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Clinical Proteomic Tumor Analysis Consortium Publishes Proteogenomic Study of Breast Cancer

NEW YORK (GenomeWeb) – Researchers from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium have shed light on the functional consequences of somatic tumor mutations by combining genomic data with mass-spec-based proteomic analyses.

Detailed in a paper published today in Nature, the "proteogenomics" study integrated proteomic and genomic data from 77 breast cancer tumors to investigate links between aberrations at gene and protein levels and potentially identify new biomarkers and therapeutic targets for the disease.

A five-year, $100 million-plus project launched in 2011, the CPTAC initiative has performed protein biomarker discovery and verification studies in tumor tissue samples previously characterized at the genomic and transcriptomic level by the NCI's Cancer Genome Atlas (TCGA) team. Specifically, the consortium, which comprises researchers from institutions around the country, including eight primary centers, undertook analyses of three tumor types – breast, colorectal, and ovarian – with the aim of profiling around 100 samples of each.

This week's breast cancer study follows a 2014 CPTAC study, also published in Nature, that looked at the proteome and genome of 95 colorectal tumors.

In the breast cancer work, the researchers used mass spec combined with isobaric labeling to quantify protein and peptide levels across the tumor samples, identifying a total of 15,369 proteins and 62,679 phosphosites and an average of 11,632 proteins and 26,310 phosphosites per tumor. They were able to quantify across the 77 tumors relative abundances of 12,553 proteins and 33,239 phosphosites.

One of the rationales behind integrating genomic and proteomic analyses is the expectation that the proteomic data will provide insights into the significance of identified genomic mutations. While genomic studies like TCGA have discovered a large number of genomic changes in cancer tissue, it is difficult to assess which are meaningful and which have little or no biological relevance. The hope is that by looking at proteomic data, researchers can identify which genomic aberrations are ultimately translated into changes at the protein level, assuming that such changes are more likely to be of significance than those that do not lead to protein alterations.

In the case of the CPTAC breast cancer study, a comparison of genetic copy number alterations with protein expression levels enabled the researchers to identify 10 new potential regulators of the disease, two of which, SKP1 and CETN3, are linked to the known oncogene EGFR.

The researchers were also able to recapitulate established molecular subtypes of breast cancer while also identifying two new potential subgroups — a stromal enriched group and a G-protein-coupled receptor group — not identified among the conventional mRNA-based subtypes.

They also conducted an outlier analysis, looking at the phosphorylation state of protein kinases measured in the study, in hopes of identifying aberrantly activated kinases that could be potential drug targets. In addition to known target HER2, this analysis identified other aberrantly activated kinases, including CDK12, PAK1, PTK2, RIPK2, and TLK2.

"It's always been important to get through to the molecules at work in the cell — the proteins — and this integrative exercise really gives us a whole new understanding of the landscape," Li Ding, assistant director of the McDonnell Genome Institute at Washington University in St. Louis and an author on the paper, said in a statement. "The proteogenomic approach shows potential for funneling down to a much smaller set of proteins and modifications that are the interesting drivers that we should think about from a therapeutic standpoint."