ArticleBritish journal of cancer2023
Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants.
Article in British journal of cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Causal association between plasma proteins and lung adenocarcinoma: a two-sample mendelian randomization study.BMC pulmonary medicine · 2025Pooled it
- Coordinated Multicellular Immune Programs and Drug Targets Revealed by Single-Cell Analysis in Driver-Mutated NSCLC.International journal of molecular sciences · 2026Article
- Machine learning-based proteogenomic data modeling identifies circulating plasma biomarkers for early detection of lung cancer.Communications medicine · 2026Article
- Integrative Multi-omics Analysis and Mendelian Randomization Reveal Potential Therapeutic Targets and their Stratification in Lung Squamous Cell Carcinoma.Current medicinal chemistry · 2026Article
- CoCo-ST detects global and local biological structures in spatial transcriptomics datasets.Nature cell biology · 2025Article
- A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Loci and Genes for Lung Cancer Risk.Cancer medicine · 2025Article
- Post-genome-wide association study dissects genetic vulnerability and risk gene expression of Sjögren's disease for cardiovascular disease.Journal of translational medicine · 2025Article
- Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma.Journal of translational medicine · 2024Article
- Proteome-wide Mendelian randomization identifies causal plasma proteins in lung cancer.iScience · 2024Article
- Involvement ofJournal of inflammation research · 2024Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPlasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer.
methodsWe investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer.
resultsNine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses.
conclusionIdentification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.
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