4.7 Article

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data

期刊

GENOME MEDICINE
卷 10, 期 -, 页码 -

出版社

BIOMED CENTRAL LTD
DOI: 10.1186/s13073-018-0546-1

关键词

Precision oncology; Personalized medicine; Translational bioinformatics; Cancer genomics; In silico prescription; Targeted therapy; Druggable genome

资金

  1. Marie-Curie Career Integration Grant (CIG) [CIG334361]
  2. Severo Ochoa FPI grant doctoral fellowship by the Spanish Ministry of Economy and Competitiveness
  3. Biomedical Research Centre (Centro Singular de Galicia) - Conselleria de Cultura, Educacion e Ordenacion Universitaria
  4. Xunta de Galicia
  5. FEDER (European Union)
  6. CITI (Centro de Investigacion Transferencia e Innovacion) from the University of Vigo
  7. Spanish National Institute of Bioinformatics, a platform of the Instituto de Salud Carlos III [INB-ISCIII, PRB2]

向作者/读者索取更多资源

Background: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. Results: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. Conclusions: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据