ArticleScientific reports2015
Systems biology approach to studying proliferation-dependent prognostic subnetworks in breast cancer.
Article in Scientific reports, 2015. 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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Who cites it
30 citing papers in PubMed.
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- ZC3H12D upregulation in head and neck squamous cell carcinoma: a potential prognostic biomarker associated with immune infiltration.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2025Article
- A Grading System of Intratumoral Tertiary Lymphoid Structure for Combined Hepatocellular-Cholangiocarcinoma: A Multicenter Pathological Study.Journal of hepatocellular carcinoma · 2025Article
- The Biological Function of POLA2 in Hepatocellular Carcinoma.Combinatorial chemistry & high throughput screening · 2024Article
- Molecular features, biological behaviors and clinical implications of mCancer biology & therapy · 2023Article
- YTHDF3as a prognostic predictive biomarker of thyroid cancer and its correlation with immune infiltration.BMC cancer · 2023Article
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- A novel prognostic related lncRNA signature associated with amino acid metabolism in glioma.Frontiers in immunology · 2023Article
- Re-wiring and gene expression changes of AC025034.1 and ATP2B1 play complex roles in early-to-late breast cancer progression.BMC genomic data · 2022Article
- Construction and validation of a novel ferroptosis-related signature for evaluating prognosis and immune microenvironment in ovarian cancer.Frontiers in genetics · 2022Article
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- Identification of the hub and prognostic genes in liver hepatocellular carcinomaFrontiers in molecular biosciences · 2022Article
- Correlation Between Immune-Related Genes and Tumor-Infiltrating Immune Cells With the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer.Frontiers in genetics · 2022Article
- ARPC2: A Pan-Cancer Prognostic and Immunological Biomarker That Promotes Hepatocellular Carcinoma Cell Proliferation and Invasion.Frontiers in cell and developmental biology · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Tumor proliferative capacity is a major biological correlate of breast tumor metastatic potential. In this paper, we developed a systems approach to investigate associations among gene expression patterns, representative protein-protein interactions, and the potential for clinical metastases, to uncover novel survival-related subnetwork signatures as a function of tumor proliferative potential. Based on the statistical associations between gene expression patterns and patient outcomes, we identified three groups of survival prognostic subnetwork signatures (SPNs) corresponding to three proliferation levels. We discovered 8 SPNs in the high proliferation group, 8 SPNs in the intermediate proliferation group, and 6 SPNs in the low proliferation group. We observed little overlap of SPNs between the three proliferation groups. The enrichment analysis revealed that most SPNs were enriched in distinct signaling pathways and biological processes. The SPNs were validated on other cohorts of patients, and delivered high accuracy in the classification of metastatic vs non-metastatic breast tumors. Our findings indicate that certain biological networks underlying breast cancer metastasis differ in a proliferation-dependent manner. These networks, in combination, may form the basis of highly accurate prognostic classification models and may have clinical utility in guiding therapeutic options for patients.
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