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Significance of platelet adhesion-related genes in colon cancer based on non-negative matrix factorization-based clustering algorithm.
Chi, Xiao-Jv; Song, Yi-Bei; Liu, Deng-He; Wei, Li-Qiang; An, Xin; Feng, Zi-Zhen; Lan, Xiao-Hua; Lan, Dong; Huang, Chao.
Afiliación
  • Chi XJ; Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, China.
  • Song YB; Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, China.
  • Liu DH; Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, China.
  • Wei LQ; Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, China.
  • An X; The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Feng ZZ; The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Lan XH; The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Lan D; Department of Medical Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Huang C; School of Information and Management, Guangxi Medical University, Nanning, China.
Digit Health ; 9: 20552076231203902, 2023.
Article en En | MEDLINE | ID: mdl-37766908
ABSTRACT

Background:

Although surgical methods are the most effective treatments for colon adenocarcinoma (COAD), the cure rates remain low, and recurrence rates remain high. Furthermore, platelet adhesion-related genes are gaining attention as potential regulators of tumorigenesis. Therefore, identifying the mechanisms responsible for the regulation of these genes in patients with COAD has become important. The present study aims to investigate the underlying mechanisms of platelet adhesion-related genes in COAD patients.

Methods:

The present study was an experimental study. Initially, the effects of platelet number and related genomic alteration on survival were explored using real-world data and the cBioPortal database, respectively. Then, the differentially expressed platelet adhesion-related genes of COAD were analyzed using the TCGA database, and patients were further classified by employing the non-negative matrix factorization (NMF) analysis method. Afterward, some of the clinical and expression characteristics were analyzed between clusters. Finally, least absolute shrinkage and selection operator regression analysis was used to establish the prognostic nomogram. All data analyses were performed using the R package.

Results:

High platelet counts are associated with worse survival in real-world patients, and alternations to platelet adhesion-related genes have resulted in poorer prognoses, based on online data. Based on platelet adhesion-related genes, patients with COAD were classified into two clusters by NMF-based clustering analysis. Cluster2 had a better overall survival, when compared to Cluster1. The gene copy number and enrichment analysis results revealed that two pathways were differentially enriched. In addition, the differentially expressed genes between these two clusters were enriched for POU6F1 in the transcription factor signaling pathway, and for MATN3 in the ceRNA network. Finally, a prognostic nomogram, which included the ALOX12 and ACTG1 genes, was established based on the platelet adhesion-related genes, with a concordance (C) index of 0.879 (0.848-0.910).

Conclusion:

The mRNA expression-based NMF was used to reveal the potential role of platelet adhesion-related genes in COAD. The series of experiments revealed the feasibility of targeting platelet adhesion-associated gene therapy.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Digit Health Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Digit Health Año: 2023 Tipo del documento: Article País de afiliación: China