Cancer Driver Mutations
Larry H. Bernstein, MD, FCAP, LPBI
LPBI
Big Data Screen Uncovers New Cancer Driver Genes
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Using publicly available information from genomic and proteomic databases, a team of scientists lead by researchers at Sanford Burnham Prebys Medical Discovery Institute (SBP) have created a new and more comprehensive catalog of driver mutations for cancer. Driver mutations are genes that handle the progression of cancerous growths. The researchers used cancer mutation and protein structure databases to identify mutations in patient tumors that alter normal protein-protein interaction (PPI) interfaces—identifying more than 100 novel cancer driver genes that may help explain how tumors that are driven by the same gene often lead to vastly different clinical outcomes.
“This is the first time that three-dimensional protein features, such as PPIs, have been used to identify driver genes across large cancer datasets,” explained lead author Eduard Porta-Pardo, Ph.D., postdoctoral fellow at SBP. “We found 71 interfaces in proteins previously unrecognized as cancer drivers, representing potential new cancer predictive markers and/or drug targets. Our analysis also identified several driver interfaces in known cancer genes, such as TP53, HRAS, PI3KCA and EGFR, proving that our method can find relevant cancer driver genes, and that alterations in protein interfaces are a common pathogenic mechanism of cancer.”
The findings from this study were published online recently in PLOS Computational Biology through an article entitled “A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces.”
The last several years have seen a massive rise in the collection of “omic” data as well as a push by institutions such as the NIH to encourage data sharing. These efforts have led to an era of extraordinary ability to systematically analyze large-scale genomic, clinical, and molecular data to better explain and predict patient outcomes—all the while hoping to find new drug targets to prevent, treat, and potentially cure cancer.
“For this study we used an extended version of e-Driver, our proprietary computational method of identifying protein regions that drive cancer. We integrated tumor data from almost 6,000 patients in The Cancer Genome Atlas (TCGA) with more than 18,000 three-dimensional protein structures from the Protein Data Bank (PDB),” remarked senior author Adam Godzik, Ph.D., director of the bioinformatics and structural biology program at SBP. “The algorithm analyzes whether structural alterations of PPI interfaces are enriched in cancer mutations, and can, therefore, identify candidate driver genes.”
The researchers acknowledged that one of the aims of the current study was to change the mindset and begun to view proteins as multifunctional factories instead of an imposing unknown void, thereby making it possible to identify novel cancer driver genes and propose molecular hypotheses to explain the diverse heterogeneity in tumor populations.
“Genes are not monolithic black boxes. They have different regions that code for distinct protein domains that are usually responsible for different functions. It’s possible that a given protein only acts as a cancer driver when a specific region of the protein is mutated,” Dr. Godzik noted. “Our method helps identify novel cancer driver genes and propose molecular hypotheses to explain how tumors apparently driven by the same gene have different behaviors, including patient outcomes.”
“Interestingly, we identified some potential cancer drivers that are involved in the immune system,” Dr. Godzik added. “With the growing appreciation of the importance of the immune system in cancer progression, the immunity genes we identified in this study provide new insight regarding which interactions may be most affected.”
This is very insightful. There is no doubt that there is the bias you refer to. 42 years ago, when I was postdocing in biochemistry/enzymology before completing my residency in pathology, I knew that there were very influential mambers of the faculty, who also had large programs, and attracted exceptional students. My mentor, it was said (although he was a great writer), could draft a project on toilet paper and call the NIH. It can’t be true, but it was a time in our history preceding a great explosion. It is bizarre for me to read now about eNOS and iNOS, and about CaMKII-á, â, ã, ä – isoenzymes. They were overlooked during the search for the genome, so intermediary metabolism took a back seat. But the work on protein conformation, and on the mechanism of action of enzymes and ligand and coenzyme was just out there, and became more important with the research on signaling pathways. The work on the mechanism of pyridine nucleotide isoenzymes preceded the work by Burton Sobel on the MB isoenzyme in heart. The Vietnam War cut into the funding, and it has actually declined linearly since.
A few years later, I was an Associate Professor at a new Medical School and I submitted a proposal that was reviewed by the Chairman of Pharmacology, who was a former Director of NSF. He thought it was good enough. I was a pathologist and it went to a Biochemistry Review Committee. It was approved, but not funded. The verdict was that I would not be able to carry out the studies needed, and they would have approached it differently. A thousand young investigators are out there now with similar letters. I was told that the Department Chairmen have to build up their faculty. It’s harder now than then. So I filed for and received 3 patents based on my work at the suggestion of my brother-in-law. When I took it to Boehringer-Mannheim, they were actually clueless.