Bioinformatics leads UCSD team to ovarian cancer biomarkers

UCSD's Christian Barrett

A team at the University of California, San Diego (UCSD), has found biomarkers for ovarian tumors by mining two National Institutes of Health (NIH)-sponsored databases. The bioinformatics-enabled research program has raised expectations that earlier diagnoses of ovarian cancer can be made, an advance that could improve outcomes in a tough therapeutic indication.

Researchers at UCSD spotted 6 mRNA isoforms found in ovarian cancer cells--but not in healthy tissues--by combing through the Cancer Genome Atlas and Genotype-Tissue Expression program. The discovery was made possible by custom bioinformatics algorithms and the two NIH-sponsored, publicly accessible databases. In total, the team scoured transcriptome sequence data from 296 ovarian cancer samples and 1,839 normal tissues, leading to the identification of 6 mRNA isoforms with sufficient tumor specificity to enable an early diagnosis.

The project builds on earlier attempts to use genetic material to diagnose cancer. "We were inspired by many studies aimed at using DNA to detect cancer," Christian Barrett, a UCSD bioinformaticist and first author of the paper, said in a statement. "But we wondered if we could instead develop an ovarian cancer detection test based on tumor-specific mRNA that has disseminated from cancer cells to the cervix and can be collected during a routine Pap test." The next step is to gather clinical data to validate the laboratory-based findings.

Barrett and his colleagues are also interested in applying their strategy to other forms of cancer, namely the 30 tumor types for which there are similarly bountiful supplies of RNA sequencing data. NIH has enabled the creation of these resources by financing multicenter data-generation programs, the scale of which is beyond the reach of almost any individual research institution. Yet while these high-profile programs have been accumulating for years, the UCSD team think the data have been underexploited to date.

"The raw transcriptome data being produced by these efforts has tremendous discovery potential, but to date they have not been rigorously evaluated for tumor-specific molecules for diagnostic and therapeutic applications," Barrett and his co-authors wrote. 

- read the release
- here's the paper (PDF)

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