Scholarlink

Purpose <p>Polycystic Ovary Syndrome (PCOS), ovarian cancer (OC), and Recurrent Pregnancy Loss (RPL) are associated pathological conditions in women. This study investigated the genetic intersections of PCOS, OC, and RPL. The objective was to uncover the shared genetic pathways and differential gene expressions that could pave the way for novel therapeutic approaches and a better understanding of these interconnected conditions.</p> Methods <p>We utilized the GEO database to obtain gene expression datasets for PCOS, OC, and RPL. A series of bioinformatics analyses were employed, including differential expression analysis, functional and pathway enrichment analysis, PPI network construction, survival analysis, and assessment of immune infiltration.</p> Results <p>We identified 60 shared differentially expressed genes (DEGs) between the three conditions. Through comprehensive methodologies, including differential expression analysis, functional enrichment, PPI network construction, and survival analysis, we identified six key hub genes such as BCL2L11, TNFSF13B, PRDM1, BARD1, HIST1H2AM, and HIST1H2AI. These genes were implicated in key biological processes and molecular functions, including genomic stability, apoptosis regulation, immune response modulation, and cell cycle control.</p> Conclusion <p>This bioinformatics investigation provides novel insights into the genetic underpinnings linking PCOS, OC, and RPL. Identifying shared DEGs and pathways enriches our understanding of these conditions and indicates potential targets for therapeutic intervention.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Bioinformatics Analysis of Gene Expression in PCOS, Ovarian Cancer and Recurrent Pregnancy Loss

  • 期刊论文

  • 发表日期：

    2025年11月27日

查看全文
  • Shrinal Vasa,
  • Shan Shibu,
  • Swayamprabha Samantaray,
  • Aditi Kaloni,
  • Nidhi Joshi,
  • Bhavin Parekh,
  • Anupama Modi

摘要

Purpose

Polycystic Ovary Syndrome (PCOS), ovarian cancer (OC), and Recurrent Pregnancy Loss (RPL) are associated pathological conditions in women. This study investigated the genetic intersections of PCOS, OC, and RPL. The objective was to uncover the shared genetic pathways and differential gene expressions that could pave the way for novel therapeutic approaches and a better understanding of these interconnected conditions.

Methods

We utilized the GEO database to obtain gene expression datasets for PCOS, OC, and RPL. A series of bioinformatics analyses were employed, including differential expression analysis, functional and pathway enrichment analysis, PPI network construction, survival analysis, and assessment of immune infiltration.

Results

We identified 60 shared differentially expressed genes (DEGs) between the three conditions. Through comprehensive methodologies, including differential expression analysis, functional enrichment, PPI network construction, and survival analysis, we identified six key hub genes such as BCL2L11, TNFSF13B, PRDM1, BARD1, HIST1H2AM, and HIST1H2AI. These genes were implicated in key biological processes and molecular functions, including genomic stability, apoptosis regulation, immune response modulation, and cell cycle control.

Conclusion

This bioinformatics investigation provides novel insights into the genetic underpinnings linking PCOS, OC, and RPL. Identifying shared DEGs and pathways enriches our understanding of these conditions and indicates potential targets for therapeutic intervention.