotomous variable, having high RAB5A levels was also associated with response in TDM1+P (OR = 5.99 (95% CI: 1.23-40.27), Fisher's exact test p = 0.01), but not in the control cohort (OR: 0 (95% CI: 0-1.74), Fisher's exact test p = 0.06); and with a biomarker x treatment interaction term of LR p = 0.001.

[0173] Although 9.76 was the optimal threshold determined by this procedure, only 2 patients in the TH cohort had RAB5A levels < 9.76. This may be due in part to the difference in RAB5A expression between the TH and TDM1+P cohorts, with RAB5A levels significantly higher in the TH cohort than in the TDM1+P cohort. The array design may have contributed to this difference. We might consider evaluating the performance of the biomarker only within the TDM1+P cohort (rather than using the model that evaluated the biomarker x treatment interaction prespecified in the analysis plan). Using a Monte Carlo procedure similar to the method described above (but fitting Model 1A only in TDM1+P), the optimal threshold that would have been selected would still be 9.76.

[0174] Step 3: Bayesian estimation of pCR rate within the RAB5A group in the setting of HER2+ graduation signature

[0175] Model 2: pCR HR+RAB5A+treatment+HR xtreatment+RAB5A xtreatment

[0176] When we applied the determined optimal threshold (9.76) to dichotomize patients into RAB5A-high (>=9.76) and RAB5A-low (<9.76) groups, the Bayesian estimated pCR probability was 68% in the TCM1+P group and 24% in the control group of RAB5A-high patients. In contrast, the estimated pCR probability was 28% in the RAB5A-low subset in the TDM1+P group and 42% in the TH group. For comparison, using the same model, the estimated pCR probability for the entire HER2+ group was 61% in the TDM1+P group and 27% in the TH group. The Bayesian pCR probability curves are shown in Figure 2. Fig.10 Shown in.

[0177] Example 3

[0178] This example shows the correlation between HSP90, Rab11a, Rab4A and Rab5a expression profiles and treatment outcomes in TH- and T-DM1+P groups in the 1-SPY2 study. The RNA expression profiles from the 1-SPY-2 data were evaluated for the correlation between pCR and HSP90, Rab11A, Rab4A and Rab5a expression levels in two treatment groups receiving T-trastuzumab + chemotherapy (TH) or trastuzumab-emtasin + pertuzumab + chemotherapy (TDM1+P). There were significant differences in Rab5A expression levels between pCR 0 and pCR 1 groups in the T-DM1+P group. In any of the two groups, there were no significant differences in any other proteins.

[0179] Trastuzumab + chemotherapy (TH)

[0180]

[0181] Trastuzumab-emtasin + pertuzumab + chemotherapy

[0182]

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[0218] All publications, patents, patent applications and accession numbers mentioned in the above specification are incorporated herein by reference in their entirety. Although the present invention has been described in conjunction with specific embodiments, it should be understood that the claimed invention should not be unduly limited to these specific embodiments. In fact, various modifications and variations of the described compositions and methods of the present invention will be apparent to those of ordinary skill in the art and are intended to fall within the scope of the appended claims.

Claims

1. Use of a reagent for detecting the expression level of RAB5 in the preparation of a diagnostic kit for an in vitro method for determining whether human cancer cells respond to: (a) an immunoconjugate targeting a surface antigen on the cancer cell, wherein the immunoconjugate is an antigen binding protein linked or bound to a drug or toxin, or (b) an antigen binding protein targeting a surface antigen on the cancer cell, wherein the antigen binding protein does not contain a drug or a toxin, the method comprising: The expression level of RAB5 in cancer cells obtained from the subject is measured by an in vitro assay, wherein an increased expression level of RAB5 compared to a dichotomous threshold value indicates responsiveness to the immunoconjugate, and a decreased expression level of RAB5 compared to the dichotomous threshold value indicates responsiveness to the antigen binding protein.

