Suppr超能文献

探索泛素化相关分子分类及特征以预测结肠癌的生存及免疫微环境。

Exploration of the ubiquitination-related molecular classification and signature to predict the survival and immune microenvironment in colon cancer.

作者信息

Xu Ji-Zhong, Wan Tian-Qi, Su Jin-Song, Song Jun-Min

机构信息

Department of Colorectal Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

出版信息

Front Genet. 2024 Aug 29;15:1292249. doi: 10.3389/fgene.2024.1292249. eCollection 2024.

Abstract

BACKGROUND

Ubiquitination, a major post-translational modification, significantly impacts tumorigenesis, progression, and prognosis. This study aims to classify colon cancer at the molecular level and create a reliable signature using ubiquitination-related genes (URGs) to assess the immune microenvironment and prognosis.

METHODS

We employed non-negative matrix factorization to subtype colon cancer based on ubiquitination-related gene (URG) expression patterns. Quantitative scores for 28 immune cell infiltrates and the tumor microenvironment were computed using single-sample gene set enrichment analysis (ssGSEA) and the Estimate algorithm. Subtype feature genes were selected through Lasso logistic regression and SVM-RFE algorithm. The ubiquitination-related signature was constructed using univariate Cox, Lasso, and stepwise regression methods to categorize patients into high and low-risk groups. Validation included log-rank tests, receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and external dataset validation. Immune therapy response was compared using Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenoscore (IPS), and submap analyses. Clinical variables and risk scores were integrated into an enhanced nomogram. The early diagnostic value of four URGs was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry. The cell proliferation was assessed through colony formation, EdU staining, and xenograft tumorigenesis assays.

RESULTS

Prognostic ubiquitination-related genes (URGs) stratified patients into subtypes, revealing differences in survival, immune cell infiltration, and pathological staging. A signature of 6 URGs (ARHGAP4, MID2, SIAH2, TRIM45, UBE2D2, WDR72) was identified from 57 subtype-related genes. The high-risk group exhibited characteristics indicative of enhanced epithelial-mesenchymal transition, immune escape, immunosuppressive myeloid-derived suppressor cells, regulatory T cell infiltration, and lower immunogenicity. In contrast, the low-risk group demonstrated the opposite trend but showed a better response to CTLA4 checkpoint inhibitors. The predictive performance of the nomogram significantly improved with the integration of risk score, stage, and age. ARHGAP4 and SIAH2 exhibit promising early diagnostic capabilities. Additionally, WDR72 knockdown significantly inhibited CRC cell proliferation both and .

CONCLUSION

Our developed ubiquitination-related signature and genes serve as promising biomarkers for colon cancer prognosis, immune microenvironment, and diagnosis.

摘要

背景

泛素化是一种主要的翻译后修饰,对肿瘤发生、发展和预后有重大影响。本研究旨在在分子水平上对结肠癌进行分类,并利用泛素化相关基因(URGs)创建一个可靠的特征来评估免疫微环境和预后。

方法

我们基于泛素化相关基因(URG)表达模式,采用非负矩阵分解对结肠癌进行亚型分类。使用单样本基因集富集分析(ssGSEA)和Estimate算法计算28种免疫细胞浸润和肿瘤微环境的定量分数。通过Lasso逻辑回归和支持向量机递归特征消除(SVM-RFE)算法选择亚型特征基因。使用单变量Cox、Lasso和逐步回归方法构建泛素化相关特征,将患者分为高风险组和低风险组。验证包括对数秩检验、受试者工作特征(ROC)分析、决策曲线分析(DCA)和外部数据集验证。使用肿瘤免疫功能障碍和排除(TIDE)、免疫表型评分(IPS)和亚图分析比较免疫治疗反应。将临床变量和风险评分整合到一个增强的列线图中。通过定量实时聚合酶链反应(qRT-PCR)和免疫组织化学证实了4个URGs的早期诊断价值。通过集落形成、EdU染色和异种移植瘤形成试验评估细胞增殖。

结果

预后泛素化相关基因(URGs)将患者分为不同亚型,揭示了生存、免疫细胞浸润和病理分期的差异。从57个亚型相关基因中鉴定出6个URGs(ARHGAP4、MID2、SIAH2、TRIM45、UBE2D2、WDR72)的特征。高风险组表现出上皮-间质转化增强、免疫逃逸、免疫抑制性骨髓来源的抑制细胞、调节性T细胞浸润和较低免疫原性的特征。相比之下,低风险组表现出相反的趋势,但对CTLA4检查点抑制剂的反应更好。列线图的预测性能随着风险评分、分期和年龄的整合而显著提高。ARHGAP4和SIAH2具有良好的早期诊断能力。此外,WDR72敲低在体内和体外均显著抑制结直肠癌细胞增殖。

结论

我们开发的泛素化相关特征和基因有望作为结肠癌预后、免疫微环境和诊断的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f4/11390591/6e1f88da2657/fgene-15-1292249-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验