Abstract
Most lung cancer patients are diagnosed at an advanced stage, limiting their treatment options with very low response rate. Lung cancer is the most common cause of cancer death worldwide. Therapies that target driver gene mutations (e.g. EGFR, ALK, ROS1) and checkpoint inhibitors such anti-PD-1 and PD-L1 immunotherapies are being used to treat lung cancer patients. Identification of correlations between driver mutations and PD-L1 expression will allow for the best management of patient treatment. 851 cases of non-small cell lung cancer cases were profiled for the presence of biomarkers EGFR, KRAS, BRAF, and PIK3CA mutations by SNaPshot/sizing genotyping. Immunohistochemistry was used to identify the protein expression of ALK and PD-L1. Total PD-L1 mRNA expression (from unsorted tumor samples) was quantified by RT-qPCR in a sub-group of the cohort to assess its correlation with PD-L1 protein level in tumor cells. Statistical analysis revealed correlations between the presence of the mutations, PD-L1 expression, and the pathological data. Specifically, increased PD-L1 expression was associated with wildtype EGFR and vascular invasion, and total PD-L1 mRNA levels correlated weakly with protein expression on tumor cells. These data provide insights into driver gene mutations and immune checkpoint status in relation to lung cancer subtypes and suggest that RT-qPCR is useful for assessing PD-L1 levels.
Highlights
Lung cancer is a leading cause of cancer death, killing more people than breast, prostate, and colorectal cancers combined [1]
The frequency of specific gene mutations was investigated; of 851 lung cancer patients, 552 were lung adenocarcinoma, in which specific gene mutations were identified in 270 patients
PD-L1 expression in lung cancer has been reported as biomarker that predicts a response to PD-1 inhibitors
Summary
Lung cancer is a leading cause of cancer death, killing more people than breast, prostate, and colorectal cancers combined [1]. More than 50% of lung cancer patients die within one year of diagnosis [1]. The advancements in molecular profiling in lung cancer have provided powerful tools for implementing new treatments, such as EGFR and ALK tyrosine kinase inhibitors. Patients with metastatic lung adenocarcinoma harbouring EGFR mutations or ALK rearrangements experience better quality of life, lower toxicity, and encouraging outcomes when they receive tyrosine kinase inhibitors [2]. A large proportion of lung cancers do not exhibit targetable driver mutations that have approved drugs by the Food and Drug Administration (FDA). Patients with KRAS mutations, the most common driver mutations in lung cancer, demonstrate low response to targeted therapies [4]
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