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Related Concept Videos

Cancer02:18

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

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Targeting Tumor Differentiation Grade-related Genes Prognostic Signature Including COL5A1 Based on Single-cell

Jianming Wei1, Xibo Gao2, Zhufeng Li1

  • 1Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China.

International Journal of Medical Sciences
|May 19, 2025
PubMed
Summary

A new prognostic signature of tumor differentiation grade-related genes was identified in gastric cancer (GC) using single-cell RNA sequencing (scRNA-seq). The gene signature and hub gene COL5A1 show promise as biomarkers for predicting GC prognosis.

Keywords:
B cells memoryCox regressionGastric cancersingle-cell RNA sequencingtumor differentiation grade

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Tumor differentiation grade is a known prognostic factor in gastric cancer (GC).
  • Previous studies highlight the importance of understanding molecular markers for GC prognosis.
  • Single-cell RNA sequencing (scRNA-seq) offers a high-resolution approach to identify novel biomarkers.

Purpose of the Study:

  • To identify a novel prognostic gene signature related to tumor differentiation grade in GC.
  • To discover new potential biomarkers for predicting GC patient outcomes.
  • To validate the identified signature and its associated genes.

Main Methods:

  • Analysis of scRNA-seq profiles from GC patients using the 'seurat' package.
  • Weighted gene co-expression network analysis (WGCNA) to identify tumor differentiation grade modules.
  • Hematoxylin and eosin (H&E) staining for differentiation grade classification and Kaplan-Meier analysis for prognosis.
  • Construction and validation of a tumor differentiation grade-related gene prognostic signature.

Main Results:

  • Identification of cell differentiation, clusters, and marker genes in GC using scRNA-seq.
  • WGCNA revealed tumor differentiation grade module as the most significant.
  • Well-differentiated tumors showed a better prognosis.
  • A validated prognostic signature comprising TNFAIP2, MAGEA3, CXCR4, COL1A1, FN1, VCAN, PXDN, COL5A1, MUC13, and RGS2 was established.
  • The hub gene COL5A1 correlated with various immune cell types in GC.

Conclusions:

  • A novel gene signature associated with tumor differentiation grade in GC has been identified.
  • This signature, particularly the hub gene COL5A1, shows potential as a prognostic biomarker for gastric cancer.
  • Further research into these genes could lead to improved diagnostic and therapeutic strategies for GC.