LAUSR

Simple Summary Recent studies exhibited the unstable prediction ability of blood-based tumor mutational burden (bTMB) when predicting the response of immune checkpoint inhibitors (ICIs) therapy in patients with non-small cell lung cancer (NSCLC). Circulating tumor DNA (ctDNA) abundance, usually represented by maximum somatic allele frequency (MSAF), was one possible confounding factor influencing bTMB ability in ICIs response prediction. We herein developed a novel approach to optimize the calculation of bTMB by integrating MSAF, namely, MSAF-adjusted bTMB (Ma-bTMB), to better select beneficiaries of ICIs. Our present results showed that this novel non-invasive biomarker could reduce the confounding effect of MSAF and ITH on bTMB calculation and effectively identify beneficiaries of ICIs in patients with advanced NSCLC, warranting future clinical trials. Abstract Introduction: Recent studies exhibited the unstable prediction ability of blood-based tumor mutational burden (bTMB) when predicting the response of immune checkpoint inhibitors (ICIs) therapy in patients with non-small cell lung cancer (NSCLC). Circulating tumor DNA (ctDNA) abundance, usually represented by maximum somatic allele frequency (MSAF), was one possible confounding factor influencing bTMB ability in ICIs response prediction. Methods: MSAF-adjusted bTMB (Ma-bTMB) was established and validated in patients with advanced NSCLC among Geneplus Cancer Genome Database (GCGD, n = 1679), Zhuo (n = 35), Wang (n = 45), POPLAR (NCT01903993, n = 211) and OAK (NCT02008227, n = 642) cohorts. Results: MSAF demonstrated a modest positive correlation with bTMB and a negative one with survival benefit. Improved survival outcomes of ICIs therapy have been observed among patients with high-Ma-bTMB compared to those with low-Ma-bTMB in Zhuo and Wang cohorts. In addition, compared to low-Ma-bTMB, high-Ma-bTMB was associated with more positive clinical benefits from ICIs therapy than chemotherapy both in POPLAR and OAK cohorts. Further exploration suggested that Ma-bTMB could precisely identify more potential ICIs beneficiaries compared to bTMB and LAF-bTMB, complementary to PD-L1 expression. Conclusions: We developed Ma-bTMB, a convenient, readily available, non-invasive predictive biomarker effectively differentiates beneficiaries of ICIs therapy in advanced NSCLC, warranting future clinical trials.