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Germline variants and impact on lung cancer outcomes following chemotherapy: A systematic review
Abdullah R Al-Matrafi1, Mark A Baxter2, Ewan R Pearson2
1School of Medicine, University of Dundee, Dundee, UK; Department of Pharmacology, College of Clinical Pharmacy, Imam Abdul Rahman Bin Faisal University, Dammam, Saudi Arabia.
Background:
Lung cancer is the primary cause of cancer deaths in the UK and globally, and the main subtypes are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Many treatment options are available, with platinum-based chemotherapy being a key component for many patients. However, variation in survival outcomes exists among individuals of European ancestry, which makes it important to identify germline genetic variants that help guide decision-making and optimise patient treatment and outcomes.
Method:
A systematic literature search was conducted in PubMed and Web of Science for lung cancer studies investigating the impact of germline genetic variants on systemic anti-cancer therapy (SACT) outcomes in populations of European ancestry. The review was conducted according to the Preferred Reporting Items of Systematic Review and Meta-Analysis (PRISMA) and Synthesis without Meta-Analysis (SWiM) guidelines.
Results:
A total of 20 studies were included in the review out of 4469 on NSCLC and SCLC, encompassing 3639 patients. The most thoroughly investigated area was NSCLC treated with platinum-based chemotherapy. Genetic variants associated with overall survival and/or progression-free survival included XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln. For non-platinum-treated NSCLC and SCLC, there was insufficient evidence to conduct a meaningful investigation.
Conclusion:
The XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln variants showed potential associations with survival outcomes among patients of European ancestry with NSCLC after platinum-based chemotherapy. To support clinical implementation, large real-world pharmacogenomics studies stratified by ancestry are needed to overcome statistical power and heterogeneity limitations.
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