Abstract

Lung cancer has long been the leading cause of cancer deaths in the United States. Lung cancer has a poor prognosis, and our understanding of who will maximally benefit from different therapies is incomplete. This article discusses genetic biomarkers that may help in this regard. From origin until February 25, 2022, PubMed database was searched for terms "non-small cell lung cancer", "genomics" and "biomarker", with special attention paid to literature published within the past 10 years. Search was language restricted to English. Additional literature was identified through hand searches of the references of retrieved literature. The most robustly described biomarkers for non-small cell lung cancer (NSCLC) are assessment of specific gene mutations. These are currently used in clinical practice for both prediction and prognostication. Abnormal mutation status of STK11/LKB1 and KEAP1-NFE2L2 are associated with poor response to radiotherapy (RT), and STK11/LKB1 is further associated with resistance to PD-L1 immunotherapy. Abnormal TP53 is associated with decreased benefit from cisplatin in squamous cell carcinoma (SCC). In terms of prognostication, RB1 mutations are associated with decreased overall survival (OS) in NSCLC and KEAP1-NFE2L2 mutations are associated with increased local recurrence (LR).Additional work has focused on gene expression levels, as well as analysis of genetic factors and signaling molecules affecting the tumor microenvironment (TME). High levels of Rad51c and NFE2L2 are associated with resistance to chemotherapy, and high Rad51c levels are further associated with resistance to RT. High nuclear expression of β-catenin has additionally been associated with poor RT response. Further, there is increasing evidence that some long non-coding RNAs (lncRNAs) may play a crucial role in regulation of tumor radiosensitivity. Much of this work has had promising early results but will require further validation before routine clinical use. Finally, there is evidence that quantification of some signaling molecules and microRNAs (miRNAs) may have clinical utility in predicting adverse outcomes in RT. An improved understanding of tumor genetics in NSCLC has led to the development of targeted therapies and improved prognostication. As more work is done in this field, more and more genetic biomarkers will become candidates for clinical use. Much work will be required to validate these findings in the clinical setting.

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