ArticleInternational journal of molecular sciences2023
Cancer Stem Cell Markers-Clinical Relevance and Prognostic Value in High-Grade Serous Ovarian Cancer (HGSOC) Based on The Cancer Genome Atlas Analysis.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 19 citations in OpenAlex.
- Multifaceted role ofiScience · 2026Article
- Prognostic model based on stem cells and oxidative stress related genes for ovarian cancer.Medicine · 2026Article
- Identification of potential genes associated with metastasis in osteosarcoma: an integrated bioinformatics analysis.Musculoskeletal surgery · 2025Review
- Therapeutic and Prognostic Relevance of Cancer Stem Cell Populations in Endometrial Cancer: A Narrative Review.Diagnostics (Basel, Switzerland) · 2025Review
- Determination of high-grade serous ovarian cancer stem cell-based subtypes and prognostic model and identification of highly expressed VSIG4 and STAB1 in macrophages.Journal of ovarian research · 2025Article
- Tumoroid model recreates clinically relevant phenotypes of high grade serous ovarian cancer (HGSC) cells, carcinoma associated fibroblasts, and macrophages.Research square · 2025Article
- Advanced drug delivery platforms target cancer stem cells.Asian journal of pharmaceutical sciences · 2025Review
- TIMP1 Overexpression in Ovarian Cancer Spheroids: Implications for Prognosis, Resistance, and Metastatic Potential.Cancers · 2025Article
- LGR5: An emerging therapeutic target for cancer metastasis and chemotherapy resistance.Cancer metastasis reviews · 2025Review
- Prognostic and therapeutic value of the Eph/Ephrin signaling pathway in pancreatic cancer explored based on bioinformatics.Scientific reports · 2024Article
- Clinicopathological significance of cancer stem cell marker CD44/SOX2 in esophageal squamous cell carcinoma (ESCC) patients and construction of a nomogram to predict overall survival.Translational cancer research · 2024Article
- Regulation of the Function and Expression of EpCAM.Biomedicines · 2024Review
- Cancer Stem Cells from Definition to Detection and Targeted Drugs.International journal of molecular sciences · 2024Review
- A Recipe for Successful Metastasis: Transition and Migratory Modes of Ovarian Cancer Cells.Cancers · 2024Review
- Characterizing tumor biology and immune microenvironment in high-grade serous ovarian cancer via single-cell RNA sequencing: insights for targeted and personalized immunotherapy strategies.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer stem cells (CSCs) may contribute to an increased risk of recurrence in ovarian cancer (OC). Further research is needed to identify associations between CSC markers and OC patients' clinical outcomes with greater certainty. If they prove to be correct, in the future, the CSC markers can be used to help predict survival and indicate new therapeutic targets. This study aimed to determine the CSC markers at mRNA and protein levels and their association with clinical presentation, outcome, and risk of recurrence in HGSOC (High-Grade Serous Ovarian Cancer). TCGA (The Cancer Genome Atlas) database with 558 ovarian cancer tumor samples was used for the evaluation of 13 CSC markers (ALDH1A1, CD44, EPCAM, KIT, LGR5, NES, NOTCH3, POU5F1, PROM1, PTTG1, ROR1, SOX9, and THY1). Data on mRNA and protein levels assessed by microarray and mass spectrometry were retrieved from TCGA. Models to predict chemotherapy response and survival were built using multiple variables, including epidemiological data, expression levels, and machine learning methodology. ALDH1A1 and LGR5 mRNA expressions indicated a higher platinum sensitivity (
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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 OpenQuestion graph.