Sensitizing tumors to checkpoint inhibitors by redox state modulators

Abstract

The present invention relates to methods of sensitizing a subject suffering from cancer or a precancerous stage to a treatment with an immune checkpoint inhibitor, and agents for use in sensitizing a subject to such a treatment.

Description

Technical Field

[0001] The present invention relates to methods for sensitizing a subject having cancer or a pre - cancerous condition to treatment with an immune checkpoint inhibitor, and reagents for sensitizing a subject to such treatment. Background Art

[0002] Cancer immunotherapy involves the attack of a patient's immune system on cancer cells. The regulation and activation of T lymphocytes depend on the signaling of T - cell receptors and co - signaling receptors, which transmit positive or negative signals for activation. The immune response of T cells is controlled by the balance of co - stimulatory and inhibitory signals, called immune checkpoints.

[0003] Immunotherapy using immune checkpoint inhibitors is revolutionizing cancer therapy. However, some patients show little or no improvement when receiving immune checkpoint inhibitor treatment. Thus, there is still a need for methods to sensitize patients to these treatments. The present invention aims to at least partially meet this need. Summary of the Invention

[0004] The present invention is based on the inventors' unexpected discovery that cancer cells having a heteroplasmic harmful mutation in mitochondrial DNA (mtDNA) may have an altered tumor microenvironment. Specifically, the inventors have demonstrated that cancer cells having harmful mtDNA mutations present at a high mutation load are associated with distinct immune cell populations present in the tumor microenvironment. As discussed in the Examples section of the present application, the inventors have found that the tumor microenvironment containing such cancer cells is enriched in natural killer (NK) cells, monocytes, CD4 + T cells, and immune cells expressing interferon - stimulated genes (ISGs), but has reduced levels of macrophages and tumor - associated neutrophils compared to the tumor microenvironments of cancer cells having no or a low harmful mtDNA mutation load.

[0005] The present inventors believe that the presence of a harmful mtDNA mutation load alters cancer cell metabolism in a manner that modifies the tumor microenvironment, rendering it favorable for the infiltration of certain immune cell populations. As discussed in the Examples section of the present disclosure, the present inventors have identified that cancer cells with heteroplasmic mutations in the MT-ND5 gene exhibit increased levels of reduced nicotinamide adenine dinucleotide (NADH), leading to disruption of the NAD+:NADH ratio and alteration of the cellular redox balance. This may result in a reverse flux of malate dehydrogenase 2 (MDH2) and accumulation of cytoplasm-derived malate via malate dehydrogenase 1 (MDH1). The increased MDH1 activity may drive glycolysis and result in excessive glucose consumption and excessive lactate release. In fact, the present inventors have confirmed that these mutations promote the utilization of pyruvate as a terminal electron acceptor and increase the glycolytic flux driven by an overly reduced NAD pool and NADH shuttling between GAPDH and MDH1, thereby mediating a Warburg-like metabolic shift. Surprisingly, the present inventors found that despite these changes, oxygen consumption and ATP synthesis remained unaffected at a 60% mutation load (also referred to herein as "variant allele frequency" or "VAF"), although the present inventors would have expected these parameters to be affected by a higher mutation load. Without wishing to be bound by this hypothesis, the present inventors believe that these metabolic changes promote the recruitment and / or survival of specific immune cell types (such as those mentioned above) into the tumor, which are less sensitive to alterations in the redox state (e.g., changes in the glucose-to-lactate ratio). The present inventors hypothesize that this reduced sensitivity may be due to the cell's preferential utilization of lactate as a carbon fuel source or lower dependence on glucose.

[0006] The present inventors then initiated a study to determine whether these findings might be relevant to clinical outcomes. Using a mouse model, the present inventors surprisingly confirmed that tumors with a VAF > 40% responded well to PD1 inhibitors, while tumors with little or no VAF responded poorly.

[0007] The present inventors have found that in the context of treatment with immune checkpoint inhibitors (such as PD-1 inhibitors, PD-L1 inhibitors, or CTLA4 inhibitors), this difference in treatment reactivity is effective. These findings are also supported by retrospective studies of small clinical cohorts of human patients who have >50% VAF due to mutations in multiple different mtDNA genes (such as MT-COI, MT-ND4, MT-CYB, MT-TY, and / or the mtDNA regulatory region). The present inventors believe that this difference in reactivity to treatment with immune checkpoint inhibitors (e.g., PD-1 inhibitors, PD-L1 inhibitors, and / or CTLA4 inhibitors) is due to metabolic changes (and resulting changes in the cancer or pre-cancerous immune microenvironment) caused by high VAF that renders cancer cells or pre-cancerous cells in the tumor sensitive to the treatment. Based on these data, the present inventors conclude that cancer or pre-cancer can be made sensitive to treatment with immune checkpoint inhibitors (e.g., PD-1 inhibitors, PD-L1 inhibitors, and / or CTLA4 inhibitors) by mimicking these metabolic changes (i.e., by altering the redox state of the cancer or pre-cancer, such as the lactate-to-glucose ratio in the cancer or pre-cancer).

[0008] The present inventors have further confirmed that when a reagent that alters the redox state (e.g., the lactate-to-glucose ratio) is provided to cancer cells (e.g., melanoma cancer cells), the cancer cells have an increased response to immune checkpoint inhibitor treatment (such as anti-PD1 treatment). Specifically, the present inventors modified wild-type Hcmel12 cells to constitutively express cytoLBnox, which recapitulates key elements of the extracellular mutant Mt-Nd5-associated metabolic phenotype, particularly glucose uptake and lactate release. When transplanted into mice, Hcmel12 cytoLBnox tumors showed comparable time-to-endpoint and endpoint tumor weights to wild-type or Mt-Nd5 mutant tumors. However, when challenged with anti-PD1 treatment, Hcmel12 cytoLBnox tumors recapitulated the Hcmel12 mt-Nd5m.12,436 80％ tumor response, confirming that specific changes in redox metabolism are sufficient to render tumors sensitive to immune checkpoint blockade (e.g., PD-1 inhibitors, PD-L1 inhibitors, and / or CTLA4 inhibitors).

[0009] Furthermore, the present inventors have found that by co-treatment with a compound that reduces the level of tumor-resident neutrophils (such as an anti-Ly6G antibody), the treatment reactivity to immune checkpoint inhibitors can be further (synergistically) enhanced in tumors with high mtDNA mutation burden or expressing cytoLbNOX.

[0010] The inventors have also demonstrated that, as shown in the immunogenic 4434 mouse model, agents that alter the redox state (e.g., the lactate to glucose ratio) in cancer or pre-cancer (such as cytoLbNOX or mitoLbNOX) can increase sensitivity to immune checkpoint inhibitors in cancers that have baseline sensitivity to immune checkpoint inhibitors.

[0011] Accordingly, the present invention provides agents that alter the redox state in cancer or pre-cancer (e.g., alter the lactate to glucose ratio) for sensitizing a subject having cancer or pre-cancer to an immune checkpoint inhibitor.

[0012] There is also provided an immune checkpoint inhibitor for treating a subject having cancer or pre-cancer, wherein the subject has been exposed to an agent that alters the redox state in cancer or pre-cancer (e.g., alters the lactate to glucose ratio).

[0013] The present invention also provides a method for sensitizing a subject having cancer or pre-cancer to an immune checkpoint inhibitor, comprising exposing the subject to an agent that alters the redox state in cancer or pre-cancer (e.g., alters the lactate to glucose ratio).

[0014] There is further provided a method for treating cancer or pre-cancer in a subject, comprising administering an immune checkpoint inhibitor to the subject, wherein the subject has been exposed to an agent that alters the redox state in cancer or pre-cancer (e.g., alters the lactate to glucose ratio).

[0015] The present invention also provides a method for treating cancer or pre-cancer in a subject, comprising:

[0016] (i) exposing the subject to an agent that alters the redox state of cancer or pre-cancer (e.g., alters the lactate to glucose ratio); and

[0017] (ii) administering an immune checkpoint inhibitor to the subject.

[0018] Suitably, the immune checkpoint inhibitor can be selected from the group consisting of: a PD-1 inhibitor, a PD-L1 inhibitor, a PD-L2 inhibitor, a CTLA4 inhibitor, a TIGIT inhibitor, a LAG-3 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, and a KIR inhibitor.

[0019] Suitably, the immune checkpoint inhibitor can be selected from the group consisting of: a PD-1 inhibitor, a PD-L1 inhibitor, and a CTLA4 inhibitor.

[0020] Suitably, the agent can increase the lactate to glucose ratio.

[0021] Preferably, the reagent alters (e.g., increases) the ratio of lactate to glucose in the interstitial fluid of cancer or pre-cancerous conditions.

[0022] Preferably, the increase in the ratio of lactate to glucose can reach higher than 3:1.

[0023] Preferably, a sample of cancer or pre-cancerous conditions may have a harmful mitochondrial DNA (mtDNA) mutation load of less than 50%.

[0024] Preferably, the harmful mitochondrial DNA (mtDNA) mutation load can be less than 40%, less than 30%, or less than 20%.

[0025] Preferably, the reagent can be selected from the group consisting of:

[0026] a) Compounds that drive glycolytic flux through MDH1, optionally, wherein the compound is selected from the group consisting of: isocitrate (isocitrate, isocitrate salt), aconitate (aconitate, aconitate salt), citrate (citrate, citrate salt), oxaloacetate (oxaloacetate, oxaloacetate salt), NADH, and NAD+ precursors;

[0027] b) Compounds that regulate the NAD(H) redox process through the malate-aspartate shuttle, optionally, wherein the compound is selected from the group consisting of: isocitrate, aconitate, citrate, oxaloacetate, malate, fumarate (fumarate, fumarate salt), argininosuccinate (argininosuccinate, argininosuccinate salt);

[0028] c) Lactate;

[0029] d) Glucose-metabolizing enzymes and / or lactate-metabolizing enzymes;

[0030] e) Inhibitors of enzymes that reduce glycolytic flux in cancer cells or pre-cancerous cells, optionally, wherein the enzyme is pyruvate dehydrogenase or pyruvate carboxylase, optionally wherein the inhibitor is a small molecule;

[0031] f) Activators of enzymes that increase glycolytic flux in cancer cells or pre-cancerous cells;

[0032] g) Activators of enzymes that increase lactate efflux in cancer cells or pre-cancerous cells, optionally wherein the enzyme is MDH1 or GAPDH, optionally wherein the activator is a small molecule;

[0033] h) Inhibitors of enzymes that reduce lactate efflux in cancer cells or pre-cancerous cells;

[0034] i) Small molecule inhibitors of enzymes in the malate-aspartate shuttle, optionally wherein the enzyme is selected from the group consisting of GOT1, GOT2, MDH1, MDH2, glutamate (glutamate, glutamate salt)-aspartate carrier, and α-ketoglutarate (α-ketoglutarate, α-ketoglutarate salt)-malate carrier;

[0035] j) Small molecule activators of enzymes in the malate-aspartate shuttle, optionally wherein the enzyme is selected from the group consisting of GOT1, GOT2, MDH1, MDH2, glutamate-aspartate carrier, and α-ketoglutarate-malate carrier;

[0036] k) Inhibitors of Complex I, Complex II, Complex III, or Complex IV;

[0037] l) Compounds that increase the harmful mtDNA mutation load in cancer or pre-cancer, optionally wherein the compound induces harmful mtDNA mutations; and / or

[0038] m) Compounds that reduce neutrophils in a subject and / or reduce neutrophils in cancer or pre-cancer, optionally wherein the neutrophils are tumor-infiltrating neutrophils (TAN).

[0039] Suitably, the reagent may be selected from the group consisting of NADH oxidase and NADPH oxidase.

[0040] Suitably, the reagent may be the enzyme NADH oxidase (e.g., from Lactobacillus brevis) or a nucleic acid encoding said enzyme. Suitably, NADH oxidase may be cytoplasmic or mitochondrial.

[0041] Suitably, the reagent may be used in combination with a tumor-associated neutrophil-reducing compound (such as an anti-Ly6G antibody).

[0042] Suitably, cancer or pre-cancer may be selected from the group consisting of childhood cancer, hematological cancer, and myeloid cancer.

[0043] Suitably, childhood cancer may be selected from the group consisting of leukemia, brain cancer, spinal cord cancer, neuroblastoma, nephroblastoma, lymphoma (such as Hodgkin lymphoma and non-Hodgkin lymphoma), rhabdomyosarcoma, retinoblastoma, and bone cancer (such as osteosarcoma and Ewing's sarcoma).

[0044] Suitably, the PD-1 inhibitor may be nivolumab.

[0045] Suitably, compounds that increase the harmful mtDNA mutation load in cancer or pre-cancer can be selected from the group consisting of: mitochondrial base editing enzymes (such as DdCBE) and mitochondrial heteroplasmy manipulation enzymes (such as mtZFN or mitoTALEN).

[0046] Suitably, harmful mtDNA mutations can be selected from the group consisting of:

[0047] (i) tRNA mutations with a MitoTIP RAW score of at least 12.6 or at least 16.25;

[0048] (ii) rRNA mutations;

[0049] (iii) Truncating mutations in mtDNA genes;

[0050] (iv) Missense mutations in mtDNA genes, where the missense mutation has an Apogee score greater than 0.5, optionally, where the missense mutation is selected from frameshift mutations, insertion mutations or deletion mutations; and / or

[0051] (v) Mutations in the mtDNA D-loop region, selected from the group consisting of: H-strand promoter (545 - 567), MT-HV2 (hypervariable segment 2) m.57 - 372 and MT-HV1 (hypervariable segment 1) - m.16024 - 16390.

[0052] Suitably, harmful mtDNA mutations can be in genes selected from the group consisting of: MT-ND5, MT-ND1, MT-ND2, MT-ND3, MT-ND4, MT-ND4L, MT-ND6, MT-CO1, MT-CO2, MT-CO3, MT-CYB, MT-ATP6, MT-ATP8, MT-TL1, MT-TA, MT-TC, MT-TD, MT-TE, MT-TF, MT-TG, MT-TH, MT-TI, MT-TK, MT-TL2, MT-TM, MT-TN, MT-TP, MT-TQ, MT-TR, MT-TS1, MT-TS2, MT-TT, MT-TV, MT-TW, MT-TY, MT-RNR1 and MT-RNR2.

[0053] Suitably, the MT-ND5 harmful mtDNA mutation can be a truncating mutation located in a region selected from: m.12418 - 12425: A insertion / deletion or m.12385 - 12390: C insertion / deletion.

[0054] Suitably, harmful mtDNA mutations can be truncating mutations, missense mutations, insertion mutations or frameshift mutations.

[0055] Those skilled in the art will appreciate that, unless the context otherwise requires particularly, any embodiment related to sensitizing a subject to an immune checkpoint inhibitor (such as a PD-1 inhibitor, a PD-L1 inhibitor, and / or a CTLA4 inhibitor) (including methods or reagents for sensitization) is equally applicable to the treatment methods (or reagents for treatment) described herein.

[0056] Throughout the description and claims of this specification, the words "comprise" and "contain" and their variants mean "including but not limited to", and they are not intended to (and do not) exclude other parts, additives, components, integers or steps.

[0057] Unless the context otherwise requires, throughout the description and claims of this specification, the singular includes the plural. In particular, in the case of using an indefinite article, unless the context otherwise requires, the specification should be understood as considering both the plural and the singular.

[0058] Features, integers, characteristics, compounds, chemical moieties or groups described in connection with a particular aspect, embodiment or example of the present invention should be understood to be applicable to any other aspect, embodiment or example described herein, unless incompatible therewith.

[0059] Various aspects of the present invention are described in further detail below. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Embodiments of the present invention are further described below with reference to the accompanying drawings, wherein:

[0061] FIG. 1 shows that mtDNA mutations are prevalent in different cancers and provides information about MT-ND5. A - The percentage of tumors with different types of somatic mtDNA variants and good coverage in each cancer type. The boxes from left to right are: truncated type, 2+ non-truncated types, rRNA type, tRNA type, missense mutation type, silent mutation type, wild type. Right: The number of samples with good coverage in each cancer type. NSC, non-small cell carcinoma. Data are from Gorelick et al., 2021. B - Circular mtDNA genome, annotated with 73 homopolymer repeat sites with a length ≥ 5 bp. The height of the dots in the circular mtDNA genome represents the number of affected samples, and the width of the dots represents the length of the repeat region (5 - 8 bp). The six solid-color homopolymer sites highlighted are statistically enriched hotspots for frameshift indels in tumors. Data are from Gorelick et al., 2021. C - Space-filling model of respiratory complex I annotated with major reactions / functions. D - Space-filling model of respiratory complex I with internally located buried MT-ND5 and its interaction with the NDUFB8 protein exposed to the solvent on the upper and lower surfaces of the highlighted complex I.

[0062] Figure 2 Shows how frequent mutations in tumor Mt-Nd5 are modeled. A - Schematic of the mouse mitochondrial genome, indicating the sites targeted by DdCBE. B - Schematic of the TALE DNA-binding domains of DdCBE pairs targeting the induction of premature stop codons at m.11,944 and m.12,436. C - Schematic of the screening method for the TALE-DdCBE library used. Briefly, candidate pairs were cloned into a vector co-expressing a fluorescently labeled protein, and transfected B78 mouse melanoma cells were sorted by fluorescence-activated cell sorting (FACS). The mutagenesis efficiency of the cells was then evaluated by sequencing.

[0063] Figure 3 Shows how frequent mutations in tumor Mt-Nd5 are generated. A - Heterogeneity of cells transfected with the indicated constructs as determined by pyrosequencing. N transfection indicates that the cells were transfected and serially restored one or four times. B - Figure 4 The mtDNA copy number of the cells in A, measured by droplet digital PCR (ddPCR). C - Western blot analysis of marker proteins of the respiratory chain complexes. Complex I (Ndufb8), Complex II (Sdhb), Complex III (Uqcrc2), Complex IV (Mt-Co1), and Complex V (Atp5a). Ponceau red is shown as a loading control.

[0064] Figure 4 Shows how frequent mutations in tumor Mt-Nd5 are generated. A - As Figure 4 Shown in C, blue native (BN) PAGE and blotting of the respiratory chain complexes were performed using antibodies. Also shown are the in-gel activities of Complex I and Complex II after BN PAGE, and the Coomassie loading control. B - The basal oxygen consumption rate (OCR) of the cells evaluated by Seahorse. C - Analysis of the energy charge state of the cells using metabolite abundance data of AMP, ADP, and ATP measured by mass spectrometry-based metabolomics. D - The NAD+:NADH ratio calculated using metabolite abundance data measured by mass spectrometry-based metabolomics.

[0065] Figure 5 Shows the effects of mt-Nd5 mutations on cellular energetics and metabolism. Metabolite abundances measured by mass spectrometry-based metabolomics from high VAF mutant cells were plotted against each other, revealing consistent metabolic changes due to two different truncating mutations in Mt-Nd5.

[0066] Figure 6Glutamine tracing reveals increased abundance of MDH1-derived malate in the cytoplasm. A - Heatmap shows significantly increased abundance of specific metabolites related to the tricarboxylic acid (TCA) cycle, urea cycle, and fumarate adducts. B - 1- 13 Schematic diagram of the labeled fate of glutamine. C - Abundance of malate m+1. D - Abundance of argininosuccinate m+1. E - Abundance of α-ketoglutarate (a-KG) m+1. F - Abundance of aconitate m+1. G - Abundance of aspartate m+1.

[0067] Figure 7 Glucose tracing shows that malate abundance increases through reverse MDH2 flux. A - U- 13 Schematic diagram of the labeled fate of glucose. B - Ratio of malate m+3:citrate m+3 obtained by mass spectrometry. C - Ratio of citrate m+3:aconitate m+3 obtained by mass spectrometry. D - Ratio of citrate m+3:pyruvate m+3 obtained by mass spectrometry.

[0068] Figure 8 MDH1 can mediate an increase in glycolytic intermediates in mutant cells. A - Heatmap representation of the abundance of glycolytic intermediates detected by mass spectrometry. B - Heatmap representation of the abundance of glycolytic intermediates after siRNA-mediated depletion of MDH1 detected by mass spectrometry. C - Western blot analysis shows knockdown of MDH1 compared to scrambled siRNA control.

[0069] Figure 9 Abundance of specific metabolites in cells treated with siRNA. A - 4- 2 Schematic diagram of the labeled fate of H1 glucose. B - Abundance of malate +1 in cells treated with scrambled siRNA obtained by mass spectrometry. C - Abundance of lactate +1 in cells treated with scrambled siRNA obtained by mass spectrometry. D - Abundance of NADH +1 in cells treated with scrambled siRNA obtained by mass spectrometry. E - Abundance of malate +1 in cells treated with siRNA to MDH1 obtained by mass spectrometry. F - Abundance of lactate +1 in cells treated with siRNA to MDH1 obtained by mass spectrometry.

[0070] Figure 10 shows the impact on cancer metabolism in the context of the Krebs cycle (A and B).

[0071] Figure 11 An experimental setup for analyzing the in vivo situation is shown.

[0072] Figure 12In vivo effects are shown. A - Survival curves of mice implanted with subcutaneous tumors. The humane endpoint was reached when the tumor measured 15 mm in any dimension. n = 12 mice per genotype. B - Dissected tumor weights. n = 10 - 12 tumors per genotype. C - Differences in the mean heterogeneity between injected cancer cells and the resulting bulk tumor heterogeneity measurements, determined by pyrosequencing. n = 11 - 12 per genotype. D - Analysis of mtDNA copy number in bulk tumors by ddPCR. n = 10 - 12 per genotype. E - Abundances of tumor metabolites with the designated genotype. n = 7 - 10 per genotype.

[0073] Figure 13 Tumor transcriptome analysis is shown. A - Volcano plot showing differential gene expression between bulk transcriptomics of mtDNA wild - type and 60% VAF m.11,944G>A tumors. B - PCA plot of the samples compared in A. Each point is a tumor. C - Volcano plot showing differential gene expression between bulk transcriptomics of mtDNA wild - type and 40% m.11,944G>A VAF tumors. D - PCA plot of the samples compared in C. Each point is a tumor. E - Volcano plot showing differential gene expression between bulk transcriptomics of 40% VAF m.11,944G>A and 60% VAF m.11,944G>A tumors. F - PCA plot of the samples compared in E. Each point is a tumor.

[0074] Figure 14 Differentially expressed genes are shown; bulk tumor GSEA - wild - type versus VAF>50%. A - Summary of differentially expressed genes between mtDNA wild - type and 60% VAF m.11,944G>A tumors. B - Provides the same information as Figure 13 A. C - Significant hits of gene set enrichment analysis (GSEA) of differentially expressed genes.

[0075] Figure 15 Differentially expressed genes are shown; bulk tumor GSEA - VAF<50% versus VAF>50%. A - Summary of differentially expressed genes between 40% VAF and 60% VAF m.11,944G>A tumors. B - Provides the same information as Figure 13 C. C - Significant hits of gene set enrichment analysis (GSEA) of differentially expressed genes.

[0076] Figure 16Shows the remodeled immune microenvironment in mtDNA mutant tumors. A - Proportion of natural killer (NK) cells detected in tumors after dissociation and flow cytometry. n = 4 - 8. B - Proportion of tumor - associated macrophages (TAM) detected in tumors after dissociation and flow cytometry. n = 9 - 14. C - Proportion of immature monocytes detected in tumors after dissociation and flow cytometry. n = 10 - 14. D - Flow cytometry gating strategy for defining TAM and monocyte populations. E - Flow cytometry gating strategy for defining natural killer cells.

[0077] Figure 17 Shows that scRNAseq analysis of tumors defines altered immune populations. A - UMAP representation of Seurat - clustered single - cell RNA sequencing (scRNAseq) data of >100,000 cells harvested from intact, dissociated mtDNA wild - type and 60% VAF m.12,436G>A tumors. n = 3 for each genotype. B - Cell type assignment based on CellRanger - derived scRNAseq data. C - Relative proportion of intermediate monocytes in cluster 3. D - Relative proportion of NK cells in cluster 11. E - Relative proportion of macrophages in cluster 6. F - Relative proportion of classical monocytes in cluster 13. G - Relative proportion of immune cells expressing interferon - stimulated genes (ISG - expressing immune cells) in cluster 7. H - Relative proportion of CD4+ NK - like T cells in cluster 24.

[0078] Figure 18 Shows Figure 17 scRNAseq analysis of the tumors described in. A - GSEA results covering all defined signature gene sets interferon - γ response clusters. B - GSEA results covering all defined signature gene sets interferon - α response clusters.

[0079] Figure 19 Shows that VAF > 50% mtDNA mutant melanomas respond to PD1 immune checkpoint blockade. A - Schematic of the experimental timeline. Cells were implanted at D0. Once tumors were palpable, usually at day 7, anti - PD1 monoclonal antibody was administered intraperitoneally (IP) to mice every 3 days until the experiment ended at day 21, when mice were sacrificed and tumors were excised. B - Tumor weights excised from mice bearing tumors of the designated genotypes treated with anti - PD1 antibody as defined in A. n = 4 - 5. C - Representative image of the tumors excised in B. D - Tumor weights excised from mice bearing tumors of the designated genotypes treated with anti - CTLA4 antibody as defined in A. n = 4 - 7. E - Representative image of the tumors excised in D.

[0080] Figure 20This shows that this leads to human treatment sensitivity. A - Stratification of a cohort of metastatic melanoma patients by mtDNA status. B - Analysis of the response rate of patients to nivolumab by tumor mtDNA mutation status. P values were determined using one-way ANOVA test with the applied Sidak multiple comparison test (C, F), one-tailed Student's t test (I), or chi-square test (H). Error bars represent SD. The measure of centrality is the mean.

[0081] Figure 21 This shows that mitochondrial base editing generates isogenic cell lines carrying two independent truncating mutations in mt-Nd5. A - Schematic of the TALE-DdCBE design employed. The TALE was integrated into a backbone containing a mitochondrial targeting cassette, split DdCBE, and uracil glycosylase inhibitor (UGI). B - Schematic of mouse mtDNA. The target sites within mt-Nd5 are indicated. C - TALE-DdCBEs for inducing G>A mutations at mt.12,436 and mt.11,944. D - Workflow for generating mt-Nd5 mutant isogenic cell lines. E - Measurement of the heterogeneity of the cells generated in D (sampling n = 6 individual wells). F - Immunoblot of indicative respiratory chain subunits. Representative results are shown. G - Abundance and in-gel activity of assembled complex I. Representative results are shown. H - mtDNA copy number (sampling n = 9 individual wells). I - Basal oxygen consumption rate (OCR) (n = 9 - 12 measurements (12 wells per measurement)). J - Energy (adenylate) charge state (sampling n = 17 individual wells). K - Proliferation rate of the cell lines in permissive growth medium. (n = 12 individual wells measured in three batches). L - NAD+:NADH ratio (measuring n = 11 - 12 individual wells). All P values were determined using one-way ANOVA test with the Sidak multiple comparison test (E, H - I, K) or Fisher LSD test (J, L). Error bars represent SD. The measure of centrality is the mean.

