Biology subjects

Reznik, E.

Publications and source records attributed to Reznik, E..

14 recordsLinked to original sources

bioRxiv2026

Random mtDNA mutagenesis maps genotype-phenotype associations across metabolic contexts and lineages

Mitochondrial DNA (mtDNA) mutations cause inherited disease, accumulate with age, and recur in tumors, yet their effects remain unresolved because existing models interrogate one engineered allele at a time. We developed mtDIVE, a random C[->]T mutagenesis platform for pooled mitochondrial forward genetics in human epithelial cells and zebrafish embryos. mtDIVE generates genotypes ranging from single substitutions to >100 mutations per molecule, impairs respiration, and causes lineage-specific developmental delay. Coupling single-cell transcriptomics with mtDNA genotyping revealed that selection on mutant genomes and their transcriptional consequences depend on metabolic state and developmental lineage. Obligate OXPHOS eliminates highly mutated cells by apoptosis, whereas glycolytic conditions promote their competitive displacement. Individual loci exert modest but non-redundant effects that predict cell state beyond aggregate mutation burden, and cancer-recurrent variants are enriched among mutations linked to reduced mitochondrial transcription. Thus, mtDIVE links mtDNA genotypes to cellular phenotypes, separating the consequences of mutation identity from mutational load.

genomics↗

bioRxiv2026

BRCA2 loss drives a PKM1-dominant glycolytic state that is selectively lethal to pyruvate kinase activation

Homologous recombination deficiency (HRD), most commonly arising from BRCA1/2 loss, is accompanied by metabolic remodeling whose contours and therapeutic implications remain poorly defined. Through pan-cancer analysis of 10,619 tumors from The Cancer Genome Atlas (TCGA) and isogenic BRCA1/2-deficient models, we show that HRD tumors display broad metabolic rewiring, with consistent alterations in glucose metabolism. Unexpectedly, BRCA1/2 loss is associated with selective upregulation of the constitutively active glycolytic enzyme Pyruvate Kinase M1 (PKM1) isoform, contrasting with the PKM2-dominant state of most cancers, and produces an elevated pyruvate kinase activity state. Overactivating PKM, with small molecules activators, including the FDA-approved drug mitapivat, triggers superoxide accumulation, disrupts PINK1-dependent mitochondrial quality control, induces DNA damage, and selectively kills BRCA2-deficient tumors in vivo, while sparing BRCA2-proficient counterparts. These findings recast HRD as a metabolic state and identify PKM activation as a candidate therapeutic strategy for biomarker-selected HR-deficient cancers.

cancer biology↗

bioRxiv2026

Combined Loss of VHL and TSC1 Drives Clear Cell Renal Cell Carcinoma with Metabolic and Redox Reprogramming that Creates an NRF2 Dependency

Cancer genomics studies have implicated combined loss of VHL and TSC1 as sufficient to initiate clear cell renal cell carcinoma (ccRCC) in humans. Here, we engineered a mouse model with kidney-specific deletion of Vhl and Tsc1. VhlF/FTsc1F/FKsp-Cre+ mice developed multifocal renal cell carcinomas starting at 7 weeks of age with 100% penetrance, and the resulting Vhl-/-Tsc1-/- tumors recapitulated the histopathology of human VHL-/-TSC1-/- ccRCC. Integrated transcriptomic and metabolomic analyses of 4-week-old preneoplastic renal cortices deficient for Vhl and Tsc1 demonstrated heightened HIF and mTORC1 signaling and unexpectedly revealed activation of an antioxidant response regulated by NRF2 (NFE2L2). Biochemical, cell biological, multi-omic, and xenograft studies identified an NRF2 dependency in human VHL-/-TSC1-/- ccRCC cells. Altogether, we report a mouse model that recapitulates human VHL-/-TSC1-/- ccRCC, delineate metabolic and redox reprogramming driven by unrestrained HIF and mTORC1 activation in the renal cortex, and identify NRF2 as a potential therapeutic vulnerability.

cancer biology↗

bioRxiv2023

The SLC1A1/EAAT3 Dicarboxylic Amino Acid Transporter is an Epigenetically Dysregulated Nutrient Carrier that Sustains Oncogenic Metabolic Programs

