ArticleFrontiers in cell and developmental biology2021
A Novel Platelet-Related Gene Signature for Predicting the Prognosis of Triple-Negative Breast Cancer.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed, 34 citations in OpenAlex.
- Identification of a novel platelet-related prognostic model for hepatocellular carcinoma.Discover oncology · 2026Article
- A Multi-Omics and machine learning platelet-related prognostic signature in multiple myeloma.Annals of hematology · 2026Article
- Effects of nucleic acid metabolism on prognosis and immune invasion of triple-negative breast cancer.Genes and immunity · 2026Article
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- Multi-omics analyses of the heterogenous immune microenvironment in triple-negative breast cancer implicate UQCRFS1 potentiates tumor progression.Experimental hematology & oncology · 2025Article
- A novel risk model consisting of nine platelet-related gene signatures for predicting prognosis, immune features and drug sensitivity in glioma.Hereditas · 2024Article
- Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.International journal of molecular sciences · 2024Review
- A platelet-related signature for predicting the prognosis and immunotherapy benefit in bladder cancer based on machine learning combinations.Translational andrology and urology · 2024Article
- Unveiling the Influence of AI Predictive Analytics on Patient Outcomes: A Comprehensive Narrative Review.Cureus · 2024Review
- Identification of N7-methylguanosine-related miRNAs as potential biomarkers for prognosis and drug response in breast cancer.Heliyon · 2024Article
- The platelet-related genes associated with the prognosis of HCC by regulating cycling T cell and prolif-TAMs.Heliyon · 2024Article
- Tigecycline-induced coagulation gene prognostic prediction model and intestinal flora signature in AML.Frontiers in immunology · 2024Article
- Artificial intelligence for chimeric antigen receptor-based therapies: a comprehensive review of current applications and future perspectives.Therapeutic advances in vaccines and immunotherapy · 2024Review
- A new 4-gene-based prognostic model accurately predicts breast cancer prognosis and immunotherapy response by integrating WGCNA and bioinformatics analysis.Frontiers in immunology · 2024Article
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- Natural killer cell-related prognostic risk model predicts prognosis and treatment outcomes in triple-negative breast cancer.Frontiers in immunology · 2023Article
- Computational identification and clinical validation of a novel risk signature based on coagulation-related lncRNAs for predicting prognosis, immunotherapy response, and chemosensitivity in colorectal cancer patients.Frontiers in immunology · 2023Article
- A simplified machine learning model utilizing platelet-related genes for predicting poor prognosis in sepsis.Frontiers in immunology · 2023Article
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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
Regarded as the most invasive subtype, triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) proteins. Platelets have recently been shown to be associated with metastasis of malignant tumors. Nevertheless, the status of platelet-related genes in TNBC and their correlation with patient prognosis remain unknown. In this study, the expression and variation levels of platelet-related genes were identified and patients with TNBC were divided into three subtypes. We collected cohorts from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, we constructed a seven-gene signature which classified the two cohorts of patients with TNBC into low- or high-risk groups. Patients in the high-risk group were more likely to have lower survival rates than those in the low-risk group. The risk score, incorporated with the clinical features, was confirmed as an independent factor for predicting the overall survival (OS) time. Functional enrichment analyses revealed the involvement of a variety of vital biological processes and classical cancer-related pathways that could be important to the ultimate prognosis of TNBC. We then built a nomogram that performed well. Moreover, we tested the model in other cohorts and obtained positive outcomes. In conclusion, platelet-related genes were closely related to TNBC, and this novel signature could serve as a tool for the assessment of clinical prognosis.
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