A mutational burden threshold that may predict patients’ response to immune checkpoint blockade therapy exists in eight solid cancer types, including melanoma, cervical cancer, and bladder-urothelial cancer, according to a recent study.
Anshuman Panda, PhD, Mayo Clinic (Phoenix, AZ), and colleagues evaluated whole-exome sequencing and RNA sequencing data of 33 solid cancer types from the Cancer Genome Atlas in order to explore whether a robust immune checkpoint-activating mutation (iCAM) burden threshold could predict immune checkpoint therapy response.
The study was published in JCO Precision Oncology (online December 7, 2017; doi:10.1200/PO.17.00146).
Ultimately, results of the study showed that a robust iCAM threshold exists in eight of 33 solid cancers. These include melanoma, lung adenocarcinoma, colon adenocarcinoma, endometrial cancer, stomach adenocarcinoma, cervical cancer, estrogen receptor-positive/human epidermal growth factor receptor 2-negative breast cancer, and bladder-urothelial cancer.
The researchers also found that iCAM-positive tumors, or tumors with a mutational burden higher than the threshold, had clear histologic evidence of lymphocytic infiltration. In addition, according to published datasets of melanoma, lung adenocarcinoma, and colon cancer, patients with iCAM-positive tumors demonstrated significantly better responses to immune checkpoint therapy vs those with iCAM-negative tumors.
According to receiver operating characteristic analysis that used the Cancer Genome Atlas predictions as the gold standard, iCAM-positive tumors can be accurately identified via clinical sequencing assays, including FoundationOne (Foundation Medicine; Cambridge, MA) or StrandAdvantage (Strand Life Sciences; Bangalore, India).
The researchers noted that iCAM-positive and iCAM-negative tumors each have distinct mutation patterns, as well as different immune microenvironments.
“In eight solid cancers, a mutational burden threshold exists that may predict response to immune checkpoint blockade,” the researchers concluded. “This threshold is identifiable using available clinical sequencing assays.”—Christina Vogt