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TCGA Study Demonstrates Benefits of Integrating Genomic, Proteomic Data


A recent investigation by the National Cancer Institute's Cancer Genome Atlas consortium into the genetic underpinnings of breast tumors also offers a glimpse of the benefits of including proteomic data in such analyses.

As they report in Nature, TCGA researchers examined primary breast tumors from a total of 825 patients across five platforms, analyzing DNA copy number, DNA methylation, exome sequences, messenger RNA, and microRNA sequences.

Additionally, they ran 403 of the samples on reverse-phase protein arrays, measuring levels of 171 cancer-related proteins and phosphoproteins, finding generally good concordance between the genomic, transcriptomic, and proteomic data, says Charles Perou, a genetics researcher at the University of North Carolina at Chapel Hill.

The DNA- and RNA-based profiles generated in the study clustered into groups that largely corresponded with four main classes of breast cancer, and, Perou notes, when the researchers "did unbiased class discovery using just the protein expression, it did largely map to [these] gene expression subtypes."

However, Perou adds, the "proteomics, and particularly the phosphoproteomics, really informed us in some ways beyond what the gene expression could tell us."

Specifically, he says, the proteomic data suggests the existence of two distinct phosphoproteomic-based subtypes within the larger gene expression-based HER2 subtype — one exhibiting high HER2 and HER1 signaling activity and the other exhibiting lower levels of such activity.

The other example "where the protein data really provided a lot of interest and headscratching," Perou says, was the group's analysis of PI3 kinase signaling, in which they found a disconnect between the PI3K signaling data obtained via the RPPA analysis and their PI3K mutation data.

"When we did a pathway-based analysis of the PI3K signaling pathway, we could see that what are believed to be protein and phospho-proteomic signatures of PI3K activation didn't correlate with PI3K mutations, but did correlate with the loss of negative regulators of that pathway, like loss of INPP4B or loss of PTEN," he says. "So there we're somewhat left with a disconnect between the mutation information and the phosphoproteomics."

This particular disagreement has been observed in previous studies, Perou notes, including in work by MD Anderson researcher Gordon Mills.

Given the discrepancy, Perou says, the "challenge now is to figure out which of these many different genetic events or protein signatures are going to be biomarkers" of responsiveness to drugs like PI3K or mTOR inhibitors.

This work is ongoing, he adds, noting that the researchers are currently reanalyzing the genetic data based upon protein and phosphoproteomic endpoints.

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