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Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data |
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| Authors: | Xi Tian Wen-Hao Xu Aihetaimujiang Anwaier Hong-Kai Wang Fang-Ning Wan Da-Long Cao Wen-Jie Luo Guo-Hai Shi Yuan-Yuan Qu Hai-Liang Zhang Ding-Wei Ye |
| Institution: | 1. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China;2. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: Conceptualization (equal), Data curation (equal), Formal analysis (lead), Methodology (lead), Software (lead), Validation (lead), Writing - original draft (equal), Writing - review & editing (equal);3. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: Data curation (lead), Formal analysis (equal), ?Investigation (equal), Methodology (equal), Software (lead), Validation (equal), Visualization (equal), Writing - original draft (equal), Writing - review & editing (equal);4. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: Formal analysis (equal), Funding acquisition (equal), Methodology (equal), Software (equal), Validation (equal), Visualization (equal);5. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: Conceptualization (equal), Data curation (equal), Formal analysis (equal), Methodology (equal), Resources (equal), Supervision (equal);6. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: Conceptualization (equal), Formal analysis (equal), Methodology (equal), Resources (equal), Software (equal), Visualization (equal);7. Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China Contribution: ?Investigation (equal), Project administration (equal), Resources (equal), Software (equal), Supervision (equal) |
| 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. |
| Keywords: | adult adrenocortical carcinoma biomarker predictive model proteomics real-world data |