Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Cancer Gene Ther. 2020 Sep;27(9):680-690. doi: 10.1038/s41417-019-0139-1. Epub 2019 Oct 9.
Histological grading (HG) is an important prognostic factor of colorectal adenocarcinoma (CRAC): the high-grade CRAC patients have poorer prognosis after tumor resection. Especially, the high-grade stage II CRAC patients are recommended to receive adjuvant chemotherapy. Due to the subjective nature of HG assessment, it is difficult to achieve consistency among pathologists, which brings patients uncertain grading outcomes and inappropriate treatments. We developed a qualitative transcriptional signature based on the within-sample relative expression orderings (REOs) of gene pairs to discriminate high-grade and low-grade CRAC. Using the stage II-III CRAC samples, we detected gene pairs with stable REOs in the high-grade samples and reversal stable REOs in the low-grade samples, and retained the gene pairs whose specific REO patterns were significantly associated with the disease-free survival of patients by univariate Cox regression model. Then, we used a forward-backward searching procedure to extract gene pairs with the highest concordance index as the final grading signature. Finally, 9 gene pairs (9-GPS) were developed to divide CRAC patients into high-grade and low-grade groups. With the signature, there were more differential expression characteristics between reclassified high-grade and low-grade groups. Significant difference of prognosis between the classified two group patients could be seen in four independent datasets. Additionally, genomic analyses showed that the classified high-grade groups were characterized by hypermutation while classified low-grade groups were characterized by frequent copy number alternations. In conclusion, the 9-GPS can provide an objective and robust grading assessment for CRAC patients, which could assist clinical treatment decision.
组织学分级(HG)是结直肠腺癌(CRAC)的一个重要预后因素:高级别 CRAC 患者在肿瘤切除后预后较差。特别是,高级别 II 期 CRAC 患者建议接受辅助化疗。由于 HG 评估的主观性,病理学家之间难以达成一致,这给患者带来不确定的分级结果和不适当的治疗。我们基于基因对的样本内相对表达顺序(REO)开发了一种定性转录特征,以区分高低级别 CRAC。使用 II 期-III 期 CRAC 样本,我们检测到在高级别样本中具有稳定 REO 的基因对和在低级别样本中具有反转稳定 REO 的基因对,并通过单变量 Cox 回归模型保留与患者无病生存显著相关的基因对的特定 REO 模式。然后,我们使用前向-后向搜索过程提取具有最高一致性指数的基因对作为最终分级特征。最终,开发了 9 个基因对(9-GPS)将 CRAC 患者分为高低级别组。使用该特征,重新分类的高级别和低级别组之间有更多的差异表达特征。在四个独立的数据集可以看到分类后两组患者预后的显著差异。此外,基因组分析表明,分类的高级别组以超突变为特征,而分类的低级别组以频繁的拷贝数改变为特征。总之,9-GPS 可为 CRAC 患者提供客观而稳健的分级评估,有助于临床治疗决策。