Combining Biomarkers for Immunotherapy

To validate two of the most widely used candidate biomarkers for immunotherapy—tumor mutation burden (TMB) and gene expression profiles (GEP) indicative of a “hot” T cell–inflamed microenvironment—Merck has released an analysis involving tumor samples from 315 patients with 22 types of cancer who received its anti–PD-1 drug pembrolizumab (Keytruda) as part of four separate clinical protocols (Science 2018;362:eaar3593).

By mining this large pan-tumor dataset, the authors show that TMB and GEP independently predict response to checkpoint blockade, yet exhibit low correlation. Considering both biomarkers, they concluded, offered the greatest predictive utility and helped reveal patterns of underlying, targetable molecular and genetic activity.

The findings suggest that each biomarker captures a distinct aspect of cancer immunobiology—tumor antigenicity and T-cell activation state, respectively. “Both are important,” says James Gulley, MD, PhD, head of the Immunotherapy Group at the NCI Center for Cancer Research, who was not involved in the study. Although smaller, single-tumor-type studies made similar inferences in the past, “we haven't had as big a dataset before.”

To parse the data, Razvan Cristescu, PhD, senior principal scientist at the Merck Research Laboratories in Boston, MA, and his colleagues stratified the 315 trial participants into four biomarker-defined groups based on their tumors' TMB and GEP scores. Cristescu's team showed that patients with high levels of both biomarkers had the greatest response rates to pembrolizumab—37% to 57%, depending on the cutoff values used to delineate high and low TMB. Response rates were under 10% for patients with low levels of both biomarkers, and between 11% and 42%, depending on the cutoffs, among those with high TMB and low GEP, or vice versa.

Cristescu's team also cross-validated the biomarkers against transcriptomic and genomic profiles from thousands of tumor samples in The Cancer Genome Atlas, which confirmed that TMB and GEP offer tumor type–agnostic signatures of biological processes related to cell proliferation, vascular invasion, myeloid infiltration, and stromal signaling. Cristescu says this provides a biological explanation for why certain pan-tumor, biomarker- defined patient groups exhibit lower response rates to pembrolizumab.

However, the biomarkers reflect a degree of molecular dysregulation specific to each tumor type as well, indicating that the clinical utility of TMB and GEP will likely vary from one indication to the next.

Erin Schenk, MD, PhD, of the University of Colorado Anschutz Medical Center in Aurora, says she could envision using the joint biomarker analysis, if prospectively validated, to rule out pembrolizumab as a monotherapy in certain patients with lung cancer. Just as she currently uses PD-L1 levels to determine whether to administer chemotherapy alongside the anti–PD-1 drug, low scores on both the TMB and GEP tests could indicate whether a patient needs a second drug alongside pembrolizumab to render the tumor susceptible to checkpoint blockade.

“ This is most helpful in identifying those patients who will not likely respond,” Schenk says. For everyone else, the biomarkers are still not sensitive enough to offer actionable guides for precision cancer care, she says, but they could prove valuable as selection criteria in clinical protocols to enrich for participants most likely to benefit.

Merck, in a 192-person trial launched in October, is now seeking to prospectively validate the utility of the joint biomarker in patients with non–small cell lung cancer treated with pembrolizumab plus either the anti-LAG3 antibody MK-4280 or the anti-VEGFR drug lenvatinib (Lenvima; Eisai). The goal is to confirm that patients with high GEP and high TMB have the highest response rate, patients with low GEP and low TMB have the lowest response rate, and patients with mixed GEP and TMB levels fall somewhere in between. –Elie Dolgin

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