Combined analysis of RNA-sequence and microarray data reveals effective metabolism-based prognostic signature for neuroblastoma.
Combined analysis of RNA-sequence and microarray data reveals effective metabolism-based prognostic signature for neuroblastoma.
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RNA序列和微阵列数据的联合分析揭示了神经母细胞瘤基于代谢的有效预后特征
DOI：
10.1111/jcmm.15650
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发表时间：
2020-09
影响因子：
5.3
通讯作者：
Zhao X
中科院分区：
文献类型：
--
作者：
Meng X;Feng C;Fang E;Feng J;Zhao X
代谢重编程和神经母细胞瘤（NB）之间的关系在很大程度上是未知的。在本研究中，一个RNA序列数据集（n = 153）用作发现队列，两个微阵列数据集（n = 498和n = 223）用作验证队列。通过比较阶段4s和阶段4 NB鉴定差异表达的代谢基因。通过LASSO回归分析选择了12个代谢基因，并将其整合到预后特征中。代谢基因签名成功地将NB患者分为两个风险组，并且在预测NB患者的生存方面表现良好。代谢基因标签的预后价值也与其他临床风险因素无关。还鉴定了9种代谢相关的长链非编码RNA（lncRNA），并整合到代谢相关的lncRNA特征中。lncRNA标签在预测NB患者的存活率方面也表现良好。这些结果表明，代谢特征有可能用于NB的风险分层。基因集富集分析（GSEA）揭示了多种代谢过程（包括氧化磷酸化和三羧酸循环，这两者都是癌症治疗的新兴靶点）在高风险NB组中富集，而在低风险NB组中没有代谢过程富集。这一结果表明，代谢重编程与NB的进展有关，靶向某些代谢途径可能是NB的有希望的治疗方法。
The relationship between metabolism reprogramming and neuroblastoma (NB) is largely unknown. In this study, one RNA‐sequence data set (n = 153) was used as discovery cohort and two microarray data sets (n = 498 and n = 223) were used as validation cohorts. Differentially expressed metabolic genes were identified by comparing stage 4s and stage 4 NBs. Twelve metabolic genes were selected by LASSO regression analysis and integrated into the prognostic signature. The metabolic gene signature successfully stratifies NB patients into two risk groups and performs well in predicting survival of NB patients. The prognostic value of the metabolic gene signature is also independent with other clinical risk factors. Nine metabolism‐related long non‐coding RNAs (lncRNAs) were also identified and integrated into the metabolism‐related lncRNA signature. The lncRNA signature also performs well in predicting survival of NB patients. These results suggest that the metabolic signatures have the potential to be used for risk stratification of NB. Gene set enrichment analysis (GSEA) reveals that multiple metabolic processes (including oxidative phosphorylation and tricarboxylic acid cycle, both of which are emerging targets for cancer therapy) are enriched in the high‐risk NB group, and no metabolic process is enriched in the low‐risk NB group. This result indicates that metabolism reprogramming is associated with the progression of NB and targeting certain metabolic pathways might be a promising therapy for NB.
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影响因子：
3.8
作者：
Lavarino, Cinzia;Cheung, Nai-Kong V.;Garcia, Idoia;Domenech, Gema;de Torres, Carmen;Alaminos, Miguel;Rios, Jose;Gerald, William L.;Kushner, Brian;LaQuaglia, Mike;Mora, Jaume
通讯作者：
Mora, Jaume
DOI：
10.1158/1078-0432.ccr-08-1815
发表时间：
2009-05-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Brodeur GM;Minturn JE;Ho R;Simpson AM;Iyer R;Varela CR;Light JE;Kolla V;Evans AE
通讯作者：
Evans AE
影响因子：
8
作者：
Khan A;Valli E;Lam H;Scott DA;Murray J;Hanssen KM;Eden G;Gamble LD;Pandher R;Flemming CL;Allan S;Osterman AL;Haber M;Norris MD;Fletcher JI;Yu DMT
通讯作者：
Yu DMT
影响因子：
45.3
作者：
BRODEUR, GM;PRITCHARD, J;VOUTE, PA
通讯作者：
VOUTE, PA
影响因子：
6.6
作者：
Benard, Jean;Raguenez, Gilda;Valteau-Couanet, Dominique
通讯作者：
Valteau-Couanet, Dominique