ArticleFrontiers in genetics2022
Identification of Prognosis Biomarkers for High-Grade Serous Ovarian Cancer Based on Stemness.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.Journal of ovarian research · 2026Article
- Fueling the Seed: Growth Factors and Cytokines Driving Cancer Stem Cells in Gynecological Malignancies.International journal of molecular sciences · 2025Review
- Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine learning, and experimental validation.Cancer immunology, immunotherapy : CII · 2025Article
- A comprehensive overview of ovarian cancer stem cells: correlation with high recurrence rate, underlying mechanisms, and therapeutic opportunities.Molecular cancer · 2025Review
- Article
- Transcription factor networks and novel immune biomarkers reveal key prognostic and therapeutic insights in ovarian cancer.Discover oncology · 2025Article
- Uncovering key regulatory pathways and prognostic biomarkers in the tumor microenvironment of high-grade serous ovarian cancer through single-cell RNA sequencing and experimental validation.Frontiers in oncology · 2025Article
- Stabilization of SQLE mRNA by WTAP/FTO/IGF2BP3-dependent manner in HGSOC: implications for metabolism, stemness, and progression.Cell death & disease · 2024Article
- Discovering therapeutic possibilities for polycystic ovary syndrome by targeting XIST and its associated ceRNA network through the analysis of transcriptome data.Scientific reports · 2024Article
- scRNA-seq revealed high stemness epithelial malignant cell clusters and prognostic models of lung adenocarcinoma.Scientific reports · 2024Article
- Identification of a Recurrence Gene Signature for Ovarian Cancer Prognosis by Integrating Single-Cell RNA Sequencing and Bulk Expression Datasets.Frontiers in genetics · 2022Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, high-grade serous ovarian cancer (HGSOC) is studied, which is the most common histological subtype of ovarian cancer. We use a new analytical procedure to combine the bulk RNA-Seq sample for ovarian cancer, mRNA expression-based stemness index (mRNAsi), and single-cell data for ovarian cancer. Through integrating bulk RNA-Seq sample of cancer samples from TCGA, UCSC Xena and single-cell RNA-Seq (scRNA-Seq) data of HGSOC from GEO, and performing a series of computational analyses on them, we identify stemness markers and survival-related markers, explore stem cell populations in ovarian cancer, and provide potential treatment recommendation. As a result, 171 key genes for capturing stem cell characteristics are screened and one vital cancer stem cell subpopulation is identified. Through further analysis of these key genes and cancer stem cell subpopulation, more critical genes can be obtained as LCP2, FCGR3A, COL1A1, COL1A2, MT-CYB, CCT5, and PAPPA, are closely associated with ovarian cancer. So these genes have the potential to be used as prognostic biomarkers for ovarian cancer.
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