2. The use according to claim 1, wherein RAB5 is selected from the group consisting of RAB5A, RAB5B and RAB5C.

3. The use according to claim 1, wherein Measuring the expression level of RAB5 in the cancer cells includes measuring the level of RAB5 mRNA or protein.

4. The use according to any one of claims 1 to 3, wherein The method further comprises the step of determining the expression level of one or more of RAB4, RAB11 or HSP90.

5. The use according to claim 4, wherein The expression level of one or more of RAB4, RAB11 or HSP90 is incorporated into an expression index with the expression level of RAB5.

6. The use according to any one of claims 1 to 3, wherein The cancer cells are: (a) obtained from a surgical tumor sample, a biopsy sample or a blood sample; and / or (b) is selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

7. The use according to any one of claims 1 to 3, wherein The cancer cells are breast cancer cells.

8. The use according to claim 4, wherein The cancer cells are: (a) obtained from a surgical tumor sample, a biopsy sample or a blood sample; and / or (b) is selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

9. The use according to claim 4, wherein The cancer cells are breast cancer cells.

10. The use according to claim 5, wherein: The cancer cells are: (a) obtained from a surgical tumor sample, a biopsy sample or a blood sample; and / or (b) is selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

11. The use according to claim 5, wherein: The cancer cells are breast cancer cells.

12. The use according to any one of claims 1 to 3, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

13. The use according to claim 4, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

14. The use according to claim 5, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

15. The use according to claim 6, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

16. The use according to claim 7, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

17. The use according to claim 8, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

18. The use according to claim 9, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

19. The use according to claim 10, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

20. The use according to claim 11, wherein The method further comprises the step of determining the expression of a surface antigen on the cancer cell.

21. The use according to claim 12, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

22. The use according to claim 12, wherein: The surface antigen is HER2.

23. The use according to claim 13, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

24. The use according to claim 13, wherein The surface antigen is HER2.

25. The use according to claim 14, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

26. The use according to claim 14, wherein The surface antigen is HER2.

27. The use according to claim 15, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

28. The use according to claim 15, wherein The surface antigen is HER2.

29. The use according to claim 16, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

30. The use according to claim 16, wherein The surface antigen is HER2.

31. The use according to claim 17, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

32. The use according to claim 17, wherein The surface antigen is HER2.

33. The use according to claim 18, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

34. The use according to claim 18, wherein The surface antigen is HER2.

35. The use according to claim 19, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

36. The use according to claim 19, wherein The surface antigen is HER2.

37. The use according to claim 20, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets one of epidermal growth factor receptor, HER2, and HER3.

38. The use according to claim 20, wherein The surface antigen is HER2.

39. Use of an immunoconjugate targeting a surface antigen of a cancer cell in the preparation of a medicament for treating cancer in a patient identified as having cancer cells expressing said surface antigen and exhibiting an increased level of RAB5 expression compared to the dichotomous threshold of claim 1, as determined by the in vitro method of claim 1, wherein: The immunoconjugate is an antigen binding protein linked or associated with a drug or toxin.

40. Use of an antigen binding protein targeting a surface antigen of a cancer cell in the preparation of a medicament for treating cancer in a patient identified as having cancer cells expressing the surface antigen and exhibiting a reduced level of RAB5 expression compared to the dichotomous threshold of claim 1, as determined by the in vitro method of claim 1, wherein: The antigen binding protein does not contain drugs or toxins.

41. The use according to claim 39, wherein The immunoconjugate binds to a cell surface antigen selected from the group consisting of HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA, CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM and MSLN.

42. The use according to claim 40, wherein The antigen binding protein binds to a cell surface antigen selected from the group consisting of HER2, HER3, EGFR, CD3ε, CD19, CD22, CD25, CD30, CD33, CD56, CEA, CD74, CD79a, CD138, NaPi2b, gpNMB, TROP-2, GUCY2C, Nectin-4, SC-16, STEAP1, FRα, IL-2R, EpCAM and MSLN.

