As promising as proteomics research is in the search for cancer biomarkers, sometimes looking for lone proteins is not enough. In 2006, the National Cancer Institute started a five-year project called the Clinical Proteomic Technologies for Cancer Initiative — a consortium made up of five different collaborative research groups working to address community-wide confusion and problems regarding the use of proteomics in the search for plasma biomarkers for cancer. "There was a lot of focus on validating proteomic technologies, mostly based on mass spec," says Matthew Ellis from Washington University in St. Louis. That project was successful enough that NCI re-awarded the grant, but with a slight twist. This time, Ellis says, "what they were looking for was proteomics that could be done in the context of cancer genomics."
The result is the newly formed Clinical Proteomic Tumor Analysis Consortium, or CPTAC, a consortium of five different centers, each of which maintains its own, separate collaborative project. Ellis — along with WashU's Reid Townsend, Boise State University's Morgan Giddings, and Xian Chen at the University of North Carolina, Chapel Hill — is taking part in one of the centers, called the Cancer Proteomic Center at Washington University, University of North Carolina, and Boise State University. The first goal of the larger CPTAC consortium is to validate biomarkers that have been identified as promising avenues for the early detection and diagnosis of cancer but have fallen short, says Boise's Giddings. But that's not the only goal the researchers have in mind. "I think the other thing is getting a deeper look at what makes cancer happen. People like Matthew Ellis have discovered these genomic aberrations that are definitely associated with the cancers," Giddings adds. "And so the question is, 'What is that doing to the proteome and how does that lead to cancer?' And I think getting the answer to that will sort of drill down into what exactly is cancer, and how can it be prevented, diagnosed, and treated in the future."
The four collaborators got together thanks to WashU's Townsend, Giddings says. Giddings had been mapping proteomics data to genomes on her own when Townsend saw a presentation of her work and suggested she get in touch with Ellis, who was studying breast cancer genomes. Once UNC's Chen got involved on the mass spec side, it seemed natural to apply for a grant as part of the larger CPTAC project, she says. "We have started the work — we did a bunch of preliminary work before we got any real funding for this because it's really cool science," Giddings says. "You get some really interesting stuff when you start looking at how aberrations in the genome that are detectable in cancer manifest themselves in the proteome. And we're just at the very beginning of that, but it's a really cool, unexplored area."
Two phases, two arms
When the CPTAC grant was re-awarded in August, collaborators from the five centers got together to discuss their strategy. It was decided, Ellis says, that the project would proceed in two phases — discovery and verification. "In the discovery phase, we would use samples [from The Cancer Genome Atlas] to do a proteomic analysis, which would yield candidates for verification, and the verification is supposed to be dominated by plasma assays," he adds.
In addition, the five centers have agreed to split their work into two arms — a clinical and a cancer biology arm. "The hypothesis [of the clinical arm] is that the genome-driven tumor secretome is a source of plasma biomarkers of clinical utility. And what all that means is that we will map protein expression in the context of genomic aberration, in the context of breast and ovarian cancer TCGA samples," Ellis says. "Of course we'll also explore indirect hypotheses that go something like, 'Tumor suppressor X is deleted, leading to deregulated mRNA Y, which encodes a secreted protein Z, which can also be detected in the plasma genome.' So basically the concept is to combine bioinformatics and gene function studies in the context of the TCGA data to come up with a list of candidates which can be searched for." This is quite different from the traditional cancer proteomics approach, which largely involves doing untargeted mass spectrometry on samples from cancer cases and controls in the hope of finding protein biomarkers. "Proteomics works much better if you know what you're looking for because you can instruct the machine to look for certain peptide sequences," Ellis adds.
In the cancer biology arm, the researchers' working hypothesis is that somatic mutations have predictable consequences on proteomic phenotypes. In this case, Ellis says, the teams aren't simply identifying peptides, but are more heavily focused on identifying any post-translational modifications such as acetylation, methylation, and phosphorylation. This arm of the research is also being done with an eye toward a third grant once CPTAC's five-year grant is up in 2016. "[For] the next RFA — if we're lucky enough for there to be one — we'd most likely be talking about a post-translational modification atlas in the context of genome-annotated samples, so we can really see how mutations were driving proteomic anomalies and signaling abnormalities using these proteome-wide assays that we develop," Ellis says. "And the clinical arm would become hypothesis-driven clinical research on predictive biomarkers because obviously there are drugs which are designed to affect PTMs."
Ellis also hopes to be able to work out a standard operating procedure for the collection of tumor samples with the preservation of post-translational modifications in mind. TCGA samples are frozen between 30 minutes to an hour after being taken from the patients, and that causes changes in the tissue that make it difficult to detect PTMs, he says. If the team can figure out the fastest way to freeze a sample after it is taken from the patient, and work out a way to find proteome-wide PTMs in an unbiased manner, then that could be the basis for a PTM cancer atlas, Ellis adds.
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The hard part
With so many people involved, organizational challenges would seem par for the course. But both Giddings and Ellis say that so far, everything is working well. Once the grants were awarded, the participants got together in Washington, DC, for a three-day meeting to set out an agenda, and they plan to continue having regular phone calls and meetings to keep each other updated and make sure they are on the same track. They've also split up into different working groups to address any issues that may arise.
Giddings says the real challenge is data integration. The consortium's members have created a working group specifically for finding the most efficient method to integrate and share data, and Giddings says this will be the toughest task. "There are different platforms, different methodologies, being used at the different centers on those samples," she adds.
Giddings says CPTAC would do well to take a look at the data integration strategy of the ENCODE project, of which she is also a part — as it has a heavy focus on integration analysis. "I think that's an incredibly important function if you're going to have a large function like [CPTAC], having the data come together and having the people and staff to do this," she says. "So that's going to be my challenge in this new consortium is convincing people to do something like what ENCODE has done and really get more focus and more resources invested into that data integration and data analysis."
Participants: Matthew Ellis and Reid Townsend, Washington University in St. Louis; Morgan Giddings, Boise State University; Xian Chen, University of North Carolina, Chapel Hill
Funding: The Cancer Proteomic Center at Washington University, University of North Carolina, and Boise State University is slated to receive around $2.2 million in 2011, and a total of about $10 million for the project's five-year run.
Timeline: The CPTAC project as a whole has a set timeline of five years, with an external review at the three-year mark to determine whether it will continue the following two years.