Center for Gastrointestinal Research, Center for Translational Genomics and Oncology, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, 3410 Worth Street, Suite 610, Dallas, TX, 75246, USA.
Department of Gastrointestinal Surgery, Tokyo Medical and Dental University Graduate School of Medicine, Tokyo, Japan.
Mol Cancer. 2019 Feb 4;18(1):19. doi: 10.1186/s12943-019-0945-y.
The current histopathological risk-stratification criteria in colorectal cancer (CRC) patients following a curative surgery remain inadequate. In this study, we undertook a systematic, genomewide, biomarker discovery approach to identify and validate key EMT-associated genes that may facilitate recurrence prediction in CRC. Genomewide RNA expression profiling results from two datasets (GSE17538; N = 173 and GSE41258; N = 307) were used for biomarker discovery. These results were independently validated in two, large, clinical cohorts (testing cohort; N = 201 and validation cohort; N = 468). We performed Gene Set Enrichment Analysis (GSEA) for understanding the function of the candidate markers, and evaluated their correlation with the mesenchymal CMS4 subtype. We identified integrin subunit beta like 1 (ITGBL1) as a promising candidate biomarker, and its high expression associated with poor overall survival (OS) in stage I-IV patients and relapse-free survival (RFS) in stage I-III patients. Subgroup validation in multiple independent patient cohorts confirmed these findings, and demonstrated that high ITGBL1 expression correlated with shorter RFS in stage II patients. We developed a RFS prediction model which robustly predicted RFS (the area under the receiver operating curve (AUROC): 0.74; hazard ratio (HR): 2.72) in CRC patients. ITGBL1 is a promising EMT-associated biomarker for recurrence prediction in CRC patients, which may contribute to improved risk-stratification in CRC.
目前,结直肠癌(CRC)患者根治性手术后的组织病理学风险分层标准仍然不足。在这项研究中,我们采用了系统的、全基因组的、生物标志物发现方法,以确定和验证可能有助于 CRC 复发预测的关键 EMT 相关基因。来自两个数据集(GSE17538;N=173 和 GSE41258;N=307)的全基因组 RNA 表达谱结果用于生物标志物发现。这些结果在两个大型临床队列(测试队列;N=201 和验证队列;N=468)中进行了独立验证。我们进行了基因集富集分析(GSEA),以了解候选标志物的功能,并评估了它们与间质 CMS4 亚型的相关性。我们确定整合素β样 1(ITGBL1)是一种很有前途的候选生物标志物,其高表达与 I-IV 期患者的总生存期(OS)和 I-III 期患者的无复发生存期(RFS)不良相关。在多个独立的患者队列中的亚组验证证实了这些发现,并表明高 ITGBL1 表达与 II 期患者的较短 RFS 相关。我们开发了一个 RFS 预测模型,该模型在 CRC 患者中能够稳健地预测 RFS(接收者操作特征曲线下的面积(AUROC):0.74;风险比(HR):2.72)。ITGBL1 是 CRC 患者复发预测中一种很有前途的 EMT 相关生物标志物,可能有助于改善 CRC 的风险分层。