4.6 Article

Maximum Somatic Allele Frequency-Adjusted Blood-Based Tumor Mutational Burden Predicts the Efficacy of Immune Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer

Journal

CANCERS
Volume 14, Issue 22, Pages -

Publisher

MDPI
DOI: 10.3390/cancers14225649

Keywords

non-small-cell lung cancer; NSCLC; maximum somatic allele frequency; MSAF; tumor mutation burden; TMB; immune checkpoint inhibitors; ICIs

Categories

Funding

  1. National Key Research and Development Project [2022YFC2505000, 2022YFC2505004]
  2. Chinese Academy of Medical Sciences Key Lab of Translational Research on Lung Cancer [2018PT31035]
  3. National Natural Sciences Foundation of China [81871889, 82072586, 82141117]
  4. Beijing Hope Run Special Fund of Cancer Foundation of China [LC2021R04]
  5. Beijing Municipal Administration of Hospitals Incubating Program [PX2020045]
  6. Capital Health Research and Development of Special Fund [2022-2-1023]

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Recent studies have shown the unstable prediction ability of blood-based tumor mutational burden (bTMB) in predicting the response to immune checkpoint inhibitors in non-small cell lung cancer patients. This study developed a novel approach, MSAF-adjusted bTMB (Ma-bTMB), to better select beneficiaries of immune checkpoint inhibitors based on the integration of maximum somatic allele frequency (MSAF). The results demonstrated that Ma-bTMB effectively identified beneficiaries of immune checkpoint inhibitors in patients with advanced NSCLC.
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. 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.

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