Kim Jin-Chul, Heo You-Jeong, Kang So-Young, Lee Jeeyun, Kim Kyoung-Mee
Samsung Medical Center, Department of Medicine, Division of Hematology-Oncology, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
Samsung Medical Center, The Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
Cancers (Basel). 2021 May 12;13(10):2316. doi: 10.3390/cancers13102316.
Although immune checkpoint inhibitors can induce durable responses in patients with multiple types of advanced cancer, only a limited number of patients have a known reliable biomarker. This study aimed to validate the IMmunotherapy Against GastrIc Cancer (IMAGiC) model, which was developed based on a previous study of four-gene and PD-L1 level, to predict immunotherapy response. We developed a clinical assay for formalin-fixed paraffin-embedded samples using quantitative real-time polymerase chain reaction to measure the expression level of the previously published four-gene set. The predictive performance was validated in a cohort of 89 patients with several advanced tumor types. The IMAGiC score was derived from tumor samples of 89 patients consisting of eight cancer types, and 73 out of 89 patients available for clinical response were analyzed with clinicopathological factors. The IMAGiC group (responder vs. non-responder) was determined with a specific value of the IMAGiC score as a cutoff, which was set by log-rank statistics for progression-free survival (PFS) divided the patients into 56 (76.7%) non-responders and 17 (23.3%) responders. Clinical responders (complete response/partial response) were higher in the IMAGiC responder group than in the non-responder group (70.6 vs. 21.4%). The median PFS of the IMAGiC responder group and non-responder was 20.8 months (95% CI 9.1-not reached) and 6.7 months (95% CI 4.9-11.1, = 0.007), respectively. Among the 17 IMAGiC responders, 11 patients had tumor mutation burden-low and microsatellite-stable tumors. This study validated a predictive model based on a four-gene expression signature. Along with conventional biomarkers, our model could be useful for predicting response to immunotherapy in patients with advanced cancer.
尽管免疫检查点抑制剂可在多种类型的晚期癌症患者中诱导持久反应，但只有少数患者具有已知的可靠生物标志物。本研究旨在验证基于先前一项关于四个基因和PD-L1水平的研究开发的抗胃癌免疫治疗（IMAGiC）模型，以预测免疫治疗反应。我们使用定量实时聚合酶链反应开发了一种针对福尔马林固定石蜡包埋样本的临床检测方法，以测量先前公布的四个基因集的表达水平。在一组89例患有多种晚期肿瘤类型的患者中验证了该预测性能。IMAGiC评分来自89例患者的肿瘤样本，这些患者包括八种癌症类型，对89例可获得临床反应的患者中的73例进行了临床病理因素分析。以IMAGiC评分的特定值作为临界值确定IMAGiC组（反应者与无反应者），该临界值通过无进展生存期（PFS）的对数秩统计设定，将患者分为56例（76.7%）无反应者和17例（23.3%）反应者。IMAGiC反应者组的临床反应者（完全缓解/部分缓解）高于无反应者组（70.6%对21.4%）。IMAGiC反应者组和无反应者组的中位PFS分别为20.8个月（95%CI 9.1-未达到）和6.7个月（95%CI 4.9-11.1，P = 0.007）。在17例IMAGiC反应者中，11例患者的肿瘤突变负荷低且微卫星稳定。本研究验证了基于四个基因表达特征的预测模型。与传统生物标志物一起，我们的模型可能有助于预测晚期癌症患者对免疫治疗的反应。
