PDF(Pubmed)
Abstract：
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.
摘要：
背景：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，以寻找预后标志物并验证其与UPR的联系。
方法：单变量cox分析用于筛选预后相关的UPR，并通过机器学习进一步筛选其中的关键UPR。ssGSEA用于计算免疫细胞丰度。单变量cox分析用于筛选预后相关的免疫细胞。多因素cox分析计算UPR评分和肿瘤免疫微环境评分(TIME评分)。WGCNA用于筛选UPR-免疫相关(UI相关)基因。使用共识聚类分析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。使用单细胞分析来分析UI相关基因的作用。我们通过细胞计数和transwell检测了TIMP1的功能。免疫印迹用于检测TIMP1是否受关键UPR基因调控。
结果：结合UPR相关基因和免疫细胞可以确定COAD患者的预后。聚类分析显示UI相关基因与COAD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起作用。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，促进结肠癌的增殖和转移。
结论：我们发现TIMP1是预后标志物，并通过实验证实TIMP1受UPR关键基因调控。
方法：单变量cox分析用于筛选预后相关的UPR，并通过机器学习进一步筛选其中的关键UPR。ssGSEA用于计算免疫细胞丰度。单变量cox分析用于筛选预后相关的免疫细胞。多因素cox分析计算UPR评分和肿瘤免疫微环境评分(TIME评分)。WGCNA用于筛选UPR-免疫相关(UI相关)基因。使用共识聚类分析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。使用单细胞分析来分析UI相关基因的作用。我们通过细胞计数和transwell检测了TIMP1的功能。免疫印迹用于检测TIMP1是否受关键UPR基因调控。
结果：结合UPR相关基因和免疫细胞可以确定COAD患者的预后。聚类分析显示UI相关基因与COAD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起作用。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，促进结肠癌的增殖和转移。
结论：我们发现TIMP1是预后标志物，并通过实验证实TIMP1受UPR关键基因调控。
