Specific CD8 T Cell States May Indicate Response to Melanoma Therapy
Source: Laboratory Equipment, December 2018
A multi-institutional research team, led by investigators at Massachusetts General Hospital (MGH) and the Broad Institute of MIT and Harvard, has identified specific states of cytotoxic CD8 T cells that are associated with patient response to checkpoint immunotherapy for melanoma. Their report published in the journal Cell also identifies specific marker proteins associated with these cell states, providing data that could help better understand why checkpoint therapy – which enables the immune system to attack cancerous tumors – doesn’t work for all patients and may enable the development of tests to help predict which patients may be helped by the approach. A companion immunotherapy study, led by a separate research team from the Broad Institute and Dana-Farber Cancer Institute, appears in the same issue of Cell.
“Checkpoint inhibition therapies have completely changed the way patients with metastatic melanoma are being treated clinically today, and since they were first approved in 2011 they have given new hope to patients who otherwise would have very poor prognosis – an average survival of under a year – and few therapeutic options,” says Nir Hacohen, director of the Center for Cancer Immunology in the MGH Center for Cancer Research, co-director of the Cell Circuits Program at the Broad Institute, and co-senior author of the Cell paper. “But even though melanoma has one of the highest response rates to checkpoint inhibition, with around 40 percent of patients responding to PD-1 checkpoint therapy, most patients will either not respond or will relapse.”
Previous studies of tumor response to PD-1 or other checkpoint inhibitors have focused on tumor-associated factors, including the number of mutations in a tumor, the levels of PD-L1 – the protein that binds to PD-1 – the abundance of CD8 T cells and expression of inflammatory genes detected before or soon after treatment began, but have had limited ability to predict patient outcomes. To identify immune-related factors in the tumor and determine their ability to predict checkpoint responses, the research team – led by Hacohen and co-senior author Gad Getz, director of the Cancer Genome Computational Analysis group at the Broad and director of Bioinformatics at the MGH Cancer Center – used single-cell RNA sequencing, which measures cell-by-cell the RNA levels of thousands of genes, to get a clearer picture of the immune landscape of patients treated with checkpoint inhibitors.