Integrated analysis identities Rho GTPases related molecular map in patients with gastric carcinoma

Shaowei Ma1, Ying Wang2, Weibo Li1

  • 1Department of Gastrointestinal Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, China.

Scientific Reports
|December 5, 2023
PubMed

Insights

Researchers identified two Rho GTPase-related gene (RGG) subtypes in gastric cancer (GC). They developed a validated RGGscore model to predict patient prognosis and immunotherapy response, aiding therapeutic guidance.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Rho GTPases play critical roles in human cancers, but their specific involvement in gastric cancer (GC) is not well understood.
  • Understanding the expression patterns and functions of Rho GTPase-related genes (RGGs) is crucial for advancing GC research.

Purpose of the Study:

  • To identify distinct molecular subtypes within gastric cancer based on Rho GTPase-related genes.
  • To develop and validate a prognostic risk model (RGGscore) for predicting outcomes in gastric cancer patients.
  • To evaluate the RGGscore's utility in predicting response to immunotherapy in GC.

Main Methods:

  • Consensus clustering analysis was employed to identify Rho GTPase-related gene (RGG) subtypes.
  • A risk model (RGGscore) was constructed and validated using independent patient cohorts.
  • Univariate and multivariate Cox regression analyses were performed to assess prognostic significance.
  • Quantitative real-time PCR (qRT-PCR) was used to examine gene expression levels.

Main Results:

  • Two distinct RGG subtypes were identified, showing significant differences in overall survival and tumor microenvironment.
  • The developed RGGscore model effectively predicted GC patient prognosis, with a high RGGscore indicating a poorer outcome.
  • The RGGscore served as an independent prognostic indicator for GC.
  • A low RGGscore was significantly associated with improved response to immunotherapy in external validation cohorts.

Conclusions:

  • A novel RGGscore model has been established for gastric cancer, offering potential for improved prognostic prediction.
  • The RGGscore demonstrates utility in stratifying patients for immunotherapy, providing valuable therapeutic guidance.
  • This study highlights the importance of Rho GTPase-related genes in gastric cancer progression and treatment response.

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