Department of Molecular Medicine, Institute of Medical Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.
Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
PLoS One. 2020 May 29;15(5):e0233717. doi: 10.1371/journal.pone.0233717. eCollection 2020.
Metastasis is known as a key step in cancer recurrence and could be stimulated by multiple factors. Calumenin (CALU) is one of these factors which has a direct impact on cancer metastasis and yet, its underlined mechanisms have not been completely elucidated. The current study was aimed to identify CALU co-expressed genes, their signaling pathways, and expression status within the human cancers. To this point, CALU associated genes were visualized using the Cytoscape plugin BisoGenet and annotated with the Enrichr web-based application. The list of CALU related diseases was retrieved using the DisGenNet, and cancer datasets were downloaded from The Cancer Genome Atlas (TCGA) and analyzed with the Cufflink software. ROC curve analysis was used to estimate the diagnostic accuracy of DEGs in each cancer, and the Kaplan-Meier survival analysis was performed to plot the overall survival of patients. The protein level of the signature biomarkers was measured in 40 biopsy specimens and matched adjacent normal tissues collected from CRC and lung cancer patients. Analysis of CALU co-expressed genes network in TCGA datasets indicated that the network is markedly altered in human colon (COAD) and lung (LUAD) cancers. Diagnostic accuracy estimation of differentially expressed genes showed that a gene panel consisted of CALU, AURKA, and MCM2 was able to successfully distinguish cancer tumors from healthy samples. Cancer cases with abnormal expression of the signature genes had a significantly lower survival rate than other patients. Additionally, comparison of CALU, AURKA, and MCM2 proteins between healthy samples, early and advanced tumors showed that the level of these proteins was increased through normal-carcinoma transition in both types of cancers. These data indicate that the interactions between CALU, AURKA, and MCM2 has a pivotal role in cancer development, and thereby needs to be explored in the future.
转移被认为是癌症复发的关键步骤，可能受到多种因素的刺激。钙结合蛋白（CALU）就是其中之一，它直接影响癌症转移，但它的潜在机制尚未完全阐明。本研究旨在鉴定 CALU 共表达基因及其信号通路，并在人类癌症中检测其表达状态。为此，使用 Cytoscape 插件 BisoGenet 可视化 CALU 相关基因，并使用基于网络的 Enrichr 应用程序对其进行注释。使用 DisGenNet 检索与 CALU 相关的疾病列表，并从癌症基因组图谱 (TCGA) 下载癌症数据集，然后使用 Cufflink 软件进行分析。使用 ROC 曲线分析估计每个癌症中差异表达基因的诊断准确性，并进行 Kaplan-Meier 生存分析以绘制患者的总体生存率。使用 40 份结直肠癌和肺癌患者的活检标本及其匹配的相邻正常组织测量了标志生物标志物的蛋白水平。TCGA 数据集 CALU 共表达基因网络分析表明，该网络在人结肠（COAD）和肺（LUAD）癌中明显改变。差异表达基因诊断准确性估计表明，由 CALU、AURKA 和 MCM2 组成的基因面板能够成功地区分癌症肿瘤与健康样本。具有标志基因异常表达的癌症病例的生存率明显低于其他患者。此外，CALU、AURKA 和 MCM2 蛋白在健康样本、早期和晚期肿瘤之间的比较表明，在这两种癌症中，这些蛋白的水平在正常-癌转变过程中升高。这些数据表明，CALU、AURKA 和 MCM2 之间的相互作用在癌症发展中起着关键作用，因此需要在未来进行探索。
