Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Biomedical Research Center, 1218 S. Fifth Avenue, Monrovia, CA, 91016, USA.
Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Gastric Cancer. 2021 May;24(3):655-665. doi: 10.1007/s10120-021-01155-y. Epub 2021 Feb 1.
Diffuse type gastric cancer (DGC), represented by low sensitivity to chemotherapy and poor prognosis, is a heterogenous malignancy in which patient subsets exhibit diverse oncological risk-profiles. This study aimed to develop molecular biomarkers for robust prognostic risk-stratification and improve survival outcomes in patients with diffuse type gastric cancer (DGC).
We undertook a systematic and comprehensive discovery and validation effort to identify recurrence prediction biomarkers by analyzing genome-wide transcriptomic profiling data from 157 patients with DGC, followed by their validation in 254 patients from 2 clinical cohorts.
Genome-wide transcriptomic profiling identified a 7-gene panel for robust prediction of recurrence in DGC patients (AUC = 0.91), which was successfully validated in an independent dataset (AUC = 0.86). Examination of 180 specimens from a training cohort allowed us to establish a gene-based risk prediction model (AUC = 0.78; 95% CI 0.71-0.84), which was subsequently validated in an independent cohort of 74 GC patients (AUC = 0.83; 95% CI 0.72-0.90). The Kaplan-Meier analyses exhibited a consistently superior performance of our risk-prediction model in the identification of high- and low-risk patient subgroups, which was significantly improved when we combined our gene signature with the tumor stage in both clinical cohorts (AUC of 0.83 in the training cohort and 0.89 in the validation cohort). Finally, for an easier clinical translation, we established a nomogram that robustly predicted prognosis in patients with DGC.
Our novel transcriptomic signature for risk-stratification and identification of high-risk patients with recurrence could serve as an important clinical decision-making tool in patients with DGC.
弥漫型胃癌（DGC）以对化疗的低敏感性和预后不良为特征，是一种异质性恶性肿瘤，其中患者亚组表现出不同的肿瘤风险特征。本研究旨在为弥漫型胃癌（DGC）患者建立稳健的预后风险分层的分子生物标志物，并改善其生存结局。
我们通过分析来自 157 名 DGC 患者的全基因组转录组谱数据，进行了系统而全面的发现和验证工作，以确定复发预测生物标志物，并在来自 2 个临床队列的 254 名患者中进行了验证。
全基因组转录组谱分析确定了一个用于 DGC 患者复发稳健预测的 7 基因组合（AUC=0.91），该组合在独立数据集（AUC=0.86）中得到成功验证。在一个训练队列的 180 个标本中进行检查，使我们能够建立一个基于基因的风险预测模型（AUC=0.78；95%CI 0.71-0.84），该模型随后在一个独立的 74 名 GC 患者队列（AUC=0.83；95%CI 0.72-0.90）中得到验证。Kaplan-Meier 分析显示，我们的风险预测模型在识别高风险和低风险患者亚组方面表现出一致的优越性，当我们将基因特征与两个临床队列中的肿瘤分期相结合时，这种优越性得到了显著改善（在训练队列中的 AUC 为 0.83，在验证队列中的 AUC 为 0.89）。最后，为了更方便地进行临床转化，我们建立了一个诺模图，能够稳健地预测 DGC 患者的预后。
我们用于风险分层和识别复发高风险患者的新型转录组特征，可以作为 DGC 患者的重要临床决策工具。
