Tumor mutational burden assessed by a targeted NGS assay to predict clinical benefit from immune checkpoint inhibitors in non-small cell lung cancer.

person Sacha Rothschild Medical Oncology, Department of Internal Medicine, University Hospital Basel, Basel, Switzerland info_outline Sacha Rothschild, Ilaria Alborelli, Katharina Leonards, Laura P Leuenberger, Spasenija Savic Prince, Kirsten D Mertz, Severin Poechtrager, Alfred Zippelius, Heinz Philipp Laubli, Jasmin Haegele, Markus Tolnay, Lukas Bubendorf, Luca Quagliata, Philip Jermann

Authors person Sacha Rothschild Medical Oncology, Department of Internal Medicine, University Hospital Basel, Basel, Switzerland info_outline Sacha Rothschild, Ilaria Alborelli, Katharina Leonards, Laura P Leuenberger, Spasenija Savic Prince, Kirsten D Mertz, Severin Poechtrager, Alfred Zippelius, Heinz Philipp Laubli, Jasmin Haegele, Markus Tolnay, Lukas Bubendorf, Luca Quagliata, Philip Jermann Organizations Medical Oncology, Department of Internal Medicine, University Hospital Basel, Basel, Switzerland, Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland, Institute of Pathology, Cantonal Hospital Baselland, Liestal, Liestal, Switzerland, Department Oncology, Hematology and Immunotherapy, Cantonal Hospital Baselland, Liestal, Liestal, Switzerland, Novartis Institutes for BioMedical Research, Basel, Switzerland, Thermo Fisher Scientific, Zug, Switzerland Abstract Disclosures Research Funding Other Pharmaceutical/Biotech Company Background: In non-small cell lung cancer (NSCLC) immune checkpoint inhibitors (ICIs) significantly improve overall survival (OS). Tumor mutational burden (TMB) has emerged as a predictive biomarker for patients treated with ICIs. Here we evaluated the predictive power of TMB measured through / by the Oncomine Tumor Mutational Load (TML - Thermo Fisher Scientific) targeted sequencing assay in 71 NSCLC patients treated with ICIs. Methods: TMB was assessed retrospectively in 71 metastatic NSCLC patients receiving ICI therapy. Clinical data (RECIST 1.1) were collected and patients were characterized as either having durable clinical benefit (DCB) or no durable benefit (NDB). Additionally, genetic alterations and PD-L1 expression were assessed and compared with TMB and response rate. Results: TMB was significantly higher in patients with DCB compared to patients with NDB (median TMB = 9.2 versus 5.3 mutations/Mb, Mann-Whitney p = 0.014). 70% of patients with high TMB (cutoff = 3rd tertile, TMB ≥ 9.2) were responders (DCB) compared to 29% of patients with low TMB (cutoff = 1st tertile, TMB ≤ 4.5). TMB-high patients showed significantly longer progression-free survival (PFS) and OS (log rank test, p = .0030 for PFS and 0 .0375 for OS, respectively). Combining PD-L1 expression and TMB value increased the predictive power of TMB. Conclusions: Our results show that the TML panel is an effective tool to stratify patients for ICI treatment. We believe that a combination of biomarkers will maximize the precision of patient selection.