The Cancer Genome Atlas (TCGA) will fund an effort by scientists at The University of Texas M. D. Anderson Cancer Center to siphon buckets of meaningful information from an ocean of data about the aberrant genetics that drive human cancers.
"Analysis and interpretation of genetic data from tumor samples is a major bottleneck to progress in understanding and treating cancer," said the project's lead principal investigator John Weinstein, M.D., Ph.D., professor and chair of M. D. Anderson's Department of Bioinformatics and Computational Biology, as well as professor in the Department of Systems Biology.
The five-year $8.3 million grant from the TCGA will allow Weinstein and colleagues to put new computational tools to work parsing the multiple genetic pathways that fuel more than 20 types of cancer. The team proposes a more flexible and efficient approach to wringing information from overwhelming quantities of data researchers generate about gene expression and variation in tumors.
"The bottom line is personalizing cancer medicine. If we can generate molecular portraits of these cancers, we will be better able to choose the right therapy for each patient," Weinstein noted. "And it also will improve cancer risk assessment, early diagnosis, prognosis and assessment of the likelihood of recurrence."
The M. D. Anderson group is a new Genome Data Analysis Center of the TCGA, which is a joint enterprise of the National Cancer Institute and the National Human Genome Research Institute, both of the National Institutes of Health. The grant is part of the expansion of TCGA, after a pilot project focused on glioblastoma, lung cancer and ovarian cancer.
Co-leaders of the project are Gordon Mills, M.D., Ph.D., professor and chair of M. D. Anderson's Department of Systems Biology, and W. K. Alfred Yung, M.D., professor and chair of the Department of Neuro-Oncology. "They will provide extraordinary expertise in the systems-oriented and clinical aspects of the overall project," Weinstein said.
Rather than focusing on individual or pairs of genetic variations in tumors, the M. D. Anderson analysis center will study multi-gene pathways and combinations of pathways, a systems biology approach that addresses the complexity of cancer growth and survival.
Weinstein's group is developing a bioinformatic pipeline to analyze TCGA data and translate findings to the clinic. "We will use several nuggets of innovation to develop applications that will usefully address the questions that biologists and clinicians have at the end of the day," Weinstein said.
A major strength of the project is M. D. Anderson's leading expertise in translational and clinical research, Weinstein said. That expertise will keep bioinformatics development connected to important questions that must be addressed for each tumor type and for different types of molecular information. Additionally, M. D. Anderson is by far the largest contributor of tumor tissue samples to TCGA. That will be particularly important in the study of less common cancers.
The team will tap M. D. Anderson's leadership in the use of Bayesian statistical analysis, an efficient and informative approach to data analysis and clinical trial design, as developed under Donald Berry, Ph.D., Professor and Head of the Division of Quantitative Sciences.
Weinstein and colleagues will apply a number of advanced computational tools and concepts based on pathway analyses, artificial intelligence-based prediction methods, and the clustered heat map representations of genomic data that Weinstein introduced in the early 1990s.