Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and Prognosis

16 Mar 2022

Abstract excerpt

Gastric cancer has remained in the top five cancers for over ten years, both in terms of incidence and mortality due to the shortage of biomarkers for disease follow-up and effective therapies. Aiming to fill this gap, we performed a bioinformatics assessment on our data and two additional GEO microarray profiles, followed by a deep analysis of the 40 differentially expressed genes identified. PPI network...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ferroptosis and cancer prognosis
Share to Galectins and Cancer Biology
Share to Peptidase Inhibition and Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 35328635
DOI: 10.3390/ijms23063214

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and PrognosisPMID 35328635Read ↗

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosisSemantic proximity Read ↗

Collagen family genes and related genes might be associated with prognosis of patients with gastric cancer: an integrated bioinformatics analysis and experimental validationSemantic proximity Read ↗

Bioinformatics analysis identifies COL1A1, THBS2 and SPP1 as potential predictors of patient prognosis and immunotherapy response in gastric cancerSemantic proximity Read ↗

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic AnalysisSemantic proximity Read ↗

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysisSemantic proximity Read ↗

Identification of Potential Biomarkers and Therapy Targets involved in Gastric Cancer Using Bioinformatics AnalysisSemantic proximity Read ↗

CTGF, FN1, IL-6, THBS1, and WISP1 genes and PI3K-Akt signaling pathway as prognostic and therapeutic targets in gastric cancer identified by gene network modelingSemantic proximity Read ↗

Identification of potential hub genes of gastric cancerSemantic proximity Read ↗

Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics AnalysisSemantic proximity Read ↗

Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancerSemantic proximity Read ↗

Identification of hub genes correlated with the pathogenesis and prognosis of gastric cancer via bioinformatics methodsSemantic proximity Read ↗

Identifying Diagnostic and Prognostic Biomarkers and Candidate Therapeutic Drugs of Gastric Cancer Based on Transcriptomics and Single-Cell Sequencing.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.