OncoMX: A Knowledgebase for Exploring Cancer Biomarkers in the Context of Related Cancer and Healthy Data

Author:

Dingerdissen Hayley M.1,Bastian Frederic23,Vijay-Shanker K.4,Robinson-Rechavi Marc23,Bell Amanda1,Gogate Nikhita1,Gupta Samir4,Holmes Evan1,Kahsay Robel1,Keeney Jonathon1,Kincaid Heather5,King Charles Hadley1,Liu David5,Crichton Daniel J.5,Mazumder Raja1

Affiliation:

1. The George Washington University, Washington DC

2. SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland

3. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland

4. University of Delaware, Newark, DE

5. NASA Jet Propulsion Laboratory, Pasadena, CA

Abstract

PURPOSE The purpose of OncoMX 1 knowledgebase development was to integrate cancer biomarker and relevant data types into a meta-portal, enabling the research of cancer biomarkers side by side with other pertinent multidimensional data types. METHODS Cancer mutation, cancer differential expression, cancer expression specificity, healthy gene expression from human and mouse, literature mining for cancer mutation and cancer expression, and biomarker data were integrated, unified by relevant biomedical ontologies, and subjected to rule-based automated quality control before ingestion into the database. RESULTS OncoMX provides integrated data encompassing more than 1,000 unique biomarker entries (939 from the Early Detection Research Network [EDRN] and 96 from the US Food and Drug Administration) mapped to 20,576 genes that have either mutation or differential expression in cancer. Sentences reporting mutation or differential expression in cancer were extracted from more than 40,000 publications, and healthy gene expression data with samples mapped to organs are available for both human genes and their mouse orthologs. CONCLUSION OncoMX has prioritized user feedback as a means of guiding development priorities. By mapping to and integrating data from several cancer genomics resources, it is hoped that OncoMX will foster a dynamic engagement between bioinformaticians and cancer biomarker researchers. This engagement should culminate in a community resource that substantially improves the ability and efficiency of exploring cancer biomarker data and related multidimensional data.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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