ArticleJournal of cellular and molecular medicine2018
Inference of patient-specific subpathway activities reveals a functional signature associated with the prognosis of patients with breast cancer.
Article in Journal of cellular and molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification and validation of a novel HOX-related classifier signature for predicting prognosis and immune microenvironment in pediatric gliomas.Frontiers in cell and developmental biology · 2023Article
- Identification and Functional Analysis of Individual-Specific Subpathways in Lung Adenocarcinoma.Genes · 2022Article
- ORN: Inferring patient-specific dysregulation status of pathway modules in cancer with OR-gate Network.PLoS computational biology · 2021Article
- Identification of Somatic Mutation-Driven Immune Cells by Integrating Genomic and Transcriptome Data.Frontiers in cell and developmental biology · 2021Article
- MiRNA-Mediated Subpathway Identification and Network Module Analysis to Reveal Prognostic Markers in Human Pancreatic Cancer.Frontiers in genetics · 2020Article
- Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme.Frontiers in oncology · 2020Article
- Silybin Prevents Prostate Cancer by Inhibited the ALDH1A1 Expression in the Retinol Metabolism Pathway.Frontiers in cell and developmental biology · 2020Article
- Inference of patient-specific subpathway activities reveals a functional signature associated with the prognosis of patients with breast cancer.Journal of cellular and molecular medicine · 2018Article
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Authors and funding
10 authors.
Funding
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Abstract
Breast cancer is one of the most deadly forms of cancer in women worldwide. Better prediction of breast cancer prognosis is essential for more personalized treatment. In this study, we aimed to infer patient-specific subpathway activities to reveal a functional signature associated with the prognosis of patients with breast cancer. We integrated pathway structure with gene expression data to construct patient-specific subpathway activity profiles using a greedy search algorithm. A four-subpathway prognostic signature was developed in the training set using a random forest supervised classification algorithm and a prognostic score model with the activity profiles. According to the signature, patients were classified into high-risk and low-risk groups with significantly different overall survival in the training set (median survival of 65 vs 106 months, P = 1.82e-13) and test set (median survival of 75 vs 101 months, P = 4.17e-5). Our signature was then applied to five independent breast cancer data sets and showed similar prognostic values, confirming the accuracy and robustness of the subpathway signature. Stratified analysis suggested that the four-subpathway signature had prognostic value within subtypes of breast cancer. Our results suggest that the four-subpathway signature may be a useful biomarker for breast cancer prognosis.
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