[0082] Figure 22 This shows that due to cellular redox imbalance, mutant cells underwent a metabolic shift towards glycolysis. A - Heatmap of the unlabeled steady-state abundances of selected mitochondrial metabolites arginine, argininosuccinate (AS), and the terminal fumarate adducts succinylcysteine (succ.Cys) and succinyl GSH (succ.GSH). B - Labeling fate of 13 C-derived from 1- 13 C-glutamine. C - Malate m+1 abundance derived from 1- 13 C-glutamine under the specified treatment (sampling n = 6 - 11 individual wells). D - Heatmap of the unlabeled steady-state metabolite abundances of selected intracellular glycolytic intermediates and extracellular lactate (ex. lactate). E - U-13 Labeling fate of C-glucose. U- under specified treatment 13 Abundance of C-glucose-derived lactate m+3 (sampled from n = 6 - 9 individual wells). G Derived from 4- 2 H1-glucose 2 Labeling fate of H; mitoLbNOX not shown for clarity. H Derived from 4- under specified treatment 2 Abundance of malate m+1 derived from H1-glucose (sampled from n = 5 - 16 individual wells). I IC of 2-DG 50 Curve (measured from n = 4 individual wells for each drug concentration). This was repeated 3 times and representative results are shown. P-values were determined using one-way ANOVA test with (A, D) Sidak multiple comparison test or Fisher LSD test (C, F, H). Error bars represent SD. Measure of centrality is the mean.

[0083] Figure 23 It is shown that tumor mtDNA mutations reshape the immune microenvironment. Survival of C57 / BL6 mice subcutaneously injected with specified cells (n = 5 - 12 animals per condition). B Endpoint tumor weight (n = 5 - 12 tumors per genotype). C Gene set enrichment analysis (GSEA) of bulk tumor RNA sequencing (RNAseq) data (n = 5 - 6 tumors per genotype). Only gene sets with adjusted P-value < 0.1 are shown. D GSEA of RNAseq obtained from the Hartwig Medical Foundation (HMF) metastatic melanoma patient cohort. Cancers were stratified into wild-type and mtDNA mutants with > 50% variant allele frequency (VAF) according to mtDNA status. E UMAP plot of whole-tumor scRNAseq clustered by seurat from specified samples. F UMAP represents cell type ID. DC, dendritic cell. pDC, plasmacytoid dendritic cell. G GSEA of malignant cells identified in scRNAseq analysis. UMAP colored according to GSEA score: H interferon alpha response; I interferon gamma response; J inflammatory response; K IL2-Stat5 signaling. L Proportion of tumor-resident neutrophils relative to total malignant and non-malignant cells (n = 17 tumors). M UMAP colored according to GSEA for the OXPHOS gene set. One-way ANOVA test and Sidak multiple comparison test (B), Wilcoxon signed-rank test (G - K), and two-tailed Student's t-test (L - O) were applied. Error bars represent SD (B) or SEM (L - O). Measure of centrality is the mean. Box plots represent interquartile range (J - M). NES: normalized expression score. In Figure 23 In C, the top bar in each pair is m.11,944 and the bottom bar is m.12,436.

[0084] Figure 24 Shows that mtDNA mutation-related microenvironment remodeling renders tumors sensitive to checkpoint blockade. A Schematic of the experimental plan and dosing schedule for anti-PD1 monoclonal antibody (mAb) treatment of B78-D14 tumors. B Representative images of tumors harvested on day 21. C Tumor weights on day 21 (n = 10 - 19 tumors per genotype). D Schematic of the experimental plan and dosing schedule for anti-PD1 mAb treatment of Hcmel12 tumors. E Representative images of tumors harvested on day 13. F Tumor weights on day 13 (n = 7 tumors per genotype). G Stratification of a cohort of metastatic melanoma patients by mtDNA status. H Analysis of the response rate of patients to nivolumab according to the tumor mtDNA mutation status. One-way ANOVA test with Sidak multiple comparison test (C), Student's one-tailed t test (F), or chi-square test (H) was applied. Error bars represent SD. The measure of centrality is the mean.

[0085] Figure 25 Shows the results of mitochondrial base editors with two independent targets in mt-Nd5. A Immunoblot of the expression after sorting of DdCBE. αHA and αFLAG show the expression of the left TALE (TALE-L) and right TALE (TALE-R), respectively. Representative results are shown. B Off-target C>T activity of DdCBE on mtDNA. The figures show the mutations detected at a heterogeneity > 2%, and are a measure of the mutations detected relative to the wild type. These mutations may not affect our key observations as the two models performed similarly in the experiments.

[0086] Figure 26 Shows the results of proteomic analysis of isogenic mt-Nd5 mutant cell lines, revealing significant changes mainly in complex I genes. Volcano plots show the detected differences in protein abundance between A mt.12436 60％ cells and B mt.11944 60％ cells compared to wild type. Differences with P < 0.05 and log2 fold change > 0.5 are shown in red (n = 3 individually collected cell pellets were measured for each cell line). C Heatmap of the protein abundance of complex I, D complex II, E complex III, F complex IV, and G complex V nuclear and mitochondrial subunits. Wilcoxon signed-rank test (A, B) and one-way ANOVA test with Sidak multiple comparison test (C - G) were applied.

[0087] Figure 27It is shown that the mt.-Nd5 truncation mutation alters the intracellular redox state and has no significant effect on mitochondrial mRNA expression or membrane potential. A Expression of mitochondrial genes (sampling of n = 12 individual cell pellets for each genotype). B Measurement of the electrical component Δ Ψ of the proton motive force, the chemical component ΔpH of the proton motive force, and the total proton motive force ΔP (sampling of n = 4 individual wells for each genotype). C GSH:GSSG ratio (sampling of n = 6 - 12 individual wells for each cell type). A higher GSH:GSSG ratio represents a more reduced intracellular environment. D Mitochondrial NADH oxidation state (sampling of n = 4 individual wells for each genotype). All P values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. The measure of centrality is the mean. In Figure 27 A, the top bar in each of the three groups is m.11,944, the middle bar is m.12,436, and the bottom bar is wild type.

[0088] Figure 28 U- 13 C-glutamine labeling results show that a portion of the increased malate abundance is derived from cytoplasmic reductive carboxylation of glutamine. A Labeling fate of 13 C derived from U- 13 C-glutamine through oxidative decarboxylation and reductive carboxylation of glutamine. B Malate m+3 abundance derived from U- 13 C-glutamine (sampling of n = 9 individual wells for each genotype). C Ratio of malate m+3:malate m+2 derived from U- 13 C-glutamine (sampling of n = 9 individual wells for each genotype). D Ratio of ASm+3:ASm+2 derived from U- 13 C-glutamine (sampling of n = 9 individual wells for each genotype). All P values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. The measure of centrality is the mean.

[0089] Figure 29 It is shown that the increase in cytoplasmic malate abundance occurs at the MDH1 level but is not directly due to overall redox changes. A Labeling fate of 13 C derived from 1- 13 C-glutamine, which only labels metabolites derived from reductive carboxylation of glutamine. B Aconitate m+1 abundance derived from 1- 13 C-glutamine (sampling of n = 9 individual wells for each genotype). C Aspartate m+1 abundance derived from 1- 13 C-glutamine (sampling of n = 9 individual wells for each genotype). D Derived from 1- 13ASm+1 abundance of C-glutamine (sampled from n = 9 individual wells for each genotype). Immunoblot of E siRNA-mediated Mdh1 depletion. Representative images are shown. F Immunoblot of cytoLbNOX expression 36 hours after sorting using αFLAG. Representative images are shown. G Derived under the specified treatment from 1- 13 ASm+1 abundance of C-glutamine (sampled from n = 6 - 12 individual wells for each genotype per condition). All P values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. Measure of centrality is the mean.

[0090] Figure 30 It is shown that the increase in malate abundance in mutant cells is partly due to the reversal of MDH2. A Derived from U- 13 Labeling trend of C-glucose 13 of C. B Derived from U- 13 Pyruvate m+3 abundance of C-glucose (sampled from n = 7 - 8 individual wells for each genotype). C Derived from U- 13 Citrate m+2:pyruvate m+3 ratio of C-glucose (sampled from n = 6 - 7 individual wells for each genotype). D Derived from U- 13 Malate m+3:citrate m+3 ratio of C-glucose, (sampled from n = 7 - 8 individual wells for each genotype). E Immunoblot of mitoLbNOX expression 36 hours after transfection using αFLAG. Representative images are shown. All P values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. Measure of centrality is the mean.

[0091] Figure 31 It is shown that 4- 2 Results of 4-H1-glucose tracer, indicating that the electron shuttle between MDH1 and GAPDH drives aerobic glycolysis. A Derived under the specified treatment from 4- 2 Lactate m+1 abundance of 4-H1-glucose (sampled from n = 7 - 9 individual wells for each genotype per condition). B Derived under the specified treatment from 4- 2 NADH m+1 abundance of 4-H1-glucose (sampled from 6 - 8 individual wells for each genotype per condition). All P values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. Measure of centrality is the mean.

[0092] Figure 32 It is shown that mutant cells show heterogeneous dose-dependent sensitivity to respiratory chain inhibitors. A IC of metformin 50 curve. IC of wild type 50= 26.31 ± 1.49 mM, mt.12436 60％ IC of 50 = 16.60 ± 2.43 mM, mt.12436 80％ IC of 50 = 5.89 ± 0.71 mM, and mt.11944 80％ IC of 50 = 22.93 ± 0.70 mM. IC of rotenone B 50 curve. IC of wild type 50 = 0.236 ± 0.026 μM, mt.12436 60％ IC of 50 = 0.235 ± 0.035 μM, mt.12436 80％ IC of 50 = 0.493 ± 0.108 μM, and mt.11944 60％ IC of 50 = 0.205 ± 0.033 μM. IC of oligomycin C 50 curve. IC of wild type 50 = 13.81 ± 3.80 μM, mt.12436 60％ IC of 50 = 13.52 ± 3.32 μM, mt.12436 80％ IC of 50 = 7.75 ± 0.56 μM, and mt.11944 80％ IC of 50 = 13.54 ± 3.32 μM (n = 4 individual wells for each genotype per drug concentration). This was repeated 3 times, and representative results are shown.

[0093] Figure 33 No significant macroscopic differences were shown for allogeneic B78-D14 lineage tumors. A Wild type, B m.12,436 40％ and C m.12,436 60％ Representative H&E subgroups of tumors. D Heterogeneity changes detected in bulk tumor samples (n = 5 - 12 tumors per genotype). E mtDNA copy number in bulk tumors (n = 4 - 13 tumors per genotype). F Heatmap of steady-state abundances of metabolic end-products fumarate adducts, succinylcysteine, and succinyl GSH, showing that metabolic changes observed in vitro are retained in vivo (n = 12 tumors per genotype). All P-values were determined using one-way ANOVA test and Sidak multiple comparison test. Error bars represent SD. Measure of centrality is the mean.

[0094] Figure 34Bulk tumor transcriptional signatures show dose-dependent, heterogeneous changes in immune-related transcriptional phenotypes. GSEA of bulk tumor RNAseq data (n = 5-6 tumors per genotype) shows mutant A 40％ versus wild type, and mutant B 60％ versus mutant 40％ Unless otherwise stated, only gene sets with adjusted p-value < 0.1 are shown. Wilcoxon signed-rank test was applied. In each pair, the top bar plot is m.11,944, and the bottom bar plot is m.12,436.

[0095] Figure 35 For scRNAseq analysis, malignant cells were identified as aneuploid cells with low or zero Ptprc (CD45) expression and high epithelial score. UMAP represents A Ptprc expression, B epithelial score, and C aneuploidy determined by copykat prediction. These criteria were adopted because B78 cells lack distinct transcriptional signatures. In each pair, the top bar plot is m.11,944, and the bottom bar plot is m.12,436.

[0096] Figure 36 The transcriptional signatures of mutant cells in vitro show no significant changes. A A total of 60% of the mutant cells have significantly co-regulated transcripts compared to wild type (n = 12 cell pellets sampled per genotype pair). Shown Amt.12436 60％ cells and B mt.11944 60％ Volcano plot of the differences in gene expression of cells compared to wild type. Differences with p < 0.05 and log2 fold change > 1 are shown in red (n = 12 individual wells sampled). Wilcoxon signed-rank test was applied.

[0097] Figure 37Shows the results of scRNAseq analysis, revealing distinct changes in the tumor immune microenvironment of mtDNA mutant tumors. Tumor-resident fractions: A immature monocytes; and B CD4+ T-cells relative to total malignant and non-malignant cells (n = 3 - 7 tumors per genotype). C UMAP colored by GSEA NES score according to an allogeneic rejection gene set. Tumor-resident fractions: D CD4+ T cells; and E natural killer (NK) cells relative to total malignant and non-malignant cells (n = 3 - 7 tumors per genotype). F Relative PD-L1 expression within each cell (n = 3 - 7 tumors per genotype). One-way ANOVA test along with Wilcoxon signed-rank test (A) and two-tailed Student's t-test (A - B, D - E) were applied. Error bars represent SEM. Measure of centrality is the mean. Box plots represent interquartile range (A - B, D - E). NES: normalized expression score. DC, dendritic cell.

[0098] Figure 38 Shows that the remodeling of the tumor microenvironment in mutant cells renders the tumors sensitive to checkpoint blockade. Tumor weights harvested on day 21 (n = 5 - 15 tumors per genotype). One-way ANOVA test along with Sidak multiple comparison test were applied. Error bars represent SD. Measure of centrality is the mean. In panels a, b, d, and e, the bar graph order from left to right in the figure is control (ctrl), ND5 60％ , and ND5 80％ .

[0099] Figure 39It is shown that HcMel12 mutant cells recapitulate the cellular and metabolic phenotypes observed in B78-D14 cells. A Heterogeneity changes when subsequently transfecting melanoma cell lines (n = 3 individual cell pellets per genotype). B Immunoblot of indicative respiratory chain subunits. Representative results are shown. C mtDNA copy number (n = 12 individual wells per genotype). D Basal oxygen consumption rate (OCR) (n = 6 measurements per genotype (12 wells per measurement)). E Proliferation rate of cell lines in permissive growth medium (n = 3 individual wells per genotype). F Energy (adenylate) charge state (n = 9 individual wells per genotype). G NAD+:NADH ratio (n = 9 individual wells per genotype). H GSH:GSSG ratio (n = 8 - 9 individual wells per genotype). I Heatmap of unlabeled steady-state abundances of selected mitochondrial metabolites arginine, argininosuccinate (AS), and the terminal fumarate adducts succinylcysteine (succ.Cys) and succinyl-GSH (succ.GSH) (n = 8 - 9 individual wells per genotype). J Heatmap of unlabeled steady-state metabolite abundances of selected intracellular glycolytic intermediates and extracellular lactate (ex. lactate) (n = 9 individual wells per genotype). P values were determined using one-way ANOVA test along with Sidak multiple comparison test for (C - D), Fisher's LSD test for (E) or one-tailed Student's t test for (F - J). Error bars represent SD. Measure of centrality is the mean.

[0100] Figure 40 It is shown that untreated Hcmel12 lineage tumors recapitulate the B78-D14 lineage. A Survival of C57 / BL6 mice subcutaneously injected with the indicated cells (n = 9 - 10 animals per genotype). B Endpoint tumor weight (n = 9 - 10 tumors per genotype). C Heterogeneity changes detected in bulk tumor samples (n = 9 tumors per genotype). D Bulk tumor mtDNA copy number (n = 9 tumors per genotype). E Heatmap of steady-state abundances of the metabolic terminal fumarate adducts, succinylcysteine, and succinyl-GSH, indicating that the metabolic changes observed in B78 mutant tumors are retained in vivo (n = 9 tumors per genotype). P values were determined using one-way ANOVA test along with Sidak multiple comparison test for (B, D) or Student's one-tailed t test for (E). Error bars represent SD. Measure of centrality is the mean.

[0101] Figure 41Shows the constitutive expression of cytoLbNOX phenocopy metabolic changes observed in mt-Nd5 mutant cells. A. Immunoblotting of cytoLbNOX expression in the clonal population using αFLAG. Representative images are shown. B. Immunoblotting of indicative respiratory chain subunits. Representative results are shown. C. mtDNA copy number (n = 9 individual wells for each genotype). D Basal oxygen consumption rate (OCR) (n = 9 - 15 measurements (6 wells per measurement) for each genotype). A significant decrease was observed in HcMel12cytoLbNOX, similar to the decrease in basal OCR measured in m.12,436 80％ cells. E. NAD+:NADH ratio (n = 11 - 12 individual wells for each genotype). F. Heatmap of metabolite abundances in U- 13 C-glucose labeling of glucose m+3, lactate m+3, pyruvate m+3, and the terminal fumarate adducts succinylcysteine (succ.Cys) and succinyl GSH (succ.GSH). B78 wild-type cells were transiently transfected with cytoLbNOX, and metabolites were extracted 3 days after sorting. A significant increase in lactate abundance was observed in cells expressing cytoLbNOX, mimicking what was observed in m.12,436 80％ cells (n = 9 - 13 individual wells for each genotype). All P values were determined using unpaired Student's t-test. Error bars represent SD. Measure of centrality is the mean.

[0102] Figure 42 Hcmel12 mutants and cytoLbNOX tumors showed neutrophil depletion and increased CD4+ T cell infiltration compared to wild-type tumors. A Gating strategy for Zombie+ live cells. B Gating strategy for neutrophils in tumors, lymph nodes, and spleens. C Gating strategy for CD4+ T cells, CD8+ T cells, NK T cells, and macrophages in tumors, lymph nodes, and spleens. Abundances of specific immune cells in D tumors, E tumor-draining lymph nodes, and F spleens in untreated mice (n = 4 - 8 samples for each genotype). Tissues were harvested on day 13. Natural killer T cells: CD4-CD8-NK1.1+. Macrophages: Cd11b+Ly6C-F4 / 80+. Neutrophils: CD11b+Ly6C+Ly6G+. All P values were determined using one-way ANOVA test and Fisher's LSD test. Measure of centrality is the mean.

[0103] Figure 43The anti-PD1 response depends on the abundance of tumor-resident neutrophils in an isogenic model of Hcmel12 melanoma. A Schematic of the experimental design and dosing schedule for treatment of Hcmel12 tumors with anti-PD1 monoclonal antibody (mAb) and G-CSF or anti-Ly6G. B Tumor weights of untreated mice compared to mice treated with G-CSF or anti-Ly6G (n = 7-8 tumors per genotype). Log2 fold changes in tumor neutrophils in untreated and treated mice in terms of C G-CSF and D anti-Ly6G compared to untreated control (n = 4-8 samples per genotype). Tumor weights of mice treated with anti-PD1 or anti-PD1 and E G-CSF or F anti-Ly6G (n = 7-8 tumors per genotype). Neutrophils: CD11b+Ly6C+Ly6G+. All P values were determined using one-way ANOVA test along with Fisher's LSD test. Error bars represent SD. Measure of centrality is mean.

[0104] Figure 44 Hcmel12 mutants and cytoLbNOX tumors show different sensitivities to immune checkpoint inhibitors (also referred to herein as immune checkpoint blockade or ICB). A Schematic of the experimental design and dosing schedule for treatment of Hcmel12 tumors with anti-PD1, anti-PDL1, or anti-CTLA4 mAb. B Representative images of tumors harvested on day 13 for each drug regimen. C Tumor weights on day 13 for each drug regimen (n = 10-12 tumors per genotype). Survival of C57BL / 6 mice (n = 10-15 animals per genotype) subcutaneously injected with the indicated cells under continuous anti-PD1 treatment. Only tumors reaching the endpoint of 15 mm are shown for cytoLbNOX. E Tumor weights at the endpoint of mice under continuous anti-PD1 treatment (n = 3-15 tumors per genotype). In continuous anti-PD1 treatment, F wild-type and m.12436 80％ (n = 15 tumors per genotype) and G cytoLbNOX tumors (n = 10 tumors per genotype) change in tumor volume recorded from the date of injection. One-way ANOVA along with Sidak multiple comparison test (C, E) or log-rank (Mantel-Cox) test (D) was applied. Tumor volume was calculated as 0.5*L*W based on caliper measurements. 2 Error bars represent SD. Measure of centrality is mean.

[0105] Figure 45Immunogenic 4434 tumors maintain distinct anti-PD1 sensitivities. A Schematic of the experimental plan and dosing regimen for anti-PD1 mAb treatment of 4434 tumors. B Representative images of treated tumors at day 20 and untreated tumors at endpoint. C Tumor weights at day 21 (n = 13 tumors per genotype). All P values were determined using a one-tailed Student's t test. Error bars represent SD. Measure of centrality is the mean.

[0106] Figure 46 Wild-type tumors implanted on the flanks relative to mitochondrial mutant or cytoLbNOX tumors are sensitive to anti-PD1. A Schematic of the tumor injection sites and dosing regimen for anti-PD1 mAb treatment of Hcmel12 tumors. B Representative images of sacrificed mice and C harvested tumors at day 13 under each condition. D Tumor weights at day 13 (n = 6 - 10 tumors per genotype). E Wild-type tumor weights with corresponding flank tumor genotypes at day 13 (n = 8 - 11 wild-type tumors). F Heatmap of circulating immune populations in blood sampled at day 11. NK cells: CD4-CD8-NK1.1+. Neutrophils: CD11b+Ly6C+Ly6G+. Monocytes: CD11b+Ly6C+F4 / 80-. Conventional dendritic cells (cDC): CD11c+MHCII+. All P values were determined using one-way ANOVA test and Fisher's LSD test. Error bars represent SD. Measure of centrality is the mean.

[0107] Figure 47 Flow cytometry of treated contralateral tumors shows an increase in CD4+ T cells. A Proportion of CD4+ T cells, B NK T cells, C CD8+ T cells, D tumor-associated macrophages (TAM), E neutrophils, and F monocytes (n = 6 - 12 tumors per condition). All P values were determined using one-way ANOVA test and Fisher's LSD test. Error bars represent SD. Measure of centrality is the mean.

[0108] Figure 48 Tumor weights and growth rates of wild-type tumors and complex IV mutant tumors.

[0109] Figure 49 Effects of anti-PD1 treatment on wild-type tumors and complex IV mutant tumors. The patents, scientific, and technical literature cited herein establish the knowledge available to those of ordinary skill in the art at the time of filing. The entire disclosures of the issued patents, published, and pending patent applications, and other publications cited herein are incorporated by reference herein to the same extent as if each such content was specifically and individually indicated to be incorporated by reference herein. In case of any inconsistencies, the present disclosure shall govern.

[0110] Figure 50 A) Endpoint tumor weights of tumors in C57 / BL6 mice subcutaneously injected with the indicated tumor cell genotypes (n = 9 - 18 animals per genotype). The measure of centrality is the mean. Error bars represent SD. B) Survival of C57 / BL6 mice subcutaneously injected with the indicated cells (n = 9 - 18 animals per genotype). The log-rank (Mantel-Cox) test was applied. *** P = <0.001. C) Heatmap of unlabeled steady-state abundances of selected metabolites in endpoint tumors of the indicated genotypes growing subcutaneously in C57 / BL6 animals. Succ.cys, succinylcysteine. n = 5 - 42 tumors per genotype. All P-values were determined using one-way ANOVA and Fisher's LSD test. * P = <0.05. D) Immunoblot analysis of endpoint whole-tumor protein extracts from tumors of the indicated genotypes growing subcutaneously in C57 / BL6 animals. E) Quantification of pSTAT1 levels in the indicated tumor genotypes. n = 3 tumors per genotype. All P-values were determined using one-way ANOVA and Fisher's LSD test. The measure of centrality is the mean. Error bars represent SD. * P = <0.05, ** P = <0.01, *** P = <0.001.

[0111] Figure 51 . There were no common large-scale tumor metabolite changes between the various conditions. Heatmap of metabolite abundance changes in the corresponding tumor lineages (n = 6 - 38 tumors per genotype) relative to wild-type tumors. A one-tailed Student's t-test (B78 and 4434) or one-way ANOVA and Sidak's multiple comparison test (Hcmel12) were applied. Error bars represent SD. The measure of centrality is the mean.

[0112] Aspects of the present invention are further described in detail below. Detailed Description

[0113] This disclosure is based on the inventors' identification of a subset of cancer or pre-cancer patients who have a more favorable therapeutic response to immune checkpoint inhibitors (such as PD-1 inhibitors, PD-L1 inhibitors, PD-L2 inhibitors, CTLA4 inhibitors, TIGIT inhibitors, LAG-3 inhibitors, TIM-3 inhibitors, BTLA inhibitors, and / or KIR inhibitors). Based on the data provided in the following examples, the inventors concluded that these patients have an altered cancer or pre-cancer lactate-to-glucose ratio and thus an altered cancer or pre-cancer redox state (indicating a Warburg-like metabolic shift). This altered redox state leads to changes in the entire tumor microenvironment, such that different proportions of immune cells are present in the cancer or pre-cancer. Specifically, the inventors observed an increase in the number of natural killer (NK) cells, monocytes, CD4+ NK-like T cells, and immune cells expressing interferon-stimulated genes (ISGs) in cancers or pre-cancers with an altered redox state (such as an altered lactate-to-glucose ratio), and a decrease in the number of macrophages.

[0114] Accordingly, in one aspect, the present invention provides a reagent for altering the redox state (e.g., altering the lactate-to-glucose ratio) of cancer or pre-cancer for sensitizing a subject having cancer or pre-cancer to an immune checkpoint inhibitor. In one example, the reagent alters the redox state (e.g., alters the lactate-to-glucose ratio) in the interstitial fluid of cancer or pre-cancer.

[0115] In a related aspect, the present invention provides a method for sensitizing a subject having cancer or pre-cancer to an immune checkpoint inhibitor, comprising exposing the subject to a reagent that alters the redox state (e.g., alters the lactate-to-glucose ratio) in cancer or pre-cancer. In one example, the reagent alters the redox state (e.g., alters the lactate-to-glucose ratio) in the interstitial fluid of cancer or pre-cancer.

[0116] In another aspect, the present invention provides an immune checkpoint for treating a subject having cancer or pre-cancer, wherein the subject has been exposed to a reagent that alters the redox state (e.g., alters the lactate-to-glucose ratio) in cancer or pre-cancer. In one example, the reagent alters the redox state (e.g., alters the lactate-to-glucose ratio) in the interstitial fluid of cancer or pre-cancer.

