NEW YORK (GenomeWeb) – The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium today named the Proteogenomic Translational Research Centers (PTRCs) that will participate in the third stage of the project.
The participating institutions include Baylor College of Medicine and the Broad Institute, which will focus on breast cancer; the Fred Hutchinson Cancer Research Center, Massachusetts General Hospital, and Mayo Clinic, which will focus on epithelial ovarian cancer; and Pacific Northwest National Laboratory and Oregon Health & Science University, which will focus on acute myeloid leukemia.
The NCI also noted that it has recently launched new Proteome Characterization Centers (PCCs) and Proteogenomic Data Analysis Centers (PGDACs) that will, respectively, characterize the biospecimens used in the project and analyze the proteogenomic data generated by the initiative. The PCCs will be hosted at the Broad Institute, Johns Hopkins University, and Pacific Northwest National Laboratory, while the PGDACs will be hosted at Baylor College of Medicine, the Broad Institute, Icahn School of Medicine at Mount Sinai, New York University School of Medicine, Washington University in St. Louis, Pacific Northwest National Laboratory, and University of Michigan.
Launched this year and slated to run for five years, with a total of $65 million in funding, this latest stage of the CPTAC initiative continues many of the efforts begun in earlier stages of the project, such as proteomic characterization of a variety of preclinical and clinical tumor samples and work to integrate genomic and proteomic data.
As the naming today of the three PTRC teams indicates, it also marks a shift into more translational research for the effort, with researchers using genomic and proteomic data to better understand patient drug response and the development of resistance.
An example of this move toward clinical applications is the ovarian cancer work being undertaken by Amanda Paulovich, director of the Early Detection Initiative at Fred Hutchinson. Under the CPTAC initiative, Paulovich and her colleagues will perform large-scale proteogenomic analyses on ovarian tumors looking for proteins linked to chemotherapy resistance.
They will then develop targeted assays to these proteins with the ultimate goal of employing these in clinical trials.
"The goal at the end of five years is to know if there’s a signature that we can use to determine who will respond to platinum-based chemotherapy," Paulovich said in a statement. "It would be great if we also are able to identify new possible therapeutic targets to help overcome treatment resistance."
Key to the effort, she noted, would be the ability of proteogenomic approaches to provide a broad look at ovarian cancer pathways across multiple levels of molecular information.
"There’s no one mechanism of resistance; we’re going to look at the entire network of proteins and genes that together have a role," she said.
The move towards proteogenomics within CPTAC began with the initiative's second stage, during which researchers undertook proteomic analyses of three tumor types — breast, colorectal, and ovarian — previously characterized at the genomic and transcriptomic levels by the NCI's Cancer Genome Atlas project.
Driven by technologies like next-generation sequencing and ongoing improvements in the breadth and quality of proteomic data, proteogenomics hopes to leverage multiple levels of molecular information to better understand biological and disease processes and improve biomarker discovery and development.
For instance, 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. Proteogenomics can potentially aid such efforts by adding proteomic data to the mix. The hope is that by looking at proteomic data, researchers can identify which genomic aberrations are ultimately translated into changes at the protein level, with the assumption being that such changes are more likely to be of significance than those that do not lead to protein alterations.
Henry Rodriguez, director of the Office of Cancer Clinical Proteomics Research, Center for Strategic Initiatives at NCI said that the second phase of the CPTAC initiative demonstrated the "great potential for new insights to come from the combined analysis of cancer proteomic and genomic data, as proteomic data provides additional, critical information that is difficult or impossible to infer from genomic data alone."
He cited the project's breast cancer work as an example of the technique' promise, noting that in that case "proteogenomics elucidated the functional consequences of somatic mutations, narrowed candidate nominations for driver genes, and identified therapeutic targets."
In that 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.
"Genetic information about a person’s cancer has provided a wealth of knowledge and significant progress in stratifying patients over the last decade, especially in the discovery and development of treatments that target specific genetic abnormalities," Rodriguez added, discussing the PTRC's planned focus on exploring questions of drug response and toxicity. "However, prediction of drug response and toxicity and the relatively rapid acquisition of resistance to such treatments significantly limit their utility and remains a challenge. Complementing genomic analysis with proteomic analysis would systematically capture the interrelationship and provide new insights to predicting clinical response to therapeutic agents."
In addition to applying existing proteogenomic workflows, the initiative's researchers will continue to develop and refine these techniques, Rodriguez noted.
"From a biology discovery perspective, data sharing and more computational assimilation is necessary to entirely use the complete data spectra acquired in genomics, transcriptomics, and proteomics studies," he said. " From a translational clinical perspective, speed, automation, and standardization will always be important."