Molecular Cluster Mining of Adrenocortical Carcinoma via Multi-Omics Data Analysis Aids Precise Clinical Therapy.

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We collected clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA, lncRNA, microRNA, and somatic mutations in ACC patients from the TCGA, GSE19750, GSE33371, and GSE49278 cohorts. Based on the MOVICS algorithm, the patients were divided into ACC1-3 subtypes by comprehensive multi-omics data analysis. We found that immune-related pathways were more activated, and drug metabolism pathways were enriched in ACC1 subtype patients. Furthermore, ACC1 patients were sensitive to PD-1 immunotherapy and had the lowest sensitivity to chemotherapeutic drugs. Patients with the ACC2 subtype had the worst survival prognosis and the highest tumor-mutation rate. Meanwhile, cell-cycle-related pathways, amino-acid-synthesis pathways, and immunosuppressive cells were enriched in ACC2 patients. Steroid and cholesterol biosynthetic pathways were enriched in patients with the ACC3 subtype. DNA-repair-related pathways were enriched in subtypes ACC2 and ACC3. The sensitivity of the ACC2 subtype to cisplatin, doxorubicin, gemcitabine, and etoposide was better than that of the other two subtypes. For 5-fluorouracil, there was no significant difference in sensitivity to paclitaxel between the three groups. A comprehensive analysis of multi-omics data will provide new clues for the prognosis and treatment of patients with ACC.", "claims": [{"id": "claim-data-access", "statement": "Multi-omics data of ACC patients including DNA methylation, gene mutations, mRNA, miRNA, and LncRNA were downloaded from TCGA-ACC dataset (https://portal.gdc.cancer.gov, accessed on 15 April 2022) and GEO dataset (https://www.ncbi.nlm.nih.gov/geo/, accessed on 15 April 2022); the miRNA expression and DNA methylation 450 matrix were download from the UCSC Xena (https://xenabrowser.net/datapages, accessed on 15 April 2022). Download the somatic mutation data from cbiopportal (https://www.cbioportal.org/, accessed on 15 April 2022). Further enquiries can be directed to the corresponding author. We declare that the data and materials in this study will be provided free of charge to scientists for noncommercial purposes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36497046", "locator": "sections[19] \"Data Availability Statement\" paragraph 2", "quote": "Multi-omics data of ACC patients including DNA methylation, gene mutations, mRNA, miRNA, and LncRNA were downloaded from TCGA-ACC dataset (https://portal.gdc.cancer.gov, accessed on 15 April 2022) and GEO dataset (https://www.ncbi.nlm.nih.gov/geo/, accessed on 15 April 2022); the miRNA expression and DNA methylation 450 matrix were download from the UCSC Xena (https://xenabrowser.net/datapages, accessed on 15 April 2022). Download the somatic mutation data from cbiopportal (https://www.cbioportal.org/, accessed on 15 April 2022). Further enquiries can be directed to the corresponding author. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["Multi-omics data of ACC patients including DNA methylation, gene mutations, mRNA, miRNA, and LncRNA were downloaded from TCGA-ACC dataset (https://portal.gdc.cancer.gov, accessed on 15 April 2022) and GEO dataset (https://www.ncbi.nlm.nih.gov/geo/, accessed on 15 April 2022); the miRNA expression and DNA methylation 450 matrix were download from the UCSC Xena (https://xenabrowser.net/datapages, accessed on 15 April 2022). Download the somatic mutation data from cbiopportal (https://www.cbioportal.org/, accessed on 15 April 2022). Further enquiries can be directed to the corresponding author. 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