[0117] The present invention further provides a method for treating cancer or pre-cancer in a subject, comprising administering an immune checkpoint inhibitor to the subject, wherein the subject has been exposed to a reagent that alters the redox state (e.g., alters the lactate-to-glucose ratio) in cancer or pre-cancer. In one example, the reagent alters the redox state (e.g., alters the lactate-to-glucose ratio) in the interstitial fluid of cancer or pre-cancer.

[0118] In another aspect, the present invention provides a method of treating cancer or pre-cancer in a subject, comprising:

[0119] (i) exposing the subject to an agent that alters the redox state of the cancer or pre-cancer (e.g., alters the lactate to glucose ratio); and

[0120] (ii) administering an immune checkpoint inhibitor to the subject. In one instance, the agent alters the redox state (e.g., alters the lactate to glucose ratio) in the interstitial fluid of the cancer or pre-cancer.

[0121] As used herein, the term "sensitize" in the context of immune checkpoint inhibitor therapy refers to increasing the sensitivity of a subject's cancer or pre-cancer to immune checkpoint inhibition therapy or reducing its resistance. Sensitization can be a cancer or pre-cancer that is insensitive to immune checkpoint inhibitor therapy prior to the subject's exposure to the agent, or increasing the sensitivity of a cancer or pre-cancer that is (at least partially) sensitive to immune checkpoint inhibitor therapy prior to the subject's exposure to the agent. A subject (or the subject's cancer or pre-cancer) that has been sensitized is more likely to respond favorably to or benefit from such treatment. In other words, immune checkpoint inhibitor therapy may or is expected to have a therapeutic effect on the subject's cancer or pre-cancer, and / or improve the therapeutic effect on the subject's cancer or pre-cancer. Such therapeutic effects can include clinical improvement of the subject's cancer or pre-cancer that has this disease or condition. Clinical improvement can be demonstrated by improvement in the pathology and / or symptoms associated with the cancer or pre-cancer. Suitably, the therapeutic effect can be demonstrated by preventing the formation of cancer or pre-cancer in the subject, slowing or arresting the progression of the subject's cancer or pre-cancer, or reversing the cancer or pre-cancer. Suitably, the cancer or pre-cancer can be reversed partially or completely. Clinical improvement of the pathology can be demonstrated by one or more of the following: a decrease in the level of a cancer or pre-cancer biomarker in the subject, a decrease in the number of cancer or pre-cancer cells in the subject, an increase in the time to cancer regrowth after cessation of treatment, prevention or delay of the development of pre-cancer to cancer, prevention of cancer regrowth at the time of cessation of treatment, a decrease in tumor invasiveness, a decrease or complete elimination of metastases, an increase in cancer cell differentiation, or an increase in survival rate. Those skilled in the art will know other suitable indications of clinical improvement of the pathology. It should be understood that the indications of clinical improvement of the pathology will vary depending on the type of cancer. Clinical improvement of symptoms associated with cancer may include, but is not limited to, partial or complete relief of pain and / or swelling, increased appetite, decreased weight loss, and / or decreased fatigue.

[0122] Appropriately, compared to non-sensitized subjects, sensitized subjects may have about 1.25-fold, 1.50-fold, 1.75-fold, 2-fold, 2.25-fold, 2.5-fold, 2.75-fold, 3-fold or more increased likelihood of treatment efficacy with PD-1 inhibitors and / or PD-L1 inhibitors.

[0123] As used herein, the term "cancer" refers to a large class of diseases that involve abnormal cell growth and have the potential to invade or spread to other parts of the body due to the presence of "cancer cells". Cancer cells may form neoplasms or subsets of tumors. A neoplasm or tumor is a group of cells that have undergone uncontrolled growth and typically form a mass or lump, but may be diffusely distributed. A tumor or neoplasm can include a mixture of cancer cells (and / or pre-cancerous cells) and healthy (i.e., non-cancerous) cells. As used herein, the term "tumor" includes cancer cells and / or pre-cancerous cells, healthy cells (e.g., stromal cells), and the tumor microenvironment including immune cells and interstitial fluid. The immune cells in the tumor microenvironment can be referred to as the "immune microenvironment" of the tumor.

[0124] The term "interstitial fluid" refers to the fluid that occupies the space between tumor cells (healthy cells, cancer cells, and / or pre-cancerous cells). Interstitial fluid can include metabolites, ions, signaling molecules, proteins, extracellular vesicles, and / or other components secreted by tumor cells and the immune cells present therein. Those skilled in the art will understand that changes in tumor cells can lead to changes in interstitial fluid. By way of example only, changes in the metabolic state of tumor cells may result in alterations in metabolites in the interstitial fluid. As demonstrated by the present inventors, such changes in the metabolic state of tumor cells may alter the tumor microenvironment, for example, by altering the immune cell population within the tumor.

[0125] "Cancer cells" can be defined by one or more of the following characteristics: reduced differentiation, self-sufficiency in growth signals, insensitivity to anti-growth signals, evasion of apoptosis, unlimited replicative potential, induction and maintenance of angiogenesis, and / or activation of tissue invasion and metastasis.

[0126] Cancer can be solid cancer or liquid cancer. Suitably, the cancer can be selected from the group consisting of childhood cancer, hematological cancer, and myeloid cancer. Suitably, the childhood cancer can be selected from the group consisting of leukemia, brain cancer, spinal cord cancer, neuroblastoma, nephroblastoma, lymphoma (such as Hodgkin lymphoma and non-Hodgkin lymphoma), rhabdomyosarcoma, retinoblastoma, and bone cancer (such as osteosarcoma and Ewing sarcoma). Suitably, the cancer can be skin cancer. Suitably, the skin cancer can be selected from the group consisting of melanoma, basal cell carcinoma, squamous cell carcinoma, Kaposi sarcoma, and keratoacanthoma. More suitably, the skin cancer may be melanoma. This application provides examples related to melanoma. However, those skilled in the art will understand that aspects of the present invention can be applied to other cancers. However, aspects of the present invention may be particularly effective in the context of melanoma.

[0127] As used herein, "precancerous" or "precancerous condition" is an abnormal condition that has the potential to become cancer (such as the cancers mentioned above), where the likelihood of becoming cancer when the abnormal condition is present is greater than when there is no abnormal condition (i.e., normal). Examples of precancerous conditions include, but are not limited to, adenoma, hyperplasia, metaplasia, dysplasia, benign neoplasia (benign tumor), in situ precancerous lesion, and polyp. In one example, the precancerous condition is a precancerous tumor. Such a tumor can include precancerous cells and healthy cells.

[0128] As will be clear to those skilled in the art, "cancer" and / or "precancerous" can be referred to as "tumor".

[0129] Suitably, in the context of the present disclosure, the cancer or precancerous condition may have a harmful mitochondrial DNA (mtDNA) mutation load. Generally, in the context of the present disclosure, subjects who are more likely to benefit from the sensitization described herein will have a cancer or precancerous condition with a low harmful mitochondrial DNA (mtDNA) mutation load. In this context, the sensitization may mimic the metabolic changes present in subjects with a high harmful mitochondrial DNA (mtDNA) mutation load (see examples below). Nevertheless, the sensitization described herein may also be beneficial to subjects with a cancer or precancerous condition with a high harmful mitochondrial DNA (mtDNA) mutation load (e.g., to further increase the therapeutic efficacy of PD-1 inhibitor and / or PD-L1 inhibitor treatment).

[0130] Suitably, cancer or pre-cancer may have a low harmful mitochondrial DNA (mtDNA) mutation load. In the context of the present disclosure, when measured solely or substantially solely on cancer or pre-cancer cells, the low harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of less than 50%. For example, when measured solely or substantially solely on cancer or pre-cancer cells, the low harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of less than 40% or less than 30%. More suitably, when measured solely or substantially solely on cancer or pre-cancer cells, the low harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of less than 20%. Suitably, in the context of the present disclosure, when measured on a sample from a subject, the low harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of less than 30%, less than 20%, less than 10%. Those skilled in the art will understand that the sample typically comprises a mixture of cancer cells (and / or pre-cancer cells) and healthy cells present in the tumor.

[0131] Suitably, cancer or pre-cancer may have a high harmful mitochondrial DNA (mtDNA) mutation load. In the context of the present disclosure, when measured solely or substantially solely on cancer or pre-cancer cells, the high harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of at least 50% or at least 60% or higher. For example, when measured solely or substantially solely on cancer or pre-cancer cells, the high harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of at least 70%, at least 80% or higher. More suitably, when measured solely or substantially solely on cancer or pre-cancer cells, the high harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of at least 60%. Suitably, in the context of the present disclosure, when measured on a sample from a subject, the high harmful mitochondrial DNA (mtDNA) mutation load can be a mutation load of at least 30%, at least 40%, at least 50% or higher. Those skilled in the art will understand that the sample typically comprises a mixture of cancer cells (and / or pre-cancer cells) and healthy cells present in the tumor.

[0132] Suitably, cancer or pre-cancer may have a high nuclear mutation load. Such cancer can be referred to as TMB-H (tumor mutation burden-high) cancer. Suitably, TBM-H cancer can be a solid cancer. Suitably, the solid cancer can be selected from the group consisting of: skin cancer (such as melanoma), lung cancer, liver cancer, kidney cancer, and head and neck cancer. Such cancers are typically found to have better sensitivity to immune checkpoint inhibitors. The inventors believe that by treating these cancers with a reagent that alters the redox state (e.g., by altering the lactate to glucose ratio), the sensitivity to checkpoint inhibitors can be further enhanced. In fact, as Figure 45As shown, it has been found that cancers with altered redox status (e.g., altered lactate to glucose ratio) due to mtDNA mutations completely regress after treatment with checkpoint inhibitors such as anti-PD1 antibodies.

[0133] Suitably, a cancer or pre-cancer may have a high nuclear mutation burden and a high mtDNA mutation burden.

[0134] In the context of the present disclosure, the term "subject" includes humans and mammals (e.g., mice, rats, pigs, cats, dogs, and horses). In suitable embodiments, the subject is a mammal, particularly a primate, especially a human. In suitable embodiments, the subject is livestock such as cattle, sheep, goats, cows, pigs, etc.; poultry such as chickens, ducks, geese, turkeys, etc.; and domestic animals, particularly pets such as dogs and cats. In certain embodiments (e.g., particularly in a research context), the subject mammal is, for example, a rodent (e.g., mice, rats, hamsters), a rabbit, a primate, or a pig (such as an inbred pig), etc. In this document, the terms "patient" and "subject" may be used interchangeably.

[0135] An immune checkpoint inhibitor is an agent that inhibits a protein or peptide (e.g., an immune checkpoint protein) that blocks the immune system, such as from attacking cancer cells. In some instances, the immune checkpoint protein that blocks the immune system prevents the production and / or activation of T cells. An immune checkpoint inhibitor can be an antibody or its antigen-binding fragment, a protein, a peptide, a small molecule, or a combination thereof. Generally, the inhibitor directly interacts with the target immune checkpoint protein (or its ligand, where appropriate) to disrupt its function / biological activity. For example, it can directly bind to the target immune checkpoint protein (or its ligand, where appropriate). In one instance, the direct binding to the target immune checkpoint protein (or its ligand, where appropriate) inhibits, prevents, or reduces the formation of the protein complex required for immune checkpoint protein function / biological activity.

[0136] PD-1 inhibitors, PD-L1, and PD-L2 inhibitors are a group of checkpoint inhibitors that block or reduce the activity of the PD-1, PD-L1, and PD-L2 immune checkpoint proteins. Pardoll provided a review in Nature Reviews Cancer (April 2012) describing the immune checkpoint pathways and the blocking of these pathways with immune checkpoint inhibitor compounds. Immune checkpoint inhibitor compounds exhibit anti-tumor activity by blocking one or more endogenous immune checkpoint pathways that downregulate the anti-tumor immune response. Inhibiting or blocking an immune checkpoint pathway generally involves inhibiting the interaction of the checkpoint receptor and ligand with the immune checkpoint inhibitor compound to reduce or eliminate the signal, and resulting in a diminished anti-tumor response.

[0137] Immune checkpoint inhibitor compounds can inhibit the signaling interaction between an immune checkpoint receptor and its corresponding ligand. Immune checkpoint inhibitor compounds can act by inhibiting (antagonizing) an immune checkpoint receptor (some examples of receptors include CTLA-4, PD-1, and NKG2A) or by inhibiting the ligand of an immune checkpoint receptor (some examples of ligands include PD-L1 and PD-L2) to block the activation of the immune checkpoint pathway. In these examples, the action of the immune checkpoint inhibitor compound is to reduce or eliminate the downregulation of certain aspects of the anti-tumor response of the immune system in the tumor microenvironment.

[0138] The immune checkpoint receptor programmed death 1 (PD-1) is expressed by activated T cells after prolonged exposure to an antigen. The engagement of PD-1 with its known binding ligands PD-L1 and PD-L2 occurs mainly in the tumor microenvironment, leading to the downregulation of the anti-tumor specific T cell response. Both PD-L1 and PD-L2 are known to be expressed on tumor cells. The expression of PD-L1 and PD-L2 on tumors is associated with reduced survival outcomes.

[0139] Many PD-1 inhibitors and / or PD-L1 inhibitors are known in the art. In some examples, the PD-1 inhibitor and / or PD-L1 inhibitor is a small organic molecule (molecular weight less than 1000 daltons), a peptide, a polypeptide, a protein, an antibody, an antibody fragment, or an antibody derivative. In some embodiments, the inhibitor compound is an antibody. In some embodiments, the antibody is a monoclonal antibody, particularly a human or humanized monoclonal antibody.

[0140] In some examples, the PD-1 inhibitor is an anti-PD-1 antibody or its derivative or antigen-binding fragment. In some embodiments, the anti-PD-1 antibody selectively binds to the PD-1 protein or its fragment. In some embodiments, the anti-PD1 antibody is nivolumab, pembrolizumab, or pidilizumab.

[0141] In some instances, the PD-L1 inhibitor is an anti-PDL-1 antibody or a derivative or antigen-binding fragment thereof. In some instances, the anti-PDL-1 antibody or a derivative or antigen-binding fragment thereof selectively binds to the PD-L1 protein or a fragment thereof. Examples of anti-PDL-1 antibodies and their derivatives and fragments are described, for example, in WO 01 / 14556, WO 2007 / 005874, WO 2009 / 089149, WO 2011 / 066389, WO 2012 / 145493; US 8,217,149, US 8,779,108; US2012 / 0039906, US 2013 / 0034559, US2014 / 0044738, and US2014 / 0356353. In some embodiments, the anti-PDL-1 antibody is MEDI4736 (durvalumab), MDPL3280A, 2.7A4, AMP-814, MDX-1105, atezolizumab (MPDL3280A) or BMS-936559.

[0142] In some instances, the anti-PDL-1 antibody is MEDI4736, also known as durvalumab. MEDI4736 is an anti-PDL-1 antibody that is selective for the PD-L1 polypeptide and blocks the binding of PD-L1 to the PD-1 and CD80 receptors. MEDI4736 can relieve PD-L1-mediated inhibition of human T cell activation in vitro and can further inhibit tumor growth in xenograft models through a T cell-dependent mechanism. For example, MEDI4736 is further described in US 8,779,108. The fragment crystallizable (Fc) domain of MEDI4736 contains a triple mutation in the constant domain of the IgG1 heavy chain that reduces binding to the complement component C1q and the Fcγ receptors responsible for mediating antibody-dependent cell-mediated cytotoxicity (ADCC).

[0143] A CTLA4 inhibitor is an inhibitor that blocks or reduces CTLA4 activity. The immune checkpoint receptor cytotoxic T lymphocyte-associated antigen 4 (CTLA4 or CTLA-4) is expressed on T cells and is involved in signal transduction pathways that reduce the level of T cell activation. It is thought that CTLA4 can downregulate T cell activation by competitively binding and sequestering CD80 and CD86. In addition, CTLA4 has been shown to be associated with enhancing the immunosuppressive activity of T Reg cells.

[0144] CTLA4 inhibitors can prevent or reduce binding to CD80 and / or CD86. In some embodiments, CTLA-4 inhibitors include antibody-binding compounds such as antibodies or antigen-binding fragments thereof. U.S. Patent Nos. 5,855,887; 5,811,097; 6,682,736; 7,452,535 disclose antibodies specific for human CTLA-4, including antibodies specific for the extracellular domain of CTLA-4 and capable of blocking its binding to CD80 or CD86; methods of preparing such antibodies; and methods of using such antibodies as anti-cancer agents. In some instances, anti-CTLA-4 antibodies are tremelimumab, ipilimumab, or pembrolizumab.

[0145] TIGIT (T cell immunoreceptor with Ig and ITIM domains) belongs to the immunoglobulin superfamily and is also known as Wucam, Vstm3, or Vsig9. TIGIT has an extracellular immunoglobulin domain, a type I transmembrane domain, and two immunoreceptor tyrosine inhibitory motifs (ITIMs). TIGIT is mainly distributed in regulatory T cells (Tregs), activated T cells, natural killer cells (NKs), etc. It is a co-inhibitory receptor protein that can bind to the positive protein CD226 (Dnam-1) and APCs on T cells. The expressed ligands CD155 (Pvr or Necl-5) and CD112 (Pvrl-2 or Nectin2) form a co-stimulatory network. Among them, TIGIT competes with CD226 for binding to CD155 and CD112, and TIGIT binds to its ligands with a higher affinity than CD226. The ligation between TIGIT and CD155 or CD112 is mediated by its cytoplasmic ITIM or ITT-like motif, recruiting the phosphatase SHIP-1 to the tail of TIGIT to trigger inhibitory signaling. In addition, the ITIM domain is also responsible for the inhibitory ability of murine TIGIT.

[0146] Suitably, TIGIT inhibitors (such as anti-TIGIT antibodies) can inhibit, reduce, or neutralize one or more activities of TIGIT, e.g., resulting in the blockade or reduction of immune checkpoints on T cells or NK cells, or reactivating the immune response by modulating antigen-presenting cells. Examples of anti-TIGIT antibodies include vibostolimab, etigilimab, triagolumab, and Domvanalimab.

[0147] The term "LAG-3", "LAG3", or "lymphocyte activation gene 3" refers to lymphocyte activation gene 3. The main ligand of LAG-3 is MHC class II, to which it binds with higher affinity than CD4. This protein negatively regulates T cell proliferation, activation, and homeostasis in a manner similar to CTLA-4 and PD-1, and has been reported to play a role in Treg inhibitory function. LAG3 is known to be involved in the maturation and activation of dendritic cells. An LAG-3 inhibitor can reduce or block the binding of LAG-3 to MHC class II molecules, thereby reducing or blocking its activity. Suitably, the LAG-3 inhibitor can be an anti-LAG-3 antibody, such as favezelimab or relatlimab.

[0148] TIM-3 is an immune checkpoint receptor that inhibits the anti-tumor response by negatively regulating the activities of CD8 T cells and antigen-presenting cells. A TIM-3 inhibitor can reduce or block the activity of TIM-3. Suitably, the TIM-3 inhibitor can be an anti-TIM-3 antibody, such as cobolimab.

[0149] B and T lymphocyte attenuator (BTLA) is an important co-signaling molecule. It belongs to the CD28 superfamily and is similar to programmed cell death 1 (PD-1) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) in terms of its structure and function. BTLA can be detected in most lymphocytes and induces immunosuppression by inhibiting B cell and T cell activation and proliferation. BTLA is found to be expressed in tumor-infiltrating lymphocytes (TIL) and is generally associated with impaired anti-tumor immune responses. A BTLA inhibitor can reduce or block the activity of BTLA. Such reduction or blockade may increase B cell and T cell activation and proliferation. Suitably, the BTLA inhibitor can be an anti-BTLA antibody, such as Tifcemalimab.

[0150] Killer immunoglobulin-like receptors (KIR) are a family of cell surface proteins present on natural killer (NK) cells. They inhibit the killing function of these cells by interacting with MHC class I molecules. A KIR inhibitor may reduce or block the activity of KIR. Such reduction or blockade may enhance the killing ability of NK cells. Suitably, the KIR inhibitor can be an anti-KIR antibody, such as lirilumab.

[0151] Suitably, the immune checkpoint inhibitor can be selected from the group consisting of: PD-1 inhibitor, PD-L1 inhibitor, PD-L2 inhibitor, CTLA4 inhibitor, TIGIT inhibitor, LAG-3 inhibitor, TIM-3 inhibitor, BTLA inhibitor, and KIR inhibitor.

[0152] Suitably, the immune checkpoint inhibitor can be an antibody. For example, the immune checkpoint inhibitor can be an anti-PD-1 antibody, anti-PD-L1 antibody, anti-PD-L2 antibody, anti-CTLA4 antibody, anti-TIGIT antibody, anti-LAG-3 antibody, anti-TIM-3 antibody, anti-BTLA antibody, and / or anti-KIR antibody.

[0153] Monoclonal antibodies, antibody fragments, and antibody derivatives for blocking the immune checkpoint pathway can be prepared by any of several methods known to those of ordinary skill in the art, including but not limited to somatic hybridization techniques and the hybridoma method. Hybridoma generation is described in Antibodies, A Laboratory Manual, Harlow and Lane, 1988, Cold Spring Harbor Publications, New York. Human monoclonal antibodies can be identified and isolated by screening a phage display library of human immunoglobulin genes, for example, by the methods described in U.S. Patent Nos. 5,223,409, 5,403,484, 5,571,698, 6,582,915, and 6,593,081. Monoclonal antibodies can be prepared using the general methods described in U.S. Patent No. 6,331,415 (Cabilly).

[0154] For example, human monoclonal antibodies can be prepared using XenoMouse TM (Abgenix, Freemont, CA) or B cell hybridomas from XenoMouse. XenoMouse is a murine host with functional human immunoglobulin genes, as described in U.S. Patent No. 6,162,963 (Kucherlapati).

[0155] Methods for preparing and using immune checkpoint antibodies are well known in the art and, by way of example only, some methods are described in the following illustrative publications. The preparation and therapeutic use of anti-CTLA-4 antibodies are described in U.S. Patent Nos. 7,229,628 (Allison), 7,311,910 (Linsley), and 8,017,144 (Korman). The preparation and therapeutic use of anti-PD-1 antibodies are described in U.S. Patent No. 8,008,449 (Korman) and U.S. Patent Application No. 2011 / 0271358 (Freeman). The preparation and therapeutic use of anti-PD-L1 antibodies are described in U.S. Patent No. 7,943,743 (Korman). The preparation and therapeutic use of anti-TIM-3 antibodies are described in U.S. Patent Nos. 8,101,176 (Kuchroo) and 8,552,156 (Tagayanagi). The preparation and therapeutic use of anti-LAG-3 antibodies are described in U.S. Patent Application No. 2011 / 0150892 (Thudium) and International Publication No. WO2014 / 008218 (Lonberg). The preparation and therapeutic use of anti-KIR antibodies are described in U.S. Patent No. 8,119,775 (Moretta). The preparation of antibodies that block the inhibitory pathway regulated by BTLA (anti-BTLA antibodies) is described in U.S. Patent No. 8,563,694 (Mataraza). In certain instances, inhibitors of PD1 and / or PD-L1 can be as described in US8354509B2 and US8900587B2, which are incorporated herein by reference. For example, immune checkpoint therapy is pembrolizumab (also known as KEYTRUDA).

[0156] The immune checkpoint inhibitor can be administered in an amount for a period of time (e.g., for a particular treatment regimen over a period of time) to provide an improvement in the pathology and / or symptoms associated with cancer or pre-cancer as described above.

[0157] The immune checkpoint inhibitor is formulated, administered, and dosed in a manner consistent with good medical practice. Factors to be considered in this context include the particular subject being treated, the clinical condition of the individual patient, the cause of the disorder, the site to which the agent is to be delivered, the method of administration, the dosing schedule, and other factors known to the practicing physician. The "therapeutically effective amount" of the immune checkpoint inhibitor to be administered will be determined by these considerations and is the minimum amount required to prevent, ameliorate, or treat or stabilize a benign, pre-cancerous, or early cancer; or to treat or prevent the occurrence or recurrence of a tumor, dormant tumor, or micrometastasis (e.g., when used as neoadjuvant therapy). The immune checkpoint inhibitor need not, but optionally can be formulated with one or more agents currently used to prevent or treat cancer.

[0158] Suitable administration routes of immune checkpoint inhibitors include, but are not limited to, oral, parenteral, subcutaneous, rectal, transmucosal, enteral administration, intramuscular, intramedullary, intrathecal, direct intraventricular, intravenous, intravitreal, intraperitoneal, intranasal or intraocular injection. Alternatively, immune checkpoint inhibitors can be administered in a local rather than a systemic manner, for example, by directly injecting the immune checkpoint inhibitor into a solid tumor or by topical application (e.g., for skin cancer).

[0159] Immune checkpoint inhibitors can be formulated according to known methods to prepare pharmaceutically useful compositions, in which the inhibitor is combined with a pharmaceutically suitable excipient or carrier in a mixture. Sterile phosphate buffered saline is an example of a pharmaceutically suitable excipient. Other suitable excipients are well known to those skilled in the art. See, for example, PHARMACEUTICAL DOSAGE FORMS AND DRUG DELIVERY SYSTEMS by Ansel et al., 5th Edition (Lea & Febiger 1990), and REMINGTON'S PHARMACEUTICAL SCIENCES edited by Gennaro, 18th Edition (Mack Publishing Company, 1990) and its revisions.

[0160] Generally, the dosage of immune checkpoint inhibitors administered to humans varies depending on factors such as the patient's age, weight, height, gender, general medical condition, and past medical history. It may be desirable to administer a dose in the range of about 1 mg / kg to 24 mg / kg as a single intravenous infusion to a subject, but lower or higher doses can also be administered depending on the circumstances. For example, for a 70-kg patient, a dose of 1 - 20 mg / kg is 70 - 1,400 mg, or for a 1.7-m patient, the dose is 41 - 824 mg / m 2 . Doses can be repeated as needed, for example, once a week for 4 - 10 weeks, once a week for 8 weeks, or once a week for 4 weeks. As needed, the frequency of administration can also be reduced, for example, every other week for several months, or monthly or quarterly for several months.

[0161] Suitably, immune checkpoint inhibitors can be used in the uses or methods described herein as the sole treatment for cancer or pre-cancer, or in combination with a secondary treatment for cancer or pre-cancer, such as surgery, radiation, chemotherapy, immunotherapy, hormone therapy, vaccine therapy, or any combination thereof.

[0162] Suitably, immune checkpoint inhibitors can be used as first-line, second-line, third-line, or further treatment for cancer or pre-cancer.

