Discovery of a Robust Gene Regulatory Network with a Complex Transcription Factor Network on Organ Cancer Cell-line RNA Sequence Data
Discovery of a Robust Gene Regulatory Network with a Complex Transcription Factor Network on Organ Cancer Cell-line RNA Sequence Data
复制标题
DOI：
10.1273/cbij.19.32
复制
发表时间：
2019-09
影响因子：
0.3
通讯作者：
Bharata Kalbuaji;Y-h. Taguchi;A. Konagaya
中科院分区：
文献类型：
--
作者：
Bharata Kalbuaji;Y-h. Taguchi;A. Konagaya
了解癌细胞发展的基因表达分析是一个基本的，但重要的一步，以进一步我们在癌症研究中的知识。我们也可能对了解可能导致癌症发展的基因相互作用感兴趣。最重要的相互作用之一是涉及转录因子基因的调节相互作用。在本研究中，我们试图构建一个新的调控网络，模仿mRNA的转录和翻译过程。我们从四种不同的癌症类型构建了这个网络：胆管癌（BDC），肺腺癌（LUAD），结直肠癌（CRC）和肝细胞癌（HCC）。我们还整合差异表达数据，以获得差异表达基因之间的相互作用。然后，我们试图找到存在于所有癌症类型中的交叉子网络。我们认为，在交叉子网络中发现的转录因子基因可能揭示了影响癌细胞生长的重要机制。在这项研究中，我们发现，在从多个癌症数据集获得的交叉子网络的富集分析中发现了TEAD 4、IRX5、HMGA 1和E2F基因家族以及SOX基因家族中的基因。这些基因为我们指出了癌细胞中细胞周期、细胞分裂和细胞增殖机制的失调。这些基因可能成为癌症治疗的新的癌症药物靶点。
Gene expression analysis for understanding cancer cell development is a basic, but an important step, to further our knowledge in cancer research. We may also be interested in understanding gene interactions that may lead to cancer development. One of the most important interactions is a regulatory interaction that involves transcription factor genes. In this research, we are attempting to construct a new regulatory network that imitates the transcription and translation processes of mRNA. We construct this network from four different cancer types: bile-duct cancer (BDC), lung adenocarcinoma (LUAD), colorectal cancer (CRC), and hepatocyte carcinoma (HCC). We also integrate differential expression data to obtain the interactions among differentially expressed genes. We then try to find intersecting sub-networks that exist across all cancer types. We believe that the transcription factor genes found in intersection sub-networks may reveal an important mechanism that affects cancer cell growth. In this research, we found that genes, such as those in the TEAD4, IRX5, HMGA1, and E2F gene family and the SOX gene family, are found in the enrichment analysis of the intersection sub-network obtained from multiple cancer data-sets. These genes point us toward dysregulation of the cell cycle, cell division, and cell proliferation mechanisms in cancer cells. These genes may become new cancer drug targets for cancer treatment.