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多组学数据分析助力肾上腺皮质癌的分子聚类挖掘实现精准临床治疗。

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

机构信息

Department of Urology, The First Affifiliated Hospital of Anhui Medical University, 218th Jixi Road, Hefei 230022, China.

Institute of Urology, Anhui Medical University, 81th Meishan Road, Hefei 230022, China.

出版信息

Cells. 2022 Nov 26;11(23):3784. doi: 10.3390/cells11233784.

DOI:10.3390/cells11233784
PMID:36497046
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9737968/
Abstract

Adrenocortical carcinoma (ACC) is a malignancy of the endocrine system. 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.

摘要

肾上腺皮质癌 (ACC) 是一种内分泌系统的恶性肿瘤。我们收集了来自 TCGA、GSE19750、GSE33371 和 GSE49278 队列的 ACC 患者的临床和病理特征、基因组突变、DNA 甲基化谱以及 mRNA、lncRNA、microRNA 和体细胞突变。基于 MOVICS 算法,我们通过综合多组学数据分析将患者分为 ACC1-3 亚型。我们发现免疫相关途径在 ACC1 亚型患者中更为活跃,药物代谢途径在 ACC1 亚型患者中富集。此外,ACC1 患者对 PD-1 免疫疗法敏感,对化疗药物的敏感性最低。ACC2 亚型患者的生存预后最差,肿瘤突变率最高。同时,细胞周期相关途径、氨基酸合成途径和免疫抑制细胞在 ACC2 患者中富集。ACC3 亚型患者中富集了甾体和胆固醇生物合成途径。DNA 修复相关途径在 ACC2 和 ACC3 亚型中富集。ACC2 亚型对顺铂、阿霉素、吉西他滨和依托泊苷的敏感性优于其他两个亚型。对于 5-氟尿嘧啶,三组之间对紫杉醇的敏感性没有显著差异。多组学数据的综合分析将为 ACC 患者的预后和治疗提供新的线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/83092948b3e9/cells-11-03784-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/7528013a1882/cells-11-03784-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/1a49b24f4a73/cells-11-03784-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/322f18d58d3e/cells-11-03784-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/c14f7fb0777e/cells-11-03784-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/83092948b3e9/cells-11-03784-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/7528013a1882/cells-11-03784-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/1a49b24f4a73/cells-11-03784-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/322f18d58d3e/cells-11-03784-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/c14f7fb0777e/cells-11-03784-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a5/9737968/83092948b3e9/cells-11-03784-g007.jpg

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