Ed Reznik

The paper introduces mtDIVE, a random mtDNA mutagenesis platform, to study genotype-phenotype associations in metabolic contexts and lineages, revealing lineage-specific effects and mutation-specific impacts.

The paper shows BRCA2 loss leads to a PKM1-dominant glycolytic state that can be targeted with PKM activators to kill HRD tumors.

This study creates a mouse model of VHL-/-TSC1-/- ccRCC, identifies metabolic and redox reprogramming, and highlights NRF2 as a therapeutic target.

This paper develops a method to engineer specific mtDNA deletions in human cells using end-joining machinery and targeted endonucleases, revealing a 75% heteroplasmy threshold for mitochondrial dysfunction.

This paper introduces a pooled sequencing strategy to address intratumoral genetic heterogeneity in cancer, showing it improves mutation detection and risk stratification while reducing costs.

The paper shows that mtDNA mutations in tumors are shaped by OXPHOS complexes, with specific mutational patterns in Complex I and V, and links these to improved survival in colorectal cancer.

The paper identifies three novel complex structural variation patterns in cancer genomes using genome graph analysis across 2,833 tumor WGS.

This paper presents a pipeline to unify RNA-seq data from different studies by removing batch effects, enabling cross-study analysis.

The paper shows that autocatalytic cycles in E. coli central carbon metabolism require specific enzyme expression and substrate affinity constraints to maintain stable fluxes.

This study examines mtDNA copy number variation across 21 solid tumor types using next-generation sequencing, finding significant depletion in bladder and kidney cancers and correlations with metabolic pathway expression and specific mutations.

The paper identifies rare functional mutations in cancer by mapping them to protein domain hotspots across 22 tumor types, revealing both known and novel mutations with functional implications.

The paper identifies metabolic gene co-expression changes in cancer, revealing dysregulated networks and transcriptional control by HNF4A in clear cell renal cell carcinoma.