Next-generation sequencing (NGS)--faster and cheaper genome sequencing--has revolutionized the search for genes connected with disease, and each week more DNA- and RNA-based biomarkers are found. In a study presented at a U.S. breast cancer meeting, the diagnostics company Genomic Health ($GHDX) used RNA sequencing to validate genes identified using a more traditional form of sequencing.
Genomic Health profiled the entire transcriptome (all the forms of the RNA in the tissue) of archival formalin-fixed paraffin embedded (FFPE) tumor specimens from 136 breast cancer patients with known clinical outcomes. According to data presented at the 2011 CTRC-AACR San Antonio Breast Cancer Symposium, the transcriptome data identified and confirmed the same genes found by the older RT-PCR technique used to develop the company's Oncotype DX breast cancer test. It also showed more than 1,800 stretches of RNA that could be linked with breast cancer recurrence, many of which have not been linked with cancer before. More research will be needed to see whether these are seen in other groups of breast cancer patients, or whether they will have any application in diagnostics.
"Next-generation sequencing allows researchers to process and analyze large volumes of data in a fraction of the time currently required by conventional gene expression profiling technologies," said Dr. Jose Esteban of Providence Saint Joseph Medical Center in Burbank, CA, a co-investigator of the study. "New methodology used in this study applies NGS-based whole transcriptome profiling to very low amounts of RNA from FFPE tissue that had been archived for up to 12 years, to provide vast amounts of data, with data quality sufficient for broad biomarker discovery from regions outside the previously identified protein-coding sections of the genome."
By matching the genes found by a well-known and well-used technique, Genomic Health has validated the use of transcriptome profiling in biomarker discovery and clinical development. This technique has the added advantage that it can be used in archival samples and samples with low levels of RNA, and could be quicker than existing techniques.
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