ArticleJournal of cellular and molecular medicine2021
Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data.
Article in Journal of cellular and molecular medicine, 2021. 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.
- Interpretable Machine Learning Model for Survival Prediction in Pediatric Adrenocortical Tumors.Journal of the Endocrine Society · 2026Article
- The Enhanced Expression of ZWILCH Predicts Poor Survival of Adrenocortical Carcinoma Patients.Biomedicines · 2023Article
- Methylation-Driven Gene PLAU as a Potential Prognostic Marker for Differential Thyroid Carcinoma.Frontiers in cell and developmental biology · 2022Article
- Identification of Prognostic Fatty Acid Metabolism lncRNAs and Potential Molecular Targeting Drugs in Uveal Melanoma.Computational and mathematical methods in medicine · 2022Article
- Mass Spectrometry-Based Proteomic Discovery of Prognostic Biomarkers in Adrenal Cortical Carcinoma.Cancers · 2021Article
- Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data.Journal of cellular and molecular medicine · 2021Article
- Identification and Validation of a Novel Prognosis Prediction Model in Adrenocortical Carcinoma by Integrative Bioinformatics Analysis, Statistics, and Machine Learning.Frontiers in cell and developmental biology · 2021Article
- Overexpression of SKA Complex Is Associated With Poor Prognosis in Gliomas.Frontiers in neurology · 2021Article
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Authors and funding
11 authors.
Funding
Abstract
This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large-scale multiomics analysis and real-world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis-related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI's GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki-67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients' prognosis using proteomic data, gene expression data and real-world data and this prognostic model showed stronger predictive value than other biomarkers (Ki-67, Beta-catenin, etc) in multi-cohorts.
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