Next Article in Journal
Betulin Suppresses Osteoclast Formation via Down-Regulating NFATc1
Next Article in Special Issue
Diagnosing Lung Cancer: The Complexities of Obtaining a Tissue Diagnosis in the Era of Minimally Invasive and Personalised Medicine
Previous Article in Journal
Ganoderma lucidum Ameliorates Non-Alcoholic Steatosis by Upregulating Energy Metabolizing Enzymes in the Liver
Previous Article in Special Issue
Immunotherapy in Non-Small Cell Lung Cancer: Shifting Prognostic Paradigms
Open AccessReview

An Update on Predictive Biomarkers for Treatment Selection in Non-Small Cell Lung Cancer

Sydney Medical School, The University of Sydney, Sydney 2006, Australia
Chris O’Brien Lifehouse, Sydney 2050, Australia
Asbestos Diseases Research Institute (ADRI), Sydney 2139, Australia
Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Sydney 2050, Australia
School of Medicine, Western Sydney University, Sydney 2560, Australia
Author to whom correspondence should be addressed.
J. Clin. Med. 2018, 7(6), 153;
Received: 17 May 2018 / Revised: 12 June 2018 / Accepted: 12 June 2018 / Published: 15 June 2018
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. View Full-Text
Keywords: NSCLC; predictive biomarkers; targeted therapy; immunotherapy NSCLC; predictive biomarkers; targeted therapy; immunotherapy
MDPI and ACS Style

Ahmadzada, T.; Kao, S.; Reid, G.; Boyer, M.; Mahar, A.; Cooper, W.A. An Update on Predictive Biomarkers for Treatment Selection in Non-Small Cell Lung Cancer. J. Clin. Med. 2018, 7, 153.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop