TMB needs company
Why predicting responses to checkpoint blockade will take more than just TMB
Tumor mutation burden is looking less like a magic bullet and more like just one of at least three variables that could jointly predict responses to checkpoint inhibitors. Combining TMB measurements with markers of T cell inflammation and antigen presentation could pinpoint responders in a wide range of cancers.
However, to avoid the pitfalls that came with measuring PD-L1, the TMB field will need to converge on standards for both methodology and validation that will allow results to be compared across trials.
By counting mutations in a patient tumor sample, TMB measures how different a cancer has become from its tissue of origin. That serves as a proxy for the likelihood the cancer cell will be targeted as non-self by the immune system.
Cancers with high TMB counts are therefore expected to be more susceptible to drugs that boost immune responses.
Numerous studies in the last five years have bolstered that hypothesis, showing high TMB count is associated with greater response to checkpoint inhibitors. The largest of these, published by Memorial Sloan Kettering Cancer Center researchers in Nature Genetics this month, showed the correlation held up in a study of 1,662 patients representing a dozen different cancer types, treated with one or more of seven different checkpoint inhibitors.
The mounting evidence for TMB led Bristol-Myers Squibb Co. to change a primary endpoint in its Phase III CheckMate -227 trial of Opdivo nivolumab plus Yervoy ipilimumab. Last February, BMS showed the anti-PD1 and anti-CTLA-4 combo increased progression-free survival (PFS) vs. chemotherapy in first-line non-small