Computational Analysis of Immunotherapy Response Paints a Complex Picture

Computational Analysis of Immunotherapy Response Paints a Complex Picture

Using an advanced computational analysis may help scientists predict which patients are likely to respond to immunotherapy. But researchers — who hope a more integrated picture of the immune response might advance immunotherapy strategies — say they’re hampered by the lack of publicly available data to use in their computations. That puts a spotlight on the issue of data sharing in medical research.

Their study, “Systematic Pan-Cancer Analysis Reveals Immune Cell Interactions in the Tumor Microenvironment,” appeared in the journal Cancer Research.

“Our study is the first, to our knowledge, that uses computational approaches to examine the effect different immune cells have on each other in the context of the tumor and outline how these interactions affect patient survival” the study’s lead author, Frederick Varn, BS, a PhD candidate at the Dartmouth-Hitchcock Medical Center in Hanover, New Hampshire, said in a news release.

Although some cancer immunotherapies aim to boost a specific immune cell type to fight a tumor, the reality is that immune cells seldom act in an isolated manner. The team found that tumors usually contain a range of immune cells. So-called cytotoxic T-cells can directly kill tumor cells, while regulatory T-cells and some myeloid cells counteract the immune attack, Varn explained.

“Understanding how these cell types infiltrate different tumors and the effect these cells have on each other and the patient can help us understand how to better harness the power of the immune system for cancer therapy,” he said.

In other words, for research on how one cell type fights cancer to have value, researchers must also consider how this cell is affected by its neighbors. The newly developed method is particularly beneficial, since it is cheap and easy to use when researchers have access to a patient’s gene activity data.

“This information can eventually be used to help identify patients likely to respond to certain immunotherapeutic approaches, as baseline immune infiltration of certain cell types has been implicated as a predictor of response to numerous immunotherapeutic approaches,” Varn said.

Eventually, doctors could use information obtained through this method to predict individual responses to immunotherapy. But to get there, the research team needs access to much more patient data. Currently, most datasets of gene expression profiles — used to assess immune cell infiltration — as well as information about patient outcomes are not publicly available. Researchers hope this will change as the field advances.

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