Single-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer.
Drug–gene interaction
Gastric cancer
Ligand–receptor interaction
Oncogenes
Single-cell RNA-seq analysis
Survival analysis
Trajectory inference
Journal
Medical oncology (Northwood, London, England)
ISSN: 1559-131X
Titre abrégé: Med Oncol
Pays: United States
ID NLM: 9435512
Informations de publication
Date de publication:
23 Sep 2023
23 Sep 2023
Historique:
received:
01
08
2023
accepted:
28
08
2023
medline:
25
9
2023
pubmed:
23
9
2023
entrez:
23
9
2023
Statut:
epublish
Résumé
The intricate association of oncogenic markers negatively impacts accurate gastric cancer diagnosis and leads to the proliferation of mortality rate. Molecular heterogeneity is inevitable in determining gastric cancer's progression state with multiple cell types involved. Identification of pathogenic gene signatures is imperative to understand the disease's etiology. This study demonstrates a systematic approach to identifying oncogenic gastric cancer genes linked with different cell types. The raw counts of adjacent normal and gastric cancer samples are subjected to a quality control step. The dimensionality reduction and multidimensional clustering are performed using Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) techniques. The adjacent normal and gastric cancer sample cell clusters are annotated with the Human Primary Cell Atlas database using the "SingleR." Cellular state transition between the distinct groups is characterized using trajectory analysis. The ligand-receptor interaction between Vascular Endothelial Growth Factor (VEGF) and cell clusters unveils crucial molecular pathways in gastric cancer progression. Chondrocytes, Smooth muscle cells, and fibroblast cell clusters contain genes contributing to poor survival rates based on hazard ratio during survival analysis. The GC-related oncogenic signatures are isolated by comparing the gene set with the DisGeNET database. Twelve gastric cancer biomarkers (SPARC, KLF5, HLA-DRB1, IGFBP3, TIMP3, LGALS1, IGFBP6, COL18A1, F3, COL4A1, PDGFRB, COL5A2) are linked with gastric cancer and further validated through gene set enrichment analysis. Drug-gene interaction found PDGFRB, interacting with various anti-cancer drugs, as a potential inhibitor for gastric cancer. Further investigations on these molecular signatures will assist the development of precision therapeutics, promising longevity among gastric cancer patients.
Identifiants
pubmed: 37740827
doi: 10.1007/s12032-023-02174-8
pii: 10.1007/s12032-023-02174-8
doi:
Substances chimiques
Receptor, Platelet-Derived Growth Factor beta
EC 2.7.10.1
Vascular Endothelial Growth Factor A
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
305Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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