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Data from Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer

Authors :
Kenneth L. Scott
Raju Kucherlapati
Peter J. Park
Gordon B. Mills
Roel G. Verhaak
Chad J. Creighton
Young Won Kim
Nicholas J. Neill
Lixing Yang
Angeliki Pantazi
Oksana Zagorodna
Yiu Huen Tsang
Kathleen Kong
Caitlin L. Grzeskowiak
Turgut Dogruluk
Nicole Villafane
Hengyu Lu
Publication Year :
2023
Publisher :
American Association for Cancer Research (AACR), 2023.

Abstract

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2, and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. Cancer Res; 77(13); 3502–12. ©2017 AACR.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........26651b4976f9547111e4b95287deb941
Full Text :
https://doi.org/10.1158/0008-5472.c.6508520.v1