43. The use according to claim 39 or 41, wherein The immunoconjugate is (a) an antibody drug conjugate selected from the group consisting of trastuzumab emtansine, vetin-brentuximab, inotuzumab, pinatuzumab vedotin, polatuzumab vedotin, lifastuzumab vedotin, glembatuzumab vedotin, coltuximab bravtansine, lorvotuzumab mertansine, indatuximab ravtansine, sacitizumab govitican, labetuzumab govitican, milatuzumab doxorubicin, indusatumab vedotin, vadastuximab talirine, denintuzumab mafodotin, enfortumab vedotin, rovalpituzumab tesirine, vandortuzumab vedotin, mirvetuximabsoravtansine, ABT-414, IMGN289, and AMG595; or (b) an immunotoxin selected from the group consisting of MH3-B1 / rGel, denileukin, moxetumomabpasudotox, oportuzumab monotox, resimmune, LMB-2, DT2219ARL, HuM195 / rGel, RG7787, MOC31PE and D2C7-IT.

44. The use according to any one of claims 39 to 42, wherein The cancer cells are selected from the group consisting of breast cancer cells, colorectal cancer cells, lung cancer cells, prostate cancer cells, melanoma cells, glioblastoma cells, pancreatic cancer cells, renal cell cancer cells, ovarian cancer cells, bladder cancer cells, endometrial cancer cells, gastrointestinal cancer cells, mesothelioma cells, multiple myeloma cells, acute myeloid leukemia cells, acute lymphoblastic leukemia cells and non-Hodgkin's lymphoma.

45. The use according to any one of claims 39 to 42, wherein The cancer cells are breast cancer cells.

46. ​​The use according to claim 39 or 41, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets the surface antigen.

47. The use according to claim 39 or 41, wherein The surface antigen is HER2.

48. The use according to claim 39 or 41, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets the surface antigen.

49. The use according to claim 39 or 41, wherein The surface antigen is HER2.

50. The use according to claim 43, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the antibody drug conjugate or immunotoxin targets the surface antigen.

51. The use according to claim 43, wherein The surface antigen is HER2.

52. The use according to claim 44, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets the surface antigen.

53. The use according to claim 44, wherein The surface antigen is HER2.

54. The use according to claim 45, wherein The surface antigen is selected from the group consisting of at least one of epidermal growth factor receptor, HER2, HER3, and combinations thereof, and the immunoconjugate or immunotoxin targets the surface antigen.

55. The use according to claim 45, wherein The surface antigen is HER2.

56. The use according to claim 46, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

57. The use according to claim 46, wherein The immunoconjugate is trastuzumab-emtansine.

58. The use according to claim 47, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

59. The use according to claim 47, wherein The immunoconjugate is trastuzumab-emtansine.

60. The use according to claim 48, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

61. The use according to claim 48, wherein The immunoconjugate is trastuzumab-emtansine.

62. The use according to claim 49, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

63. The use according to claim 49, wherein The immunoconjugate is trastuzumab-emtansine.

64. The use according to claim 50, wherein The antibody drug conjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

65. The use according to claim 50, wherein The immunoconjugate is trastuzumab-emtansine.

66. The use according to claim 51, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

67. The use according to claim 51, wherein The immunoconjugate is trastuzumab-emtansine.

68. The use according to claim 52, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

69. The use according to claim 52, wherein The immunoconjugate is trastuzumab-emtansine.

70. The use according to claim 53, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

71. The use according to claim 53, wherein The immunoconjugate is trastuzumab-emtansine.

72. The use according to claim 54, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

73. The use according to claim 54, wherein The immunoconjugate is trastuzumab-emtansine.

74. The use according to claim 55, wherein The immunoconjugate or immunotoxin is selected from the group consisting of trastuzumab-emtansine, ABT-414, IMGN289, AMG595 and AMG595.

75. The use according to claim 55, wherein The immunoconjugate is trastuzumab-emtansine.

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