Millions of genetic mutations have been identified in cancer. But, not all mutations cause cancer and treatments are available for only a few of those causing cancer. At The University of Texas Health Science Center at Houston (UTHealth), scientists have created a new way to sort out cancer–causing mutations that respond to treatment.

“We’ve developed a powerful approach for identifying actionable cancer–causing mutations,” said Zhongming Zhao, PhD, the corresponding and senior author of the paper in the journal Cancer Research. Zhao is the director of the Center for Precision Health in the School of Biomedical Informatics and School of Public Health at UTHealth.

Using their novel computational method, Zhao and his colleagues were able to winnow about 740,000 mutations identified in approximately 5,000 tumor samples in 16 cancer types down to 47 significantly mutated proteins. Research on these mutations indicated that they may respond to drug treatment.

“Our goal is to categorize the cellular mutations that alter the signaling pathways leading to cancer,” Zhao said. “These are the mutations that impact the function of genes and proteins in cancer.”

Zhao’s team studies a category of enzymes called kinase that functions on signaling transduction. More than 20 drugs targeting kinases have been approved for clinical use.

“We need to learn more about this category of enzymes because patients can respond to such kinase inhibitors, but also later develop a resistance to them,” Zhao said. “Kinases are involved in complex signaling pathways that can adapt over time.”

Zhao’s team specifically investigated the biochemical reactions called phosphorylation that occur when a kinase interferes with the normal function of a gene or protein. Using this new approach, the researchers identified thousands of tumor mutations that may contribute to abnormal tumor growth or anticancer agent resistance by altering phosphorylation.

“This study, although based on computational and statistical approaches, could help inform many promising mutant proteins for drug development in rapidly evolving precision oncology,” Zhao said.

The research team named the approach KNMPx: kinome–wide network module for cancer pharmacogenomics.

Junfei Zhao, PhD, and Feixiong Cheng, PhD, are the first co–authors. Cheng is currently with Harvard Medical School and Northeastern University. Zhao is a faculty member of The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences.

The study is titled, “Tissue–specific signaling networks rewired by major somatic mutations in human cancer revealed by proteome–wide discovery.”