Tumor mutational burden (TMB) was an accurate predictor of response to treatment with immune checkpoint inhibitors for female patients with melanoma, but not for male patients, according to results of a study presented by Sinha et al during the virtual American Association for Cancer Research (AACR) Annual Meeting 2021 (Abstract 29).

In June 2020, the U.S. Food and Drug Administration (FDA) approved the immune checkpoint inhibitor pembrolizumab to treat adult and pediatric patients who have advanced solid tumors with a high TMB. The FDA set the threshold for treatment of patients whose tumors have 10 or more mutations per megabase (TMB > 10 mut/Mb).

Early research has suggested that high TMB levels may be associated with better response to immune checkpoint inhibition, and that the response may differ between males and females. “This motivated us to examine the sex-specific implications, if any, of the TMB > 10 mut/Mb threshold for selecting patients to be treated with immune checkpoint inhibitors,” said the study’s lead author, Neelam Sinha, MS, a member of the Cancer Data Science Laboratory at the Center for Cancer Research, part of the National Cancer Institute.

The researchers analyzed data from Memorial Sloan Kettering Cancer Center’s MSK-IMPACT tumor-profiling panel. They examined data from 1,286 patients treated with anti–PD-1/PD-L1 monotherapy, 99 patients treated with anti–CTLA-4 monotherapy, and 255 treated with a combination of the two. They focused on the nine cancer types that had TMB and clinical response data for at least 50 patients.

Differences Observed

Consistent with previous reports, they first found that female patients with melanoma had a median of 6.51 mut/Mb, while male patients had a median of 11.81 mut/Mb.

Female patients whose tumors had TMB > 10 mut/Mb had 81% better overall survival following immune checkpoint inhibition compared with female patients who had TMB below the current threshold. In contrast, no significant differences were observed in treatment response between male patients with TMB above and below the 10 mut/Mb threshold.

The researchers did not find any significant sex-dependent differences in the response to anti–CTLA-4 therapies, different chemotherapies, or combination therapies when analyzed using the TMB > 10 mut/Mb threshold.

In the analysis of other cancer types, female patients with glioblastoma had a similar trend of better response to immune checkpoint inhibition based on the current TMB threshold; however, the data did not reach statistical significance, possibly due to small sample size, said coauthor Sanju Sinha, also a member of the Cancer Data Science Lab at the Center for Cancer Research and a PhD candidate in the Biological Sciences Graduate Program at the University of Maryland.

“First, it is important to note that TMB > 10 mut/Mb is not currently required for patients with melanoma to receive pembrolizumab. However, as clinicians may still take this threshold into account while considering therapies for a patient, it is important to raise awareness to this bias,” said Mr. Sinha. “Second, in cancer types like glioblastoma and cancer of unknown primary, the FDA TMB criterion does currently apply. Hence, more data must be gathered to carefully assess whether its usage may induce a sex bias.”

The authors said the results of this study suggest that more research is necessary to fully assess the utility of TMB as a predictor of immunotherapy response. “The overall value of TMB as a predictor of response is quite moderate, as many factors are involved in a patient’s response to immunotherapy,” said Ms. Sinha. “If the current TMB threshold also induces a sex bias, its usage as a biomarker requires further scrutiny.”

Ms. Sinha added that the study results could add to research on cancer health disparities, which encompass sex as well as racial, ethnic, socioeconomic, and cultural differences. “Addressing long-standing sex disparities in health care can help ensure equal treatment opportunities and benefit both sexes,” she said.

Disclosure: This research was performed under the supervision of Eytan Ruppin, MD, PhD, Chief of the Cancer Data Science Laboratory, and supported by the Intramural Research Program of the National Cancer Institute. For full disclosures of the study authors, visit abstractsonline.com.