Zhang Jinqiang, Baddoo Melody, Han Chang, Strong Michael J, Cvitanovic Jennifer, Moroz Krzysztof, Dash Srikanta, Flemington Erik K, Wu Tong
Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, New Orleans, Louisiana, USA.
Bioinformatics Core, Tulane Health Sciences Center and Tulane Cancer Center, New Orleans, Louisiana, USA.
Oncotarget. 2016 Aug 2;7(31):49232-49245. doi: 10.18632/oncotarget.10249.
Although much progress has been made in understanding cancer cellular metabolism adaptation, the co-regulations between genes of metabolism and cancer pathways and their interactions remain poorly characterized. Here, we applied gene co-expression network analysis to 1509 metabolic gene expression data generated from 120 HCC and 180 non-tumor human liver tissues by microarray. Our analyses reveal that metabolism genes can be classified into different co-expression modules based on their associations with HCC related traits. The co-regulation mechanism of the carbon metabolism genes in normal liver tissues was interrupted during the processes of carcinogenesis. In parallel, we performed RNAseq analysis of HCC and non-tumor human liver tissues, and identified a unique 22-carbon-metabolism-gene-signature of increased expression. This gene signature was further verified in multiple microarray data sets, and its prognostic value was also proven by HCC patients' survival data from TCGA. Additionally, the tumorigenic function of two representative genes, CS and ACSS1, were validated experimentally by cell growth and spheroid formation assays. The current study provides evidence for the reprogramming of the co-regulation network between carbon metabolism and cancer pathway genes in HCC. In addition, this study also reveals a unique 22-carbon-metabolism-gene-expression-signature in HCC. Strategies targeting these genes may represent new therapeutic approaches for HCC treatment.
尽管在理解癌症细胞代谢适应方面已经取得了很大进展，但代谢基因与癌症通路基因之间的协同调控及其相互作用仍未得到充分表征。在这里，我们对通过微阵列从120例肝癌和180例非肿瘤人类肝脏组织中生成的1509个代谢基因表达数据应用了基因共表达网络分析。我们的分析表明，代谢基因可以根据它们与肝癌相关特征的关联分为不同的共表达模块。正常肝脏组织中碳代谢基因的协同调控机制在致癌过程中被中断。同时，我们对肝癌和非肿瘤人类肝脏组织进行了RNA测序分析，并鉴定出一个独特的表达增加的22碳代谢基因特征。该基因特征在多个微阵列数据集中得到进一步验证，其预后价值也通过来自TCGA的肝癌患者生存数据得到证实。此外，通过细胞生长和球体形成试验，实验验证了两个代表性基因CS和ACSS1的致瘤功能。本研究为肝癌中碳代谢与癌症通路基因之间的协同调控网络重编程提供了证据。此外，本研究还揭示了肝癌中一个独特的22碳代谢基因表达特征。针对这些基因的策略可能代表了肝癌治疗的新方法。
