Scott Kopetz

PRIORITI uses language models to predict target-indication success in drug discovery, achieving high accuracy and robustness across different benchmarks.

The paper identifies human gene modules enriched for genetic interactions using a combinatorial knockout platform and validates their conservation and rewiring across cancer cell lines.

This study shows that human tumor slices better predict patient responses to an oncolytic virus than mouse models, highlighting indication-specific efficacy.

This study identifies KDM5D on the Y chromosome as a suppressor of CD8+ T cell antitumor immunity in males, linking it to TCR and cholesterol-exhaustion programs.

This study shows BET + MAPK inhibitors improve efficacy against BRAFV600E CRC by inducing epigenetic reprogramming and cellular plasticity through enhancer dynamics disruption.

TmSNet predicts tumor cell-specific total mRNA expression from multi-omic data, achieving high accuracy across cancer types and external cohorts.

The paper develops DeMixNB, a deconvolution model for sparse-count RNA sequencing data, showing its utility in analyzing tumor cell plasticity in breast and lung cancer.

This study shows that specific KRAS mutations, like A59E, cooperate with other genetic alterations in CRC and affect response to EGFR inhibitors.

This study identifies the YAP1-SDC1 axis as a driver of resistance to mKRAS inhibitors in gastrointestinal cancers and suggests targeting this axis to overcome resistance.

This study investigates the effect of IL-1R1 blockade on CD40 agonist therapy in PDAC, finding it does not improve efficacy and worsens liver toxicity.

The paper identifies adaptive plasticity tumor (APT) cells that reduce response to MAPK inhibitors in colorectal cancer by increasing stemness and ASCL2 expression, and shows that targeting APT cells improves therapy efficacy.

This study shows that oncogenic KRAS mutations in colorectal cancer cells lead to a unique mechanotransduction response to peristalsis, increasing cancer stem cell enrichment and tumorigenicity.

The paper develops CliPP to estimate subclonal mutation load (sML) and shows it predicts survival and immunotherapy response in cancers with low to moderate TMB.

This study identifies paclitaxel as a synergistic partner for trametinib in KRAS-mutated colorectal cancer, showing enhanced anti-tumor effects in vitro and in vivo.

DeMixSC improves deconvolution accuracy by using single-cell RNA-seq and a benchmark dataset to account for technological discrepancies in complex tissue samples.

CopyKit is a computational tool that resolves clonal substructure and reconstructs genetic lineages in tumors using single cell copy number data.

The paper quantifies tumor-specific total mRNA expression from bulk data and shows its association with clinical outcomes across 15 cancer types.

The paper examines the expression of ACE2 and TMPRSS2 in single-cell RNA sequencing datasets from different parts of the gastrointestinal tract to assess SARS-CoV-2 entry potential in enterocytes.

The paper introduces a method to construct gene-specific methylation profiles for integrative methylation-expression analysis in cancer, showing improved explanation of expression variability and identification of methylation differences across cancer subtypes.

The paper presents an R pipeline using DeMixT for tumor-stroma-immune transcriptome deconvolution, showing immune proportion variations in COAD and PRAD datasets.