Blood Tumor Mutational Burden as a Predictive Biomarker in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC)

Abstract

The cancer-associated mortalities in the world have been linked with lung cancer, and millions of deaths are recorded every year. Non-small cell lung cancer (NSCLC) constitutes about 85 percent of the total lung cancer, and the diagnosis is usually late. The use of immunotherapy, in particular, immune checkpoint inhibitors (ICIs) that serve as programmed death-1 (PD-1) receptor and programmed death ligand-1 (PD-L1), has radically changed the treatment approach of advanced NSCLC over the last ten years. Even after the research proved survival rates of many patients have been improved with the help of immunotherapy, few of them can receive long-term clinical responses. This is why it is necessary to find the credible biomarkers acting as excellent predictors of treatment reaction to optimize therapeutic interventions, and one of them is the amount of the tumor mutational burden (TMB), which is the sum of somatic mutations per megabase of DNA in tumor cells. The traditional TMB assay technique utilizes tumor tissue using whole-exome sequencing (WES), and it can be regarded as the gold standard of the mutation detection technique. Tissue biopsies are, however, linked with the following shortcomings: they are invasive, heterogeneous, and an adequate supply of tissues is not available. To address these issues, blood-based tumor mutational burden (bTMB) has been developed as a minimally invasive biomarker, which is grounded on circulating tumor DNA (ctDNA) in plasma. Recent studies suggest that high bTMB levels are predictive of better patient clinical outcomes with immune checkpoint inhibitors. The provided review article will offer an in-depth discussion of the biological foundations of bTMB, its significance as a forecasting biomarker of immunotherapy in advanced NSCLC, the use of bTMB involving clinical implications and benefits, obstacles to its utilization, potential limitations to its administration, and the perspectives of its application to precision oncology.