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An Update on Predictive Biomarkers for Treatment Selection in Non-Small Cell Lung Cancer
Tamkin Ahmadzada1, Steven Kao2,3,4, Glen Reid5,6
1Sydney Medical School, The University of Sydney, Sydney 2006, Australia. tahm4852@uni.sydney.edu.au.
Abstract:
It is now widely established that management of lung cancer is much more complex and cannot be centered on the binary classification of small-cell versus non-small cell lung cancer (NSCLC). Lung cancer is now recognized as a highly heterogeneous disease that develops from genetic mutations and gene expression patterns, which initiate uncontrolled cellular growth, proliferation and progression, as well as immune evasion. Accurate biomarker assessment to determine the mutational status of driver mutations such as EGFR, ALK and ROS1, which can be targeted by specific tyrosine kinase inhibitors, is now essential for treatment decision making in advanced stage NSCLC and has shifted the treatment paradigm of NSCLC to more individualized therapy. Rapid advancements in immunotherapeutic approaches to NSCLC treatment have been paralleled by development of a range of potential predictive biomarkers that can enrich for patient response, including PD-L1 expression and tumor mutational burden. Here, we review the key biomarkers that help predict response to treatment options in NSCLC patients.
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