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基于免疫的胃癌风险分层和免疫治疗疗效评估基因标志物的开发和验证。

Development and Verification of an Immune-Based Gene Signature for Risk Stratification and Immunotherapeutic Efficacy Assessment in Gastric Cancer.

机构信息

Department of Pathology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001 Heilongjiang, China.

Department of Obstetrics and Gynecology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001 Heilongjiang, China.

出版信息

Dis Markers. 2021 Nov 11;2021:4251763. doi: 10.1155/2021/4251763. eCollection 2021.

Abstract

OBJECTIVE

Due to the molecular heterogeneity of gastric cancer, only minor patients respond to immunotherapeutic schemes. This study is aimed at developing an immune-based gene signature for risk stratification and immunotherapeutic efficacy assessment in gastric cancer.

METHODS

An immune-based gene signature was developed in gastric cancer by LASSO method in the training set. The predictive performance was validated in the external datasets. KEGG pathways related to risk scores were assessed by GSEA. Based on multivariate Cox regression analysis, a nomogram was established. Sensitivity to chemotherapy drugs was evaluated between high- and low-risk samples. The relationships of risk scores with infiltration levels of immune cells, stromal scores, immune scores, immune cell subgroups, and overall response to anti-PD-L1 therapy were determined.

RESULTS

Our results showed that high risk scores were indicative of undesirable survival outcomes both in the training set ( < 0.0001) and the validation set ( = 0.002). Moreover, this signature could independently predict patients' survival (HR: 2.656 (1.919-3.676) and < 0.001). Subgroup analysis confirmed the sensitivity of this signature in predicting prognosis (all < 0.05). Cancer-related pathways were primarily enriched in high-risk samples, such as MAPK and TGF- pathways ( < 0.05). By incorporating stage and the risk score, we established a nomogram for predicting one-, three-, and five-year survival probability. Patients with high-risk scores were more sensitive to chemotherapy drugs ( < 0.05). There was heterogeneity in immune cells between high- and low-risk samples ( < 0.05). Samples with progressive disease exhibited the highest risk score, and those with complete response had the lowest risk score ( < 0.05).

CONCLUSION

This immune-based gene signature might be representative of a promising prognostic classifier for predicting risk stratification and immunotherapeutic efficacy in gastric cancer, assisting personalized therapy and follow-up plan.

摘要

目的

由于胃癌的分子异质性,只有少数患者对免疫治疗方案有反应。本研究旨在开发一种基于免疫的基因特征,用于胃癌的风险分层和免疫治疗效果评估。

方法

通过 LASSO 方法在训练集中建立基于免疫的基因特征。在外部数据集中验证预测性能。通过 GSEA 评估与风险评分相关的 KEGG 通路。基于多变量 Cox 回归分析,建立列线图。评估高风险和低风险样本之间对化疗药物的敏感性。确定风险评分与免疫细胞浸润水平、基质评分、免疫评分、免疫细胞亚群以及抗 PD-L1 治疗总体反应之间的关系。

结果

我们的结果表明,高风险评分在训练集(<0.0001)和验证集(=0.002)中均预示着不良的生存结局。此外,该特征可以独立预测患者的生存(HR:2.656(1.919-3.676),<0.001)。亚组分析证实了该特征预测预后的敏感性(均<0.05)。癌症相关通路主要富集在高风险样本中,如 MAPK 和 TGF-β通路(<0.05)。通过纳入分期和风险评分,我们建立了一个预测一年、三年和五年生存率的列线图。高风险评分的患者对化疗药物更敏感(<0.05)。高风险和低风险样本之间的免疫细胞存在异质性(<0.05)。进展性疾病样本的风险评分最高,完全缓解样本的风险评分最低(<0.05)。

结论

该基于免疫的基因特征可能是一种有前途的预后分类器,可用于预测胃癌的风险分层和免疫治疗效果,为个性化治疗和随访计划提供帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91c5/8602949/4fbc70ea5774/DM2021-4251763.001.jpg

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