Objective

Hepatocellular carcinoma (HCC) is an intractable disease because patients with HCC frequently develop sorafenib resistance after long-term chemotherapy. Although studies has demonstrated the availability of cumulative information on drug-resistant patients, little is known about the strategies and molecular mechanisms to reverse sorafenib resistance. Here, the present study identified critical mRNAs and transcription factors (TFs) associated with sorafenib resistance of HCC and evaluated the significance correlation between drug-resistant genes and TFs in comprehensive network for HCC xenografts mice.

Methods

The expression profiles of mRNAs were compared between sorafenib-acquired resistant tissue and sorafenib sensitive tissue utilizing RNA-Seq data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Gene Ontology and KEGG pathway analysis were performed to investigate the biological function of significantly dysregulated mRNA. Furthermore, the Kaplan-Meier survival analyses were performed to evaluate the effect of mRNA on over survival. Subsequently, TFs were predicted using TRANSFAC and TF-mRNA regulatory networks were visualized using cytoscape software.

Results

A total of 827 mRNAs were found to be differentially expressed in sorafenib-acquired resistant tissue compared with control. Thereafter, the results of functional enrichment analysis showed the dysregulated mRNAs involved in drug-resistant signaling pathway, including MAPK, JAK-STAT, TGF-β and drug-metabolism cytochrome P450 signaling pathway. CDK1, CDKN1A and TAPBP might serve as prognostic signature of resistance of HCC to sorafenib according to the survival analysis. Furthermore, TF-mRNA networks were constructed. There were 18 TFs were predicted to regulate differentially expressed mRNAs, which play an essential role in the regulation of dysfunctional gene networks. NFKB1 was presented in the TF-mRNA networks as the node with the highest degree and MYC was predicted as prognostic TF in drug resistance of HCC

Conclusions

Taken together, our findings showed that novel mRNAs and TFs, which served as critical biomarkers to predict survival and therapeutic targets of resistance to sorafenib in HCC. Furthermore, we constructed the TF-mRNA networks, which provides valuable theoretical references to further evaluate the molecular mechanisms of resistance to sorafenib in HCC.

中文翻译：

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肝细胞癌中与索拉非尼耐药相关的分子机制的综合网络分析。

目的

肝细胞癌（HCC）是一种难治性疾病，因为长期化疗后，HCC患者经常出现索拉非尼耐药。尽管研究表明可获得关于耐药患者的累积信息，但对逆转索拉非尼耐药性的策略和分子机制知之甚少。在这里，本研究确定了与肝癌索拉非尼耐药相关的关键mRNA和转录因子（TFs），并评估了HCC异种移植小鼠网络中耐药基因与TFs之间的显着相关性。

方法

利用癌症基因组图谱（TCGA）和基因表达综合（GEO）的RNA-Seq数据，比较索拉非尼获得的耐药组织和索拉非尼敏感组织之间的mRNA表达谱。进行了基因本体论和KEGG通路分析以研究显着失调的mRNA的生物学功能。此外，进行了Kaplan-Meier生存分析以评估mRNA对过度生存的影响。随后，使用TRANSFAC预测TF，并使用cytoscape软件可视化TF-mRNA调控网络。

结果

与对照相比，发现在索拉非尼获得性耐药组织中共有827个mRNA差异表达。此后，功能富集分析的结果显示参与抗药性信号传导途径的mRNA失调，包括MAPK，JAK-STAT，TGF-β和药物代谢细胞色素P450信号传导途径。根据生存分析，CDK1，CDKN1A和TAPBP可能是肝癌对索拉非尼耐药的预后标志。此外，构建了TF-mRNA网络。预计有18个TF调控差异表达的mRNA，这在功能异常的基因网络的调控中起着至关重要的作用。NFKB1在TF-mRNA网络中呈最高程度的结节出现，而MYC被预测为HCC耐药的预后性TF

结论

综上所述，我们的研究结果表明，新颖的mRNA和TF作为预测HCC对索拉非尼耐药的生存率和治疗靶标的关键生物标志物。此外，我们构建了TF-mRNA网络，为进一步评估HCC对索拉非尼耐药的分子机制提供了有价值的理论参考。