[0163] In some aspects, the present invention relates to a reagent that alters the redox state of cancer or pre-cancer (e.g., alters the lactate to glucose ratio), and is used to sensitize a subject (with cancer or pre-cancer) to immune checkpoint inhibitors (e.g., PD-1 inhibitors, PD-L1 inhibitors, PD-L2 inhibitors, CTLA4 inhibitors, TIGIT inhibitors, LAG-3 inhibitors, TIM-3 inhibitors, BTLA inhibitors, and / or KIR inhibitors). For example, the agent alters the lactate to glucose ratio in the interstitial fluid of cancer or pre-cancer.

[0164] For the reagent to alter the redox state (e.g., alter the lactate to glucose ratio), the cells of cancer or pre-cancer must be exposed to the reagent. In this context, the term "exposure" refers to an active step of bringing cancer or pre-cancer cells into contact with the reagent to alter the redox state (e.g., lactate to glucose ratio) and / or providing the reagent that alters the redox state (e.g., lactate to glucose ratio) to cancer or pre-cancer cells. Exposure can be in vitro, in vivo, or ex vivo. After in vitro or ex vivo exposure, the cells can be introduced (e.g., re-introduced) into a subject with cancer or pre-cancer.

[0165] As used herein, the term "redox state" or "metabolic state" refers to the cytoplasmic and / or mitochondrial ratio of NAD+:NADH in the cancer or pre-cancer microenvironment (e.g., throughout the tumor and / or the interstitial fluid of cancer or pre-cancer (also referred to herein as tumor interstitial fluid)). The inventors have found that reducing the NAD+:NADH ratio (mtDNA mutations) and / or increasing the deviation of the NAD+:NADH ratio from the steady-state level within cancer and / or pre-cancer cells exerts an immunomodulatory effect on the tumor, making it more sensitive to immune checkpoint inhibitors. The steady-state level in the context can refer to the level in wild-type (e.g., non-cancerous cells and / or cancer cells without mtDNA mutations). The NAD+:NADH ratio is tightly regulated in cells because the directionality and activity of numerous reactions (glycolysis, gluconeogenesis, fatty acid synthesis, DNA repair (PARP is NAD+-dependent), histone acetylation, etc.) depend on it.

[0166] In some embodiments, a reagent can be provided by nucleic acid transduction or transfection of cancer or pre-cancerous cells with a reagent that encodes for altering the redox state (e.g., altering the lactate to glucose ratio). Suitably, the encoded reagent can be an enzyme. Suitably, the enzyme can be an enzyme that increases glucose uptake and / or lactate release. For example, the enzyme can be selected from the group consisting of NADH oxidase and NADPH oxidase. As an example, NADH oxidase can be from Lactobacillus brevis. This enzyme can be referred to herein as "LbNOX". The enzyme can be suitably expressed in the cytoplasm of cancer or pre-cancerous cells. LbNOX expressed in the cytoplasm can be referred to herein as cytoLbNOX. Alternatively or additionally, the enzyme can be suitably expressed in the mitochondria of cancer or pre-cancerous cells. LbNOX expressed in the mitochondria can be referred to herein as mitoLbNOX.

[0167] By comparing B78-D14 m.12,436 80％ 、Hcmel12 m.12,436 80％ 、and the bulk tumor metabolite changes of Hcmel12cytoLbNOX tumors, which did not show any changes in common metabolites, the inventors believe that, surprisingly, the altered redox state (e.g., altered redox state of cancer and / or pre-cancerous cells) is direction-independent, and the total metabolite abundance changes are insufficient to alter the tumor immune microenvironment and render cancer or pre-cancer sensitive to treatment with immune checkpoint inhibitors. In this context, "direction-independent" may refer to a change in the direction of the NAD+:NADH ratio.

[0168] Suitably, a reagent (such as NADH oxidase, e.g., cytoLbNOX and / or mitoLbNOX) can be used in combination with a tumor-associated neutrophil-reducing compound. A tumor-associated neutrophil-reducing compound is a compound that reduces the number of tumor-resident neutrophils within a tumor. In the present context, tumor-resident neutrophils can also be referred to as tumor-associated neutrophils. The reduction can be, for example, by blocking the infiltration of tumor-resident neutrophils into the tumor, by reducing the number of neutrophils in a subject (e.g., by killing and / or blocking the production / maturation of neutrophils), or both. The killing of neutrophils can be by antibody-dependent cell-mediated cytotoxicity (ADCC). Compounds that can reduce tumor-resident neutrophils include, for example, anti-Ly6G antibodies, anti-GR1 antibodies, and / or other antibodies specific for certain neutrophil antigens (such as antibodies specific for human neutrophil antigens (HNA), selected from the group consisting of: HNA-1a, HNA-1b, and HNA-1c). These antibodies can be used to identify and eliminate neutrophils expressing these antigens.

[0169] As used herein, the term "alteration" refers to a change relative to a reference value, which may be an increase or a decrease.

[0170] Suitably, the reagents described herein alter the NAD+:NADH ratio in cancer or pre-cancer. As described elsewhere herein, the alteration may be an increase or a decrease in the NAD+:NADH ratio.

[0171] Suitably, the formulations described herein increase the lactate-to-glucose ratio in cancer or pre-cancer. Suitably, the reagent increases the lactate-to-glucose ratio in the tumor to higher than 2.5:1, 3:1, 3.5:1, 4:1 or higher.

[0172] Suitably, the reagents described herein increase the lactate-to-glucose ratio in the interstitial fluid of cancer or pre-cancer. Suitably, the reagent increases the lactate-to-glucose ratio in the tumor interstitial fluid to higher than 2.5:1, 3:1, 3.5:1, 4:1 or higher.

[0173] As used herein, the term "increased" or "increase" generally refers to the difference between a relevant level (such as metabolite, mutation load, etc.) and a suitable corresponding reference value, that is, at least about 10% higher than the reference value, for example, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90% higher than the reference value.

[0174] As used herein, the term "decrease" or "decreased" generally refers to the difference between a relevant level (such as metabolite, mutation load, etc.) and a suitable corresponding reference value, that is, decreased by at least about 5%, at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90% or the like compared to the reference value.

[0175] As used herein, in the context of a reagent that alters the lactate-to-glucose ratio, the "reference value" may be the corresponding parameter (such as the NAD+:NADH ratio, or the lactate-to-glucose ratio) of cancer or pre-cancer before exposure to the reagent. Many reagents that alter the redox state of cancer or pre-cancer (e.g., alter the lactate-to-glucose ratio) are known in the art. In addition, methods for determining lactate and glucose levels are known in the art and can be used in a conventional manner (see, for example, Cengiz et al. 2009 doi:10.1089 / dia.2009.0002; and Spahar-Deleze et al. 2021 doi:10.3390 / chemosensors9080195). Assays for measuring the NAD+:NADH ratio are also well known in the art.

[0176] The reagent can be used as a pretreatment. In this context, the reagent can be regarded as neoadjuvant therapy. The reagent can be provided before or concomitantly with immune checkpoint inhibitors (such as PD-1 inhibitors, PD-L1 inhibitors, PD-L-2 inhibitors, CTLA4 inhibitors, TIGIT inhibitors, LAG-3 inhibitors, TIM-3 inhibitors, BTLA inhibitors, and / or KIR inhibitors).

[0177] The reagent can be formulated as needed. For example, the reagent can be infused. As used herein, "infusion" refers to a solution, emulsion, or suspension. In one instance, the reagent can be injected into cancer or pre-cancer. Generally, the reagent is a cell-permeable compound or its precursor.

[0178] The reagent can be in the form of a pharmaceutical composition. The pharmaceutical composition can also contain a pharmaceutically acceptable diluent, carrier, or excipient. Such compositions can generally also contain pharmaceutically acceptable concentrations of salts, buffers, preservatives, compatible carriers, supplementary immune enhancers such as adjuvants and cytokines, and optionally other therapeutic agents.

[0179] The composition can also include antioxidants and / or preservatives. As antioxidants, mention can be made of thiol derivatives (such as thioglycerol, cysteine, acetylcysteine, cystine, dithioerythritol, dithiothreitol, glutathione), tocopherols, butylated hydroxyanisole, butylated hydroxytoluene, sulfites (such as sodium sulfate, sodium bisulfite, acetone bisulfite, sodium metabisulfite, sodium sulfite, formaldehyde bisulfite, sodium thiosulfate), and nordihydroguaiaretic acid. Suitable preservatives can be, for example, phenol, chlorobutanol, benzyl alcohol, methyl paraben, propyl paraben, benzalkonium chloride, and cetylpyridinium chloride.

[0180] The phrase "pharmaceutically acceptable" is used herein to refer to those compounds, materials, compositions, and / or dosage forms that are suitable, within the scope of reasonable medical judgment, for contact with the tissues of humans or animals without excessive toxicity, irritation, allergic response, or other problems or complications (commensurate with a reasonable benefit / risk ratio).

[0181] It should be understood that the above pharmaceutical compositions can be suitable for treating cancer or pre-cancer, particularly the various forms of cancer described herein.

[0182] The reagent can be administered to a subject by any suitable route through which a therapeutically effective amount of the reagent can be provided.

[0183] The reagent can be any suitable reagent. For example, it can be a small molecule, metabolite, antibody, nucleic acid, enzyme, etc.

[0184] Suitably, the enzyme can be NADH oxidase, such as from Lactobacillus brevis. This enzyme may be referred to herein as "LbNOX". The enzyme can be appropriately expressed in the cytoplasm of cancerous or pre-cancerous cells.

[0185] Suitably, the nucleic acid can encode NADH oxidase, such as from Lactobacillus brevis (i.e., LbNOX). The nucleic acid can incorporate different nucleic acid sequences, such as a vector.

[0186] In one example, the vector is a plasmid, viral vector or cosmid, optionally wherein the vector is selected from the group consisting of: lentivirus, retrovirus, adeno-associated virus, adenovirus, vaccinia virus, canarypox virus, herpes virus, minicircle vector and synthetic DNA or RNA.

[0187] As used herein, the term "vector" refers to a nucleic acid sequence capable of transporting another nucleic acid sequence operably linked thereto. The vector can replicate autonomously or can integrate into the host DNA. The vector can include restriction endonuclease sites for insertion of recombinant DNA and can include one or more selectable markers or suicide genes. The vector can be a nucleic acid sequence in the form of a plasmid, phage or cosmid. Preferably, the vector is suitable for expression in a cell (i.e., the vector is an "expression vector"). Preferably, the vector is suitable for expression in human T cells such as CD8 + T cells or CD4 + T cells, or stem cells, iPS cells or NK cells. In some aspects, the vector is a viral vector, such as a retroviral vector, lentiviral vector or adeno-associated viral vector. Optionally, the vector is selected from the group consisting of: adenovirus, vaccinia virus, canarypox virus, herpes virus, minicircle vector and synthetic DNA or synthetic RNA.

[0188] Preferably, the (expression) vector is capable of replicating in a host cell and being stably passed on to progeny.

[0189] The vector can contain regulatory sequences. As used herein, "regulatory sequences" refers to DNA or RNA elements capable of controlling gene expression. Examples of expression control sequences include promoters, enhancers, silencers, TATA boxes, internal ribosome entry sites (IRES), attachment sites for transcription factors, transcription terminators, polyadenylation sites, etc. Optionally, the vector includes one or more regulatory sequences operably linked to the nucleic acid sequence to be expressed. Regulatory sequences include sequences that direct constitutive expression, as well as tissue-specific regulation and / or inducible sequences.

[0190] Optionally, the vector contains a nucleic acid sequence of interest operably linked to a promoter. As used herein, a "promoter" refers to a nucleotide sequence in DNA to which RNA polymerase binds to initiate transcription. The promoter can be inducible or constitutively expressed. Alternatively, the promoter is under the control of a repressor or stimulatory protein. The promoter may be a promoter that is not naturally occurring in the host cell (e.g., it may be a foreign promoter). Those skilled in the art are well aware of the appropriate promoters for expressing a target protein, where the selected promoter depends on the host cell.

[0191] "Operably linked" means that a single one or a combination of the following control elements are joined to a coding sequence in a functional relationship (e.g., in a linkage relationship) such that the expression of the coding sequence is directed.

[0192] The vector may contain a transcription terminator. As used herein, a "transcription terminator" refers to a DNA element that terminates the function of the RNA polymerase responsible for transcribing DNA into RNA. A preferred transcription terminator is characterized by a stretch of T residues preceded by a GC-rich dyad symmetry region.

[0193] The vector may include translation control elements. As used herein, a "translation control element" refers to a DNA or RNA element that controls the translation of mRNA. A preferred translation control element is a ribosome binding site. Preferably, the translation control element is from a homologous system as the promoter, such as the promoter and its associated ribozyme binding site. Preferred ribosome binding sites are known and depend on the selected host cell.

[0194] The vector may contain restriction endonuclease recognition sites. As used herein, a "restriction endonuclease recognition site" refers to a motif on DNA that is recognized by a restriction endonuclease.

[0195] The vector may include a selectable marker. As used herein, a "selectable marker" refers to a protein that confers a phenotype on a cell when expressed in the host cell, which phenotype allows the selection of cells expressing the selectable marker gene. Typically, this may be a protein that confers a new beneficial property on the host cell (e.g., antibiotic resistance), or it may be a protein that is expressed on the cell surface and can thus be used for antibody binding. Appropriate selectable markers are well known in the art.

[0196] Optionally, the vector may also contain a suicide gene. As used herein, a "suicide gene" encodes a protein that induces modified cell death upon treatment with a specific drug. As an example, suicide can be induced in cells modified with the herpes simplex virus thymidine kinase gene after treatment with a specific nucleoside analogue (including ganciclovir), in cells modified with human CD20 after treatment with an anti-CD20 monoclonal antibody, and in cells modified with inducible caspase 9 (iCasp9) after treatment with AP1903 (reviewed in BS Jones, LS Lamb, F Goldman, A Di Stasi; Improving the safety of cell therapy products by suicide gene transfer. Front Pharmacol. (2014) 5:254). Suitable suicide genes are well known in the art.

[0197] Preferably, the vector contains those genetic elements necessary for the host cell to express the binding proteins described herein. The elements required for transcription and translation in a host cell include a promoter, a coding region for the protein of interest, and a transcription terminator.

[0198] Those skilled in the art are well aware of the molecular techniques available for preparing (expressing) vectors, and how to transduce or transfect an (expressing) vector into a suitable host cell (to thereby produce the modified cells described further below). The (expressing) vector systems described herein can be introduced into cells by conventional techniques such as transformation, transfection or transduction. "Transformation", "transfection" and "transduction" generally refer to techniques for introducing an exogenous (exogenous) nucleic acid sequence into a host cell, and thus include methods such as electroporation, microinjection, gene gun delivery, retroviral, lentiviral or adeno-associated viral vector transduction, liposome transfection, superfection, etc. The specific method used generally depends on the vector and cell type. Suitable methods for introducing nucleic acid sequences and vectors into host cells such as human cells are well known in the art; see, for example, Sambrook et al (1989) Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory, Cold Spring Harbor, N.Y; Ausubel et al (1987) Current Protocols in Molecular Biology, John Wiley and Sons, Inc., NY; Cohen et al (1972) Proc. Natl. Acad. Sci. USA 69, 2110; Luchansky et al (1988) Mol. Microbiol. 2, 637-646.

[0199] Suitable examples of reagents for altering the redox state (e.g., lactate to glucose ratio) in cancer or pre-cancer are provided below. As will be clear to those skilled in the art, these reagents can be used to alter the redox state (e.g., lactate to glucose ratio) in the interstitial fluid of cancer or pre-cancer.

[0200] Suitably, the reagent can be a compound that promotes glycolytic flux via MDH1. For example, the reagent can be isocitrate, aconitate, citrate, oxaloacetate or a NADH or NAD+ precursor.

[0201] Suitably, the reagent can be a compound that regulates NAD(H) redox handling via the malate-aspartate shuttle. For example, the compound can be selected from the group consisting of: isocitrate, aconitate, citrate, oxaloacetate, malate, fumarate, argininosuccinate.

[0202] Suitably, the reagent can be lactate. In one example, lactate can be administered to cancer or pre-cancer by lactate infusion.

[0203] Suitably, the reagent can be a glucose metabolism enzyme and / or a lactate metabolism enzyme. Optionally, the glucose metabolism enzyme can be selected from the group consisting of: hexokinase, phosphoglucose isomerase, phosphofructokinase, aldolase, isomerase, triosephosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate kinase, phosphoglycerate mutase, enolase, pyruvate kinase. Optionally, the lactate metabolism enzyme is lactate dehydrogenase (LDH) (e.g., lactate dehydrogenase A and / or lactate dehydrogenase B).

[0204] Suitably, the reagent can be an inhibitor of an enzyme that reduces glycolytic flux in cancer cells or pre-cancerous cells. Optionally, the enzyme can be pyruvate dehydrogenase or pyruvate carboxylase.

[0205] Suitably, the reagent can be an activator of an enzyme that increases lactate efflux in cancer cells or pre-cancerous cells. Optionally, the enzyme is MDH1 or GAPDH.

[0206] Suitably, the reagent can be a small molecule inhibitor of an enzyme in the malate-aspartate shuttle. Optionally, the enzyme is selected from the group consisting of: GOT1, GOT2, MDH1, MDH2, glutamate-aspartate carrier, and α-ketoglutarate-malate carrier.

[0207] Suitably, the reagent can be a small molecule activator of an enzyme in the malate-aspartate shuttle. Optionally, the enzyme can be selected from the group consisting of: GOT1, GOT2, MDH1, MDH2, glutamate-aspartate carrier, and α-ketoglutarate-malate carrier.

[0208] Suitably, the reagent can be an inhibitor of Complex I, Complex II, Complex III, or Complex IV. Suitably, the inhibitor of the Complex I inhibitor can be rotenone. Suitably, the inhibitor of the Complex II inhibitor can be thenoyltrifluoroacetone. Suitably, the inhibitor of the Complex III inhibitor can be selected from the group consisting of: antimycin A, myxothiazol, and stigmatellin. Suitably, the inhibitor of the Complex IV inhibitor can be cyanide.

[0209] Suitably, the reagent that changes the redox state can change the pyruvate-to-lactate ratio. Thus, the changed redox state can be indicated by the changed pyruvate-to-lactate ratio.

[0210] The present inventors have established a link between the altered immune cell population in the tumor microenvironment, the altered metabolic state in cancer or pre-cancer, and the high harmful mtDNA mutation load. Based on this, the present inventors believe that increasing the harmful mtDNA mutation load in cancer or pre-cancer will render cancer or pre-cancer sensitive to treatment with immune checkpoint inhibitors.

[0211] Thus, a reagent that alters the redox state in cancer or pre-cancer, such as a reagent that alters (e.g., increases) the lactate-to-glucose ratio, can be a compound that increases the harmful mtDNA mutation load in cancer or pre-cancer. A compound that increases the harmful mtDNA mutation load can do so by mutating individual mtDNA molecules or by removing unmutated mtDNA molecules. Methods for determining the harmful mitochondrial DNA (mtDNA) mutation load in cancer or pre-cancer samples from a subject are known in the art.

[0212] Optionally, the compound induces harmful mtDNA mutations (i.e., introduces mutations into the mtDNA of cancer or pre-cancer).

[0213] Suitably, the reagent can be a compound that increases the harmful mtDNA mutation load in cancer or pre-cancer, where the compound is selected from the group consisting of: mitochondrial base editing enzymes (such as DdCBE) and mitochondrial heteroplasmy manipulating enzymes (such as mtZFN, mitoTALEN, or other nucleases). It should be understood that an increase in this context is compared to the mutation load before the cancer or pre-cancer is exposed to the reagent described herein.

[0214] As used herein, the term "harmful mtDNA mutation" refers to a mutation that adversely affects the structure and / or function of the mtDNA element it encodes, as opposed to a neutral mutation (such as a silent point mutation) that has neither a positive nor a negative mutation on the corresponding coding element.

[0215] Methods for identifying harmful mtDNA mutations are known in the art. By way of example only, harmful mtDNA mutations can be selected from the group consisting of:

[0216] (i) tRNA mutations with a MitoTIP RAW score of at least 12.6 or at least 16.25;

[0217] (ii) rRNA mutations;

[0218] (iii) Truncating mutations in mtDNA genes;

[0219] (iv) Missense mutations in mtDNA genes, where the missense mutation has an Apogee score greater than 0.5, optionally where the missense mutation is selected from frameshift mutations, insertion mutations, or deletion mutations; and / or

[0220] (v) Mutations in the mtDNA D-loop region, selected from the group consisting of: the H-strand promoter (m.545-567), hypervariable segment 2 (MT-HV2; m.57-372), and hypervariable segment 1 (MT-HV1; m.16024-16390).

[0221] tRNA mutations can be in genes selected from the group consisting of: MT-TL1, MT-TA, MT-TC, MT-TD, MT-TE, MT-TF, MT-TG, MT-TH, MT-TI, MT-TK, MT-TL2, MT-TM, MT-TN, MT-TP, MT-TQ, MT-TR, MT-TS1, MT-TS2, MT-TT, MT-TV, MT-TW, and MT-TY.

[0222] rRNA mutations can be in genes selected from the group of MT-RNR1 and MT-RNR2.

[0223] Truncating or missense mutations can be in tRNA, rRNA, or protein-coding genes.

[0224] Protein-coding genes can be selected from the group consisting of: MT-ND5, MT-ND1, MT-ND2, MT-ND3, MT-ND4, MT-ND4L, MT-ND6, MT-CO1, MT-CO2, MT-CO3, MT-CYB, MT-ATP6, and MT-ATP8. These genes encode proteins that function as subunits of mitochondrial respiratory chain complexes, specifically NADH:ubiquinone oxidoreductase (Complex I), ubiquinol:cytochrome c oxidoreductase (Complex III), cytochrome c oxidase (Complex IV), or ATP synthase (Complex V). Thus, mutations can be in mtDNA genes encoding subunits of mitochondrial respiratory chain complexes (selected from the group consisting of Complex I, Complex III, Complex IV, and Complex V).

[0225] Suitably, harmful mtDNA mutations are truncating mutations, missense mutations, insertion mutations, or frameshift mutations.

[0226] Suitably, harmful mutations can be in the gene MT-ND5. Suitably, harmful mutations can be truncating mutations located in regions selected from: m.12418-12425:A indel or m.12385-12390:C indel.

[0227] Suitably, harmful mutations can be missense mutations in the MT-CO1, MT-ND5, MT-ND4, MT-CYB, or MT-TY genes.

[0228] Suitably, missense mutations can be selected from the group consisting of: m.6318C>T, m.12730G>A, m.11736T>C, m.15140G>A, m.5843A>G, and m.6214G>A.

[0229] Optionally, the inserted mutations may be selected from the group consisting of: m.16183:CC insertion - deletion and m.16192:T insertion - deletion.

[0230] The terms "mtDNA mutation load", "mtDNA heteroplasmy", "variant allele frequency", or "VAF" refer to mtDNA mutations that occur in the same cell or group of cells and co - exist with the wild - type allele. In the context of the present disclosure, the term "determine" or "determining" refers to measuring the level of mtDNA molecules containing a harmful mutation in a cell or group of cells and comparing that level to the level of mtDNA molecules that do not contain such a harmful mutation (or to the total number of mtDNA molecules present in the cell or group of cells). It should be understood that mtDNA molecules that do not contain a harmful mutation may contain other mutations, but within the meaning of the present disclosure, these mutations are not harmful.

[0231] MtDNA mutation load can generally be expressed as a percentage. For example, a mutation load of 30% means that 30% of the mtDNA molecules in a cell or group of cells (such as a sample) carry a harmful mtDNA mutation. The harmful mutations may be the same or different among all the mutated mtDNA molecules. More preferably, for measuring the mutation load, the harmful mutations in all the mutated mtDNA molecules may be the same. However, it should be understood that the mtDNA molecules with a harmful mutation used for determining the mutation load may have other (additional) harmful mutations.

[0232] Methods for determining mtDNA mutation load are well - known in the art and include mtDNA sequencing, such as single - cell mtDNA sequencing. Methods for determining mtDNA mutation load are described, for example, in Sobenin et al., 2014 (doi:10.1155 / 2014 / 292017).

[0233] In the context of some of the methods disclosed herein, the harmful mtDNA mutation load is determined in cancer or pre - cancerous samples from a subject.

[0234] The term "sample" refers to any group of cells that contains cancer cells and / or pre - cancerous cells derived from a subject. A sample can generally include a mixture of healthy cells (i.e., non - cancerous and non - pre - cancerous cells) and cancer cells (and / or pre - cancerous cells). A sample can include a tumor component, such as cells (cancer cells, pre - cancerous cells, and healthy cells), as well as interstitial fluid.

[0235] Suitably, the sample comprises at least 5%, at least 10%, at least 15%, at least 20% or more cancer cells and / or pre-cancerous cells. For example, the sample can comprise at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50% or more cancer cells and / or pre-cancerous cells.

[0236] Compared to measuring the harmful mtDNA mutation load only in cancer cells or pre-cancerous cells completely or substantially, the presence of healthy cells (which can substantially not contain harmful mtDNA mutation load) can reduce the (total) harmful mtDNA mutation load measured in the sample.

[0237] In this context, the term "substantially only" means that cancer cells account for at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or more of the cells in the sample.

[0238] Thus, by way of example only, when the harmful mtDNA mutation load in a cancer or pre-cancer sample obtained from a subject is measured to be about 30%, the harmful mtDNA-mutation load of the cancer cells or pre-cancerous cells present in the sample can particularly be greater than 30%, greater than 40%, greater than 50%, greater than 60%, greater than 70%, greater than 80% or greater than 90%.

[0239] Suitably, with reference to solid cancers, the sample can be a biopsy sample, a smear sample or an interstitial fluid sample.

[0240] Suitably, with reference to liquid cancers, the sample can be a blood sample (e.g., a whole blood sample, a plasma sample or a serum sample) or a urine sample.

[0241] Those skilled in the art will appreciate that the amount of mtDNA molecules with harmful mutations is used to determine the level of mutation load in a cell or group of cells. Herein, the proportion of mtDNA molecules with harmful mutations is referred to as "harmful mtDNA mutation load". Those skilled in the art will understand that a low proportion of mtDNA molecules with harmful mutations will correspond to a low harmful mtDNA mutation load, which may be asymptomatic (i.e., having little or no effect on the overall mitochondrial function of the cell). In contrast, a high proportion of mtDNA molecules with harmful mutations will correspond to a high harmful mtDNA mutation load, which may be symptomatic in the context of the present disclosure, i.e., having an adverse effect on the overall mitochondrial function of the cell. The adverse effect on the overall mitochondrial function of the cell may be determined by an altered redox state (e.g., mitochondrial and / or cytoplasmic metabolic state), which may be due to: an alteration in mitochondrial redox homeostasis, a decrease in oxidative phosphorylation, an increase in oxidative stress, or any combination thereof. These changes may further lead to an alteration in the cancer or pre-cancerous microenvironment, such as the interstitial fluid of the entire tumor and / or cancer or pre-cancer (also referred to herein as the interstitial fluid of the tumor). As explained in more detail below, the altered tumor microenvironment may be more or less favorable for specific populations of immune cells.

