Department of General Surgery, Institute of General Surgery, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu Province, China.
Department of General Surgery, Institute of General Surgery, Northern Jiangsu People's Hospital, Yangzhou, China.
BMC Cancer. 2024 Aug 8;24(1):978. doi: 10.1186/s12885-024-12730-8.
The unfolded protein response (UPR) is associated with immune cells that regulate the biological behavior of tumors. This article aims to combine UPR-associated genes with immune cells to find a prognostic marker and to verify its connection to the UPR.
Univariate cox analysis was used to screen prognostically relevant UPRs and further screened for key UPRs among them by machine learning. ssGSEA was used to calculate immune cell abundance. Univariate cox analysis was used to screen for prognostically relevant immune cells. Multivariate cox analysis was used to calculate UPR_score and Tumor Immune Microenvironment score (TIME_score). WGCNA was used to screen UPR-Immune-related (UI-related) genes. Consensus clustering analysis was used to classify patients into molecular subtype. Based on the UI-related genes, we classified colon adenocarcinoma (COAD) samples by cluster analysis. Single-cell analysis was used to analyze the role of UI-related genes. We detected the function of TIMP1 by cell counting and transwell. Immunoblotting was used to detect whether TIMP1 was regulated by key UPR genes.
Combined UPR-related genes and immune cells can determine the prognosis of COAD patients. Cluster analysis showed that UI-related genes were associated with clinical features of COAD. Single-cell analysis revealed that UI-related genes may act through stromal cells. We defined three key UI-related genes by machine learning algorithms. Finally, we found that TIMP1, regulated by key genes of UPR, promoted colon cancer proliferation and metastasis.
We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.
未折叠蛋白反应(UPR)与调节肿瘤生物学行为的免疫细胞有关。本文旨在将 UPR 相关基因与免疫细胞相结合,寻找一种预后标志物,并验证其与 UPR 的关系。
采用单因素 cox 分析筛选与预后相关的 UPR,并进一步通过机器学习筛选其中的关键 UPR。ssGSEA 用于计算免疫细胞丰度。单因素 cox 分析筛选与预后相关的免疫细胞。多因素 cox 分析计算 UPR_score 和肿瘤免疫微环境评分(TIME_score)。WGCNA 用于筛选 UPR-免疫相关(UI-相关)基因。共识聚类分析用于将患者分为分子亚型。基于 UI 相关基因,我们通过聚类分析对结肠腺癌(COAD)样本进行分类。单细胞分析用于分析 UI 相关基因的作用。我们通过细胞计数和 Transwell 检测 TIMP1 的功能。免疫印迹用于检测 TIMP1 是否受关键 UPR 基因调控。
联合 UPR 相关基因和免疫细胞可以确定 COAD 患者的预后。聚类分析表明,UI 相关基因与 COAD 的临床特征相关。单细胞分析显示,UI 相关基因可能通过基质细胞发挥作用。我们通过机器学习算法定义了三个关键的 UI 相关基因。最后,我们发现 TIMP1 受 UPR 关键基因调控,促进了结肠癌的增殖和转移。
我们发现 TIMP1 是一个预后标志物,并通过实验证实 TIMP1 受 UPR 关键基因的调控。