Integration of Tumor Mutation Burden and PD-L1 Testing in Routine Laboratory Diagnostics in Non-Small Cell Lung Cancer

Autor: Lukas C. Heukamp, Balázs Jóri, S. Schatz, Eva-Maria Willing, Matthias Kröger, Harry J.M. Groen, Linda Diehl, Stefanie Schmidt, Markus Falk, Hayat Oum El Kheir Ramdani, Frank Griesinger, Markus Tiemann, C. Wesseler, Roopika Menon, Petra Hoffknecht
Přispěvatelé: Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Cancers, 12(6):1685, 1-14. MDPI AG
Cancers
Volume 12
Issue 6
Cancers, Vol 12, Iss 1685, p 1685 (2020)
ISSN: 2072-6694
Popis: In recent years, Non-small cell lung cancer (NSCLC) has evolved into a prime example for precision oncology with multiple FDA-approved &ldquo
precision&rdquo
drugs. For the majority of NSCLC lacking targetable genetic alterations, immune checkpoint inhibition (ICI) has become standard of care in first-line treatment or beyond. PD-L1 tumor expression represents the only approved predictive biomarker for PD-L1/PD-1 checkpoint inhibition by therapeutic antibodies. Since PD-L1-negative or low-expressing tumors may also respond to ICI, additional factors are likely to contribute in addition to PD-L1 expression. Tumor mutation burden (TMB) has emerged as a potential candidate
however, it is the most complex biomarker so far and might represent a challenge for routine diagnostics. We therefore established a hybrid capture (HC) next-generation sequencing (NGS) assay that covers all oncogenic driver alterations as well as TMB and validated TMB values by correlation with the assay (F1CDx) used for the CheckMate 227 study. Results of the first consecutive 417 patients analyzed in a routine clinical setting are presented. Data show that fast reliable comprehensive diagnostics including TMB and targetable alterations are obtained with a short turn-around time. Thus, even complex biomarkers can easily be implemented in routine practice to optimize treatment decisions for advanced NSCLC.
Databáze: OpenAIRE