[0242] The altered redox state can be indicated by an increase in one or more cellular metabolites selected from the group consisting of: fumarate, lactate, malate, acetyl coenzyme A, aspartate, glucose, glucose 6-phosphate, glutamine, glucose 3-phosphate, glycolytic intermediates, fumarate adducts (such as succinyl GSH and / or succinyl cysteine), and argininosuccinate. In particular, the altered redox state can be indicated by an increase in the fumarate adducts succinyl GSH and / or succinyl cysteine (also referred to herein as succ.cys and succ.gsh, respectively).

[0243] Additionally or alternatively, the altered redox state may include a decrease in one or more cellular metabolites selected from the group consisting of: alpha-ketoglutarate, pyruvate, phosphoenolpyruvate, and succinate.

[0244] The harmful mtDNA mutation load may alter the NAD+:NADH ratio in the mitochondria and / or cytoplasm. Appropriately, the harmful mtDNA mutation load may increase the NAD+:NADH ratio in the mitochondria and / or cytoplasm. As shown in the examples, a perturbed NAD+:NADH ratio may lead to a partial reverse flux of MDH2 within the mitochondria (which can be determined from the ratio of (m+3) malate, citrate, aconitate, and pyruvate derived from pyruvate carboxylase).

[0245] By way of example only, the altered redox state may include changes in TCA cycle and / or urea cycle metabolites. Appropriately, these metabolites may be related to the malate-aspartate shuttle (MAS) and fumarate within the mitochondria and / or cytoplasm. As described in detail in the examples, the inventors used 1- 13 C-glutamine tracer, which revealed that changes in the NAD+:NADH ratio were associated with increased malate m+1 abundance and increased argininosuccinate m+1 abundance, but not with a-KG m+1, aconitate m+1, or aspartate m+1, indicating an increase in MDH1 flux. Thus, the altered mitochondrial metabolic state may include an increase in MDH1 flux.

[0246] By way of example only, the altered redox state may include an imbalance between lactate and glucose in a tumor (e.g., in tumor interstitial fluid). As described elsewhere herein, an altered lactate-to-glucose ratio in cancer or pre-cancer can render the cancer or pre-cancer sensitive to PD-1 inhibitors and / or PD-L1 inhibitors. In this context, the altered lactate-to-glucose ratio may be an increased lactate-to-glucose ratio.

[0247] By way of example only, the altered redox state may include an imbalance between pyruvate and lactate in a tumor (e.g., in tumor interstitial fluid). Thus, a harmful mtDNA mutation load may alter the redox state in a tumor (e.g., tumor interstitial fluid) (e.g., altering the pyruvate-to-lactate ratio).

[0248] The inventors believe that the altered redox state in cancer or pre-cancer (e.g., the altered lactate-to-glucose ratio) is responsible for these cancers or pre-cancers having significantly different proportions of immune cells in the tumor microenvironment. Given the data in the Examples section herein, the inventors believe that the altered lactate-to-glucose ratio in cancer or pre-cancer is associated with an increase in the levels of immune cells (selected from the group consisting of: NK cells; monocytes; CD4+ T cells; and immune cells expressing ISG) and / or a decrease in the levels of macrophages (e.g., tumor-associated macrophages) and / or neutrophils.

[0249] Appropriately, in the context of the present disclosure, the reagent may be a reagent that increases the levels of immune cells (selected from the group consisting of: NK cells; monocytes; CD4+ T cells; and immune cells expressing ISG) and / or decreases the levels of macrophages (e.g., tumor-associated macrophages) and / or neutrophils.

[0250] Appropriately, the reagent may decrease the level of neutrophils (e.g., tumor-infiltrating neutrophils). It should be understood that such a reagent may decrease the level of neutrophils (e.g., tumor-infiltrating neutrophils) by altering the redox state in cancer or pre-cancer.

[0251] Thus, in a further aspect, the present invention provides an immune checkpoint inhibitor for treating a subject having cancer or pre - cancer, wherein the subject has been exposed to an agent that reduces neutrophils (e.g., tumor - infiltrating neutrophils).

[0252] The present invention also provides a method of sensitizing a subject having cancer or pre - cancer to an immune checkpoint inhibitor, comprising exposing the subject to an agent that reduces neutrophils (e.g., tumor - infiltrating neutrophils).

[0253] The present invention also provides a method of treating cancer or pre - cancer in a subject, comprising administering an immune checkpoint inhibitor to the subject, wherein the subject has been exposed to an agent that reduces neutrophils (e.g., tumor - infiltrating neutrophils).

[0254] The present invention also provides a method of treating cancer or pre - cancer in a subject, comprising:

[0255] (i) exposing the subject to an agent that reduces neutrophils (e.g., tumor - infiltrating neutrophils); and

[0256] (ii) administering an immune checkpoint inhibitor to the subject.

[0257] As used herein, the term "NK cell" or "natural killer cell" refers to a subset of peripheral blood lymphocytes defined by the expression of CD56 or CD16 and the absence of the T - cell receptor (CD3).

[0258] As used herein, the term "monocyte" refers to a subset of immune cells produced in the bone marrow and migrating through the blood to body tissues where they become macrophages. Suitably, monocytes are immature, intermediate or classical monocytes. Immature monocytes are Lys6C and F480 positive. Intermediate monocytes are CD14+ and CD16+. Classical monocytes are CD14+ and CD16-.

[0259] As used herein, the term "CD4 NK - like T cell" refers to an immune cell subset of cytotoxic T cells that co - express NK receptors such as CD56, CD16 and / or CD57.

[0260] The term "CD4+ T cell" refers to helper T cells.

[0261] The term "immune cells expressing ISG" refers to a subset of cells that express interferon - stimulated genes.

[0262] The term "macrophage" refers to a subset of phagocytic cells differentiated from monocytes. The term "tumor-associated macrophage" (TAM) generally refers to macrophages present in the microenvironment of cancer (such as a tumor).

[0263] The term "neutrophil" refers to a type of white blood cell granulocyte that are the first responders of inflammatory cells. In future cancers and / or pre-cancers, neutrophils may be present within the tumor. Such neutrophils may be referred to as tumor-infiltrating neutrophils (TAN). The presence of TAN may be associated with poor prognosis.

[0264] Suitably, the level of NK cells can be increased by at least 100%, at least 150%, at least 200%, etc. Suitably, the level of tumor-associated macrophages can be decreased by at least 25%, at least 50%, at least 75%, etc. Suitably, the level of immature monocytes can be increased by at least 100%, at least 150%, at least 200%, etc.

[0265] Suitably, the level of CD4+ T cells can be increased by at least 20%, at least 50%, at least 100%, at least 200%, etc.

[0266] Suitably, the level of neutrophils can be decreased by at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or more.

[0267] Unless otherwise defined herein, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. For example, Singleton and Sainsbury, Dictionary of Microbiology and Molecular Biology, 2d Ed., John Wiley and Sons, NY (1994); and Hale and Marham, The Harper Collins Dictionary of Biology, HarperPerennial, NY (1991) provide one of ordinary skill in the art with a general dictionary of many of the terms used in the present invention. Although any methods and materials similar or equivalent to those described herein can be used in the practice of the present invention, the preferred methods and materials are described herein. Accordingly, the terms defined immediately below will be described more fully by reference to the entire specification. Further, as used herein, unless the context clearly dictates otherwise, the singular terms "a," "an," and "the" include plural referents. Unless otherwise indicated, nucleic acids are written left to right in a 5' to 3' direction; amino acid sequences are written left to right in an amino to carboxyl direction. It should be understood that the present invention is not limited to the specific methods, protocols, and reagents described, as these may vary depending on the context used by one of ordinary skill in the art.

[0268] The following non-limiting examples illustrate aspects of the present invention.

[0269] Example

[0270] Example 1

[0271] Results

[0272] The inventors have conducted the experiments described in detail below. The data generated are shown in the corresponding figures and described in the corresponding figure legends.

[0273] The inventors had previously identified that mtDNA mutations are abundant in cancer (see Figure 1 herein, obtained from the data of Gorelick et al., 2021). Interestingly, they observed a recurrence of high levels of truncated mutations at specific positions in mtDNA, which had never been observed before. Most of these are located in the complex I genes (MT-ND), and ND5 is the most commonly affected gene. Complex I is part of the respiratory chain, oxidizes NADH to NAD+, and transfers these electrons in a two-electron reduction to ubiquinone (Q) to produce ubiquinol (QH2), the energy of which is coupled to pumping protons across the mitochondrial inner membrane.

[0274] To study the role of truncating mutations in ND5, the present inventors now designed DdCBE (mitochondrial base editor) into regions of ND5 where premature stop codons were conceivably introduced (see Figure 2 ). After screening a library of candidates in B78 melanoma cells, the present inventors identified reagents for the m.12,436G>A and m.11,944G>A mutations that were effective in Mt-Nd5, both of which converted tryptophan codons to in-frame stop codons (TGA>TAA).

[0275] Using these reagents, the present inventors were able to produce cell lines with a heterogeneity (or variant allele frequency, VAF) of approximately 40% or approximately 60% for two truncating mutations (see Figure 3 ). These mutations did not affect mtDNA copy number, but a mutation dose-dependent loss of Ndufb8 protein expression was observed, which could be predicted if lower levels of Mt-Nd5 were produced.

[0276] Using native gels, the present inventors determined that the level of intact Complex I was reduced in 60% VAF cells compared to parental cells (see Figure 4 ). However, oxygen consumption rate (OCR) was not affected, and the adenylate charge was not negatively impacted, indicating that these cells were not in an energy crisis. Importantly, these cells showed an altered NAD+:NADH ratio, which could be expected since Complex I is the major cellular site of NADH oxidation. A metabolomic profile was used to compare 60% VAF cells, revealing equivalent changes in the metabolic profiles between two genetically distinct models of Mt-Nd5 truncation (see Figure 5 ).

[0277] Changes in TCA cycle metabolites may be related to the cytosolic components of the malate-aspartate shuttle (MAS) and fumarate treatment, which led the present inventors to evaluate the components of MAS within the mitochondria as well as these components within the cytosol (see Figure 6 ). To study MAS in the cytosol, the present inventors used 1- 13 C-glutamine tracing, which revealed that the change in the NAD+:NADH ratio was associated with increased malate m+1 abundance and increased argininosuccinate m+1 abundance, but not with a-KG m+1, aconitate m+1, or aspartate m+1, suggesting increased MDH1 flux rather than a) increased reductive carboxylation of glutamine, or b) increased production of argininosuccinate (and then subsequently fumarate and malate) in aspartate, which contributed to the increased steady-state abundance of malate.

[0278] Changes in TCA cycle metabolites may be related to the cytosolic components of the malate-aspartate shuttle (MAS) and fumarate treatment, which led the inventors to evaluate the components of MAS within the mitochondria and these components within the cytoplasm. Using U- 13 -C glucose, the results showed that a perturbed NAD+:NADH ratio led to a partial reverse flux of MDH2 within the mitochondria, which could be determined from the ratios of pyruvate carboxylase-derived (m+3) malate, citrate, aconitate, and pyruvate (see Figure 7 ).

[0279] The ND5 mutations in these cells were also associated with increased abundances of glycolytic intermediates (see Figure 8 , particularly Figure 8 A). MDH1 has previously been described as facilitating (by an unknown means, but likely physical interaction) the shuttle of NADH between GAPDH and MDH1. The inventors suspected that by enhanced glucose oxidation and through interaction with GAPDH, MDH1 regeneration of NAD+ could conceivably offset elevated cellular NADH. When Mdh1 was knocked down using siRNA (see Figure 8 B), significant changes in the abundances of glycolytic intermediates were observed, which further implied that MDH1 activity driven by NAD+:NADH imbalance supported the Figure 8 increase in the abundances of glycolytic intermediates shown in

[0280] Using 4- 2 H1 glucose tracing, the inventors demonstrated a preferential shuttle of electrons from glucose to malate in Mt-Nd5 mutant cells, which was not due to an increase in cellular NADH m+1 levels (see Figure 9 ). Lactate m+1 was unaffected. After MDH1 knockdown, this preferential shuttle was abolished. MDH1 knockdown was also associated with a decrease in glycolytic flux (as Figure 8 shown) and a proportional increase in lactate +1 labeling in ND5 mutant cells, indicating that GAPDH may also shuttle electrons to LDH under specific circumstances.

[0281] Figure 10A A summary of the relevant metabolic pathways is shown. A summary of how these change when the Mt-Nd5 truncated mutation occurs is as Figure 10BAs shown. Briefly, high NADH results in reverse flux of MDH2 and accumulation of cytoplasmic malate produced by MDH1. This leads to elevated fumarate, thereby increasing argininosuccinate synthesis and production of fumarate adducts succinyl-GSH / succinyl-cysteine (not shown in the schematic for clarity). Increased MDH1 activity drives glycolysis and results in excessive glucose consumption / lactate release. Oxygen consumption and ATP synthesis are unaffected at 60% VAF, although they may be affected at higher VAFs.

[0282] Then, the inventors characterized it in vivo by implanting mouse melanoma cells into immunocompetent mice and allowing tumor formation (see the experimental protocol in Figure 11 ). No significant differences in endpoint time or tumor weight were observed between wild-type (WT) and mutant, or between different VAFs. The VAF difference between the implanted cells and the resulting tumors (estimated from bulk DNA extraction) was not VAF-dependent and did not show a clear selection (the downward trend may be due to stromal contamination), and no observable differences in the mtDNA copy number of the tumors were found, but there were significant metabolic changes between low and high VAF tumors and the control group (see Figure 12 ). Of particular note were succ.Cys and succ.GSH.

[0283] Although the tumors did not appear to differ by the measurement methods used to date, when examined by bulk RNAseq, there were clear and significant differences in the transcriptional profiles between the control group and high VAF tumors, and between the control group and low VAF tumors. There were more modest but still some significant changes between low and high VAF tumors (see Figure 13 ).

[0284] Comparing control and high VAF transcriptional data using gene set enrichment analysis revealed a large number of differentially regulated processes, mainly related to cell-cell interaction, receptor signaling, and the immune system (see Figure 14 ). Of particular note was natural killer cell-mediated cytotoxicity.

[0285] When comparing low and high VAF tumors, the list of significantly altered GSEA outputs was much shorter and now focused more broadly on the immune system (see Figure 15 ). Again, of particular note was natural killer cell-mediated cytotoxicity.

[0286] Then, the inventors analyzed the tumors by flow cytometry (see Figure 16)。Significant changes in populations are shown—NK cells, TAMs, and immature monocytes, and tumor residency appears to be differentially regulated by tumor mtDNA VAF. Single-cell RNA sequencing further supports these data, indicating that multiple macrophage, monocyte, and NK cell residency populations are differentially regulated by the presence of high VAF mtDNA mutations (see Figure 17 ).

[0287] These changes in resident immune cells are associated with the pan-tumor interferon-stimulated gene response (see Figure 18 ), which is thought to be because natural killer cells and CD4+ NK-like T cells are the major sources of interferon-γ. Interestingly, the only cell populations that did not show an interferon-γ response were clusters 24 and 25, which are CD4+ NK-like T cells and myeloid dendritic cells, respectively. Dendritic cells are also a major source of interferon-α, and interestingly, cluster 25 is also one of only two populations that did not show a significantly enhanced interferon-α response.

[0288] The inventors then sought to analyze the effect of using treatments (e.g., checkpoint blockade such as anti-PD1 treatment or anti-CTLA-4 treatment) in our mice on how the mice would respond to replication. Surprisingly, the results showed that in this highly aggressive mouse melanoma model, high VAF mtDNA mutant melanomas were differentially sensitive to anti-PD1 monoclonal antibody treatment ( Figure 19 ). However, they were insensitive to anti-CTLA4 monoclonal antibody treatment.

[0289] The inventors then evaluated whether this was related to clinical outcomes. In a small clinical cohort study conducted (Riaz et al., 2017), they identified tumors with mtDNA mutations with a >50% VAF of pathogenic mtDNA mutations and calculated that the likelihood of these tumors responding to nivolumab (anti-PD1) immunotherapy was 2.5-fold higher than that of mtDNA wild-type or low VAF tumors, where 40% of >50% VAF tumors responded compared to 17% of <50% VAF tumors (see Figure 20 ). In the total metastatic melanoma cohort treated with nivolumab (n = 70), only 15 patients responded to the treatment. Of these 15, 12 had a partial response and 3 had a complete response. Surprisingly, 2 of the 3 complete responders were classified as >50% VAF in this article.

[0290] Thus, the inventors have identified a new method for identifying cancer subjects who may benefit from anti-PD1 treatment.

[0291] Materials and Methods

[0292] 1. Maintenance of cell lines

[0293] B78 melanoma cells were cultured in standard Dulbecco's Modified Eagle Medium (DMEM) (Gibco), which contained 4.5 g / L glucose and 110 mg / L sodium pyruvate, and contained 20% fetal bovine serum (FBS) (Gibco), 1% penicillin-streptomycin (Gibco), 1X GLUTAMAX (Gibco) and 100 μg / mL uridine (Sigma). Cells were incubated at 37 °C and 5% CO2, and split when approximately 80% confluent.

[0294] 2. Animal models

[0295] All animal experiments were conducted in accordance with the UK Animals (Scientific Procedures) Act 1986 under PPL P72BA642F. C57BL / 6 mice were used for all studies, with a maximum of 5 per cage, housed in temperature-controlled (21 °C) rooms with a 12-hour light-dark cycle. Male mice with an average age of 6 weeks were used.

[0296] 0.25x 10 6 cells were resuspended in 50 μL of RPMI (Gibco) and matrix (Corning) at a 1:1 ratio. Cells were injected into the flanks, and mice were sacrificed at a tumor endpoint of 15 mm. Mice receiving checkpoint blockade treatment were given 200 mg of Ultra-LEAF TM purified anti-mouse CD279 (PD-1) (Biolegend) by intraperitoneal injection. Mice were dosed 7 days after injection of tumor cells, twice a week until sacrificed on day 21 after injection, and tumors were harvested.

[0297] 3. Constructs and plasmids

[0298] Transcription activator-like effector (TALE) domains were designed. The TALE domains were cloned into the pcmCherry or pTracer backbone.

[0299] 4. Primers and siRNA

[0300] PyroMark assay primers for measuring mt.11944 heterogeneity

[0301] Forward sequence: CTTCATTATTAGCCTCTTAC (SEQ ID NO:1)

[0302] Reverse sequence: GTCTGAGTGTATATATCATG (SEQ ID NO:2)

[0303] Sequencing: CTATTGAATTTATGGTGACT (SEQ ID NO:3)

[0304] PyroMark assay primers for measuring mt.11944 heterogeneity

[0305] Forward sequence: ATATTCTCCAACAACAACG (SEQ ID NO:4)

[0306] Reverse sequence: GTTATTATTAGTCGTGAGG (SEQ ID NO:5)

[0307] Sequencing: CTATTGCTGATGGTAGT (SEQ ID NO:6)

[0308] ddPCR EvaGreen primers

[0309] ND5 forward sequence: TGCCTAGTAATCGGAAGCCTCGC (SEQ ID NO:7)

[0310] ND5 reverse sequence: TCAGGCGTTGGTGTTGCAGG (SEQ ID NO:8)

[0311] VDAC1 forward sequence: CTCCCACATACGCCGATCTT (SEQ ID NO:9)

[0312] VDAC1 reverse sequence: GCCGTAGCCCTTGGTGAAG (SEQ ID NO:10)

[0313] siRNA for metabolomics experiments

[0314] ON-TARGETplus Mouse MDH1 siRNA - SmartPool (L-051206-01-0005)

[0315] ON-TARGETplus Non-targeting Control Pool (D-001810-10-05)

[0316] 5. Antibodies

[0317] Primary and secondary antibodies for immunoblotting and BN-PAGE

[0318] Total OXPHOS Rodent WB Antibody Cocktail (ab110413) (used at 1:800)

[0319] MDH1 Polyclonal Antibody (15904-1-AP) (used at 1:1000)

[0320] 800CW Goat anti - Rabbit IgG (Licor) (used at 1:10,000)

[0321] 680RD Donkey anti - Mouse IgG (Licor) (used at 1:10,000)

[0322] Antibodies for flow cytometry

[0323] All antibodies were purchased from Biolegend and are anti - mouse antibodies.

[0324] Targets Fluorophores CD45 A700 CD11b FITC F4180 BV510 CD11c BV785 MHCII BV421 Lv6c Perpcy5.5 CD115 BV711 CX3CR1 BV605 SiglecF A647 Gp38 PE CD31 Pecy7 Epcam BV650

[0325] Table 1: Neutrophil, Eosinophil, Monocyte, and Macrophage Detection Panel

[0326] Targets Fluorophores CD3 BV605 CD45 BV421 Nk1.1 Perpcy5.5 PD-1 BV510 CD69 BV650 CD44 BV711 CD8 FITC CD4 Pecy7 B220 BV785 CD622 A700 CD27 APC CD3 BV605

[0327] Table 2: T - cell Detection Panel

[0328] 6. Cell transfection and FACS

[0329] Seed B78 cells in a 10 - cm dish to reach approximately 50% confluence on the day of transfection. Mix 20 μg of DNA with 40 μL of P3000 TM reagent and combine with 30 μL of Lipofectamine TM 3000 in a final volume of 1000 μL of OptiMEM. The transfection reagent was purchased from Invitrogen. Set up negative controls simultaneously and incubate the mixture at room temperature for 15 - 20 minutes, then add it to the dish. Incubate the cells at 37°C and 5% CO2 for 24 hours.

[0330] Prepare cells for fluorescence - activated cell sorting (FACS) in 1 ml of DMEM and 1 μg / mL of 4',6 - diamidino - 2 - phenylindole dihydrochloride (DAPI). Sort live cells to detect co - expression of mCherry and GFP and allow 10 days for recovery before heterogeneity measurement.

[0331] 7. DNA extraction

[0332] Aspirate the cell culture medium and wash the cells once with PBS. Dissociate the cells using 1X trypsin (Gibco), resuspend in cell culture medium, and centrifuge at 300 g for 5 minutes. Resuspend the pellet in 200 μL of PBS according to the manufacturer's instructions and extract DNA using the DNeasy Blood and Tissue Kit (Qiagen). Then measure the DNA concentration using NanoDrop.

[0333] Process tumor tissue (up to 20 mg) using the DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer's instructions.

[0334] 8. Pyromark PCR

[0335] According to Section 7, mix 40 ng of genomic DNA extracted from cells with 12.5 μL of 5X PyroMark PCR Master Mix, 0.05 μL of 100 μM forward and reverse primers, 2.5 μL of CoralLoad Concentrate, and water to a final volume of 25 μL. All reagents were purchased from Qiagen. Perform PCR and anneal at 60 °C according to the manufacturer's instructions.

[0336] Design pyromark assays using PyroMark Assay Design 2.0 software. Perform assays on the PyroMark Q48 Autoprep using 10 μL of each PCR product according to the manufacturer's instructions.

[0337] 9. Digital Droplet PCR (ddPCR)

[0338] Mix 1 ng / μL of sample DNA with 10 μL of ddPCR Supermix for EvaGreen (2X) (BioRad), 110 nM forward and reverse primers, and water to a final volume of 20 μL per well. Prepare samples in triplicate in a 96-well plate. Use the PX1 TM PCR Plate Sealer (Bio-Rad) to seal the plate at 180 °C for 10 seconds and briefly centrifuge to remove any bubbles. An automated droplet generator (Bio-Rad) is used to form droplets in a new 96-well plate. Reseal the plate and place it in a C1000 Touch Thermal Cycler (Bio-Rad) for PCR. Perform PCR according to the Bio-Rad ddPCR protocol for EvaGreen. After completion, use the QX200 TM Droplet Reader (Bio-Rad) to quantify the DNA.

[0339] 10. Immunoblotting

[0340] The cultured cells were digested and centrifuged at 1000 g to precipitate. The pellet was washed once with PBS and kept on ice. An appropriate amount of lysis buffer [10 mL of radioimmunoprecipitation assay (RIPA) buffer (Invitrogen), 100 μL of 1% Triton X-100 (Invitrogen), and 100 μL of Halt TM Protease and Phosphatase Inhibitor Cocktail (100X) (Invitrogen)] was added to each pellet and placed on ice for 10 minutes. The lysate solution was centrifuged at 14,000 g for 5 minutes at 4 °C. Protein quantification was performed using the Pierce BCA Protein Assay Kit (Invitrogen) in a 96-well plate according to the manufacturer's instructions.

[0341] The protein samples were made to a final concentration of 100 μg in 50 μL. Based on the BCA assay, an appropriate amount of the supernatant was mixed with 1:4 of the total volume of NuPAGE TM LDS Sample Buffer (4X) (Invitrogen) and 1:10 of the total volume of NuPAGE TM Sample Reducing Agent (10X) (Invitrogen). The samples were incubated at 37 °C for 20 minutes and then loaded into a Bolt TM 4-12% Bis-Tris Plus Gel (Invitrogen). A PageRuler TM Pre-Stained Protein Ladder (Invitrogen) was used. The gel was run at 180 V until the dye front reached the end of the gel.

[0342] Once run, the proteins were transferred to a nitrocellulose membrane by wet transfer. The gel was placed in a "transfer sandwich" in the order of sponge, filter paper, gel, nitrocellulose membrane, filter paper, and sponge. An aqueous solution of 25 mM Tris, 192 mM glycine (pH 8.3), and 20% methanol was used as the buffer and the transfer was run at 100 V for 1 hour. Then the membrane was washed in 1X TBST and then blocked with 5% non-fat milk in 1X TBST on a roller at room temperature for 1 hour. Then the solution was replaced with the primary antibody prepared in 5% non-fat milk in 1X TBST. The membrane was placed on a roller at 4 °C overnight. The next day, the membrane was washed three times with 1X TBST on a roller at room temperature for 5 minutes and then the secondary antibody was added in 1X TBST. The membrane was covered and incubated on a roller at room temperature for 1 hour. Then the membrane was washed three times with 1X TBST for 5 minutes and then imaged on a Licor Odyssey Fc imaging system.

