Evidence map›Paper›PMID 39221174›Full record

ArticleBiomedical engineering and computational biology2024

Reclassify High-Grade Serous Ovarian Cancer Patients Into Different Molecular Subtypes With Discrepancy Prognoses and Therapeutic Responses Based on Cancer-Associated Fibroblast-Enriched Prognostic Genes.

Xiangxiang Liu, Guoqiang Ping, Dongze Ji, Zhifa Wen, Yajun Chen

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Article in Biomedical engineering and computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiangxiang LiuDepartment of Clinical Laboratory, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing, Jiangsu, China.
Guoqiang PingDepartment of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Dongze JiDepartment of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Zhifa WenDepartment of Clinical Laboratory, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing, Jiangsu, China.
Yajun ChenDepartment of Clinical Laboratory, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing, Jiangsu, China.ORCID https://orcid.org/0009-0007-1983-1997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer-associated fibroblasts (CAFs) play critical roles in the metastasis and therapeutic response of high-grade serous ovarian cancer (HGSC). Our study intended to select HGSC patients with unfavorable prognoses and therapeutic responses based on CAF-enriched prognostic genes. The bulk RNA and single-cell RNA sequencing (scRNA-seq) data of tumor tissues were collected from the TCGA and GEO databases. The infiltrated levels of immune and stromal cells were estimated by multiple immune deconvolution algorithms and verified through immunohistochemical analysis. The univariate Cox regression analyses were used to identify prognostic genes. Gene Set Enrichment Analysis (GSEA) was conducted to annotate enriched gene sets. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore potential alternative drugs. We found the infiltered levels of CAFs were remarkedly elevated in advanced and metastatic HGSC tissues and identified hundreds of genes specifically enriched in CAFs. Then we selected 6 CAF-enriched prognostic genes based on which HGSC patients were reclassified into 2 subclusters with discrepancy prognoses. Further analysis revealed that the HGSC patients in cluster-2 tended to undergo poor responses to traditional chemotherapy and immunotherapy. Subsequently, we selected 24 novel potential therapeutic drugs for cluster-2 HGSC patients. Moreover, we discovered a positive correlation of infiltrated levels between CAFs and monocytes/macrophages in HGSC tissues. Collectively, our study successfully reclassified HGSC patients into 2 different subgroups that have discrepancy prognoses and responses to current therapeutic methods.

Indexed as

cancer-associated fibroblastimmunityOvarian cancerprognosistherapy

Identifiers

PMID39221174
PMCPMC11365035

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.