THE REZNIK LAB
COMPUTATIONAL CANCER METABOLISM
MEMORIAL SLOAN KETTERING CANCER CENTER
About Our Lab
Our lab skews toward the overlooked, the misunderstood, and the assumed, and we believe the most provocative and exciting science can often lurk in the darkest corner. We strive to be an inclusive, diverse, and scientifically ethical one, and to harness the different intellectual perspectives of our members to think deeply about how cellular metabolism works inside of a tumor.
Mission
Our goal is to discover new metabolic phenomena in cancer, understand their genetic/physical basis, and translate discoveries to ultimately improve the lives of cancer patients
Vision
We work to achieve our goals through collaboration with experimental biologists and physicians and by thinking about how to distill basic principles from large, complicated, and confounded metabolic measurements.
Science
Our research draws on multimodal genetic, metabolomic, and clinical data to understand how metabolic adaptations confer selective advantages to tumors, serve as biomarkers of response and resistance to therapy, and poise tumors for effective targeted intervention.
Our Favorite Stories
Immunometabolic coevolution defines unique microenvironmental niches in ccRCC
Cell Metabolism, 2023
Using multimodal metabolic profiling, we study intratumoral metabolomic heterogeneity in clear cell renal cell carcinoma (ccRCC) and discover it is driven by the oxidative stress response and coevolves with specific patterns of immune infiltration.
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A multimodal atlas of tumour metabolism reveals the architecture of gene–metabolite covariation
Nature Metabolism, 2023
An investigation of the new CAMP dataset, showing that gene–metabolite covariation in cellularly heterogeneous tissue arises from interactions between genes and metabolites and from remodeling of the bulk metabolome.
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MIRTH: Metabolite Imputation via Rank-Transformation and Harmonization
Genome Biology, 2022
An introduction to a new tool MIRTH, which imputes unmeasured metabolite abundances by jointly modeling metabolite covariation across datasets which have heterogeneous coverage of metabolite features
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Mitonuclear genotype remodels the metabolic and microenvironmental landscape of Hürthle cell carcinoma
Science Advances, 2022
An analysis of genomic, metabolomic, and immunophenotypic data of HCC and other thyroid cancers.
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Respiratory complex and tissue lineage drive recurrent mutations in tumour mtDNA
Nature Metabolism, 2021
An investigation of how the mitochondrial genome is frequently and functionally disrupted across many cancers, with major implications for patient stratification, prognosis and therapeutic development.
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Phase and context shape the function of composite oncogenic mutations
Nature, 2020
A discussion of how composite mutations, which are found in nearly one in four human tumors, are driver alterations that arise from context- and allele-specific selective pressures, and lead to complex functions of biological and therapeutic importance.
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A Landscape of Metabolic Variation across Tumor Types
Cell Systems, 2018
A computational framework for making metabolomics data from different laboratories play nice, and the discovery of common metabolic signatures of aggressive disease across many cancer types.
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Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity
Cell Reports, 2017
Reconstruction and analysis of the small molecule regulatory network (SMRN) of the model organism Escherichia coli. Metabolic control analysis indicates a fundamental trade-off between regulation and enzymatic activity, which is combined with metabolomic measurements and the SMRN to make inferences on the sensitivity of enzymes to their regulators.
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An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma
Cancer Cell, 2016
Metabolic profiling of 138 matched clear cell renal cell carcinoma (ccRCC) pairs found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response, and led to an integrated pathway-level metabolic atlas.
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Mitochondrial DNA copy number variation across human cancers
eLife, 2016
A survey of mtDNA copy number variation across 22 tumor types profiled by The Cancer Genome Atlas project that highlights the extent of mtDNA copy number variation in tumors and points to related therapeutic opportunities. The results highlight the extent of mtDNA copy number variation in tumors and point to related therapeutic opportunities
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Flux imbalance analysis and the sensitivity of cellular growth to changes in metabolite pools
PLOS Computational Biology, 2013
Deviations from flux balance are informative of in vivo metabolite concentrations, suggesting that the sensitivity of metabolic optima to violations of steady state constraints carries biologically significant information on the processes that control intracellular metabolites in the cell.
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