[0343] 11. Blue native-PAGE

[0344] 11.1 Mitochondrial isolation

[0345] The cells were expanded to approximately 100x10 6 cells for mitochondrial isolation. The cells were trypsinized and pelleted into a 15 ml falcon tube. The cell pellet was washed twice in ice-cold PBS, centrifuged at 600 g between each step, and then resuspended in half volume of hypotonic buffer IB 0.1 (3.5 mM Tris-HCl pH 7.8, 2.5 mM NaCl, 0.5 mM MgCl2). The cell suspension was homogenized 80 - 100 times using a dounce homogenizer. Immediately, the packed cells of 1 / 10 of the original volume of hypertonic buffer IB 10 (0.35 M Tris-HCl pH 7.8, 0.25 M NaCl, 50 mM MgCl2) were added to the suspension, and the homogenate was transferred to a clean 15 ml falcon tube. The homogenizer was rinsed with isotonic buffer IB 1 (35 mM Tris-HCl pH 7.8, 25 mM NaCl, 5 mM MgCl2) to collect the remaining cells and added to the homogenate. The sample was centrifuged at 12,000 g for 3 minutes at 4°C to remove nuclear contamination. The supernatant was transferred to a clean tube, and this step was repeated to ensure minimal contamination. Then the supernatant was centrifuged at 17,000 g for 2 minutes at 4°C to pellet the mitochondria. Then the mitochondrial pellet was washed with homogenization medium (0.32 M sucrose, 10 mM Tris-HCl pH 7.4, 1 mM EDTA) and centrifuged again. Immediately, the mitochondrial fraction was used for BN-PAGE.

[0346] 11.2 BN-PAGE gel and imaging

[0347] All reagents were purchased through Invitrogen.

[0348] The mitochondrial pellet was dissolved in cold 1X NativePage TM sample buffer containing 1% digitonin. The sample was incubated on ice for 15 minutes and then centrifuged at 20,000 g for 30 minutes at 4°C. The protein concentration was determined using the Pierce TM BCA assay kit according to the manufacturer's instructions. Samples up to 100 μg were prepared in 50 μl of 1X NativePage TM sample buffer containing 1% digitonin. Immediately before loading the samples, NativePAGE 5% G-250 sample additive was added to each sample to a final concentration of 0.5%.

[0349] This experiment used NativePage TM Novex 3-12% Bis-Tris gel. Take out the cassette and wash the wells with dark blue cathodic buffer (1X NativePage TM Running buffer, 1X NativePage TM Cathode additive (in water)). Place the gel securely into the XCell SureLock Mini-Cell. Fill the outer chamber with approximately 600 mL of anodic buffer (1X NativePage TM Running buffer (in 950 mL water)) and approximately 200 mL of dark blue cathodic buffer in the inner chamber. Then load the samples into the wells together with NativeMark TM Unstained Protein Standard. Run the gel at 150 V and when the dye front has run down approximately 1 / 3, switch the dark blue cathodic buffer to light blue cathodic buffer zone (1X NativePage TM Running buffer, 0.1X NativePage TM Cathode additive (in water)). Then let the gel run until the dye front reaches the bottom of the cell.

[0350] Transfer the proteins to a PVDF membrane using the wet transfer method highlighted in Section 11. The transfer buffer used in this experiment was 1X NuPage Transfer Buffer and the transfer was run at 60 V for 1 hour.

[0351] Then block and blot the membrane according to the method in Section 10.

[0352] 12. Seahorse assay

[0353] One day before the assay, seed the cells at 20,000 cells / well in a Seahorse XF96 cell culture microplate (Agilent). The outer rows and columns are left empty and the cells are plated down each column. Also add 200 μL of MQ water to each well of the Seahorse XF96 sensor cartridge microplate and incubate overnight at 37 °C with 50 mL of Seahorse XF calibrant solution.

[0354] The next day, discard the water in the Seahorse XF96 sensor cartridge microplate and replace it with 200 μL of pre-warmed calibrant solution. Incubate the cartridge at 37 °C for 45 - 60 minutes. Add oligomycin, FCCP, rotenone, and antimycin A to separate ports of the Seahorse cartridge to a final concentration of 1 mM. Then place the cartridge into the Seahorse XF96 analyzer for calibration.

[0355] Meanwhile, wash the cell culture plate once with PBS. Add 150 μL of Seahorse medium (25 mM glucose, 1 mM sodium pyruvate, 2 mM L-glutamine, and 1% FBS in Seahorse XF medium) to each well and incubate at 37 °C for 30 minutes. After successful calibration, then place the plate into the Seahorse XF96 analyzer. Measure the oxygen consumption rate and extracellular acidification rate using the mitochondrial stress test template on the manufacturer's website.

[0356] 13. Metabolomics

[0357] 13.1 Experimental medium

[0358] For the steady-state metabolomics experiment, use the cell culture medium as described in Section 1, which contains 2 mM L-glutamine (Gibco) instead of 1X GLUTAMAX. Plasmax was purchased from Ximbio and supplemented with 2.5% dialyzed FBS for these experiments.

[0359] U- 13 C glucose and 4- 2 H glucose were prepared using DMEM without glucose (Gibco) and supplemented with 20% FBS, 1 mM sodium pyruvate, 100 μg / mL uridine, and 25 mM U- 13 C glucose or 4- 2 H glucose.

[0360] Use standard DMEM supplemented with 20% FBS, 100 μg / mL uridine, and 4 mM U- 13 C glutamine or 1- 13 C glutamine to prepare U- 13 C glutamine and 1- 13 C glutamine medium.

[0361] 13.2 Intracellular and medium metabolite extraction

[0362] Seed the cells in 12-well plates (in triplicate) to reach approximately 70 - 80% confluence on the day of extraction. The next day, aspirate the medium and replace it with the experimental medium, and incubate the cells for 24 hours for extraction the following day.

[0363] All work was conducted on ice to minimize significant metabolite changes. For media analysis, 20 μL of media from each well was added to 980 μL of ice-cold extraction media (50% LC / MS-grade methanol, 30% LC / MS-grade acetonitrile, 20% LC / MS-grade water). The media from each plate was then rapidly removed and the plates were washed twice with ice-cold PBS. The plates were tapped on absorbent paper to remove the remaining PBS and then 200 μL of ice-cold extraction media was added to each well. The plates were stored at 4 °C and the extraction media was transferred to ice-cold microcentrifuge tubes. Samples were centrifuged at 14,000 g for 10 min at 4 °C and then transferred to screw-cap vials. Samples were stored at -80 °C until run on a mass spectrometer by an in-house facility.

[0364] Traces from all experiments were analyzed using Tracefinder 4.0.

[0365] 13.3 Sample normalization

[0366] Plates used for extraction were air-dried at room temperature and stored at 4 °C for up to two weeks until protein determination.

[0367] The Lowry assay was used to measure the protein concentration in each well. Briefly, 200 μL of solution A (aqueous solution of 05% deoxycholate and 1 M sodium hydroxide) was added to each well, as well as to another plate (with a BSA standard curve), and the plates were shaken vigorously for 40 min at room temperature. 2 mL of solution B (0.629 mM disodium copper ethylenediaminetetraacetate, 189 mM sodium carbonate, and 200 mM sodium hydroxide) was added and the plates were shaken for 10 min. Then 200 μL of Folin & Ciocalteu phenol reagent (Sigma) was added to each well and the plates were incubated for 40 min at room temperature on a shaker. Then 200 μL from each well was transferred to a 96-well plate and the absorbance was read at 750 nm using a SpectraMax ABS Plus (Molecular Devices). The protein concentration was calculated from the standard curve and used for trace normalization.

[0368] 13.4 siRNA knockdown

[0369] For each siRNA experiment, seed 12,000 cells in each well of a 12-well plate. Plate each condition in triplicate. The next day, for each well, add 5 μL of 5 μM siRNA to 95 μL of Opti-MEM. In a separate tube, add 5 μL of DharmaFECT 1 transfection reagent (Horizon Discovery) to 95 μL of Opti-MEM. Before mixing, allow the tubes to equilibrate at room temperature for 5 minutes. Incubate the samples at room temperature for 15 - 20 minutes. Then add 800 μL of standard medium to the suspension and add to the cells. After 48 hours, add the experimental medium and extract as per Section 14.2.

[0370] 14. Bulk cell and tissue transcriptomics

[0371] Pellet 1 x 10 6 cells into a 1.5 ml microcentrifuge tube and store at -80 °C. Tumor tissue (approx. 20 mg) is stored in RNAlater TM stabilization solution (Invitrogen) and kept at -80 °C. Then send the samples on dry ice to Azenta for sample processing, sequencing, and analysis.

[0372] 15. Flow cytometry

[0373] Chop the harvested tumor (approx. 30 mg) and resuspend in digestion buffer (500 U / mL collagenase I, 100 U / mL collagenase IV, and 0.2 mg / mL DNase I in RPMI). Incubate the samples at 37 °C in a shaking rotor for 40 minutes. Then pass the samples through a 40 μm filter and centrifuge at 800 g for 3 minutes to pellet the cells. Resuspend the cells in 200 μL of FACS buffer and aliquot into two wells of a round-bottom 96-well plate. Centrifuge the plate at the same speed and discard the supernatant. Resuspend the cell pellet in 100 μL of 1:1000 Zombie Aqua (BioLegend) in PBS. Keep the plate at 4 °C for 20 minutes. As described in Section 6, recentrifuge the plate and resuspend the cell pellet in 100 μL of each flow plate made in FACS buffer. Keep the plate at 4 °C for at least 60 minutes. Recentrifuge the plate and resuspend the cell pellet in 100 μL of 4% Pierce TM 16% formaldehyde (Invitrogen) and incubate at room temperature for 10 minutes. Centrifuge the plate again and resuspend the samples in 100 μL of FACS buffer. Wrap the plate with parafilm and aluminum foil and store at 4 °C for up to 2 weeks.

[0374] Resuspend the fixed samples in FACS buffer and transfer to FACS tubes when ready to run. Record 10x10 6 events per sample on the Fortessa and analyze using FlowJo.

[0375] 16. Tumor single-cell RNA sequencing

[0376] Digest the tumor tissue according to Section 15. Then resuspend the cells in 1 ml of FACS buffer (PBS solution with 2% FBS and 0.5 mM EDTA) containing 1 μg / mL of DAPI. Viable cells are sorted and submitted to the internal institute for barcoding using the 10x Genomics chromium platform and the 3' library preparation kit. Sequencing is performed at the Glasgow Polyomics Institute. Align the single-cell sequencing reads to the mouse GRCm39 reference genome using CellRanger (version 7.0.1) and analyze the expression raw count matrix using the Seurat software package (version 4.0.6). Further separate malignant and non-malignant cells based on the whole-genome copy number landscape changes evaluated by the copykat software package (version 1.1.0). Annotate the cell types of each cluster identified in the Seurat workflow using SingleR (version 1.10.0) by comparing the gene expression correlations with known cell types in the mouse reference dataset. Perform differential gene expression analysis on the log-normalized gene expression using the MAST algorithm within the FindMarkers function in Seurat.

[0377] 17. Analysis of clinical trial data by Riaz et al.

[0378] ChrM aligned reads for patient tumor and normal samples were collected and processed according to the previously described pipeline, which is now publicly available (e.g., see Gorelick et al., Nature Metabolism 2021). Mutation identification and calculated heterogeneity were used to classify patients into mtDNA wild-type, <50% VAF, or >50% VAF groups.

[0379] The reader's attention is directed to all papers and documents filed simultaneously with or before this specification in relation to this application, and these papers and documents are available for public inspection together with this specification, and the contents of all these papers and documents are incorporated herein by reference.

[0380] All features disclosed in this specification (including any accompanying claims, abstract and drawings) and / or all steps of any method or process thus disclosed may be combined in any combination, except combinations in which at least some of these features and / or steps are mutually exclusive.

[0381] Unless expressly stated otherwise, each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by an alternative feature serving the same, equivalent or similar purpose. Thus, unless expressly stated otherwise, each feature disclosed is only an instance of a general series of equivalent or similar features.

[0382] The invention is not limited to the details of any of the foregoing embodiments. The invention extends to any novel feature or any combination of novel features among the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel step or any combination of novel steps among the steps of any method or process thus disclosed.

[0383] Sequences

[0384] PyroMark assay primers for measuring mt.11944 heterogeneity Forward sequence: CTTCATTATTAGCCTCTTAC (SEQ ID NO:1)

[0385] Reverse sequence: GTCTGAGTGTATATATCATG (SEQ ID NO:2)

[0386] Sequencing: CTATTGAATTTATGGTGACT (SEQ ID NO:3)

[0387] PyroMark assay primers for measuring mt.11944 heterogeneity Forward sequence: ATATTCTCCAACAACAACG (SEQ ID NO:4)

[0388] Reverse sequence: GTTATTATTAGTCGTGAGG (SEQ ID NO:5)

[0389] Sequencing: CTATTGCTGATGGTAGT (SEQ ID NO:6)

[0390] ddPCR EvaGreen primers

[0391] ND5 forward sequence: TGCCTAGTAATCGGAAGCCTCGC (SEQ ID NO:7)

[0392] ND5 reverse sequence: TCAGGCGTTGGTGTTGCAGG (SEQ ID NO:8)

[0393] Forward sequence of VDAC1: CTCCCACATACGCCGATCTT (SEQ ID NO:9)

[0394] Reverse sequence of VDAC1: GCCGTAGCCCTTGGTGAAG (SEQ ID NO:10)

[0395] References

[0396] Gorelick et al., 2021, Nature Metabolism Apr; 3(4):558 - 570.

[0397] Riaz et al., 2017 doi:10.1016 / j.cell.2017.09.028. Epub 2017 Oct 12.

[0398] Example 2

[0399] Results

[0400] The inventors induced premature stop codons at the tryptophan (TGA) codons within mouse mt - Nd5, similar to the hot - spot mutations present in the human MT - ND5 gene in tumors 1 ( Figure 21 A - C). TALE - DdCBE G1397 / G1333 candidates carrying a nuclear export signal were synthesized and screened in mouse B78 - D14 amelanotic melanoma cells (B.16 derivative, Cdkn2a - deficient) 9 that target the m.12,436G>A and m.11,944G>A sites to identify effective pairs Figure 1D ). Expression of the functional pairs Figure 25 A) led to approximately 40% or approximately 60% mutational heterogeneity of the isogenic cell population carrying the m.12,436G>A or m.11,944G>A truncating mutations after a single transfection or four consecutive transfections (designated as m.12,436 40％ 、m.12,436 60％ 、m.11,944 40％ and m.11,944 60％ )( Figure 21 E), as well as limited off - target mutations Figure 25 B). The resulting stable isogenic cell lines showed a heterogeneity - dependent decrease in the expression of complex I subunit Ndufb8, with no effect on other respiratory chain components Figure 21 F). This was supported by m.12,436 60％ and m.11,944 60％Tandem mass tag (TMT)-based mass spectrometry proteomics of cell lines( Figure 26 ) and blue native PAGE analysis( Figure 21 G), supported the finding that, apart from the proportion of fully assembled complex I, the abundance of individual complex I subunits was decreased without a significant impact on other components of the OXPHOS system. In-gel activity assays of complex I and complex II activities further supported this finding( Figure 21 G). The mtDNA copy number was not affected by the mutation incidence or the level of heteroplasmy( Figure 21 H), and the mt-Nd5 transcript levels were unchanged in m.12,436 60％ and m.11,944 60％ mutant cells compared to the control, which is consistent with the lack of nonsense-mediated decay in mammalian mitochondria( Figure 27 A). Interestingly, no heteroplasmic cells showed a significant decrease in oxygen consumption( Figure 21 I), adenylate energy charge( Figure 21 J), or cell proliferation( Figure 21 K). However, a ~10 mV decrease in the electrical component of the mitochondrial proton motive force Δ Ψ was detected, which combined with a commensurate trend of a ~10 mV increase in the chemical component ΔpH, resulted in an unchanged total proton motive force ΔP( Figure 27 B). The NAD+:NADH ratio was significantly affected in mutant cells( Figure 21 L), which was also reflected in the reduced:oxidized glutathione (GSH:GSSG) ratio( Figure 27 C). The effect on the cellular redox balance was further determined using NAD(P)H fluorescence in m.12,436 60％ and m.11,944 60％ cells( Figure 27 D). Collectively, these data suggest that truncating mutations in mt-Nd5 have a heteroplasmy-dependent effect on the abundance of complex I. In turn, partial complex I deficiency disrupts the cellular redox balance without significantly affecting cellular energy homeostasis, oxygen consumption, or proliferation.

[0401] m.12,436 60％ and m.11,944 60％ Unlabeled metabolomics measurements of cells revealed consistent differences in metabolite abundances in these cells relative to the control( Figure 5 ), with significantly increased steady-state abundances of malate, lactate, fumarate, argininosuccinate (AS), and the metabolic end-fumarate adducts succinylcysteine and succinyl GSH( Figure 22A). The heterogeneous dependent increase in lactate and malate abundance under constant succinate conditions in mutant cells suggests that electron flow into mitochondria via the malate-aspartate shuttle (MAS) may be affected by changes in the cellular redox state. To investigate this, the inventors first used U- 13 C-glutamine isotope tracing measures the contribution of glutamine-derived carbon to tricarboxylic acid (TCA) cycle metabolites ( Figure 28 A). This shows an increase in the abundance of malate in cytosolic oxaloacetate (OAA) derived from citrate by ATP citrate lyase as determined by the abundance of malate m+3 and the ratio of malate m+3:m+2, indicating a significant increase in heterotrophic dependence relative to the control ( Figure 28 B, C), a similar m+3:m+2 labeling pattern was also observed for urea cycle metabolites AS ( Figure 28 D). Then, the inventors tracked 1- 13 The metabolic direction of carbon in C-glutamine, the 1- 13 C-glutamine specifically labels metabolites derived from the reductive carboxylation (RC) of glutamine ( Figure 22 B, Figure 29 A). This suggests that the increase in the abundance of malate m+1 occurs at the MDH1 level ( Figure 22 C), but not significantly in the downstream or upstream metabolites aconitic acid and aspartic acid ( Figure 29 B, C), the m+1 labeling pattern of AS again matches that of malic acid ( Figure 29 D). Increased abundance of malate m+1 and AS+1 is sensitive to siRNA-mediated depletion of Mdh1 but not to cytosolic-targeted LbNOX (cytoLbNOX, a water-forming NADH oxidase). 10 ) is not sensitive to expression ( Figure 22 C, Figure 29 EG), indicating that the increase in malate abundance occurs at least in part in the cytosol via MDH1 but is not directly due to an overall change in the cytosolic NAD+:NADH redox balance.

[0402] Cellular and extracellular lactate levels were elevated, as well as the abundance of several glycolytic intermediates ( Figure 22 D) shows that pyruvate is used as an electron acceptor to rebalance NAD+:NADH by lactate dehydrogenase (LDH). 13 C-glucose tracer ( Figure 22 E), the inventors observed that m.12,436 60％ and m.11,944 60％ The abundance of lactate m+3 increased in cells, which was abolished by cytoLbNOX expression ( Figure 22 F, Figure 30A). The increase in lactate m+3 did not change the pyruvate m+3 level ( Figure 30 B), nor did it change the entry of glucose-derived carbon into the TCA cycle via pyruvate dehydrogenase (PDH) (determined by the citrate m+2:pyruvate m+3 ratio) ( Figure 30 C). However, there was a significant change in the fate of carbon entering the TCA cycle via pyruvate carboxylase (PC), as indicated by the malate m+3:citrate m+3 ratio, indicating a reversal of MDH2 ( Figure 30 D). The association of MAS with glycolysis has been a topic of recent interest, and several reports have linked mitochondrial dysfunction to the shuttle of NADH between GAPDH and MDH1 / LDH 11,12 . Using 4- 2 H1-glucose isotope tracing ( Figure 22 G), the present inventors observed an increase in the abundance of malate m+1 in m.12,436 60％ and m.11,944 60％ cells, with a similar trend in lactate m+1 abundance, and thus sensitivity to mitoLbNOX treatment and siRNA-mediated depletion of Mdh1 ( Figure 22 H, Figure 31 A, B), supporting the view that the NAD+:NADH imbalance caused by partial loss of Complex I supports enhanced glycolytic flux by coupling the cytosolic part of MAS to glycolysis. In turn, this increased glycolytic flux renders m.12,436 50 more sensitive to the competitive phosphoglucose isomerase inhibitor 2-deoxyglucose (2-DG) compared to wild-type cells (IC 60％ = 1.62 mM ± 0.063 mM), with this sensitivity further enhanced in the m.12,436 50 model (IC 60％ = 0.81 mM ± 0.064 mM) and m.11,944 50 cells (IC 80％ = 1.04 mM ± 0.040 mM) ( Figure 22 I). m.12,436 50 models (IC 60％ = 0.46 mM ± 0.080 mM), m.12,436 80％ and m.11,944 60％ cells also showed enhanced sensitivity to the low-affinity Complex I inhibitor metformin compared to wild-type ( Figure 32 A). 60% of the mutants did not show differential sensitivity to the potent Complex I inhibitor rotenone, although interestingly, m.12,436 80％ showed resistance compared to wild-type ( Figure 32B). None of the mutants showed differential sensitivity to the complex V inhibitor oligomycin. Figure 32 C). Collectively, these data indicate that truncating mutations in mt-Nd5 of complex I induce a Warburg-like metabolic state through redox imbalance rather than energy crisis. This affects the cytosolic and mitochondrial components of MAS, increases glycolytic flux, enhances sensitivity to inhibition of this adaptive metabolic strategy, and generates elevated levels of the characteristic terminal fumarate adducts succinyl-GSH and succinyl-cysteine.

[0403] After determining the specific changes in redox metabolism driven by truncating mutations in complex I, the inventors next sought to determine the impact of these metabolic changes on tumor biology. Isogeneic allografts of m.11,944G>A cells, m.12,436G>A cells, and wild-type controls were performed subcutaneously in immunocompetent C57 / Bl6 mice, and tumors formed in 100% of the grafts. The growth rates of all tumors reached similar human endpoints. Figure 23 A), with similar weights and macroscopic histological features. Figure 23 B, Figure 33 A-C). Bulk measurements of tumor heterogeneity showed a slight, comparably reduced heterogeneity of approximately 10% between the transplanted cells and the resulting tumors, which may reflect stromal and immune cell infiltration. Figure 33 D), and there were no consistent changes in mtDNA copy number detected at the bulk level. Figure 33 E). Measurement of metabolites in m.11,944 60％ mutant and control tumors revealed elevated abundances of the terminal fumarate adducts succinyl-GSH and succinyl-cysteine, which are characteristic of the metabolic rewiring observed in vitro. Figure 33 F). These markers of persistently altered tumor metabolic profiles, combined with distinct transcriptional signatures between control and mutant tumors. Figure 23 C), showed a significant elevation of several features of immune infiltration and signaling alterations in mutant tumors compared to controls, particularly allogeneic rejection, interferon γ (Ifng), and interferon α (Ifna) responses. Higher heterogeneity was associated with increased signals in the same genome. Figure 34), indicating a heterogeneous dose-dependent anti-tumor immune response. To contrast these findings with human data, the inventors utilized the Hartwig Medical Foundation (HMF) metastatic melanoma cohort and classified it into wild-type and >50% variant allele frequency (VAF) groups based on pathogenic mtDNA mutation status (see Methods). This yielded a set of 355 tumor samples (272 wild-type, 83 >50% VAF), of which 233 had transcriptional profiles. GSEA analysis revealed a consistent transcriptional phenotype between the tumors of patients carrying highly heterogeneous pathogenic mtDNA mutations and those identified in our model system ( Figure 23 D), supporting this observation. To further dissect these effects, the inventors performed whole-tumor single-cell RNA sequencing (scRNAseq) on seven control tumors, three m.12,436 60％ tumors, three m.11,944 60％ tumors, and three m.12,436 80％ tumors, obtaining 163,343 single-cell transcriptomes. Cells were clustered using Seurat and cellRanger, and the initial cell IDs were determined by scType (see Methods)( Figure 35 E, F). The assignment of malignant cells was based on: i) low or no Ptprc (CD45) expression; ii) high epithelial score 13 ; iii) aneuploidy determined by copykat analysis 14 ( Figure 35 ). Consistent with the bulk tumor transcriptional profiles, GSEA in malignant cells showed an increase in the Ifna and Ifng signatures combined with a decrease in the glycolysis signature in highly heterogeneous tumors ( Figure 23 G), which was not observed in vitro prior to implantation ( Figure 36 ). The downstream regulation of primary metabolism and subsequent immune signaling on malignant cells was also reflected in altered mTORC1 nutrient sensing, transcriptional control of metabolic genes by myc, and TNFa signaling ( Figure 23 G). GSEA in non-malignant cell clusters showed similar tumor-wide changes in transcriptional phenotypes, again observing increased Ifna, Ifng, inflammatory response, and IL2-Stat5 signaling ( Figure 23 H-K). These indicators of a broad anti-tumor immune response were accompanied by a decrease in neutrophil residence time ( Figure 3 L) and alterations in monocyte maturity ( Figure 37 A, B), with the shift in neutrophil metabolic status indicated by increased OXPHOS gene expression ( Figure 23M). Other typical gene sets that enhance the anti-tumor response, such as allogeneic rejection, also increase with the biphasic trend of the proportion of tumor-resident natural killer cells and CD4+ T cells ( Figure 37 C-E). Collectively, these data indicate that in a heterogeneity-dependent manner, the mt-Nd5 mutation is sufficient to reshape the tumor microenvironment (TME) and promote the anti-tumor immune response.

