Abstract PR09: Harnessing synthetic lethality to predict clinical outcomes of cancer treatment

Conclusions: ISLE is predictive of the patients' response for the majority of current cancer drugs. Of paramount importance, the predictions of ISLE are based on SLi between (potentially) all genes in the cancer genome, thus prioritizing treatments for patients whose tumors do not bear specific actionable mutations in cancer driver genes, offering a novel approach to precision-based cancer therapy. The predictive performance of ISLE is likely to further improve with the expected rapid accumulation of additional cancer omics and clinical phenotypic data.Citation Format: Joo Sang Lee, Avinash Das, Livnat Jerby-Arnon, Dikla Atias, Arnaud Amzallag, Cyril H. Benes, Talia Golan, Eytan Ruppin. Harnessing synthetic lethality to predict clinical outcomes of cancer treatment [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr PR09.

Source: Molecular Cancer Therapeutics - October 2, 2017 Category: Cancer & Oncology Authors: Lee, J. S., Das, A., Jerby-Arnon, L., Atias, D., Amzallag, A., Benes, C. H., Golan, T., Ruppin, E. Tags: New Technology and Bioinformatics: Oral Presentations - Proffered Abstracts Source Type: research