Inactivation of pVHL tumor suppressor in clear cell Renal Cell Carcinoma (ccRCC) increases the abundance of Histone H3 lysine 27 acetylation (H3K27ac). We hypothesized that H3K27ac, a marker of transcriptional activation, drives the expression of critical oncogenes in ccRCC. Using H3K27ac ChIP-Seq; RNA-Seq; an in vivo positive selection screen; cell-based functional studies; and clinical validations; here, we report the identification of the SLC1A1/EAAT3 aspartate (Asp) and glutamate (Glu) transporter as a ccRCC oncogene. pVHL loss promotes SLC1A1 expression in a HIF-independent manner. Importantly, SLC1A1 inactivation depletes Asp/Glu-derived metabolites, impedes ccRCC growth both in vitro and in vivo, and sensitizes ccRCCs to metabolic therapeutics (e.g., glutaminase blockers). Finally, in human ccRCC biospecimens, higher SLC1A1 expression is associated with metastatic disease and clusters with elevated expression of other solute carriers, but not HIF/Hypoxia pathways. Altogether, our studies identify a HIF-independent metabolic hub in ccRCC and credential SLC1A1 as an actionable ccRCC oncogene. STATEMENT OF SIGNIFICANCETargeting chronic HIF activation underlies many therapeutic strategies in ccRCC; but, unfortunately, is not curative. SLC1A1, instead, represents a HIF-independent ccRCC dependency, which is targetable alone and together with other antimetabolites, such as glutaminase inhibitors. These observations identify an actionable metabolic program that functions independent of HIF in ccRCC.

cancer biology↗

bioRxiv2023

Tumour mitochondrial DNA mutations drive aerobic glycolysis to enhance checkpoint blockade

The mitochondrial genome encodes essential machinery for respiration and metabolic homeostasis but is paradoxically among the most common targets of somatic mutation in the cancer genome, with truncating mutations in respiratory complex I genes being most over-represented1. While mitochondrial DNA (mtDNA) mutations have been associated with both improved and worsened prognoses in several tumour lineages1-,3, whether these mutations are drivers or exert any functional effect on tumour biology remains controversial. Here we discovered that complex I-encoding mtDNA mutations are sufficient to remodel the tumour immune landscape and therapeutic resistance to immune checkpoint blockade. Using mtDNA base editing technology4 we engineered recurrent truncating mutations in the mtDNA-encoded complex I gene, Mt-Nd5, into murine models of melanoma. Mechanistically, these mutations promoted utilisation of pyruvate as a terminal electron acceptor and increased glycolytic flux without major effects on oxygen consumption, driven by an over-reduced NAD pool and NADH shuttling between GAPDH and MDH1, mediating a Warburg-like metabolic shift. In turn, without modifying tumour growth, this altered cancer cell-intrinsic metabolism reshaped the tumour microenvironment in both mice and humans, promoting an anti- tumour immune response characterised by loss of resident neutrophils. This subsequently sensitised tumours bearing high mtDNA mutant heteroplasmy to immune checkpoint blockade, with phenocopy of key metabolic changes being sufficient to mediate this effect. Strikingly, patient lesions bearing >50% mtDNA mutation heteroplasmy also demonstrated a >2.5-fold improved response rate to checkpoint inhibitor blockade. Taken together these data nominate mtDNA mutations as functional regulators of cancer metabolism and tumour biology, with potential for therapeutic exploitation and treatment stratification.

cancer biology↗

bioRxiv2022

A Multimodal Atlas of Tumor Metabolism Reveals the Architecture of Gene-Metabolite Co-regulation

Tumor metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and study gene-metabolite coregulation in cancer, we assembled the Cancer Atlas of Metabolic Profiles (cAMP) of metabolomic and transcriptomic data from 988 tumor/normal specimens spanning 11 cancer types. Meta-analysis of the cAMP revealed two classes of Gene-Metabolite Interactions (GMIs) that transcended cancer types. The first corresponded to a small number of gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative metabolite-pool-size-controlling genes. A second class of GMIs represented a small number of hub metabolites, including quinolinate and NAD+, which correlated to many genes specifically expressed on immune cell populations. These results provide evidence that gene-metabolite coregulation in human tissue arises, in part, from both mechanistic interactions between genes/metabolites, and from metabolic remodeling in specific immune microenvironments.

cancer biology↗

bioRxiv2022

Molecular Characterization of the Tumor Microenvironment in Renal Medullary Carcinoma

