ArticleHereditas2025
Exploring the association between rheumatoid arthritis and non-small cell lung cancer risk: a transcriptomic and drug target-based analysis.
Article in Hereditas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Beyond Comorbidity: Pulmonary Adenocarcinoma in a Patient with Rheumatoid Arthritis-A Case Report and Literature Review.Life (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundNon-small cell lung cancer (NSCLC) is a common subtype of lung cancer that has received considerable attention for its potential association with rheumatoid arthritis (RA). However, current understanding of the relationship between RA and NSCLC risk remains limited and in-depth studies of molecular mechanisms are lacking.
methodsWe obtained transcriptomic data of NSCLC from the Gene Expression Omnibus (GEO) database and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differential genes. We then used Mendelian randomisation (MR) analysis to explore the causal relationship between RA and NSCLC, but the results showed no direct causal relationship between RA and NSCLC. In light of this finding, we shifted our research focus to investigate the effect of RA therapeutics on NSCLC risk. A drug-targeted MR analysis of drugs available for the treatment of RA was performed by searching for drugs that target NSCLC differential genes associated with RA.
resultsWe found that several of the drugs corresponding to NSCLC differential genes associated with RA are used to treat RA. By drug-targeted MR analysis of drugs, we found that some drugs do have an effect on the risk of developing NSCLC, increasing the risk of developing NSCLC.
conclusionThis study employed transcriptomic analysis and MR of drug targets to elucidate the potential correlation between RA and the risk of developing NSCLC. The identification of NSCLC differentially expressed genes associated with RA and their drug targets has provided new perspectives for an in-depth understanding of the pathogenesis of NSCLC. Furthermore, an additional immune infiltration analysis demonstrated that, in NSCLC tissues, the infiltration levels of specific immune cell subpopulations, including regulatory T cells (Tregs), activated natural killer cells (NK cells) and unpolarised macrophages (M0), exhibited notable differences. These findings emphasise the significant role that immune cell interactions between RA and NSCLC may play in disease progression. Furthermore, through the analysis of validation histology, we have further confirmed the potential role of differential genes associated with RA in the development of NSCLC. The expression levels of these genes demonstrated significant differences in NSCLC samples, providing a basis for possible future therapeutic targets and biomarkers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.