Abstract
Disparities between risk, treatment outcomes and survival rates in cancer patients across the world may be attributed to socioeconomic factors. In addition, the role of ancestry is frequently discussed. In preclinical studies, high-throughput drug screens in cancer cell lines have empowered the identification of clinically relevant molecular biomarkers of drug sensitivity; however, the genetic ancestry from tissue donors has been largely neglected in this setting. In order to address this, here, we show that the inferred ancestry of cancer cell lines is conserved and may impact drug response in patients as a predictive covariate in high-throughput drug screens. We found that there are differential drug responses between European and East Asian ancestries, especially when treated with PI3K/mTOR inhibitors. Our finding emphasizes a new angle in precision medicine, as cancer intervention strategies should consider the germline landscape, thereby reducing the failure rate of clinical trials.
Highlights
Pre-clinical studies in drug development can help to refine the target population and increase the success of clinical trials [1]
In the last two decades, the Cancer Genome Atlas (TCGA) [5] and International Cancer Gene Consortium (ICGC) [6] have pioneered the molecular characterisation of cancer patients. These efforts have revealed core cancer genes and their driver mutations, which are conserved in cancer cell lines (CCL) [7], and focusing on these somatic mutations assisted the identification of potential biomarkers [2]
We only found a handful of enriched cancer genes, namely for Asian CCLs; NF1 mutations are more abundant for GBM and mutations in MLL2 or PIK3R1 are more prevalent for colorectal adenocarcinoma (COREAD)
Summary
Pre-clinical studies in drug development can help to refine the target population and increase the success of clinical trials [1] To this end, cancer cell lines are simplified and scalable models of human tumours, and enable the high-throughput exploration of pharmacogenetic interactions [2,3,4]. Ancestry as discovery an independent factor or covariate in enable drug response model interactions with in patient demographics. CTRP, generating hypotheses forfor ancestral comparisons of drug response in GDSC, validated with CTRP, generating hypotheses patient stratifications in clinical trials based on demographics.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