Renal medullary carcinoma (RMC) is a highly aggressive disease associated with sickle hemoglobinopathies and universal loss of the tumor suppressor gene SMARCB1. RMC has a relatively low rate of incidence compared with other renal cell carcinomas (RCCs) that has hitherto made molecular profiling difficult. To probe this rare disease in detail we performed an in-depth characterization of the RMC tumor microenvironment using a combination of genomic, metabolic and single-cell RNA-sequencing experiments on tissue from a representative untreated RMC patient, complemented by retrospective analyses of archival tissue and existing published data. Our study of the tumor identifies a heterogenous population of malignant cell states originating from the thick ascending limb of the Loop of Henle within the renal medulla, displaying the hallmarks of increased resistance to cell death by ferroptosis and proteotoxic stress driven by MYC-induced proliferative signals. Specifically, genomic characterization of RMC tumors provides substantiating evidence for the recently proposed dependence of SMARCB1-difficient cancers on an intact CDKN2A-p53 pathway and we suggest increased cystine-mTORC-GPX4 signaling also plays a role within transformed RMC cells. We further propose that RMC has an immune landscape comparable to that of untreated RCCs, including heterogenous expression of the immune ligand CD70 within a sub-population of tumor cells, which could provide an immune-modulatory role that serves as a viable candidate for therapeutic targeting.

cancer biology↗

bioRxiv2021

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

Progression to metastatic disease remains the main cause of cancer death. Yet, the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we present MSK-MET, an integrated pan-cancer cohort of tumor genomic and clinical outcome data from more than 25,000 patients. We analyzed this dataset to identify associations between tumor genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma and HR-positive breast ductal carcinoma, but not in others, such as colorectal adenocarcinoma, pancreatic adenocarcinoma and high-grade serous ovarian cancer. We also identified specific somatic alterations associated with increased metastatic burden and specific routes of metastatic spread. Our data offer a unique resource for the investigation of the biological basis for metastatic spread and highlight the crucial role of chromosomal instability in cancer progression.

cancer biology↗

bioRxiv2021

Genomic and Metabolic Hallmarks of SDH- and FH-Deficient Renal Cell Carcinomas

PurposeSuccinate dehydrogenase-deficient and fumarate hydratase-deficient renal cell carcinomas (SDHRCC and FHRCC) are rare kidney cancers driven by loss of metabolically proximal enzymes. We sought to define and compare the genomic and metabolomic hallmarks of these entities. Experimental DesignWe analyzed SDHRCC and FHRCC tumors with either immunohistochemical evidence of loss of protein expression or genomically-confirmed biallelic inactivation of SDHA/B/C/D/AF2 or FH. Somatic alterations were identified using clinical pipelines, and allele-specific copy number changes were identified using FACETS. Mass-spectrometry-based metabolomic profiling was performed on available SDHRCC and FHRCC tumors. ResultsForty two patients were analyzed (25 FHRCC, 17 SDHRCC). In the germline analysis, 16/17 SDHRCC harbored a germline alteration in SDHB, whereas only 17/22 FHRCC had pathogenic germline FH variants. SDHRCC had a lower mutation burden (p = 0.02) and copy number alteration burden (p = 0.0002) than FHRCC. All SDHRCC presented with deletion of chromosome 1p (overlapping SDHB), whereas FHRCC demonstrated high but not ubiquitous loss of 1q (FH locus). Both SDHRCC and FHRCC demonstrated significant, idiopathic accumulation of the metabolite guanine. FHRCC tumors had elevated levels of urea cycle metabolites (argininosuccinate, citrulline, and fumarate), whereas SDHRCC had elevation of numerous acylcarnitines. These characteristic metabolic changes enabled the identification of a previously unrecognized SDH-deficient RCC. ConclusionDespite sharing similar genetic etiology, SDHRCC and FHRCC represent distinct molecular entities with unique genetic and metabolic abnormalities. Translational RelevanceMutations to the TCA cycle enzymes Succinate Dehydrogenase (SDH) and Fumarate Hydratase (FH) predispose individuals to unique subtypes of renal cell carcinoma (SDHRCC and FHRCC, respectively). Defining the genetic and metabolic hallmarks of these diseases is critical for advancing new diagnostic and therapeutic approaches for these rare but biologically intriguing entities. Despite a superficially similar genetic etiology, SDHRCC and FHRCC demonstrated significantly fewer secondary mutations to other cancer-associated genes and copy number aberrations than FHRCC, and was distinguished by universal loss-of-heterozygosity of chromosome 1p. Metabolomic analysis identified pathways disrupted in both SDHRCC and FHRCC, including the massive accumulation of free guanine, as well as pathways uniquely disrupted in each of the two entities. These metabolomic findings enabled the identification of a previously unidentified case of unclassified RCC with SDH deficiency, suggesting that metabolomic profiling may aid in phenotypic classification of tumors and uncover novel therapeutic targets.

