Evidence map›Paper›PMID 40853920›Full record

SynthesisPLoS genetics2025

Circulating proteins associated with histological subtypes of lung cancer from genetic and population-based perspectives.

Zhangyan Lyu, Guojin Si, Mengbo Xing, Wenxuan Li, Ximin Gao, Meng Wang, Fengju Song, Kexin Chen

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Zhangyan LyuDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Guojin SiDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Mengbo XingDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Wenxuan LiDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Ximin GaoDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.
Meng WangDepartment of Lung Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China.
Fengju SongDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.ORCID https://orcid.org/0000-0003-1542-0828
Kexin ChenDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, accounting for millions of deaths annually. Its major subtypes-lung squamous carcinoma (LUSC), lung adenocarcinoma, and small-cell LC-exhibit distinct risk factors and genetic susceptibilities, necessitating the use of subtype-specific biomarkers. Two-sample Mendelian randomization (MR) analyses were conducted using protein quantitative trait loci from the UK Biobank Pharma Proteomics Project and deCODE datasets. A robust analytical framework, including reverse MR, meta-analysis, summary-data-based MR tests, and colocalization, cisMR-cML, MR.CUE and phenotype scanning analyses were used to identify proteins associated with LC risk. We conducted a systematic review to contextualize our research findings. Follow-up analyses, including pathway enrichment, protein-protein interaction network analysis, and druggability evaluations, were used to explore the mechanisms and therapeutic potential of the identified proteins. Significant proteins were validated using population-level proteomic data from the UK Biobank (UKB). The results showed that twenty-five proteins were significantly associated with LC or its subtypes, including 15 novel findings. 60S ribosomal protein L14 (RPL14) and advanced glycosylation end-product-specific receptor (AGER) emerged as the strongest discovery, demonstrating consistent and significant associations across both MR and population-level analyses. RPL14 exhibited positive associations with overall LC risk (MR_meta: odds ratio [OR]: 2.012, 95% confidence interval [CI]: 1.297-3.119; UKB: OR: 1.509, 95% CI: 1.015-2.244). Similarly, AGER showed significant protective effects against LUSC risk (MR_meta: OR: 0.572, 95%CI: 0.368-0.889; UKB: OR: 0.366, 95% CI: 0.158-0.850). Pathway analysis revealed the involvement of these proteins in immune regulation and tumorigenesis. Among the 13 identified druggable targets, RPL14 and AGER showed therapeutic potential as approved or investigational drugs targeting these proteins. These findings offer new insights into the pathogenesis of LC and potential therapeutic targets.

Indexed as

Biomarkers, TumorCarcinoma, Squamous CellLung NeoplasmsGenetic Predisposition to DiseaseHumansMendelian Randomization AnalysisProtein Interaction MapsProteomicsQuantitative Trait LociRibosomal ProteinsRisk FactorsUnited KingdomBiomarkers, TumorRibosomal Proteins

Identifiers

PMID40853920
PMCPMC12377608

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Registered trials

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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.