Integrative analysis-based identification and validation of a prognostic immune cell infiltration-based model for patients with advanced gastric cancer
Integrative analysis-based identification and validation of a prognostic immune cell infiltration-based model for patients with advanced gastric cancer
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基于综合分析的晚期胃癌患者预后免疫细胞浸润模型的识别和验证
DOI：
10.1016/j.intimp.2021.108258
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发表时间：
2021-10-19
影响因子：
5.6
通讯作者：
Xu, Huimian
中科院分区：
文献类型：
--
作者：
Pan, Siwei;Gao, Qi;Xu, Huimian
背景：由于晚期胃癌（GC）肿瘤内的高度异质性和低水平的免疫细胞浸润（ICI），因此仍然难以进行个体化预后评估。因此，本研究试图开发一种能够根据肿瘤 ICI 程度对 GC 患者进行分类并评估预后的模型。方法：估计 GSE15459、GSE57303 和 GSE62254 数据集中 GC 患者的 ICI 程度，并通过无监督聚类方法对患者进行分组，然后通过 Cox 和 LASSO 回归分析确定 ICI 聚类相关基因与预后的关联。然后通过GC肿瘤组织样本的免疫组织化学染色来验证主要风险基因。结果：570 名患者分为三个簇，并鉴定出 289 个 ICI 簇相关基因。构建了基于六个关键 ICI 风险基因（CXCL11、RBPMS2、LOC400043、JCHAIN、CT83 和 ORM1）表达的预后模型。与其他患者相比，根据该模型被确定为高风险的患者的临床特征和生存结果较差。研究发现辅助干预对于表达高水平 RBPMS2、JCHAIN 或 ORM1 的患者更有益。此外，经证实，GC 肿瘤组织中表达低水平 JCHAIN 或 CT83 的患者在 CMU 队列中表现出明显更好的预后。结论：根据瘤内 ICI 程度成功地将晚期 GC 患者分组，并开发并验证了基于 6 个 ICI 风险基因的预后评估模型。
Backgrounds: Advanced gastric cancer (GC) remains difficult to conduct individualized prognostic evaluations owing to the highly heterogeneous nature and the low level of immune cell infiltration (ICI) within GC tumors. This study thus sought to develop a model capable of classifying GC patients according to the degree of tumor ICI and gauging prognosis. Methods: The degree of ICI in GC patients from the GSE15459, GSE57303, and GSE62254 datasets were estimated, and these values were used to group patients via an unsupervised clustering approach, after which ICI cluster-related genes were identified the association with prognosis through Cox and LASSO regression analyses. The primary risk genes were then verified by immunohistochemical staining of GC tumor tissue samples. Results: 570 patients were clustered into three clusters and 289 ICI cluster-related genes were identified. A prognostic model based on the expression of six crucial ICI risk genes (CXCL11, RBPMS2, LOC400043, JCHAIN, CT83, and ORM1) wa constructed. Patients identified as being high risk based upon the model have poorer clinical features and survival outcomes compared to the other patients. Adjuvant intervention was found to be more beneficial for patients expressing high levels of RBPMS2, JCHAIN, or ORM1. Furthermore, patients expressing low levels of JCHAIN or CT83 in GC tumor tissues were verified to exhibit a significantly better prognosis in a CMU cohort. Conclusion: Advanced GC patients were successfully grouped into clusters based on the degree of intratumoral ICI, and a prognostic evaluation model based on 6 ICI risk genes was developed and validated.