Background: Fibrosis in most organs has proven to be an critical factor related to high risk of morbidity and mortality, but an adequate assessment of fibrosis severity is still challenging. This study tried to evaluate fibrosis severity through a fibrosis transcriptional signature. Methods: A fibrosis transcriptional signature was developed through an integrated analysis of multiple expression profiling datasets of human organs with fibrosis-related diseases. A fibrosis severity score for each sample was the calculated through gene set variation analysis (GSVA), and its role in evaluating fibrosis severity was then analyzed. Results: Ten expression profiling datasets of human tissues with organ failure were integrated with robust rank aggregation method, and a fibrosis severity score consisting of 149 genes. Most of those included genes were involved in fibrogenic pathways. GSEA analysis revealed that fibrosis transcriptional signature was significantly enriched in the fibrogenic tissues. Additionally, we found that fibrosis transcriptional signature could effectively differentiate fibrosis tissues and non-fibrosis tissues. Conclusion: This study developed an useful fibrosis transcriptional signature involved in fibrosis-related diseases. This fibrosis transcriptional signature is helpful in precisely evaluating the fibrosis severity in common organs at the transcriptional level.

中文翻译：

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开发和验证用于评估器官纤维化的转录签名

背景：大多数器官中的纤维化已被证明是与发病率和死亡率高风险相关的关键因素，但是对纤维化严重程度的充分评估仍然具有挑战性。这项研究试图通过纤维化转录特征来评估纤维化的严重程度。方法：通过对与纤维化相关疾病的人体器官的多表达谱数据集进行综合分析，开发出纤维化转录签名。通过基因组变异分析（GSVA）计算每个样品的纤维化严重程度评分，然后分析其在评估纤维化严重程度中的作用。结果：将十个器官衰竭的人体组织的表达谱数据集与鲁棒秩聚合方法进行了整合，纤维化严重程度评分由149个基因组成。这些基因中的大多数都参与了纤维形成途径。GSEA分析显示，纤维化的转录特征在纤维化组织中显着丰富。此外，我们发现纤维化转录签名可以有效区分纤维化组织和非纤维化组织。结论：本研究开发了一种与纤维化相关疾病有关的有用的纤维化转录特征。这种纤维化的转录特征有助于在转录水平上精确评估常见器官的纤维化严重程度。我们发现纤维化的转录特征可以有效地区分纤维化组织和非纤维化组织。结论：本研究开发了一种与纤维化相关疾病有关的有用的纤维化转录特征。这种纤维化转录特征有助于在转录水平上准确评估常见器官的纤维化严重程度。我们发现纤维化的转录特征可以有效地区分纤维化组织和非纤维化组织。结论：本研究开发了一种与纤维化相关疾病有关的有用的纤维化转录特征。这种纤维化转录特征有助于在转录水平上准确评估常见器官的纤维化严重程度。