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Using Bioinformatics to Identify the Next Big Cancer Drug

Using Bioinformatics to Identify the Next Big Cancer Drug

By: Sarah Massey, M.Sc.

Posted on: in News | Life Science News

Physicians from the University of Texas M.D. Anderson Cancer Center, in collaboration with engineers from the University of Houston, have developed a new bioinformatics program that can identify immune cells which could be effective in treating cancer.

The software is one of the recent advances in the relatively new field of medicine known as immunotherapy. This field aims to find a way to use the patient’s immune system to target and destroy cancer cells while leaving normal cell types unharmed.

Some immunotherapies have been successful for patients participating in clinical trials however they aren’t ubiquitous. The researchers from the University of Houston hope to identify better-functioning immune cells that would offer new immunotherapeutic options to patients.

Current therapies for cancer including radiation and chemotherapy can be highly effective at killing the tumor cells but they show little to no discretion between normal and disease tissues. This leads to damage of healthy cells and potential long-term side-effects including heart and nerve damage and reproductive issues.

The new software named Time-lapse Imaging Microscopy in Nanowell Grids (TIMING) is able to potentially identify hundreds of thousands of T cell variants – a type of white blood cell important in immune function – and their ability to kill cancer cells. Their research will be published in the August 15 issue of Bioinformatics.

“There is a huge need to develop tools and techniques to unravel the interactions between the immune cells and the tumor cells. For example, you don’t want the immune cells to kill other cells,” Badri Roysam, chairman of the University of Houston Department of Electrical and Computer Engineering.

The TIMING program works by recording the cell-to-cell interactions between immune cells and cancer cells in a nanowell grid. The resulting time-lapse video can be used to analyze samples from diverse cancer types such as leukemia and melanoma and determine how effective the T cells are at fighting the disease.

The antigens presented on the cancer cells vary from cell-to-cell which means the immune system must be able to recognize a number of targets in order to kill the cancer cells. “We have to be able to cope with heterogeneity in cancer,” Roysam said. “Every patient is different, which means we have to make immunotherapy adaptable to different patients.”

This new technology is in its infancy and according to Roysam, multiple improvements must be made. Currently the TIMING software takes anywhere from a few hours to a few days to complete its analysis. Roysam would like to make the program run 100 times faster to make it a valuable tool for pharmaceutical companies and research labs.

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