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Abstract：
BACKGROUND: Adrenocortical carcinoma (ACC) is one of the most lethal endocrine malignancies and there is a lack of clinically useful markers for prognosis and patient stratification. Therefore our aim was to identify clinical and genetic markers that predict outcome in patients with ACC.
METHODS: Clinical and genetic data from a total of 162 patients with ACC were analyzed by combining an independent cohort consisting of tumors from Yale School of Medicine, Karolinska Institutet, and Düsseldorf University (YKD) with two public databases [The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)]. We used a novel bioinformatical pipeline combining differential expression and messenger RNA (mRNA)- and DNA-dependent survival. Data included reanalysis of previously conducted whole-exome sequencing (WES) for the YKD cohort, WES and RNA data for the TCGA cohort, and RNA data for the GEO cohort.
RESULTS: We identified 3903 significant differentially expressed genes when comparing ACC and adrenocortical adenoma, and the mRNA expression levels of 461/3903 genes significantly impacted survival. Subsequent analysis revealed 45 of these genes to be mutated in patients with significantly worse survival. The relationship was significant even after adjusting for stage and age. Protein-protein interaction showed previously unexplored interactions among many of the 45 proteins, including the cancer-related proteins DNA polymerase delta 1 (POLD1), aurora kinase A (AURKA), and kinesin family member 23 (KIF23). Furthermore 14 of the proteins had significant interactions with TP53 which is the most frequently mutated gene in the germline of patients with ACC.
CONCLUSIONS: Using a multiparameter approach, we identified 45 genes that significantly influenced survival. Notably, many of these genes have protein interactions not previously implicated in ACC. These findings may lay the foundation for improved prognostication and future targeted therapies.
METHODS: Clinical and genetic data from a total of 162 patients with ACC were analyzed by combining an independent cohort consisting of tumors from Yale School of Medicine, Karolinska Institutet, and Düsseldorf University (YKD) with two public databases [The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)]. We used a novel bioinformatical pipeline combining differential expression and messenger RNA (mRNA)- and DNA-dependent survival. Data included reanalysis of previously conducted whole-exome sequencing (WES) for the YKD cohort, WES and RNA data for the TCGA cohort, and RNA data for the GEO cohort.
RESULTS: We identified 3903 significant differentially expressed genes when comparing ACC and adrenocortical adenoma, and the mRNA expression levels of 461/3903 genes significantly impacted survival. Subsequent analysis revealed 45 of these genes to be mutated in patients with significantly worse survival. The relationship was significant even after adjusting for stage and age. Protein-protein interaction showed previously unexplored interactions among many of the 45 proteins, including the cancer-related proteins DNA polymerase delta 1 (POLD1), aurora kinase A (AURKA), and kinesin family member 23 (KIF23). Furthermore 14 of the proteins had significant interactions with TP53 which is the most frequently mutated gene in the germline of patients with ACC.
CONCLUSIONS: Using a multiparameter approach, we identified 45 genes that significantly influenced survival. Notably, many of these genes have protein interactions not previously implicated in ACC. These findings may lay the foundation for improved prognostication and future targeted therapies.
摘要：
背景：肾上腺皮质癌（ACC）是最致命的内分泌恶性肿瘤之一，缺乏临床上有用的预后和患者分层标志物。因此，我们的目标是确定预测ACC患者预后的临床和遗传标记。
方法：通过结合由耶鲁大学医学院的肿瘤组成的独立队列，分析了来自总共162例ACC患者的临床和遗传数据。卡罗林斯卡学院，和杜塞尔多夫大学（YKD）拥有两个公共数据库[癌症基因组图谱（TCGA）和基因表达综合（GEO）]。我们使用了一种新的生物信息学管道，将差异表达与信使RNA（mRNA）和DNA依赖性存活相结合。数据包括先前对YKD队列进行的全外显子组测序（WES）的再分析，TCGA队列的WES和RNA数据，和GEO队列的RNA数据。
结果：当比较ACC和肾上腺皮质腺瘤时，我们确定了3903个显著差异表达的基因，461/3903基因的mRNA表达水平显着影响生存率。随后的分析显示，这些基因中有45个在生存率明显较差的患者中发生突变。即使在调整阶段和年龄后，这种关系也很重要。蛋白质-蛋白质相互作用显示了45种蛋白质中许多蛋白质之间以前未探索的相互作用，包括癌症相关蛋白DNA聚合酶δ1（POLD1），极光激酶A（AURKA），和驱动蛋白家族成员23（KIF23）。此外，14种蛋白质与TP53具有显着的相互作用，TP53是ACC患者种系中最常见的突变基因。
结论：使用多参数方法，我们确定了45个显著影响存活的基因.值得注意的是,这些基因中的许多具有先前未涉及ACC的蛋白质相互作用。这些发现可能为改善预后和未来的靶向治疗奠定基础。
方法：通过结合由耶鲁大学医学院的肿瘤组成的独立队列，分析了来自总共162例ACC患者的临床和遗传数据。卡罗林斯卡学院，和杜塞尔多夫大学（YKD）拥有两个公共数据库[癌症基因组图谱（TCGA）和基因表达综合（GEO）]。我们使用了一种新的生物信息学管道，将差异表达与信使RNA（mRNA）和DNA依赖性存活相结合。数据包括先前对YKD队列进行的全外显子组测序（WES）的再分析，TCGA队列的WES和RNA数据，和GEO队列的RNA数据。
结果：当比较ACC和肾上腺皮质腺瘤时，我们确定了3903个显著差异表达的基因，461/3903基因的mRNA表达水平显着影响生存率。随后的分析显示，这些基因中有45个在生存率明显较差的患者中发生突变。即使在调整阶段和年龄后，这种关系也很重要。蛋白质-蛋白质相互作用显示了45种蛋白质中许多蛋白质之间以前未探索的相互作用，包括癌症相关蛋白DNA聚合酶δ1（POLD1），极光激酶A（AURKA），和驱动蛋白家族成员23（KIF23）。此外，14种蛋白质与TP53具有显着的相互作用，TP53是ACC患者种系中最常见的突变基因。
结论：使用多参数方法，我们确定了45个显著影响存活的基因.值得注意的是,这些基因中的许多具有先前未涉及ACC的蛋白质相互作用。这些发现可能为改善预后和未来的靶向治疗奠定基础。
