Itzel Timo, Scholz Peter, Maass Thorsten, Krupp Markus, Marquardt Jens U, Strand Susanne, Becker Diana, Staib Frank, Binder Harald, Roessler Stephanie, Wang Xin Wei, Thorgeirsson Snorri, Müller Martina, Galle Peter R, Teufel Andreas
Department of Medicine I, University of Regensburg, 93053, Regensburg, Department of Medicine I, Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55131, Mainz, Department of Pathology, University of Heidelberg, 69120, Germany and Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, 20892 MD, USA.
Bioinformatics. 2015 Jan 15;31(2):216-24. doi: 10.1093/bioinformatics/btu586. Epub 2014 Sep 18.
Co-regulated genes are not identified in traditional microarray analyses, but may theoretically be closely functionally linked [guilt-by-association (GBA), guilt-by-profiling]. Thus, bioinformatics procedures for guilt-by-profiling/association analysis have yet to be applied to large-scale cancer biology. We analyzed 2158 full cancer transcriptomes from 163 diverse cancer entities in regard of their similarity of gene expression, using Pearson's correlation coefficient (CC). Subsequently, 428 highly co-regulated genes (|CC| ≥ 0.8) were clustered unsupervised to obtain small co-regulated networks. A major subnetwork containing 61 closely co-regulated genes showed highly significant enrichment of cancer bio-functions. All genes except kinesin family member 18B (KIF18B) and cell division cycle associated 3 (CDCA3) were of confirmed relevance for tumor biology. Therefore, we independently analyzed their differential regulation in multiple tumors and found severe deregulation in liver, breast, lung, ovarian and kidney cancers, thus proving our GBA hypothesis. Overexpression of KIF18B and CDCA3 in hepatoma cells and subsequent microarray analysis revealed significant deregulation of central cell cycle regulatory genes. Consistently, RT-PCR and proliferation assay confirmed the role of both genes in cell cycle progression. Finally, the prognostic significance of the identified KIF18B- and CDCA3-dependent predictors (P = 0.01, P = 0.04) was demonstrated in three independent HCC cohorts and several other tumors. In summary, we proved the efficacy of large-scale guilt-by-profiling/association strategies in oncology. We identified two novel oncogenes and functionally characterized them. The strong prognostic importance of downstream predictors for HCC and many other tumors indicates the clinical relevance of our findings.
Supplementary data are available at Bioinformatics online.
在传统的微阵列分析中无法识别共同调控的基因，但从理论上讲，它们在功能上可能紧密相连[关联有罪（GBA），特征有罪]。因此，用于特征有罪/关联分析的生物信息学程序尚未应用于大规模癌症生物学研究。我们使用Pearson相关系数（CC）分析了来自163种不同癌症实体的2158个完整癌症转录组的基因表达相似性。随后，对428个高度共同调控的基因（|CC|≥0.8）进行无监督聚类，以获得小的共同调控网络。一个包含61个紧密共同调控基因的主要子网显示出癌症生物功能的高度显著富集。除驱动蛋白家族成员18B（KIF18B）和细胞分裂周期相关3（CDCA3）外，所有基因均与肿瘤生物学具有已证实的相关性。因此，我们独立分析了它们在多种肿瘤中的差异调控，发现在肝癌、乳腺癌、肺癌、卵巢癌和肾癌中存在严重失调，从而证明了我们的GBA假设。在肝癌细胞中过表达KIF18B和CDCA3，随后进行微阵列分析，发现中心细胞周期调控基因存在显著失调。一致地，RT-PCR和增殖试验证实了这两个基因在细胞周期进程中的作用。最后，在三个独立的肝癌队列和其他几种肿瘤中证明了所鉴定的KIF18B和CDCA3依赖性预测因子的预后意义（P = 0.01，P = 0.04）。总之，我们证明了大规模特征有罪/关联策略在肿瘤学中的有效性。我们鉴定了两个新的癌基因并对其进行了功能表征。下游预测因子对肝癌和许多其他肿瘤具有很强的预后重要性，表明我们的发现具有临床相关性。
补充数据可在《生物信息学》在线获取。
