ArticleScientific reports2024
Prognostic model based on tumor stemness genes for triple-negative breast cancer.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Methylglyoxal-derived glycated albumin enhances the stemness potential of invasive ductal carcinoma-derived breast cancer stem-like cell line KAIMRC1.Oncology letters · 2026Article
- Integrative QSP Modeling of Cancer Stem Cells in Triple-Negative Breast Cancer: Impacts on Tumor Immunity and Response to Immune Checkpoint Inhibitors.CPT: pharmacometrics & systems pharmacology · 2026Article
- Development of predictive models for the prognosis of triple-negative breast cancer using multiple transcriptomic analyses.PloS one · 2026Article
- CHML regulates migration and invasion in hepatocellular carcinoma via transcriptional and metabolic reprogramming.Frontiers in oncology · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Triple-negative breast cancer (TNBC) is an aggressive disease with a poor prognosis and lack of effective treatment. In this study, TNBCs were analyzed from the perspective of tumor stemness based on scRNA-seq data. The analysis showed that tumor cells of TNBC were divided into 4 subtypes, with subtype 2 having the highest stemness score. A prognostic model of 7 tumor stemness-related genes (AP2S1, CHML, FABP7, FADS2, PAXX, SDC1 and TOP2A) was developed based on marker genes of this subtype and TCGA data, and the predictive power of this feature was well validated in different clinical subgroups. TNBC patients in the low TS group had a better prognosis. In addition, drug sensitivity analysis showed that patients in the high TS (tumor stemness) score group were more sensitive to PD-L1 inhibitors and the chemotherapeutic agents. In conclusion, our study developed a prognostic model based on TNBC tumor stemness cell marker genes, which has a good ability to predict the prognosis of TNBC patients and the effect of response to drug therapy.
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