GDF11 rapidly increases lipid accumulation in liver cancer cells through ALK5-dependent signaling

Here we used RNA-Seq to unravel the gene expression patterns and related signaling pathways that might be responsible for the observed changes in the lipidome upon GDF11 treatment of hepatocellular carcinoma cells (HCC), HepG2. RNA-seq analysis was performed after 24h of GDF11 (100ng/ml) treatment to investigate its involvement in lipid metabolism. Genes exhibiting absolute fold-change values >2 and p-values <0.05 were considered differentially expressed between contrasts and statistical differences in gene expression were assessed by the ANOVA test. The significance threshold was set to 0.05. Treatment with recombinant GDF11 had an extensive effect on the overall gene expression profile in HepG2 cells and heatmap analysis clearly segregated control and GDF11 treated samples. In total, we identified 3,357 differentially expressed genes, of which 2,422 were over-expressed, and 935 were downregulated. To gain more deep mechanistic insight into the biological processes and pathway associations with these differentially expressed genes, we analyzed our transcriptomic data by STRING pathway unbiased analysis for annotated molecular interactions of selected genes employing Kegg pathways database. The 5 top most significantly influenced canonical pathways/cellular processes were the ones related to TGF-β signaling, extracellular matrix remodeling, focal adhesion, PI3K-AKT signaling, and cytochrome P450-dependent metabolism. Profiling the transcriptome of hepatocelular cell line HepG2 after the treatment with recombinant GDF11 protein.

本研究采用RNA测序（RNA-Seq）技术，解析重组生长分化因子11（GDF11）处理肝癌细胞（HCC）株HepG2后，脂质组发生的变化所对应的基因表达模式及潜在相关信号通路。
本研究在GDF11（100ng/ml）处理24小时后开展RNA测序分析，以探究其在脂质代谢中的调控作用。本研究以绝对倍数变化值>2且P值<0.05作为差异表达基因的筛选标准，采用方差分析（ANOVA）检验基因表达的统计学差异，显著性阈值设定为0.05。
重组GDF11处理对HepG2细胞的整体基因表达谱具有广泛影响，热图分析可清晰区分对照组与GDF11处理组样本。本研究共筛选得到3357个差异表达基因，其中2422个基因表达上调，935个基因表达下调。
为深入解析差异表达基因所参与的生物学过程及通路关联，本研究基于京都基因与基因组百科全书（KEGG, Kyoto Encyclopedia of Genes and Genomes）通路数据库，采用STRING数据库的无偏通路分析方法，对筛选基因的注释化分子互作关系进行解析。
本研究筛选得到的前5个受影响最显著的经典通路/细胞过程分别为转化生长因子β（TGF-β）信号通路、细胞外基质重塑、黏着斑、磷脂酰肌醇3-激酶-蛋白激酶B（PI3K-AKT）信号通路，以及细胞色素P450依赖型代谢通路。
本研究对重组GDF11蛋白处理后人肝癌细胞系HepG2开展了转录组谱分析。