Flexible, efficient bioinformatic tools will dig into mountains of tumor genetic data

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.

Professor of Bioinformatics and Computational Biology Jonas Almeda, Ph.D., is a leading expert in semantic web, a flexible database infrastructure that's easily expandable to accommodate new types of searches. Searching a standard relational database requires loading the data and then searching it for the desired information, Weinstein explained. A semantic web structure allows searches based on a subject-predicate-object format that can home more directly to the information sought, dramatically speeding up searches. With an appropriate graphics card, more data crunching can be done in the browser of the user's laptop, rather than in a distant server. That also speeds processing time and relieves pressure on the server.

Team member David Kane of SRA International, a longtime collaborator of Weinstein's, is an expert in the Agile software development paradigm. Traditional software development involves extensive planning and consultation with users before any code is written. "The central tenet of agile development is that you get something working quickly via close consultation between biologists and software engineers. The biologists then are the initial testers and users, and the software is grown organically. The initial investment is small, so you don't have to be afraid of changing direction if necessary," Weinstein said.

Kane used the agile approach to develop the Miner Suite of bioinformatics software with Weinstein at the National Cancer Institute. Weinstein worked at the NCI for more than 30 years, and directed what has been considered a precursor project to the Cancer Genome Atlas before coming to M. D. Anderson in January 2008. Advances based on the Miner Suite will be used in this project.

The TCGA grant application was Weinstein's first to his former employer.

Findings and tools generated by the project will be open source, available to other TCGA research teams, and in a format compatible with both The Cancer Genome Atlas and the NCI's Cancer Biomedical Informatics Grid (caBIG).

Weinstein has done a series of calculations to put the challenge of sorting out the many variables of the cancer genome in perspective. "If you unpacked the DNA in every cell of a single person and stretched it end to end, it would circle the equator 917,000 times – the equivalent of 120 round trips to the sun. One error in replicating the genome in one unlucky place – over a length of 120 trips to the sun and back – can lead to cancer. Our challenges are to understand how that happens -- and to know what to do about it if we can't prevent it in the first place."