Evidence map›Paper›PMID 42681916›Full record

ArticleChemical biology & drug design2026

Integrative Multi-Omics Analysis Identifies Thrombosis-Associated Molecular Features Linked to Germline Susceptibility and Immune Cell Communication in Gastric Cancer.

Xiaogang Lu, Lin Sun, Fujun Jin, Biao Cheng, Ying Huang, Yuzhu Tang, Xiaolong Nie, Feng Gao

Abstract read
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Article in Chemical biology & drug design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiaogang LuDepartment of Emergency, Xinqiao Hospital, Army Medical University, Chongqing, China.
Lin SunDepartment of Gastroenterology, Chongqing Southeast Hospital, Chongqing, China.
Fujun JinDepartment of Oncology, Chongqing Southeast Hospital, Chongqing, China.
Biao ChengDepartment of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, China.
Ying HuangDepartment of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, China.
Yuzhu TangDepartment of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, China.
Xiaolong NieDepartment of Radiology, Yunyang County Maternal and Child Health Hospital, Chongqing, China.
Feng GaoDepartment of Anesthesiology, People's Hospital of Fengjie County, Chongqing, China.ORCID https://orcid.org/0009-0006-7314-7638

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence indicates that coagulation-related molecular programs are associated with thrombosis, tumor progression, and molecular dysregulation in gastric cancer (GC). However, thrombosis-associated molecular features in GC and their potential links to inherited susceptibility remain insufficiently understood. Integrated analyses of transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were performed to identify thrombosis-associated genes and establish a machine learning-based prognostic signature. Genome-wide association study (GWAS), expression quantitative trait loci (eQTL), transcriptome-wide association study (TWAS), and Mendelian randomization (MR) analyses were conducted to investigate susceptibility-associated transcriptional programs in GC. Functional assays were used to evaluate candidate genes associated with malignant phenotypes. Single-cell RNA sequencing (scRNA-seq) and cell-cell communication analyses were further performed to characterize cell-type-specific expression patterns and potential intercellular interactions. A total of 22 differentially expressed thrombosis-associated genes were identified, and a prognostic signature comprising 14 genes was established. The signature stratified patients into high- and low-risk groups and showed prognostic performance in both the training and validation cohorts. Integrative GWAS, eQTL, and TWAS analyses identified susceptibility-associated transcriptional programs that were positively correlated with the thrombosis-associated risk score. Silencing ACTN2 and CRYAB significantly reduced GC cell migration and invasion. scRNA-seq analysis revealed relatively high CRYAB expression in neutrophils, and CellChat analysis suggested potential neutrophil-B cell interactions involving COLLAGEN-related signaling. This integrative multi-omics study identified a thrombosis-associated molecular signature linked to prognosis and germline susceptibility-associated transcriptional programs in GC. ACTN2 and CRYAB may represent candidate genes associated with GC cell migration and invasion, while single-cell analysis suggested potential immune-related communication features.

Indexed as

Cell CommunicationStomach NeoplasmsThrombosisCell Line, TumorGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultiomicsQuantitative Trait LociACTN2CRYABgastric cancergermline susceptibilitythrombosis‐associated molecular signature

Identifiers

PMID42681916
PMCPMC13534880

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