Using bioinformatics to create cancer vaccines

November 30, 2014 − by Suzanne Elvidge − in Big data, Big data in research, Data analytics, Data mining, Drug development − No Comments

Biologists, immunologists and computational bioinformaticians have worked together to find protein mutations on cancer cells that could lead to new personalised vaccines. The research has been published in the Journal of Experimental Medicine.

As cancer cells mutate, they create new proteins on their surface that could be targets for vaccines; the challenge is to find the best antigens to create an antitumor T cell response, without targeting the similar epitopes on healthy cells. Researchers at the University of Connecticut have created two tools that look at the differences between the mutated proteins on the cancer cells and the unmutated ones on the healthy cells (the differential agretopic index), and at the stability of the interaction between MHC I (the molecules that present antigens to the immune system) and the target antigen. The initial results, in mouse skin cancer, have been positive.

“We want to break the immune system’s ignorance,” says Pramod Srivastava, director of the Carole and Ray Neag Comprehensive Cancer Center at UConn Health. “For example, there could be 1,000 subtle changes in the cancer cell epitopes, but only 10 are “real,” meaning significant to the immune system.”

The first target will be ovarian cancer, a form of cancer that often responds well to initial surgery and chemotherapy, and then returns with serious consequences within a year or two.

“This has the potential to dramatically change how we treat cancer,” says Srivastava. “This research will serve as the basis for the first ever genomics-driven personalized medicine clinical trial in immunotherapy of ovarian cancer, and will begin at UConn Health this fall.”

In the planned clinical trial, the team will sequence DNA from the tumours of 15 to 20 women with ovarian cancer, and use that information to make a personalized vaccine for each woman. The initial response and period of remission will allow the team time to create and administer the therapeutic vaccine, and the expected relapse allows them to see whether the vaccine has made a difference within just a couple of years.

“This research is a great example of how diverse disciplines create synergy under the umbrella of genomics,” says UConn’s vice president for research, Jeffrey Seemann.

UConn researchers have applied for two patents for their new technique, and a Connecticut start-up company, Accuragen, in which Srivastava has a financial interest, has obtained an option to license the patents.

GenoKey was not involved in this research, but its powerful data mining technologies and massively parallel processing can support analyses and highly complex datasets.





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