ArticleGenes2022
The Value of the Stemness Index in Ovarian Cancer Prognosis.
Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 29 citations in OpenAlex.
- The resilient subset: cancer stem cells at the core of immunotherapy resistance.Immunotherapy advances · 2026Review
- Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications.Translational oncology · 2025Article
- Machine Learning-Based Prognostic Signature in Breast Cancer: Regulatory T Cells, Stemness, and Deep Learning for Synergistic Drug Discovery.International journal of molecular sciences · 2025Article
- Molecular Signatures of Cancer Stemness Characterize the Correlations with Prognosis and Immune Landscape and Predict Risk Stratification in Pheochromocytomas and Paragangliomas.Bioengineering (Basel, Switzerland) · 2025Article
- The expression landscape and clinical significance of methyltransferase-like 17 in human cancer and hepatocellular carcinoma: a pan-cancer analysis using multiple databases.Cancer cell international · 2025Article
- Stemness-driven clusters in ovarian cancer: immune characteristics and prognostic implications.Frontiers in oncology · 2025Article
- Application of artificial intelligence-based stemness index in cancer.Frontiers in oncology · 2025Review
- Stemness-Relevant Gene Signature for Chemotherapeutic Response and Prognosis Prediction in Ovarian Cancer.Stem cells international · 2025Article
- Integrated analysis of spatial transcriptomics and CT phenotypes for unveiling the novel molecular characteristics of recurrent and non-recurrent high-grade serous ovarian cancer.Biomarker research · 2024Article
- Silencing immune-infiltrating biomarker CCDC80 inhibits malignant characterization and tumor formation in gastric cancer.BMC cancer · 2024Article
- AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication.British journal of cancer · 2024Article
- Identifying Explainable Machine Learning Models and a Novel SFRP2International journal of molecular sciences · 2023Article
- Stemness signature and targeted therapeutic drugs identification for Triple Negative Breast Cancer.Scientific data · 2023Article
- Identification of STEAP3-based molecular subtype and risk model in ovarian cancer.Journal of ovarian research · 2023Article
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- Stemness genes and miR-1247-3p expression associate with clinicopathological parameters and prognosis in lung adenocarcinoma.PloS one · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OC) is one of the most common gynecological malignancies. It is associated with a difficult diagnosis and poor prognosis. Our study aimed to analyze tumor stemness to determine the prognosis feature of patients with OC. At this job, we selected the gene expression and the clinical profiles of patients with OC in the TCGA database. We calculated the stemness index of each patient using the one-class logistic regression (OCLR) algorithm and performed correlation analysis with immune infiltration. We used consensus clustering methods to classify OC patients into different stemness subtypes and compared the differences in immune infiltration between them. Finally, we established a prognostic signature by Cox and LASSO regression analysis. We found a significant negative correlation between a high stemness index and immune score. Pathway analysis indicated that the differentially expressed genes (DEGs) from the low- and high-mRNAsi groups were enriched in multiple functions and pathways, such as protein digestion and absorption, the PI3K-Akt signaling pathway, and the TGF-β signaling pathway. By consensus cluster analysis, patients with OC were split into two stemness subtypes, with subtype II having a better prognosis and higher immune infiltration. Furthermore, we identified 11 key genes to construct the prognostic signature for patients with OC. Among these genes, the expression levels of nine, including
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