[0404] The treatment of malignant melanoma can include immune checkpoint blockade (ICB) with monoclonal antibodies (mAbs) against the immune checkpoint receptor PD1 expressed on T and B cells, blocking PD-L1 / 2 binding to limit tumor-induced immune tolerance. However, more broadly, the effectiveness of anti-PD1 therapy and the ICB response in melanoma patients are bimodal, with a large proportion of patients showing no response to the treatment and a poor disease spectrum. The limited efficacy of ICB has previously been associated with immunosuppressive tumor-associated neutrophils 15 , so the inventors inferred that even in an aggressive model of poorly immunogenic melanoma (such as B78-D14), mt-Nd5 mutant tumors might show differential sensitivity to ICB. In addition, the exhausted neutrophil population in mt-Nd5 mutant tumors also showed the highest PD-L1 expression ( Figure 37 F). To test this, the inventors performed further subcutaneous syngeneic transplantation of m.12,436 40％ , m.12,436 60％ , m.12,436 80％ , m.11,944 40％ , m.11,944 60％ and wild-type tumors in immunocompetent animals. Within 7 days after transplantation, the tumors grew untreated, and the animals were given an intraperitoneal anti-PD1 mAb regimen every 3 days until the end of the experiment ( Figure 24 A). A reduction in the heterogeneity-defined endpoint tumor weight was observed across all mtDNA mutant tumors, with higher mutant heterogeneity showing a greater response to treatment ( Figure 24 B, C, Figure 38 ), which is consistent with an increased sensitivity of mtDNA mutant tumors to immunotherapy. To validate these data, the inventors sought to further establish an independent model of aggressive, poorly immunogenic murine melanoma ( Figure 39 A). This resulted in engineered Hcmel12 (Hgf, Cdk4 R24C ) 16 cells to carry >80% of the m.12,436G>A mutation, indicating that its cellular and metabolic phenotypes were consistent with B78-D14 ( Figure 39 B-J). Hcmel12 m.12,436 80％and wild-type Hcmel12 cells were transplanted into mice using a similar experimental workflow as before ( Figure 24 D). When untreated, the end-point time and end-point tumor weight of Hcmel12 m.12,436 80 and wild-type tumors were comparable ( Figure 40 A, B). Changes in overall heterogeneity, copy number, and tumor metabolism were also similar to those of B78-D14 tumors ( Figure 40 C-D). Additionally, when anti-PD1 treatment was administered, a mtDNA mutation-dependent response was observed in Hcmel12, to a similar extent as in B78-D14 ( Figure 24 E, F). To dissect the enhanced ICB response into metabolic and non-metabolic effects of mtDNA mutations, the inventors modified wild-type Hcmel12 cells to constitutively express cytoLbNOX, which recapitulated key elements of the extracellular mutant Mt-Nd5-associated metabolic phenotype, particularly glucose uptake and lactate release ( Figure 41 ). When transplanted into mice, Hcmel12cytoLbNOX tumors showed comparable end-point times and end-point tumor weights to wild-type or Mt-Nd5 mutant tumors ( Figure 40 A, B). When challenged with anti-PD1 treatment, Hcmel cytoLbNOX tumors recapitulated the response of Hcmelmt-Nd5 m.12,436 80％ tumors, indicating that specific changes in redox metabolism associated with mtDNA mutations are sufficient to render tumors sensitive to ICB ( Figure 24 E, F). To contrast these findings in mice with real-world clinical data, the inventors re-analyzed a previously reported, well-characterized cohort of mostly untreated metastatic melanoma patients who received a dosing regimen of anti-PD1 mAb nivolumab ( 17 . By identifying mtDNA-mutated cancers and stratifying this patient cohort solely based on cancer mtDNA mutation status ( Figure 24 G), 70 patients in this cohort were divided into three groups: mtDNA wild-type (33), <50% VAF (23), and >50% VAF (14). For partial or complete response to nivolumab, the cancer mtDNA mutation status - initial cohort response rate was 22%, but the response rate for >50% mtDNA mutation VAF cancers was 2.6-fold that of wild-type or <50% VAF cancers ( Figure 24 H), recapitulating our laboratory findings in patients.

[0405] These data confirm that somatic mtDNA mutations, commonly observed in human tumors, can have a direct impact on the cancer cell metabolic phenotype. Compared to germline mtDNA mutations that occur clinically,6 Tumor mtDNA mutations can exert these effects at relatively low heteroplasmy loads without negatively impacting oxygen consumption or energy homeostasis. The observed direct link between redox perturbation and enhanced glycolytic flux subtly alters our view of mtDNA mutations, making them events of adaptive gain of function rather than complete loss of function, and the finding that mtDNA mutations can support aerobic glycolysis warrants further evaluation of classical Warburg metabolism 18 and the relationship between mtDNA mutation status.

[0406] In addition to the intrinsic effects in cancer cells, the data presented here reveal that the functional consequence of somatic mtDNA mutations in tumor biology is the remodeling of the TME, mediating susceptibility to ICB. Similar to those described herein, truncated mutations of mtDNA affect 10% of all cancers, regardless of tissue lineage, and non-truncated pathogenic mtDNA mutations are present in an additional 40 - 50% of all cancers. The anti-tumor immune response in these cancers is also expected to be widely affected.

[0407] In addition to exploiting mtDNA mutation tumor susceptibility, our data suggest that the nature of the ICB response control effect observed by the inventors is primarily metabolic. Therefore, reconstructing this metabolic state in mtDNA wild-type or "immunologically cold" tumor types may also be beneficial.

[0408] Furthermore, the inventors have confirmed that the level of pSTAT1 is actually significantly elevated in tumors expressing mitoLbNOX compared to wild-type. When combined with Figure 50 the remaining data presented, this suggests that the role of mitoLbNOX in immunotherapy is similar to that of cytoLbNOX, if not more effective (since in immunocompetent animals, the growth of mitoLbNOX tumors in the untreated setting is significantly slower than wild-type, where cytoLbNOX tumor growth is comparable to wild-type in the untreated immunocompetent setting.

[0409] Methods

[0410] Maintenance, transfection, and FACS of cell lines

[0411] B78 melanoma cells (RRID:CVCL_8341) and Hcmel12 cells 16 in the presence of GLUTAMAX TM, maintained in DMEM containing 0.11 g / L sodium pyruvate, 4.5 g / L D-glucose (Life Technologies), supplemented with 1% penicillin / streptomycin (P / S) (Life Technologies) and 10% FBS (Life Technologies). Cells were grown in an incubator at 37 °C and 5% CO2. Cells were transfected with Lipofectamine 3000 (Life Technologies) at a ratio of 5 μg of DNA: 7.5 μl of Lipofectamine 3000. Cells were sorted as outlined in 19 and then grown in the same basal DMEM medium supplemented with 20% FBS and 100 μg / mL uridine (Sigma).

[0412] Use of animal models

[0413] Animal experiments were conducted in accordance with the UK Animals (Scientific Procedures) Act 1986 (P72BA642F) and complied with the ARRIVE guidelines approved by the local Animal Welfare and Ethical Review Board of the University of Glasgow. Mice were housed in conventional cages in the animal room at a controlled temperature (19 - 23 °C) and humidity (55 ± 10%), with a 12-hour light / dark cycle. Only male C57BL / 6 mice of approximately 8 weeks of age were used in the experiments. They were injected subcutaneously with 2.5 x 10 5 B78 cells or 1 x 10 4 HcMel12 cells, both prepared in a 1:1 RPMI (Life Technologies) and Matrigel (Merck). Mice were sacrificed at the end point of 15 mm tumor measurement.

[0414] For immunotherapy experiments, mice received a dosing regimen of 200 μg of anti-PD1, administered intraperitoneally twice a week. The first dose was administered 7 days after injection, and all mice were sacrificed 21 days or 13 days after injection of B78 or HcMel12 cells, respectively.

[0415] Construction of DdCBE plasmids

[0416] TALEs targeting mt.12,436 and mt.11,944 were designed on the advice of Beverly Mok and David Liu (Broad Institute, USA). As Figure 1A shown, synthetic TALEs (ThermoFisher GeneArt) were synthesized, with the left TALE cloned into pcDNA3.1(-)_mCherry 19 and the right cloned into pTracer CMV / Bsd 19Co-expression of mCherry and GFP is respectively allowed.

[0417] Pyrosequencing analysis

[0418] DNA was extracted from cell pellets using the DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer's instructions. Then, 50 cycles of PCR were performed using the PyroMark PCR Mix (Qiagen) with an annealing temperature of 50 °C and an extension time of 30 seconds. The PCR products were run on the PyroMark Q48 Autoprep (Qiagen) according to the manufacturer's instructions.

[0419] PCR primers for mt.12,436

[0420] Forward sequence: 5’-ATATTCTCCAACAACAACG-3’

[0421] Reverse sequence: 5’-Biotin-GTTATTATTAGTCGTGAGG-3’

[0422] PCR primers for mt.11,944

[0423] Forward sequence: 5’-CTTCATTATTAGCCTCTTAC-3’

[0424] Reverse sequence: 5’-Biotin-GTCTGAGTGTATATATCATG-3’

[0425] Sequencing primers for mt.12,436

[0426] 5’-TTGGCCTCCACCCAT-3’

[0427] Sequencing primers for mt.11,944

[0428] 5’-TAATTACAACCTGGCACT-3’

[0429] Protein extraction and measurement

[0430] Cells were lysed in RIPA buffer (Life Technologies) supplemented with cOmplete Mini Tablet and cOmplete Mini Protease Inhibitor Tablet (Roche). Samples were incubated on ice for 20 minutes and then centrifuged at 14,000 g for 20 minutes. Then, the isolated supernatant containing total cellular proteins was quantified using the DC Protein Assay (Bio-Rad Laboratories) according to the manufacturer's instructions.

[0431] Immunoblotting

[0432] To detect proteins by Western blotting, 60 μg of protein was resolved on a SDS-PAGE 4-12% Bis-Tris Bolt gel (Life Technologies). Proteins were transferred onto a nitrocellulose membrane using a Mini Trans-Bolt transfer cell (Bio-Rad Laboratories). The membrane was then stained with Ponceau S staining solution (Life Technologies) to measure the loading, and then incubated overnight with primary antibodies prepared in 1X TBST solution with 5% milk. Imaging was performed using an Odyssey DLx imaging system (Licor).

[0433] Antibodies:

[0434] Total OXPHOS Rodent WB Antibody Cocktail (1:800, ab110413, Abcam)

[0435] Monoclonal anti- M2 antibody (1:1000, F1804, Sigma)

[0436] Recombinant anti-vinculin antibody (1:10,000, ab129002, Abcam)

[0437] Mitochondrial isolation

[0438] Cells were grown in falcon 5-layer cell culture flasks (Scientific Laboratory Supplies) and grown to near 100% confluence. Then the cells were harvested and mitochondria were extracted as 20 described.

[0439] Blue native PAGE

[0440] Dissolve the isolated mitochondria in 1X NativePage sample buffer (Life Technologies) supplemented with 1% digitonin. Incubate the samples on ice for 10 minutes and then centrifuge at 20,000 g for 30 minutes at 4 °C. Isolate the supernatant and quantify the total extracted protein using the DC protein assay (Bio-Rad Laboratories). Prepare and run the samples on a NativePage 4-12% Bis-Tris gel according to the manufacturer's instructions (Life Technologies). For immunoblotting, transfer the samples to a PVDF membrane using a Mini Trans-Bolt transfer cell (Bio-Rad Laboratories). Subsequent probing and imaging were performed as described above for immunoblotting. Visualize the loading on a parallel gel using Coomassie blue.

[0441] As 20 described, perform in-gel assays for the activities of Complexes I and II.

[0442] Digital droplet PCR

[0443] mt-Nd5 primers

[0444] Forward sequence: 5’-TGCCTAGTAATCGGAAGCCTCGC-3’

[0445] Reverse sequence: 5’-TCAGGCGTTGGTGTTGCAGG-3’

[0446] VDAC1 primers

[0447] Forward sequence: 5’-CTCCCACATACGCCGATCTT-3’

[0448] Reverse sequence: 5’-GCCGTAGCCCTTGGTGAAG-3’

[0449] Prepare samples in triplicate in a 96-well plate using 1 ng of DNA, 100 nM of each primer, 10 μL of QX200 ddPCR EvaGreen Supermix, and water (to 20 μL). Then perform droplet generation, PCR, and measurement on a QX200 Droplet Digital PCR System (Bio-Rad Laboratories) according to the manufacturer's instructions, with the primer annealing temperature set at 60 °C.

[0450] Seahorse assay

[0451] Perform the Seahorse XF Cell Mito Stress Test (Agilent) according to the manufacturer's instructions. Briefly, one day before the assay, seed the cells at 2x 10 4 cells / well into a Seahorse 96-well plate. The sensor cartridge is also allowed to hydrate overnight in water at 37 °C. Replace the water with Seahorse XF Calibrant and re-incubate the sensor cartridge for 45 minutes. Then, add oligomycin, FCCP, rotenone, and antimycin A to their respective Seahorse ports to a final concentration of 1 μM in the wells before performing sensor calibration on the Seahorse XFe96 Analyzer (Agilent). At the same time, replace the cell culture medium with 150 μL of Seahorse XF medium supplemented with 1% FBS, 25 mM glucose, 1 mM sodium pyruvate, and 2 mM glutamine and incubate at 37 °C for 30 minutes. After calibration, then insert the cell plate into the analyzer and run.

[0452] For normalization of the readings, protein extraction and measurement were performed as described above.

[0453] In vitro metabolomics

[0454] Seed the cells two days before metabolite extraction to achieve 70 - 80% confluence on the day of extraction. Incubate the plate overnight at 37 °C and 5% CO2. The next day, supplement the cells with an excess of fresh medium to prevent starvation during extraction. For the steady-state experiments, prepare the medium as described above, replacing GLUTAMAX with 2 mM L-glutamine TM . For the U- 13 C-glucose and 4- 2 H1-glucose isotope tracer experiments, prepare the medium as follows: DMEM, glucose-free (Life Technologies), supplemented with 0.11 g / L sodium pyruvate, 2 mM L-glutamine, 20% FBS, 100 μg / mL uridine, and 25 mM glucose isotope (Cambridge Isotopes). For the isotope tracer experiments using U- 13 C-glutamine and 1- 13 C-glutamine, DMEM containing 4.5 g / L D-glucose and 0.11 g / L sodium pyruvate was supplemented with 20% FBS, 100 μg / mL uridine, and 4 mM glutamine isotope (Cambridge Isotopes).

[0455] On the day of extraction, 20 μL of medium was added to 980 μL of extraction buffer in each well. Then the cells were washed twice with ice-cold PBS. Then extraction buffer (50:30:20, v / v / v, methanol / acetonitrile / water) (600 μL per 2x10 6 was added to each well and incubated at 4 °C for 5 minutes. The samples were centrifuged at 16,000 g for 10 minutes at 4 °C, and the supernatant was transferred to a liquid chromatography-mass spectrometry (LC-MS) glass vial and stored at -80 °C until run on the mass spectrometer.

[0456] Metabolite profiling and subsequent targeted metabolomics analysis were performed as described in 21 . The compound peak areas were normalized to the total measured protein per well quantified using the modified Lowry assay 21 .

[0457] In vitro determination of fumarate

[0458] Prepare samples as described above.

[0459] Fumarate analysis was performed using a Q Exactive Orbitrap mass spectrometer (Thermo Scientific) coupled with an Ultimate 3000 HPLC system (Thermo Fisher Scientific). Metabolite separation was performed using a HILIC-Z column (InfinityLab Poroshell 120, 150 x 2.1 mm, 2.7 μm, Agilent), and the mobile phase consisted of a mixture of A (40 mM ammonium formate, pH = 3) and B (90% ACN / 10% 40 mM formamide). The flow rate was set at 200 μL / min, and the injection volume was 5 μL. The gradient started at 10% A for 2 minutes, followed by a linear increase to 90% A for 15 minutes; then 90% A was held for 2 minutes, followed by a linear decrease to 10% A for 2 minutes, and finally re-equilibrated with 10% A for 5 minutes. The total run time was 25 minutes. The Q Exactive mass spectrometer was operated in negative mode with a resolution of 70,000 at 200 m / z, in the range of 100 m / z to 150 m / z (auto gain control (AGC) target of 1 x 10 6 , and a maximum injection time (IT) of 250 ms).

[0460] siRNA knockdown for metabolomics

[0461] 1.2 x 12 4Cells were seeded into 12-well cell culture plates and incubated overnight at 37 °C and 5% CO2. The next day, cells were transfected with 5 μL of 5 μM siRNA and 5 μL of DharmaFECT 1 transfection reagent (Horizon Discovery). Cells were transfected with ON-TARGETplus MDH1 siRNA (L-051206-01-0005, Horizon Discovery) or ON-TARGETplus nontargeting control siRNA (D-001810-10-05, Horizon Discovery). The next day, cells were replenished with excess medium, and metabolites were extracted 48 hours after transfection as described above.

[0462] LbNOX treatment for metabolomics

[0463] pUC57-LbNOX (addgene #75285) and pUC57-mitoLbNOX (addgene #74448) were obtained. The two enzyme sequences were amplified using Phusion PCR (Life Technologies) according to the manufacturer's instructions. These products were cloned into pcDNA3.1(-)_mCherry 19 for subsequent experiments.

[0464] Forward sequence for LbNOX: 5’-GGTGGTGCTAGCCGCATGAAGGTCA CCG-3’

[0465] Forward sequence for mitoLbNOX: 5’-GGTGGTGCTAGCCGCATGCTCGC TACAAG-3’

[0466] Reverse sequence: 5’-GGTGGTGGATCCTTACTTGTCATCGTCATC-3’

[0467] Cells were transfected and sorted as described above, and 3 x 10 4 mCherry+ cells were seeded per well in 12-well plates. Cells were allowed to recover overnight at 37 °C and 5% CO2, and then excess medium was added to each well. Metabolites were extracted the next day and analyzed as described above.

[0468] Global tumor metabolomics

[0469] At harvest, tumor fragments (20 - 40 mg) were snap-frozen on dry ice. Metabolites were extracted using a Precellys Evolution homogenizer (Bertin) with 25 μL of extraction buffer per mg of tissue. Samples were then centrifuged at 16,000 g for 10 minutes at 4 °C, and the supernatant was transferred to LC-MS glass vials and stored at -80 °C until analysis.

[0470] Samples were run and subsequent targeted metabolomics analysis was performed as described in 21 . Compound peak areas were normalized using tissue mass.

[0471] Calculate cell sensitivity to 2-DG

[0472] Cells were plated at 500 cells / well in 200 μL of cell culture medium in 96-well plates. The plates were incubated overnight at 37 °C and 5% CO2. The next day, the medium was replaced with 0 - 100 mM 2-DG, in quadruplicate. The plates were imaged every 4 hours on an IncuCyte Zoom (EssenBioscience) for 5 days. Final confluence measurements were calculated using the system algorithm, and IC 50 .

[0473] Global tumor RNA sequencing

[0474] Tumor fragments (20 - 40 mg) were stored in RNAlater (Sigma) and kept at -80 °C. Samples were sent to GeneWiz Technologies for RNA extraction and sequencing.

[0475] HcMel12 transduction

[0476] cytoLbNOX was cloned into the lentiviral plasmid pLex303 via NheI and BamHI restriction sites and transduction of HcMel12 was performed as described in 22 . Transduced cells were selected by supplementing with 8 μg / mL blasticidin, and single clones were picked from the total surviving population. cytoLbNOX expression was confirmed using immunoblotting.

[0477] pLEX303 was a gift from David Bryant (Addgene plasmid #162032; http: / / n2t.net / addgene:162032; RRID:Addgene_162032).

[0478] Hartwig dataset analysis

[0479] The dataset of the Hartwig Medical Foundation (HMF) includes WGS data of tumor metastasis normal matched samples from 355 melanoma patients (primary tumor site in the skin), and RNA sequencing data of additional tumor samples from 233 patients. The nomenclature and annotation of mtDNA somatic mutations were as described previously 1 . Briefly, variants called by both Mutect2 and samtools mpileup were retained and fused using vcf2maf, which embeds the Variant Effect Predictor (VEP) variant annotator. Variants within repetitive regions (chrM:302-315, chrM:513-525, and chrM:3105-3109) were filtered out. Next, as described previously, variants were filtered out if the variant allele fraction (VAF) in the tumor sample was less than 1% and less than 0.24% in the normal sample (Yuan et al., 2020). Finally, somatic variants were retained when supported by at least one read in both the forward and reverse directions. Samples with mtDNA complex I truncating mutations (frameshift indels, translation start site, and nonsense mutations) and missense mutations with a VAF > 50% were classified as mutant, and the rest were wild-type. Gene expression data were obtained from the output generated by the isofox pipeline provided by HMF. The adjusted transcripts per million (“adjTPM”) gene counts for each sample were combined into a matrix. Gene expression and mutation data were used for differential expression analysis with DESeq2 in R using the DESeqDataSetFromMatrix function. Gene set enrichment analysis (GSEA) was performed in R using fGSEA against the mSigDB Hallmark gene set collection (v.7.5.1), with a minimum set size of 15 genes, a maximum set size of 500 genes, and 20,000 permutations. The normalized enrichment score (NES) ranks significantly upregulated and downregulated gene sets.

[0480] Statistical methods

[0481] No statistical test was used to determine the sample size. Mice were randomly assigned to different experimental groups. The samples were blinded to the machine operators (metabolomics, proteomics, RNA sequencing). The researchers were blinded to the experimental groups of the in vivo anti-PD1 experiment. The specific statistical tests used to determine significance, group size (n), and P value are provided in the legend. P values < 0.05, < 0.01, and < 0.001 are indicated as *, **, and *** in the figures, respectively. All statistical analyses were performed using Prism (GraphPad) and Rstudio.

[0482] Data and code availability statement

[0483] All non-commercial plasmids used have been deposited at addgene (Gammage Lab). All metabolomics data, mtDNA sequencing, bulk and single-cell RNA sequencing, and proteomics data included in this study are available in the Supplementary Information or through the designated public repositories.

[0484] mtDNA sequencing

[0485] Cell DNA was amplified using PrimeStar GXL DNA polymerase (Takara Bio) according to the manufacturer's instructions to generate two overlapping mtDNA products of approximately 8 kbp.

[0486] Primers

[0487] Forward sequence 1: 5’-ACTGATATTACTATCCCTAGGAGG-3’

[0488] Reverse sequence 1: 5’-TTTGAGTAGAACCCTGTTAGG-3’

[0489] Forward sequence 2: 5’-GGCCTGATAATAGTGACGC-3’

[0490] Reverse sequence 2: 5’-GGTTGGGTTTAGTTTTTGTTTGG-3’

[0491] The resulting amplicons were sequenced using the Illumina Nextera kit (150 cycles, paired-end). To determine the percentage of non-target C mutations in mtDNA, we first identified all C / G nucleotides with sufficient sequencing coverage (>1000X) in the reference and experimental samples. Then, for each of the 4 experimental samples, we determined the positions in the experimental sample where the sequencing reads corresponded to G>A / C>T mutations. We further filtered the resulting list of mutations to retain only mutations with a heterogeneity of more than 2% and removed mutations that were also present in the control samples. Finally, the non-target percentage was calculated as the fraction of mutated positions among all possible C / G positions.

[0492] Sample preparation for MS analysis

[0493] Cells were lysed in a buffer containing 4% SDS in 100 mM Tris-HCl pH 7.5 and 55 mM iodoacetamide. Then, as previously described in 23Samples were prepared by the method described in [reference], with slight modifications. First, alkylated proteins were digested with endoprotease Lys-C (1:33 enzyme:lysate) for 1 hour, and then with trypsin (1:33 enzyme:lysate) overnight. Digested peptides from each experimental condition and pool sample were differentially labeled using the TMT16-plex reagent (Thermo Scientific) according to the manufacturer's instructions. The fully labeled samples were mixed in equal amounts and desalted using a 100 mg SepPak C18 reversed-phase solid-phase extraction column (Waters). TMT-labeled peptides were separated by high-pH reversed-phase chromatography on a C18 column (150×2.1 mm i.d. - Kinetex EVO (5 μm, )) using a two-step gradient from 1% to 28% of B (80% acetonitrile) in 42 minutes and then from 28% to 46% of B in 13 minutes, yielding a total of 21 fractions for MS analysis.

[0494] UHPLC-MS / MS analysis

[0495] Peptides were separated by nano-scale C18 reversed-phase liquid chromatography using the EASY-nLC II 1200 (Thermo Scientific) coupled with an Orbitrap Fusion Lumos mass spectrometer (Thermo Sciences). Elution was performed using a binary gradient of buffer A (water) and B (80% acetonitrile), both containing 0.1% formic acid. Samples were loaded with 6 μl of buffer A and injected into a 50 cm fused-silica emitter (NewObjective) internally packed with ReproSil-Pur C18-AQ, 1.9 μm resin (Dr Maisch GmbH). The packed emitter was maintained at 50 °C by a column oven (Sonation) integrated into the nanoelectrospray ion source (Thermo Scientific). Peptides were eluted at a flow rate of 300 nl / min using different gradients optimized for three sets of fractions: 1 - 7, 8 - 15, and 16 - 21 23。The collection duration for each fraction was 185 minutes. The eluted peptides were electrosprayed into the mass spectrometer using a nanoelectrospray ion source (Thermo Scientific). An active background ion reduction device (ESI source solution) was used to reduce the air pollutant signal level. Xcalibur software (Thermo Scientific) was used for data acquisition. A full scan in the mass range of 350 - 1400 m / z was obtained at 60,000 resolution at 200 m / z, with a target value of 500,000 ions and a maximum injection time of 50 ms. The most intense ions were fragmented by higher energy collision dissociation in a 3 - second cycle time, with a maximum injection time of 120 ms or a target value of 100,000 ions. The peptide fragments were analyzed in the Orbitrap at 50,000 resolution.

[0496] Proteomics data analysis

[0497] The MS raw data was processed with MaxQuant software 24 v.1.6.1.4 and searched with the Andromeda search engine 25 against SwissProt 26 Mus musculus (25,198 entries). The first and main searches were performed with a precursor mass tolerance of 20 ppm and 4.5 ppm, respectively, and an MS / MS tolerance of 20 ppm. The minimum peptide length was set to six amino acids, and the specificity of trypsin cleavage was required, allowing a maximum of two missing cleavage sites. MaxQuant was set to perform quantification on "reported ion MS2", and TMT16plex was set as the isobaric tag. MaxQuant corrected for interference between TMT channels using the correction factors provided by the manufacturer. The "filter by PIF" option was activated, and a "reported ion tolerance" of 0.003 Da was used. The modification of cysteine residues by iodoacetamide (carbamidomethylation) and methionine oxidation and N - terminal acetylation modifications were designated as variable. The false discovery rate (FDR) for peptides, proteins, and sites was set to 1%. The MaxQuant output ProteinGroup.txt file was used for protein quantification analysis with Perseus software 27 version 1.6.13.0. The dataset was filtered to remove potential contaminants and reverse peptides that matched the decoy database, as well as proteins identified only by sites. Only proteins with at least one unique peptide and quantified in all replicates of at least one experimental group were used for analysis. Missing values for each column were added individually. The TMT - corrected protein intensities were first normalized by the median of all intensities measured in each replicate, and then the LIMMA plugin in Perseus was used 28Normalization was performed. Using a permutation-based Student's t-test with an FDR set to 1%, proteins significantly regulated between the two groups were selected.

