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Stage-Specific Co-expression Network Analysis for Cancer Biomarker Discovery

机译:癌症生物标志物发现的阶段特定的共表达网络分析

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Identification of conserved gene network modules in different stages of cancer may lead to uncovering mechanisms behind cancer initiation and progression. This work is based on two hypotheses. Hypothesis-l: the network modules conserved in all cancer stages are potential biomarkers related to the trajectory of cancer development or progression of cancer from initiation to stage-to-stage to metastasis. Hypothesis-2: The network modules from a stage, which are not conserved in other stages, can be considered as the stage-specific biomarkers for diagnosis.To test the hypotheses, gene expression and clinical data of Breast Invasive Carcinoma (BRCA) from The Cancer Genome Atlas (TCGA) were used for analysis. Gene expression data was divided into five groups- stage I to stage IV and normal tissue samples. First, the co-expression networks for each of the four stages and normal samples were generated. Second, the modules from each of the stage-specific networks were discovered using weighted gene co-expression network analysis (WGCNA). Third, survival analysis was performed to identify the prognostically significant modules. Fourth, module preservation analysis was performed to determine whether a module from one stage is preserved in other cancer stages as well as in normal stage. Finally, gene ontology and pathway enrichment analyses were performed for the prognostically significant and conserved modules.The present study discovered several gene-network modules for breast cancer preserved in all cancer stages and are significant in overall survival; hence, they can be considered potential biomarkers for cancers, related to the trajectory of cancer development. The modules that were found not to be conserved in different stages can be considered as stage-specific biomarkers.
机译:的癌症不同阶段的保守基因网络模块标识可导致后面癌症引发和进展的机制揭开。这项工作是基于两个假设。假设-L:在所有癌症阶段保守的网络模块是与癌症的发展或从引发癌症进展的轨迹到阶段到阶段转移潜在生物标志物。假设-2:从阶段的网络模块,其未在其他阶段保守的,可以被认为是从该阶段特异性生物标记diagnosis.To试验的假设,基因表达和乳腺浸润性癌(BRCA)的临床数据癌症基因组图谱(TCGA)用于分析。基因表达数据分成五个组 - 阶段I到IV期和正常组织样品。首先,生成用于每个的四个阶段和正常样品的共表达网络。其次,从各阶段特异性网络的模块使用加权基因共表达网络分析(WGCNA)被发现。三,进行生存分析,找出预后显著模块。第四,进行模块保护分析,以确定在其它癌症阶段以及在正常阶段从一个阶段的模块是否被保留。最后,基因本体和途径富集分析的预后显著和保守modules.The本研究进行发现乳腺癌的几个基因网络模块保存在所有癌症阶段,在总体生存显著;因此,它们可以被认为是癌症的潜在生物标志物,与癌症发展的轨迹。发现不使模块在不同的阶段可以被认为是阶段特异性生物标志物是保守的。

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