Dr. Sanjana on the Use of Whole-Exome Sequencing to Predict Immunotherapy Response in Advanced Tumors

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Neville E. Sanjana, PhD, discusses a study on the predictive utility of the Cancer Immunotherapy Response CLassifiEr in advanced-stage cancers.

Neville E. Sanjana, PhD, core faculty member, New York Genome Center, associate professor, Department of Biology, New York University, discusses a study on the predictive utility of the Cancer Immunotherapy Response CLassifiEr (CIRCLE) in advanced-stage cancers.

Although immunotherapy has greatly improved the treatment of advanced-stage cancers, only a subset of patients will experience long-term responses, Sanjana begins. Accordingly, a two-step approach using whole-exome sequencing was developed to improve the identification of patient populations who would derive more benefit from treatment with immune checkpoint inhibitors (ICIs), Sanjana says.

Established laboratory diagnostics focus on analyzing tumor mutational burden (TMB) to inform immunotherapy treatment decisions, Sanjana continues, noting that this approach identifies the quantity of mutations in the genome. A high number of mutations indicates that the tumor will produce a significant amount of neoantigens, thereby increasing the likelihood of a patient's response to immunotherapy, Sanjana explains.

Unlike TMB, which is calculated by analyzing many genes, CIRCLE specifically sequences protein-coding genes to identify the location of disease-associated mutations, Sanjana continues. Identifying these predictive genes and pathways may better clarify the relationship between genomic factors and a patient’s candidacy for immunotherapy, he adds.

The study combined data from 6 previous immunotherapy studies across advanced tumor types, Sanjana states. Despite including all patients treated with an ICI, the overall study population was relatively modest, he notes. Accordingly, there was a mismatch between the number of patients and the number of candidate genes sequenced in whole-exome sequencing.

To overcome this limitation, a two-step approach was employed, Sanjana explains. Candidate genes were initially nominated based on abnormally high TMB, adjusting for genomic factors. Gene enrichment was then assessed based on whether patients responded to immunotherapy, Sanjana concludes. 

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