V

Vahid Bahrambeigi

Yale University

ORCID: 0000-0002-7964-6087

Publishes on Biochemical and Molecular Research, Protein Kinase Regulation and GTPase Signaling, Extracellular vesicles in disease. 40 papers and 887 citations.

40Publications
887Total Citations

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Top publicationsby citations

Mechanisms of Resistance to Oncogenic KRAS Inhibition in Pancreatic Cancer
Julien Dilly, Megan T. Hoffman, Laleh Abbassi et al.|Cancer Discovery|2024
Cited by 226Open Access

KRAS inhibitors demonstrate clinical efficacy in pancreatic ductal adenocarcinoma (PDAC); however, resistance is common. Among patients with KRASG12C-mutant PDAC treated with adagrasib or sotorasib, mutations in PIK3CA and KRAS, and amplifications of KRASG12C, MYC, MET, EGFR, and CDK6 emerged at acquired resistance. In PDAC cell lines and organoid models treated with the KRASG12D inhibitor MRTX1133, epithelial-to-mesenchymal transition and PI3K-AKT-mTOR signaling associate with resistance to therapy. MRTX1133 treatment of the KrasLSL-G12D/+; Trp53LSL-R172H/+; p48-Cre (KPC) mouse model yielded deep tumor regressions, but drug resistance ultimately emerged, accompanied by amplifications of Kras, Yap1, Myc, Cdk6, and Abcb1a/b, and co-evolution of drug-resistant transcriptional programs. Moreover, in KPC and PDX models, mesenchymal and basal-like cell states displayed increased response to KRAS inhibition compared to the classical state. Combination treatment with KRASG12D inhibition and chemotherapy significantly improved tumor control in PDAC mouse models. Collectively, these data elucidate co-evolving resistance mechanisms to KRAS inhibition and support multiple combination therapy strategies. Significance: Acquired resistance may limit the impact of KRAS inhibition in patients with PDAC. Using clinical samples and multiple preclinical models, we define heterogeneous genetic and non-genetic mechanisms of resistance to KRAS inhibition that may guide combination therapy approaches to improve the efficacy and durability of these promising therapies for patients. See related commentary by Marasco and Misale, p. 2018.

Homozygous and hemizygous CNV detection from exome sequencing data in a Mendelian disease cohort
Tomasz Gambin, Zeynep Coban‐Akdemir, Bo Yuan et al.|Nucleic Acids Research|2016
Cited by 126Open Access

We developed an algorithm, HMZDelFinder, that uses whole exome sequencing (WES) data to identify rare and intragenic homozygous and hemizygous (HMZ) deletions that may represent complete loss-of-function of the indicated gene. HMZDelFinder was applied to 4866 samples in the Baylor-Hopkins Center for Mendelian Genomics (BHCMG) cohort and detected 773 HMZ deletion calls (567 homozygous or 206 hemizygous) with an estimated sensitivity of 86.5% (82% for single-exonic and 88% for multi-exonic calls) and precision of 78% (53% single-exonic and 96% for multi-exonic calls). Out of 773 HMZDelFinder-detected deletion calls, 82 were subjected to array comparative genomic hybridization (aCGH) and/or breakpoint PCR and 64 were confirmed. These include 18 single-exon deletions out of which 8 were exclusively detected by HMZDelFinder and not by any of seven other CNV detection tools examined. Further investigation of the 64 validated deletion calls revealed at least 15 pathogenic HMZ deletions. Of those, 7 accounted for 17-50% of pathogenic CNVs in different disease cohorts where 7.1-11% of the molecular diagnosis solved rate was attributed to CNVs. In summary, we present an algorithm to detect rare, intragenic, single-exon deletion CNVs using WES data; this tool can be useful for disease gene discovery efforts and clinical WES analyses.