[0498] Mitochondrial membrane potential and pH gradient

[0499] As 29-30 described, multi-wavelength spectrometry was used to measure the membrane potential and pH gradient. Briefly, isolated cultured cells were gently tapped and then centrifuged and resuspended at a density of 1×10 7 cells / mL in FluroBrite supplemented with 2 mM glutamine in a temperature control room. Then, changes in the mitochondrial cytochrome oxidation state were measured using multi-wavelength spectrometry. The baseline oxidation state was measured by back-calculation, using hypoxia to fully reduce the cytochrome, and a combination of 4 μM FCCP and 1 μM rotenone to fully oxidize the cytochrome. Then, the membrane potential was calculated based on the redox balance of the b-heme of the bc1 complex, and the pH gradient was measured using a turnover model based on the turnover rate and redox span of the bc1 complex. 30 。

[0500] Mitochondrial NADH oxidation state

[0501] Changes in NAD(P)H fluorescence and mitochondrial membrane potential were measured simultaneously using 365 nm excitation. Then, the resulting emission spectra were measured using a multi-wavelength spectrometer. 29 Assuming that the cytoplasmic NADH pool and NADPH pool did not change during these interventions and short time periods, the baseline oxidation state of the mitochondrial NADH pool was back-calculated using hypoxia to fully reduce and 4 μM FCCP to fully oxidize the mitochondrial NADH pool, respectively.

[0502] H&E staining

[0503] According to 31 the description, hematoxylin and eosin (H&E) staining and slide scanning were performed.

[0504] Single-cell RNA sequencing methodology

[0505] 1-Preprocessing, batch effect correction, and clustering of single-cell RNA transcriptomic data

[0506] CellRanger (v.7.0.1) was used to map the reads in the FASTQ files to the mouse reference genome (GRCm39). 32 。The Seurat (v.4.2.0) package in R (v.4.2.1) was used to process the preprocessed gene count matrix generated by cellRanger. 33。As an initial quality control step, cells with fewer than 200 genes and genes expressed in fewer than 3 cells were filtered out. Then, cells with mitochondrial count > 5%, UMI count > 37000, and gene count < 500 were filtered out. The filtered gene count matrix (31647 genes and 127356 cells) was normalized using a normalization function (using the log(normalized) method), and the scale factor was set to 10000. The findvariablefeatures function was used to identify 2000 highly variable genes for principal component analysis. The top 50 principal components were selected for downstream analysis. The RunHarmony function in the harmony package (v.0.1.0) with default parameters was used to correct batch effects 34 。The RunUMAP function with the "harmony" subtraction was used to generate UMAPs for clustering analysis. The findclusters function was used to set the resolution parameter to 1.6.

[0507] 2-Epithelial scoring

[0508] The average gene expression of cytokeratin, Epcan, and Sfn was used to calculate the epithelial score.

[0509] 3-Single-cell copy number estimation

[0510] CopyKat (v.1.1.0) was used to estimate the copy number status of each cell 14 。The parameters were set as ngene.chr = 5, win.size = 25, KS.cut = 0.1, genome = "mm10", and cells annotated as T cells or NK cells in the UMAP were used as diploid reference cells.

[0511] 4-Identification of differentially expressed marker genes

[0512] The findallmarkers function in the Seurat R package was used to identify the genes with the highest differential expression in each cluster. The parameters for differential expression were set as at least a 1.25-fold change in fold change (logfc.threshold = 1.25), adjusted p-value < 0.05, where gene expression was detected in at least 10% of the cells in each cluster (min.pct = 0.1). The top 20 highly differentially expressed genes in each cluster ranked by average fold change were defined as marker genes.

[0513] 5-Pathway enrichment analysis of single-cell transcriptomic data

[0514] For cells in each identified cluster in UMAP, the Wilcoxon rank-sum test was performed using the wilcoxauc function in the presto R package (version 1.0.0) to obtain the fold change and p-value of all genes between cells in the high heterogeneity group in the mutant group and the control group 35 According to the formula notation (log2FC)*(-log 10 (p-value)), genes were ranked in descending order. The ranked gene list and the mouse hallmark pathways (mh.all.v2002.1.Mm.symbols.gmt) in the MSigDB database were used as the input for gene set enrichment analysis, using the fgsea function in the fgsea R package (v.1.22.0) with parameters eps = 0, minSize = 5, maxSize = 500 36 。

[0515] References

[0516] 1. Gorelick, A.N. et al. Respiratory complex and tissue lineage drive recurrent mutations in tumour mtDNA. Nat. Metab. (2021) doi:10.1038 / s42255-021-00378-8.

[0517] 2. Hopkins, J.F. et al. Mitochondrial mutations drive prostate cancer aggression. Nat. Commun. (2017) doi:10.1038 / s41467-017-00377-y.

[0518] 3. B. et al. OXPHOS remodeling in high-grade prostate cancer involves mtDNA mutations and increased succinate oxidation. Nat. Commun. 11, (2020).

[0519] 4. Mok, B.Y. et al. A bacterial cytidine deaminase toxin enables CRISPR-free mitochondrial base editing. Nature 583, 631–637 (2020).

[0520] 5. Kim, M., Mahmood, M., Reznik, E. & Gammage, P. A. Mitochondrial DNA is a major source of driver mutations in cancer. Trends in Cancer 8, 1046–1059 (2022).

[0521] 6. Gorman, G. S. et al. Mitochondrial diseases. Nat. Rev. Dis. Prim. (2016) doi:10.1038 / nrdp.2016.80.

[0522] 7. Yuan, Y. et al. Comprehensive molecular characterization of mitochondrial genomes in human cancers. Nat. Genet. 52, 342–352 (2020).

[0523] 8. Guerrero-Castillo, S. et al. The Assembly Pathway of Mitochondrial Respiratory Chain Complex I. Cell Metab. (2017) doi:10.1016 / j.cmet.2016.09.002.

[0524] 9. Graf, L. H., Kaplan, P. & Silagi, S. Efficient DNA-mediated transfer of selectable genes and unselected sequences into differentiated and undifferentiated mouse melanoma clones. Somat. Cell Mol. Genet. (1984) doi:10.1007 / BF01534903.

[0525] 10. Titov, D. V. et al. Complementation of mitochondrial electron transport chain by manipulation of the NAD+ / NADH ratio. Science(80-.).(2016) doi:10.1126 / science.aad4017.

[0526] 11. Gaude, E. et al. NADH Shuttling Couples Cytosolic Reductive Carboxylation of Glutamine with Glycolysis in Cells with Mitochondrial Dysfunction. Mol. Cell 69, 581 - 593.e7(2018).

[0527] 12. Wang, Y. et al. Saturation of the mitochondrial NADH shuttles drives aerobic glycolysis in proliferating cells. Mol. Cell 82, 3270 - 3283.e9(2022).

[0528] 13. Dong, J. et al. Single - cell RNA - seq analysis unveils a prevalent epithelial / mesenchymal hybrid state during mouse organogenesis. Genome Biol.(2018) doi:10.1186 / s13059 - 018 - 1416 - 2.

[0529] 14. Gao, R. et al. Delineating copy number and clonal substructure in human tumors from single - cell transcriptomes. Nat. Biotechnol.(2021) doi:10.1038 / s41587 - 020 - 00795 - 2.

[0530] 15. Coffelt, S. B., Wellenstein, M. D. & De Visser, K. E. Neutrophils in cancer: Neutral no more. Nat. Rev. Cancer 16, 431–446 (2016).

[0531] 16. Bald, T. et al. Ultraviolet-radiation-induced inflammation promotes angiotropism and metastasis in melanoma. Nature 507, 109–113 (2014).

[0532] 17. Riaz, N. et al. Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab. Cell (2017) doi:10.1016 / j.cell.2017.09.028.

[0533] 18. DeBerardinis, R. J. & Chandel, N. S. We need to talk about the Warburg effect. Nat. Metab. 2, 127–129 (2020).

[0534] 19. Gammage, P. A., Van Haute, L. & Minczuk, M. Engineered mtZFNs for manipulation of human mitochondrial DNA heteroplasmy. in Methods in Molecular Biology vol. 1351 145–162 (Humana Press Inc., 2016).

[0535] 20. Fernandez-Vizarra, E. & Zeviani, M. Blue-Native Electrophoresis to Study the OXPHOS Complexes. in Methods in Molecular Biology (2021). doi:10.1007 / 978-1-0716-0834-0_20.

[0536] 21. Villar, V. H. et al. Hepatic glutamine synthetase controls N5-methylglutamine in homeostasis and cancer. Nat. Chem. Biol. (2022) doi:10.1038 / s41589-022-01154-9.

[0537] 22. Nacke, M. et al. An ARF GTPase module promoting invasion and metastasis through regulating phosphoinositide metabolism. Nat. Commun. (2021) doi:10.1038 / s41467-021-21847-4.

[0538] 23. Cao, X. et al. The mammalian cytosolic thioredoxin reductase pathway acts via a membrane protein to reduce ER-localised proteins. J. Cell Sci. 133, (2020).

[0539] 24. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, (2008).

[0540] 25. Cox, J. et al. Andromeda: A peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

[0541] 26. Apweiler, R. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res. 38, (2010).

[0542] 27. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nature Methods (2016) doi:10.1038 / nmeth.3901.

[0543] 28. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

[0544] 29. Rocha, M. & Springett, R. Measuring the functionality of the mitochondrial pumping complexes with multi-wavelength spectroscopy. Biochim. Biophys. Acta - Bioenerg. 1860, 89–101 (2019).

[0545] 30. Kim, N., Ripple, M. O. & Springett, R. Measurement of the mitochondrial membrane potential and pH gradient from the redox poise of the hemes of the bc1 complex. Biophys. J. 102, 1194–1203 (2012).

[0546] 31. Papalazarou, V., Drew, J., Juin, A., Spence, H. J. & Nixon, C. Collagen-VI expression is negatively mechanosensitive in pancreatic cancer cells and supports the metastatic niche. J. Cell Sci. 135, (2022).

[0547] 32. Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 2017 81 8, 1–12 (2017).

[0548] 33. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e29 (2021).

[0549] 34. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 2019 1612 16, 1289–1296 (2019).

[0550] 35. Korsunsky, I., Nathan, A., Millard, N. & Raychaudhuri, S. Presto scales Wilcoxon and auROC analyses to millions of observations. bioRxiv 653253 (2019).

[0551] 36. Korotkevich, G. & Sukhov, V. Fast gene set enrichment analysis. bioRxiv 1–29 (2016).

[0552] Example 2

[0553] Effect of tumor-infiltrating neutrophils on the response to immune checkpoint inhibitors

[0554] Tumor-associated neutrophils can play a role in suppressing the response of melanoma patients to ICB. In fact, single-cell RNA sequencing of B78-D14 mutant tumors revealed a significant decrease in the proportion of tumor neutrophils (data not shown). This was further confirmed using flow cytometry ( Figure 42 A-C), where the inventors observed a decrease in neutrophil infiltration in Hcmel12m.12,43683% and cytoLbNOX tumors relative to wild type ( Figure 42 D). This was reflected in the tumor-draining lymph nodes ( Figure 42E). Interestingly, an increase in CD4+ T cells was observed in tumors and associated lymph nodes ( Figure 42 D, E), while an increase in CD8+ T cells, NK cells, and macrophages was only observed for cytoLbNOX tumors ( Figure 3 .34D). In contrast, the proportion of NK cells and neutrophils in the spleens of mice transplanted with allogeneic mtDNA mutants and cytoLbNOX tumors was increased compared to wild-type ( Figure 42 F).

[0555] To determine whether neutrophil depletion was necessary for the observed ICB sensitivity, the inventors chose to use G-CSF and anti-Ly6G treatment to manipulate the proportion of tumor-associated neutrophils. Hcmel12 wild-type, m.12,436 83％ and cytoLbNOX cells were allografted into C57BL / 6 mice and treated with G-CSF or anti-Ly6G with or without anti-PD1 ( Figure 43 A).

[0556] As expected, the inventors observed an increase in tumor-associated neutrophils in genotypes treated with G-CSF, while anti-Ly6G significantly reduced the proportion of neutrophils ( Figure 43 B, C). When taken at the same endpoint, this did not affect the tumor weight of untreated tumors ( Figure 43 D). Notably, G-CSF treatment abrogated the sensitivity of m.12,436 83％ and cytoLbNOX tumors to anti-PD1 ( Figure 43 E). In contrast, depletion of tumor-associated neutrophils sensitized wild-type tumors to ICB treatment ( Figure 43 F). Collectively, the inventors demonstrated that tumor-associated neutrophils coordinate and negatively regulate the response to anti-PD1 treatment.

[0557] These results could justify the use of reagents that alter the lactate-to-glucose ratio (such as cytoLbNOX or another NADH oxidase) in combination with a reagent that depletes tumor-resident neutrophils (such as an anti-Ly6G antibody).

[0558] Materials and Methods

[0559] Use of Animal Models

[0560] Animal experiments were conducted in accordance with the UK Animals (Scientific Procedures) Act 1986 (P72BA642F) and adhered to the ARRIVE guidelines approved by the local Animal Welfare and Ethical Review Board of the University of Glasgow. Mice were housed in conventional cages in the animal room at a controlled temperature (19 - 23 °C) and humidity (55 ± 10%), with a 12-hour light-dark cycle. Only male C57BL / 6 mice at approximately 8 weeks of age were used in the experiments, and 2.5 x 10 5 B78 cells or 1 x 10 4 HcMel12 cells, both prepared for subcutaneous injection and made in PBS, were subcutaneously injected. Mice were sacrificed at the endpoint of 15 mm tumor measurement.

[0561] For immunotherapy experiments, mice received a dosing regimen of 200 μg of anti-PD1, administered intraperitoneally twice a week. The first dose was given 7 days after injection, and all mice were sacrificed 21 days or 13 days after injection of B78 or HcMel12 cells, respectively.

[0562] Mice were given 5 μg of murine recombinant G-CSF (stem cell) or 100 μg of anti-mouse Ly6G clone 1A8 (2B Scientific) intraperitoneally every 2 days after transplantation for neutrophil depletion experiments.

[0563] Example 3

[0564] Response of melanoma surrogate models to immune checkpoint inhibitors

[0565] Notably, cytoLbNOX tumors were sensitive to anti-PD1 treatment, while catalytic mutant tumors did not show that only redox dysfunction plays a role in immunotherapy. The cytoLbNOX tumor weight was observed to be less than 50% of that of mtDNA mutant tumors ( Figure 44 A - C), which was reflected in anti-PDL1 treatment ( Figure 44 A - C). Interestingly, anti-CTLA4 therapy regulated tumor growth through spatially and temporally separated mechanisms, resulting in a less reduced difference in tumor weight between mtDNA mutants and cytoLbNOX tumors ( Figure 44 A - C). Further treatment of Hcmel12 wild-type, m.12436 80％ and cytoLbNOX tumors with anti-PD1 to an extended human endpoint showed limited survival extension in mice bearing mtDNA mutant tumors, while most cytoLbNOX tumors showed complete regression ( Figure 44 D). Tumors reaching the 15 mm endpoint did not differ in terms of tumor weight or tumor volume ( Figure 44 E - G).

[0566] Although both immunogenic 4434 wild-type and m.12,436 tumors responded to anti-PD1 treatment, the mtDNA mutant tumors completely regressed by day 20, while the wild-type tumor weights were still measurable, which is consistent with our observations of differential responses in the non-immunogenic B78-D14 and Hcmel12 models( Figure 45 ). Collectively, these data suggest that regardless of the melanoma cell lineage, complex I truncating mutations trigger differential heterogeneous dose-dependent responses to immunotherapy, potentially mediated through alterations in redox balance, as observed by using Hcmel12 cells expressing cytoLbNOX.

[0567] These results suggest that treatment with agents that alter the lactate-to-glucose ratio in cancer or precancer can increase the sensitivity (at least to some extent) of cancer or precancer that is already sensitive (at least to some extent) to immune checkpoint inhibitors.

[0568] Example 4

[0569] Sensitivity of contralateral WT tumors to checkpoint inhibitors

[0570] The inventors tested whether the remodeling of the immune context extended beyond the tumor microenvironment in their melanoma mouse models. Hcmel12 cells of the same or different genotypes were subcutaneously injected into the opposite sides of mice and treated with anti-PD1 according to the same protocol as above( Figure 46 A). Mt.12,436 83％ and cytoLbNOX tumors responded to immunotherapy when injected on each side of the same mouse, while wild-type tumors did not( Figure 46 B-D). However, it is noteworthy that wild-type tumors were sensitive to anti-PD1 treatment when injected contralaterally to m.12,436 83％ or cytoLbNOX tumors in the same mouse( Figure 46 B-D). Comparison of wild-type tumor weights when injected contralaterally to m.12,436 83％ or cytoLbNOX tumors revealed that, relative to wild-type, when implanted contralateral to wild-type tumors, tumor weights were reduced by approximately 50%( Figure 46 E). Interestingly, there was no difference in the reduction of wild-type tumor weights when injected contralaterally to m.12,436 83％ or cytoLbNOX, indicating that these two genotypes have similar effects on the systemic immune system( Figure 46 E).

[0571] Analysis of the immune cell populations in the derived circulating blood before the endpoint did not reveal any significant changes in cell proportions( Figure 46F). However, further flow cytometry analysis of the tumor immune population showed that when injected contralaterally to these genotypes, m.12,436 83％ and cytoLbNOX tumors, as well as wild-type tumors, had a significant increase in CD4+ T cells ( Figure 3 .47A). In contrast, NK T cells and CD8+ T cells did not show significant changes in tumor-associated populations in the samples ( Figure 46 B, C). Due to the size of the cytoLbNOX tumors when injected on both the left and right sides, they could not be used to evaluate lymphocyte populations.

[0572] Myeloid cell characterization showed that relative to non-responsive wild-type, reactive tumors had reduced TAM and neutrophils, and an inverse increase in the monocyte population, although the changes were not as pronounced as those observed in CD4+ T cells ( Figure 46 D-F).

[0573] Collectively, these data indicate that distal effects occurred following anti-PD1 treatment, suggesting a systemic change in the immune environment, as shown by the parallel changes in the proportions of immune cells in wild-type tumors injected contralaterally to m.12,436 83％ and cytoLbNOX, but not in wild-type tumors themselves (non-injected).

[0574] Example 5 - mtDNA Mutations in Complex 4

[0575] Mt-Co1 is a mitochondrially encoded subunit of Complex IV. The inventors prepared DddA-derived cytosine base editors (DdCBEs) to introduce a G>A point mutation at position m.6214 in this protein in the mouse mitochondrial genome.

[0576] When implanted into Bl6 mice, these tumors grew at a rate comparable to wild-type and reached comparable endpoint weights within a similar time ( Figure 48 A-B).

[0577] When challenged with anti-PD1, Mt-Co1 mutant tumors were significantly smaller in size at the endpoint compared to wild-type tumors. This heterogeneity was significantly lower than that required for a strong immune response by Mt-Nd5 truncation mutations, which may be due to the more profound impact of Complex IV deletion on the respiratory chain ( Figure 49 A-C).

[0578] This result indicates that mutations in complexes other than Complex I lead to tumor sensitivity to checkpoint inhibitors, further supporting the important role of intracellular metabolic changes in enhancing tumor sensitivity to checkpoint inhibitors.

[0579] Example 6

[0580] Enhance sensitivity to anti-CTLA4 therapy and anti-PD-L1 therapy

[0581] Such as Figure 44 As shown in B, after treatment with different types of immune checkpoint inhibitors (such as PD1 inhibitors, PD-L1 inhibitors, and CTLA4 inhibitors), the tumors of 12,436 83％ and the tumors expressing cytoLbNOX were significantly smaller.

Claims

1. A reagent for altering the redox state in cancer or pre - cancer, for use in sensitizing a subject having cancer or pre - cancer to an immune checkpoint inhibitor.

2. An immune checkpoint inhibitor for use in treating a subject having cancer or pre - cancer, wherein the subject is exposed to a reagent that alters the redox state in the cancer or pre - cancer.

3. A method of sensitizing a subject having cancer or pre - cancer to an immune checkpoint inhibitor, comprising exposing the subject to a reagent that alters the redox state in the cancer or pre - cancer.

4. A method of treating cancer or pre - cancer in a subject, comprising administering an immune checkpoint inhibitor to the subject, wherein the subject is exposed to a reagent that alters the redox state in the cancer or pre - cancer.

5. A method of treating cancer or pre - cancer in a subject, comprising: (i) exposing the subject to an agent that alters the redox state in the cancer or pre-cancer; and (ii) administering an immune checkpoint inhibitor to the subject.

6. The reagent for use, the inhibitor for use, or the method according to any one of claims 3 to 5, wherein the reagent that alters the redox state alters the lactate - to - glucose ratio in the cancer or pre - cancer.

7. The reagent for use, the inhibitor for use, or the method according to claim 6, wherein the reagent increases the lactate - to - glucose ratio, optionally wherein the lactate - to - glucose ratio is increased to higher than 3:

1.

8. The reagent for use, the inhibitor for use, or the method according to any one of the preceding claims, wherein a sample of the cancer or pre - cancer has a harmful mitochondrial DNA (mtDNA) mutation load of less than 50%.

9. The reagent for use, the inhibitor for use, or the method according to claim 8, wherein the harmful mitochondrial DNA (mtDNA) mutation load is less than 40%, less than 30%, or less than 20%.

10. The reagent for use, the inhibitor for use, or the method according to any one of the preceding claims, wherein the reagent is selected from the group consisting of: a) Compounds that drive glycolytic flux through MDH1, optionally wherein the compounds are selected from the group consisting of isocitrate, aconitate, citrate, oxaloacetate, NADH, and NAD+ precursors; b) Compounds that regulate NAD(H) redox handling through the malate-aspartate shuttle, optionally wherein the compounds are selected from the group consisting of: isocitrate, aconitate, citrate, oxaloacetate, malate, fumarate, argininosuccinate; c) Lactate, pyruvate; d) Glucose-metabolizing enzymes and / or lactate-metabolizing enzymes; e) Inhibitors of enzymes that reduce glycolytic flux in cancer cells or pre-cancerous cells, optionally wherein the enzyme is pyruvate dehydrogenase or pyruvate carboxylase, and optionally wherein the inhibitor is a small molecule; f) Activators of enzymes that increase glycolytic flux in cancer cells or pre-cancerous cells; g) Activators of enzymes that increase lactate efflux in cancer cells or pre-cancerous cells, optionally wherein the enzyme is MDH1 or GAPDH, and optionally wherein the activator is a small molecule; h) Inhibitors of enzymes that reduce lactate efflux in cancer cells or pre-cancerous cells; i) Small molecule inhibitors of enzymes in the malate-aspartate shuttle, optionally wherein the enzymes are selected from the group consisting of: GOT1, GOT2, MDH1, MDH2, glutamate-aspartate carrier, and α-ketoglutarate-malate carrier; j) Small molecule activators of enzymes in the malate-aspartate shuttle, optionally wherein the enzymes are selected from the group consisting of: GOT1, GOT2, MDH1, MDH2, glutamate-aspartate carrier, and α-ketoglutarate-malate carrier; k) Inhibitors of Complex I, Complex II, Complex III, or Complex IV; l) Compounds that increase the harmful mtDNA mutation load in the cancer or pre-cancer, optionally wherein the compound induces harmful mtDNA mutations; and / or m) Compounds that reduce neutrophils in the subject and / or reduce neutrophils in the cancer or pre-cancer, optionally wherein the neutrophils are tumor-infiltrating neutrophils (TAN).

11. The reagent for use, inhibitor for use, or method according to any one of the preceding claims, wherein the reagent is the enzyme NADH oxidase or a nucleic acid encoding the enzyme, optionally wherein the enzyme is from Lactobacillus brevis, and further optionally wherein the enzyme is selected from the group consisting of cytoLbNOX and mitoLbNOX.

12. A reagent for use, an inhibitor for use, or a method according to any one of the preceding claims, wherein the cancer or pre-cancer is selected from the group consisting of childhood cancers, hematological cancers, and myeloid cancers.

13. A reagent for use, an inhibitor for use, or a method according to claim 12, wherein the childhood cancer is selected from the group consisting of leukemia, brain cancer, spinal cord cancer, neuroblastoma, nephroblastoma, lymphoma (such as Hodgkin lymphoma and non-Hodgkin lymphoma), rhabdomyosarcoma, retinoblastoma, and bone cancer (such as osteosarcoma and Ewing's sarcoma).

14. A reagent for use, an inhibitor for use, or a method according to any one of the preceding claims, wherein the immune checkpoint inhibitor is selected from the group consisting of PD-1 inhibitors, PD-L1 inhibitors, PD-L2 inhibitors, CTLA4 inhibitors, TIGIT inhibitors, LAG-3 inhibitors, TIM-3 inhibitors, BTLA inhibitors, and KIR inhibitors, optionally wherein the immune checkpoint inhibitor is selected from the group consisting of PD-1 inhibitors, PD-L1 inhibitors, and CTLA4 inhibitors, and further optionally wherein the PD-1 inhibitor is nivolumab.

15. A reagent for use, an inhibitor for use, or a method according to claim 10, wherein the compound that increases the harmful mtDNA mutation load in the cancer or pre-cancer is selected from the group consisting of mitochondrial base editing enzymes (such as DdCBE) and mitochondrial heteroplasmy manipulation enzymes (such as mtZFN or mitoTALEN).

16. A reagent for use, an inhibitor for use, or a method according to any one of claims 8 to 15, wherein the harmful mtDNA mutations are selected from the group consisting of: (i) tRNA mutations having a MitoTIP RAW score of at least 12.6 or at least 16.25; (ii) rRNA mutations; (iii) truncating mutations in mtDNA genes; (iv) missense mutations in mtDNA genes, wherein the missense mutation has an Apogee score greater than 0.5, optionally wherein the missense mutation is selected from frameshift mutations, insertion mutations, or deletion mutations; and / or (v) mutations in the mtDNA D-loop region, selected from the group consisting of the H-strand promoter (545 - 567), MT-HV2 (hypervariable segment 2) m.57 - 372, and MT-HV1 (hypervariable segment 1) - m.16024 - 16390.

17. A reagent for use, an inhibitor for use, or a method according to any one of claims 7 to 16, wherein the harmful mtDNA mutation is in a gene selected from the group consisting of: MT-ND5, MT-ND1, MT-ND2, MT-ND3, MT-ND4, MT-ND4L, MT-ND6, MT-CO1, MT-CO2, MT-CO3, MT-CYB, MT-ATP6, MT-ATP8, MT-TL1, MT-TA, MT-TC, MT-TD, MT-TE, MT-TF, MT-TG, MT-TH, MT-TI, MT-TK, MT-TL2, MT-TM, MT-TN, MT-TP, MT-TQ, MT-TR, MT-TS1, MT-TS2, MT-TT, MT-TV, MT-TW, MT-TY, MT-RNR1 and MT-RNR2.

18. A reagent for use, an inhibitor for use, or a method according to any one of claims 8 to 17, wherein the harmful mtDNA mutation in MT-ND5 is a truncation mutation in a region selected from: m.12418-12425: A insertion / deletion or m.12385-12390: C insertion / deletion.

19. A reagent for use, an inhibitor for use, or a method according to any one of claims 7 to 18, wherein the harmful mtDNA mutation is a truncation mutation, a missense mutation, an insertion mutation or a frameshift mutation.

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