The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes.
The Expression Profiles of ADME Genes in Human Cancers and Their Associations with Clinical Outcomes.
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DOI：
10.3390/cancers12113369
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发表时间：
2020-11-13
期刊：
影响因子：
5.2
通讯作者：
Meech R
中科院分区：
文献类型：
--
作者：
Hu DG;Mackenzie PI;Nair PC;McKinnon RA;Meech R
大约有300个基因根据其在药物吸收、分布、代谢和排泄（ADME）中的作用被经典地定义为ADME基因。人类癌症中ADME基因的表达谱及其对癌症患者生存的影响仍有待系统评估。我们的泛癌基因表达分析显示，大约一半的ADME基因在所有21种评估的癌症中表达。大多数基因在不同癌症内和不同癌症之间表现出高度可变的表达。我们的泛癌生存分析确定了一组核心ADME基因，其肿瘤内表达与这些癌症的总生存率相关。这些发现强调了ADME基因作为癌症预后生物标志物和治疗靶点的潜在意义。我们提出，肿瘤内表达的ADME基因可以影响癌症患者的生存，不仅通过药物代谢和处置，但也代谢和处置的许多内源性分子，可以燃料和/或刺激癌症的生长。ADME基因是一组参与药物吸收、分布、代谢和排泄（ADME）的基因。肿瘤内ADME基因的表达谱被认为会影响癌症患者的生存率;然而，这还没有得到系统的研究。在这项研究中，我们对癌症基因组图谱（TCGA）的泛癌症数据集进行了全面分析，揭示了21种不同癌症类型中ADME基因的差异肿瘤内表达谱。大多数基因在癌症特异性患者队列中也显示出较高的个体间变异性。使用Kaplan-Meier曲线和logrank检验，我们发现32个核心ADME基因中的20个基因的肿瘤内表达水平与这些癌症的总生存期（OS）相关。在这些基因中，有5个基因在包括SKCM在内的3种癌症中与不利的OS显著相关（ABCC2，GSTP1），KIRC（CYP2D6、CYP2E1）、PAAD（UGT 2B7）;在12种癌症中，16种与有利的OS显著相关，包括BLCA（UGT 2B 15）、BRCA（CYP 2D 6）、COAD（NAT 1）、HNSC（ABCB 1）、KIRC（ABCG 2、CYP3A4、SLC22A2、SLC22A6）、KIRP（SLC22A2）、LIHC（CYP2C19、CYP2C8、CYP2C9、CYP3A5、SLC22A1）、LUAD（SLC15A2）、LUSC（UGT 1A1）、PAAD（ABCB 1）、SARC（ABCB 1）和SKCM（ABCB 1、DYPD）。总的来说，这些数据提供了令人信服的证据，支持ADME基因作为预后生物标志物和潜在的治疗靶点。我们认为ADME基因的肿瘤内表达可能通过多种机制影响癌症患者的生存率，这些机制包括代谢/转运抗癌药物、激活抗癌药物以及代谢/转运各种参与代谢促进癌细胞和/或控制促生长信号通路的内源性分子。
There are roughly 300 genes that are classically defined as ADME genes based on their roles in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes in human cancers and their impact on cancer patient survival remain to be systematically assessed. Our pan-cancer gene expression analysis revealed that about half of all ADME genes were expressed in all 21 cancers assessed. Most genes showed highly variable expression within and among different cancers. Our pan-cancer survival analysis identified a set of core ADME genes whose intratumoral expression was associated with overall survival in these cancers. These findings highlight the potential implication of ADME genes as cancer prognostic biomarkers and therapeutic targets. We propose that intratumoral expression of ADME genes can influence cancer patient survival through not only drug metabolism and disposition, but also metabolism and disposition of numerous endogenous molecules that can fuel and/or stimulate cancer growth. ADME genes are a group of genes that are involved in drug absorption, distribution, metabolism, and excretion (ADME). The expression profiles of ADME genes within tumours is proposed to impact on cancer patient survival; however, this has not been systematically examined. In this study, our comprehensive analyses of pan-cancer datasets from the Cancer Genome Atlas (TCGA) revealed differential intratumoral expression profiles for ADME genes in 21 different cancer types. Most genes also showed high interindividual variability within cancer-specific patient cohorts. Using Kaplan-Meier plots and logrank tests, we showed that intratumoral expression levels of twenty of the thirty-two core ADME genes were associated with overall survival (OS) in these cancers. Of these genes, five showed significant association with unfavourable OS in three cancers, including SKCM (ABCC2, GSTP1), KIRC (CYP2D6, CYP2E1), PAAD (UGT2B7); sixteen showed significant associations with favourable OS in twelve cancers, including BLCA (UGT2B15), BRCA (CYP2D6), COAD (NAT1), HNSC (ABCB1), KIRC (ABCG2, CYP3A4, SLC22A2, SLC22A6), KIRP (SLC22A2), LIHC (CYP2C19, CYP2C8, CYP2C9, CYP3A5, SLC22A1), LUAD (SLC15A2), LUSC (UGT1A1), PAAD (ABCB1), SARC (ABCB1), and SKCM (ABCB1, DYPD). Overall, these data provide compelling evidence supporting ADME genes as prognostic biomarkers and potential therapeutic targets. We propose that intratumoral expression of ADME genes may impact cancer patient survival by multiple mechanisms that can include metabolizing/transporting anticancer drugs, activating anticancer drugs, and metabolizing/transporting a variety of endogenous molecules involved in metabolically fuelling cancer cells and/or controlling pro-growth signalling pathways.
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影响因子：
7.3
作者：
Gao J;Aksoy BA;Dogrusoz U;Dresdner G;Gross B;Sumer SO;Sun Y;Jacobsen A;Sinha R;Larsson E;Cerami E;Sander C;Schultz N
通讯作者：
Schultz N
影响因子：
64.8
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影响因子：
64.5
作者：
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通讯作者：
Cancer Genome Atlas Research Network
影响因子：
14.9
作者：
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通讯作者：
Noushmehr H
影响因子：
3.8
作者：
Anaya, Jordan
通讯作者：
Anaya, Jordan