Jason M. Sheltzer

This study identifies genetic vulnerabilities from chromosome loss events in cancer by analyzing CRISPR screening data and copy number profiles, revealing paralogous gene dependencies as therapeutic targets.

This study corrects a complex Chromosome 8 rearrangement in vitro, identifies differentially expressed genes, and shows partial rescue of neural differentiation defects.

This study uses explainable machine learning to identify factors that buffer protein levels in aneuploid cancer cells, finding key predictors and implications for therapy.

This study reveals that PAC-1, a clinical-stage oncology compound, targets drug-resistant cancers by disrupting iron homeostasis and exploiting MDR1 expression to induce iron depletion.

This study shows CDK11 is critical for cancer cell survival and identifies 1p36 deletions as a biomarker for CDK11 inhibitor sensitivity, but on-target toxicity limits therapeutic efficacy.

The paper estimates the arrival time of clonal copy number gains in tumors and shows they promote mutational diversification and malignant growth.

Across hundreds of human cancer cell lines, most proteins exhibit dosage compensation against chromosome copy number changes, buffering complex subunits, cell cycle genes, and even oncogenes and tumor suppressors.

This study shows camostat mesylate inhibits SARS-CoV-2 by blocking TMPRSS2 and its metabolite GBPA also has antiviral activity, suggesting no resistance through TMPRSS2-related proteases.

The paper introduces a non-parametric Bayesian method for density estimation in sequence space and applies it to study pre-mRNA splicing and karyotypic diversity in human cancer.