New Insight into Genetics May Improve Cancer Immunotherapy


Some tumors can remain undetected from current cancer treatments.

More than 100 new genetic regions that affect the immune response to cancer was identified in a study published in Cancer Immunology Research.

A large portion of current immunotherapies rely on a similar strategy that involves releasing the brakes on the immune system. These treatments are successful if the immune system is able to recognize the tumor as a threat, allowing immune cells to infiltrate.

However, some tumors are still able to block immune cells from entering into the tumor, or remain undetected.

“To develop immunotherapies that are relevant to a wide range of cancers, we need to know a lot more about how the immune system interacts with tumors,” said senior study author Adam Godzik, PhD. “Our study provides many new leads for this endeavor.”

In the study, researchers found 122 potential immune response drivers by analyzing a large published genomic database.

“We are exploring cancer mutations at fine resolution by accounting for the fact that mutations can affect the encoded protein in different ways depending on where the resulting change is located,” said lead study author Eduard Porta-Pardo, PhD. “Our algorithm, domainXplorer, identifies correlations between a phenotype, in this case the amount of immune cells in the tumor, and mutations in individual protein domains — parts of a protein with distinct functions. While several of these correspond to proteins with known roles in immune response, many others offer new directions for cancer immunology research, which could point to new targets for immunotherapy.”

The findings provide further insight into cancer research and the use of genomic data allows for faster and more expansive material for deeper analysis.

“This work emphasizes the value of open data,” Godzik said. “Because we could access genomic data from over 5000 tumor samples from The Cancer Genome Atlas (TCGA), we could jump straight to analysis without having to set up a big collaborative network to gather and sequence so many samples. Our plan for the next phase of this research is to use this algorithm to search for genetic regions correlating with the levels of specific immune cell types within the tumor, which will reveal further details of cancer immunology.”

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