» Articles » PMID: 39263038

Identifying Genetically-supported Drug Repurposing Targets for Non-small Cell Lung Cancer Through Mendelian Randomization of the Druggable Genome

Overview
Date 2024 Sep 12
PMID 39263038
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Lung cancer is responsible for most cancer-related deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of cases. Targeted therapy has made promising advancements in systemic treatment for NSCLC over the last two decades, but inadequate drug targets with clinically proven survival benefits limit its universal application in clinical practice compared to chemotherapy and immunotherapy. There is an urgent need to explore new drug targets to expand the beneficiary group. This study aims to identify druggable genes and to predict the efficacy and prognostic value of the corresponding targeted drugs in NSCLC.

Methods: Two-sample mendelian randomization (MR) of druggable genes was performed to predict the efficacy of their corresponding targeted therapy for NSCLC. Subsequent sensitivity analyses were performed to assess potential confounders. Accessible RNA sequencing data were incorporated for subsequent verifications, and Kaplan-Meier survival curves of different gene expressions were used to explore the prognostic value of candidate druggable genes.

Results: MR screening encompassing 4,863 expression quantitative trait loci (eQTL) and 1,072 protein quantitative trait loci (pQTL, with 453 proteins overlapping) were performed. Seven candidate druggable genes were identified, including , , and for lung adenocarcinoma, and , and for lung squamous cell carcinoma. The results were validated by further transcriptomic investigations.

Conclusions: Drugs targeting genetically supported genomes are considerably more likely to yield promising efficacy and succeed in clinical trials. We provide compelling genetic evidence to prioritize drug development for NSCLC.

References
1.
King E, Davis J, Degner J . Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLoS Genet. 2019; 15(12):e1008489. PMC: 6907751. DOI: 10.1371/journal.pgen.1008489. View

2.
Siegel R, Miller K, Fuchs H, Jemal A . Cancer statistics, 2022. CA Cancer J Clin. 2022; 72(1):7-33. DOI: 10.3322/caac.21708. View

3.
Kamat M, Blackshaw J, Young R, Surendran P, Burgess S, Danesh J . PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019; 35(22):4851-4853. PMC: 6853652. DOI: 10.1093/bioinformatics/btz469. View

4.
Gill D, Cameron A, Burgess S, Li X, Doherty D, Karhunen V . Urate, Blood Pressure, and Cardiovascular Disease: Evidence From Mendelian Randomization and Meta-Analysis of Clinical Trials. Hypertension. 2020; 77(2):383-392. PMC: 7803439. DOI: 10.1161/HYPERTENSIONAHA.120.16547. View

5.
Ali S, Dunmore H, Karres D, Hay J, Salmonsson T, Gisselbrecht C . The EMA Review of Mylotarg (Gemtuzumab Ozogamicin) for the Treatment of Acute Myeloid Leukemia. Oncologist. 2019; 24(5):e171-e179. PMC: 6516123. DOI: 10.1634/theoncologist.2019-0025. View