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基于 ER 应激相关基因的系统分析鉴定 WFS1 为结肠癌的一个新的治疗靶点。

System analysis based on the ER stress-related genes identifies WFS1 as a novel therapy target for colon cancer.

机构信息

School of Life Sciences, State Key Laboratory Base of Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China.

School of Pharmacy, Key Laboratory of Nano-carbon Modified Film Technology of Henan Province, Diagnostic Laboratory of Animal Diseases, Xinxiang University, Xinxiang, Henan 453000, China.

出版信息

Aging (Albany NY). 2022 Nov 28;14(22):9243-9263. doi: 10.18632/aging.204404.

Abstract

BACKGROUND

Colon cancer (COAD) is the third-largest common malignant tumor and the fourth major cause of cancer death in the world. Endoplasmic reticulum (ER) stress has a great influence on cell growth, migration, proliferation, invasion, angiogenesis, and chemoresistance of massive tumors. Although ER stress is known to play an important role in various types of cancer, the prognostic model based on ER stress-related genes (ERSRGs) in colon cancer has not been constructed yet. In this study, we established an ERSRGs prognostic risk model to assess the survival of COAD patients.

METHODS

The COAD gene expression profile and clinical information data of the training set were obtained from the GEO database (GSE40967) and the test set COAD gene expression profile and clinical informative data were downloaded from the TCGA database. The endoplasmic reticulum stress-related genes (ERSRGs) were obtained from Gene Set Enrichment Analysis (GSEA) website. Differentially expressed ERSRGs between normal samples and COAD samples were identified by R "limma" package. Based on the univariate, lasso, and multivariate Cox regression analysis, we developed an ERSRGs prognostic risk model to predict survival in COAD patients. Finally, we verified the function of WFS1 in COAD through experiments.

RESULTS

We built a 9-gene prognostic risk model based on the univariate, lasso, and multivariate Cox regression analysis. Kaplan-Meier survival analysis and Receiver operating characteristic (ROC) curve revealed that the prognostic risk model has good predictive performance. Subsequently, we screened 60 compounds with significant differences in the estimated half-maximal inhibitory concentration (IC50) between high-risk and low-risk groups. In addition, we found that the ERSRGs prognostic risk model was related to immune cell infiltration and the expression of immune checkpoint molecules. Finally, we determined that knockdown of the expression of WFS1 inhibits the proliferation of colon cancer cells.

CONCLUSIONS

The prognostic risk model we built may help clinicians accurately predict the survival of patients with COAD. Our findings provide valuable insights into the role of ERSRGs in COAD and may provide new targets for COAD therapy.

摘要

背景

结肠癌(COAD)是世界上第三大常见恶性肿瘤和第四大癌症死亡原因。内质网(ER)应激对大量肿瘤的细胞生长、迁移、增殖、侵袭、血管生成和化疗耐药性有很大影响。尽管 ER 应激已知在各种类型的癌症中发挥重要作用,但尚未构建基于 ER 应激相关基因(ERSRGs)的结肠癌预后模型。在这项研究中,我们建立了一个 ERSRGs 预后风险模型,以评估 COAD 患者的生存情况。

方法

从 GEO 数据库(GSE40967)中获取 COAD 基因表达谱和训练集的临床信息数据,从 TCGA 数据库中下载 COAD 基因表达谱和测试集的临床信息数据。从基因集富集分析(GSEA)网站获得内质网应激相关基因(ERSRGs)。使用 R“limma”包识别正常样本和 COAD 样本之间差异表达的 ERSRGs。基于单变量、lasso 和多变量 Cox 回归分析,我们开发了一个 ERSRGs 预后风险模型,以预测 COAD 患者的生存情况。最后,我们通过实验验证了 WFS1 在 COAD 中的功能。

结果

我们基于单变量、lasso 和多变量 Cox 回归分析建立了一个 9 个基因的预后风险模型。Kaplan-Meier 生存分析和接收者操作特征(ROC)曲线表明,该预后风险模型具有良好的预测性能。随后,我们筛选了高风险和低风险组之间估计半最大抑制浓度(IC50)有显著差异的 60 种化合物。此外,我们发现 ERSRGs 预后风险模型与免疫细胞浸润和免疫检查点分子的表达有关。最后,我们确定下调 WFS1 的表达抑制了结肠癌细胞的增殖。

结论

我们构建的预后风险模型可能有助于临床医生准确预测 COAD 患者的生存情况。我们的研究结果为 ERSRGs 在 COAD 中的作用提供了有价值的见解,并可能为 COAD 的治疗提供新的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/280c/9740360/ba234e38689e/aging-14-204404-g001.jpg

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