cancer biology↗

bioRxiv2021

Resource-efficient pooled sequencing expands translational impact in solid tumors

Intratumoral genetic heterogeneity (ITH) poses a significant challenge to utilizing sequencing for decision making in the management of cancer. Although sequencing of multiple tumor regions can address the pitfalls of ITH, it does so at a significant increase in cost and resource utilization. We propose a pooled multiregional sequencing strategy, whereby DNA aliquots from multiple tumor regions are mixed prior to sequencing, as a cost-effective strategy to boost translational value by addressing ITH while preserving valuable residual tissue for secondary analysis. Focusing on kidney cancer, we demonstrate that DNA pooling from as few as two regions significantly increases mutation detection while reducing clonality misattribution. This leads to an increased fraction of patients identified with therapeutically actionable mutations, improved patient risk stratification, and improved inference of evolutionary trajectories with an accuracy comparable to bona fide multiregional sequencing. The same approach applied to non-small-cell lung cancer data substantially improves tumor mutational burden (TMB) detection. Our findings demonstrate that pooled DNA sequencing strategies are a cost-effective alternative to address intrinsic genetic heterogeneity in clinical settings.

genomics↗

bioRxiv2020

Respiratory complex and tissue lineage drive mutational patterns in the tumor mitochondrial genome

Mitochondrial DNA (mtDNA) encodes essential protein subunits and translational machinery for four distinct complexes of oxidative phosphorylation (OXPHOS). Using repurposed whole-exome sequencing data, we demonstrate that pathogenic mtDNA mutations arise in tumors at a rate comparable to the most common cancer driver genes. We identify OXPHOS complexes as critical determinants shaping somatic mtDNA mutation patterns across tumor lineages. Loss-of-function mutations accumulate at an elevated rate specifically in Complex I, and often arise at specific homopolymeric hotspots. In contrast, Complex V is depleted of all non-synonymous mutations, suggesting that mutations directly impacting ATP synthesis are under negative selection. Both common truncating mutations and rarer missense alleles are associated with a pan-lineage transcriptional program, even in cancer types where mtDNA mutations are comparatively rare. Pathogenic mutations of mtDNA are associated with substantial increases in overall survival of colorectal adenocarcinoma patients, demonstrating a clear functional relationship between genotype and phenotype. The mitochondrial genome is therefore frequently and functionally disrupted across many cancers, with significant implications for patient stratification, prognosis and therapeutic development.

genomics↗

bioRxiv2019

Novel patterns of complex structural variation revealed across thousands of cancer genome graphs

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g. deletion, translocation) or complex (e.g. chromothripsis, chromoplexy) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,833 tumor whole genome sequences (WGS), we introduce three complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early replicating regions and superenhancers, and are enriched in breast and ovarian cancers. Rigma comprise "chasms" of low-JCN deletions at late-replicating fragile sites in esophageal and other gastrointestinal (GI) adenocarcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold back inversions that are enriched in acral but not cutaneous melanoma and associated with a previously uncharacterized mutational process of non-APOBEC kataegis. Clustering of tumors according to genome graph-derived features identifies subgroups associated with DNA repair defects and poor prognosis.

genomics↗

bioRxiv2018

Isoform switching as a mechanism of acquired resistance to isocitrate dehydrogenase inhibition

Somatic mutations in cytosolic or mitochondrial isoforms of isocitrate dehydrogenase (IDH1 or IDH2, respectively) contribute to oncogenesis via production of the metabolite 2-hydroxyglutarate (2HG). Isoform-selective IDH inhibitors suppress 2HG production and induce clinical responses in patients with IDH1- and IDH2-mutant malignancies. Despite the promising activity of IDH inhibitors, the mechanisms that mediate resistance to IDH inhibition are poorly understood. Here, we describe four clinical cases that identify mutant IDH isoform switching, either from mutant IDH1 to mutant IDH2 or vice versa, as a mechanism of acquired clinical resistance to IDH inhibition in solid and liquid tumors.\n\nSignificanceIDH-mutant cancers can develop resistance to isoform-selective IDH inhibition by \"isoform switching\" from mutant IDH1 to mutant IDH2 or vice versa, thereby restoring 2-hydroxyglutarate (2HG) production by the tumor. These findings underscore a role for continued 2HG production in tumor progression and suggest therapeutic strategies to prevent or overcome resistance.

cancer biology↗

bioRxiv2017

Enabling cross-study analysis of RNA-Sequencing data

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

bioinformatics↗