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AuthorSekaran, Karthik
AuthorVarghese, Rinku Polachirakkal
AuthorZayed, Hatem
AuthorEl Allali, Achraf
AuthorGeorge Priya Doss, C.
Available date2024-01-29T11:14:45Z
Publication Date2023-09-23
Publication NameMedical Oncology
Identifierhttp://dx.doi.org/10.1007/s12032-023-02174-8
CitationSekaran, K., Varghese, R. P., Zayed, H., El Allali, A., & George Priya Doss, C. (2023). Single-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer. Medical Oncology, 40(10), 305.
ISSN1357-0560
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85171855522&origin=inward
URIhttp://hdl.handle.net/10576/51327
AbstractThe 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.
SponsorIndian Council of Medical Research - funding number: 2021-5570, 2021-6359, BMI/12(13)/2021, VIR/COVID-19/31/2021/ECD-I
Languageen
PublisherSpringer Nature
SubjectDrug–gene interaction
Gastric cancer
Ligand–receptor interaction
Oncogenes
Single-cell RNA-seq analysis
Survival analysis
Trajectory inference
TitleSingle-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer
TypeArticle
Issue Number10
Volume Number40
ESSN1559-131X
dc.accessType Full Text


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