Autor: |
Akram Alwithenani, Drew Bethune, Mathieu Castonguay, Arik Drucker, Gordon Flowerdew, Marika Forsythe, Daniel French, John Fris, Wenda Greer, Harry Henteleff, Mary MacNeil, Paola Marignani, Wojciech Morzycki, Madelaine Plourde, Stephanie Snow, Paola Marcato, Zhaolin Xu |
Jazyk: |
angličtina |
Rok vydání: |
2021 |
Předmět: |
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Zdroj: |
PLoS ONE, Vol 16, Iss 5, p e0251080 (2021) |
Druh dokumentu: |
article |
ISSN: |
1932-6203 |
DOI: |
10.1371/journal.pone.0251080 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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