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基于免疫相关基因构建食管腺癌患者预后特征模型。

Development of a prognostic signature of patients with esophagus adenocarcinoma by using immune-related genes.

机构信息

Shihezi University School of Medicine, Shihezi, Xinjiang, China.

Department of Thoracic Surgery, Shandong Second Provincial General Hospital, Shandong ENT Hospital, Jinan, Shandong, China.

出版信息

BMC Bioinformatics. 2021 Nov 1;22(1):536. doi: 10.1186/s12859-021-04456-2.

Abstract

BACKGROUND

Esophageal adenocarcinoma (EAC) is an aggressive malignancy with a poor prognosis. The immune-related genes (IRGs) are crucial to immunocytes tumor infiltration. This study aimed to construct a IRG-related prediction signature in EAC.

METHODS

The related data of EAC patients and IRGs were obtained from the TCGA and ImmPort database, respectively. The cox regression analysis constructed the prediction signature and explored the transcription factors regulatory network through the Cistrome database. TIMER database and CIBERSORT analytical tool were utilized to explore the immunocytes infiltration analysis.

RESULTS

The prediction signature with 12 IRGs (ADRM1, CXCL1, SEMG1, CCL26, CCL24, AREG, IL23A, UCN2, FGFR4, IL17RB, TNFRSF11A, and TNFRSF21) was constructed. Overall survival (OS) curves indicate that the survival rate of the high-risk group is significantly shorter than the low-risk group (P = 7.26e-07), and the AUC of 1-, 3- and 5- year survival prediction rates is 0.871, 0.924, and 0.961, respectively. Compared with traditional features, the ROC curve of the risk score in the EAC patients (0.967) is significant than T (0.57), N (0.738), M (0.568), and Stage (0.768). Moreover, multivariate Cox analysis and Nomogram of risk score are indicated that the 1-year and 3-year survival rates of patients are accurate by the combined analysis of the risk score, Sex, M stage, and Stage (The AUC of 1- and 3-years are 0.911, and 0.853).

CONCLUSION

The 12 prognosis-related IRGs might be promising therapeutic targets for EAC.

摘要

背景

食管腺癌(EAC)是一种侵袭性恶性肿瘤,预后不良。免疫相关基因(IRGs)对免疫细胞浸润肿瘤至关重要。本研究旨在构建 EAC 的 IRG 相关预测特征。

方法

从 TCGA 和 ImmPort 数据库中分别获取 EAC 患者和 IRG 的相关数据。通过 Cistrome 数据库进行 COX 回归分析构建预测特征,并探索转录因子调控网络。利用 TIMER 数据库和 CIBERSORT 分析工具进行免疫细胞浸润分析。

结果

构建了由 12 个 IRG(ADRM1、CXCL1、SEMG1、CCL26、CCL24、AREG、IL23A、UCN2、FGFR4、IL17RB、TNFRSF11A 和 TNFRSF21)组成的预测特征。总体生存(OS)曲线表明,高危组的生存率明显短于低危组(P=7.26e-07),1、3 和 5 年生存率预测率的 AUC 分别为 0.871、0.924 和 0.961。与传统特征相比,EAC 患者风险评分的 ROC 曲线(0.967)明显优于 T(0.57)、N(0.738)、M(0.568)和分期(0.768)。此外,多变量 Cox 分析和风险评分列线图表明,通过风险评分、性别、M 期和分期的联合分析,1 年和 3 年生存率的预测较为准确(1 年和 3 年的 AUC 分别为 0.911 和 0.853)。

结论

12 个预后相关的 IRG 可能是 EAC 有前途的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/273f/8559413/2501a501dcaa/12859_2021_4456_Fig1_HTML.jpg

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