High tumor mutational burden (TMB)—the number of mutations found in cancer cells, reported Sept. 29 in Cancer Cell, a Cell Press journal – may not be an accurate biomarker in different cancer patient populations. The findings may have important implications for clinical decision-making in the treatment of immune checkpoint inhibitors, a type of immunotherapy.
“This study uncovers potential technical issues with TMB as a biomarker in diverse populations that have not been appreciated before.” Co-corresponding author Dan, Harvard Medical School “Biomarker studies of underrepresented populations are critical to ensuring that disparities are minimized in the era of precision medicine,” said Alexander Gusev of the Na-Farber Cancer Institute.
ICI pembrolizumab was recently approved by the U.S. Food and Drug Administration (FDA) for the treatment of solid tumors with high TMB. As TMB is used in clinical decision-making, generalizability to a variety of real-world settings is a prerequisite for its validity and utility as a biomarker. Leaving aside the issue of accurate estimation of TMB, it is critical to understand its generalizability as a biomarker across different patient cohorts, as high TMB cutoffs have been established primarily in studies of Caucasian patients of European ancestry. However, the extent to which TMB high classification can be generalized as an accurate biomarker for different patient populations remains unknown.
To address this question, Gusev and Jian Carrot-Zhang of Memorial Sloan-Kettering Cancer Center (co-corresponding author) analyzed more than 2,000 patients with common solid tumors who had undergone ICI therapy genetic ancestors. They assessed clinical outcomes such as overall survival and time to ICI failure. “To our knowledge, this is the largest analysis of the interaction between genetic ancestry, TMB and immunotherapy outcome,” Gusev said.
In two independent clinical cohorts, commonly used pure tumor sequencing panel estimates of TMB overclassified individuals into the TMB-high group, particularly among non-Europeans. This bias was especially pronounced in patients of Asian or African ancestry. According to the results, misclassification with high TMB is expected to affect 21% of patients of European ancestry, compared with 37% and 44% of affected patients of Asian or African ancestry, respectively.
“If this holds true in the general patient population, it will have a significant impact on treatment choices for many patients,” Gusev said, “It is important to note that this is purely a technical bias. This study proposes a method for correcting tumor TMB estimates, as well as a widely applicable correction calculation method.”
As a proof-of-concept, the researchers tested the TMB recalibration method in non-small cell lung cancer patients treated with ICI.
“This does not mean that TMB should not be used as a biomarker in individuals of non-European ancestry, but it does mean that more research and data collection is needed to determine use in optimizing treatment Precise thresholds for outcomes,” Gusev said. “We also hope this underscores the importance of assessing the accuracy of biomarkers in different populations.”
Further analysis showed that changes in the MGA gene were associated with longer overall survival and time to ICI failure in Europeans, not with outcomes in Africans, and with worse outcomes in Asians. “Our observation of ancestry-specific effects in some individual driver genes suggests that this phenomenon may not be unique to TMB, but also applies to individual mutations and has implications for other targeted therapies,” Gusev said.
However, an important limitation of the study was the small sample size of non-Europeans in both groups of researchers. “Accelerating the collection of data and results from these populations is critical so that we can better understand how TMB and other biomarkers can effectively generalize to all patients,” Gusev said. “The sample size limited us to study more. Cancer types, individual genome alterations and the ability for more population-specific particle effects—all of which could yield important additional insights.”
Read the original paper: https://www.cell.com/cancer-cell/fulltext/S1535-6108(22)00386-5
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