Evidence map›Paper›PMID 41049426›Full record

SynthesisInternational journal of medical sciences2025

Plasma Proteome Profiling Identifies Biomarkers and Potential Drug Targets for Non-Small Cell Lung Cancer.

Minghui Zhao, Xiaoke Di, Yucui Zhao

Abstract readMeta-Analysis
In one paragraph

Synthesis in International journal of medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Minghui ZhaoDepartment of Radiation Oncology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Xiaoke DiDepartment of Radiation Oncology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Yucui ZhaoDepartment of Radiation Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC), as one of the most commonly diagnosed cancers globally, requires expedited identification of new drug targets. We conducted proteome-wide MR using genetic data for 4,853 plasma proteins. Summary-level data on lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) were extracted from GWAS meta-analyses (11,273 and 7,426 cases, respectively) and FinnGen cohort (1,590 and 1,510 cases, respectively). We genetically identified eight proteins with a causal role in the etiology of NSCLC. Lower levels of five proteins (CDH17, CXADR, FAM3D, POGLUT3, SFTPB) and higher levels of two proteins (CEACAM5, KLK1) were linked to increased LUAD risk, while higher CD14 levels were associated with elevated LUSC risk. Two proteins, POGLUT3 and SFTPB were validated through Bayesian colocalization. One protein SFTPB was identified using SMR and HEIDI tests. Bidirectional MR found no reverse causality. The primary findings were validated through scRNA-seq, GeneMANIA, GO analysis, druggability assessments and PheWAS analysis. These protein-coding genes are primarily expressed in epithelial cells, macrophages, monocytes, and endothelial cells. Furthermore, CEACAM5, KLK1, and CD14 correspond to existing drugs. These proteins may deepen our comprehension of the etiology and could serve as appealing novel biomarkers and drug targets for NSCLC management.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorCarcinoma, Non-Small-Cell LungLung NeoplasmsProteomeCarcinoma, Squamous CellGenome-Wide Association StudyHumansBiomarkers, TumorProteomebiomarkerdrug targetnon-small cell lung cancer.proteome-wide Mendelian randomization

Identifiers

PMID41049426
PMCPMC12492361

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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.