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Exploring tumor microenvironment in molecular subtyping and prognostic signatures in ovarian cancer and identification of SH2D1A as a key regulator of ovarian cancer carcinogenesis

  • 0Department of Gynecology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Heliyon +

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September 30, 2024

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September 30, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study identified two molecular subgroups in ovarian cancer (OV) based on the tumor microenvironment (TME). A prognostic model using TME genes effectively stratified patients, and SH2D1A was found to promote OV cell migration and proliferation.

Area Of Science

  • Oncology
  • Immunology
  • Genetics

Background

  • Ovarian cancer (OV) presents a poor prognosis due to late diagnosis and limited targeted therapies.
  • The tumor microenvironment (TME) is critical in solid tumor progression and presents a therapeutic target.

Purpose Of The Study

  • To identify molecular subtypes of ovarian cancer based on TME characteristics.
  • To develop a prognostic model for ovarian cancer using TME-related genes.
  • To investigate the role of SH2D1A in ovarian cancer progression.

Main Methods

  • Utilized bulk and single-cell RNA sequencing data from multiple cohorts (TCGA-OV, ICGC, GSE, EMTAB).
  • Applied consensus clustering to identify molecular subgroups and machine learning for prognostic model construction.
  • Performed in vitro experiments (Transwell, CCK8 assays) to assess cell migration and proliferation after SH2D1A knockdown.

Main Results

  • Identified two distinct molecular subgroups (C1 and C2) based on TME gene expression, with C1 exhibiting higher TME activity, increased cancer-associated fibroblasts, M1 macrophages, and CD8+ T cells.
  • Developed a TME-related prognostic signature with strong predictive power across datasets; high-risk patients displayed a more immunosuppressive TME and higher tumor stemness.
  • Found significantly higher SH2D1A mRNA expression in OV cell lines and demonstrated that SH2D1A knockdown reduced ovarian cancer cell migration and proliferation.

Conclusions

  • TME-associated genes are effective for molecular subtyping and developing prognostic models in ovarian cancer.
  • A TME-based prognostic model provides robust prognostic stratification for ovarian cancer patients.
  • SH2D1A plays a significant role in promoting ovarian cancer cell proliferation and migration.

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