Ma Yuteng, Wang Zhe, Sun Jian, Tang Jingtong, Zhou Jianping, Dong Ming
Department of Gastrointestinal Surgery, First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Onco Targets Ther. 2023 Dec 11;16:1027-1042. doi: 10.2147/OTT.S428150. eCollection 2023.
Colon cancer is one of the leading causes of death worldwide, and screening of effective molecular markers for the diagnosis is prioritised for prevention and treatment. This study aimed to investigate the diagnostic and predictive potential of genes related to the lipid metabolism pathway, regulated by a protein called sterol-regulatory element-binding transcription Factor 2 (SREBF2), for colon cancer and patient outcomes.
We used machine-learning algorithms to identify key genes associated with SREBF2 in colon cancer based on a public database. A nomogram was created to assess the diagnostic value of these genes and validated in the Cancer Genome Atlas. We also analysed the relationship between these genes and the immune microenvironment of colon tumours, as well as the correlation between gene expression and clinicopathological characteristics and prognosis in the China Medical University (CMU) clinical cohort.
Three genes, , and , were identified as hub genes related to SREBF2 and colon cancer. Using the TCGA dataset, receiver operating characteristic curve analysis showed the area under the curve values of 0.943, 0.976, and 0.868 for , and , respectively. In the CMU cohort, SREBF2 and DHCR7 expression levels were correlated with TNM stage and tumour invasion depth (P < 0.05), and high DHCR7 expression was related to poor prognosis of colon cancer (P < 0.05). Furthermore, gene expression was positively correlated with the abundance of M0 and M1 macrophages and inversely correlated with the abundance of M2 macrophages, suggesting that the immune microenvironment may play a role in colon cancer surveillance. There was a correlation between and expression across cancers in the TCGA database.
This study highlights the potential of as a diagnostic marker and therapeutic target for colon cancer.
结肠癌是全球主要死因之一,因此优先筛查有效的诊断分子标志物以用于预防和治疗。本研究旨在探讨由一种名为固醇调节元件结合转录因子2(SREBF2)的蛋白质调控的、与脂质代谢途径相关的基因对结肠癌及患者预后的诊断和预测潜力。
我们基于一个公共数据库,使用机器学习算法来识别结肠癌中与SREBF2相关的关键基因。创建了一个列线图来评估这些基因的诊断价值,并在癌症基因组图谱中进行了验证。我们还分析了这些基因与结肠肿瘤免疫微环境之间的关系,以及在中国医科大学(CMU)临床队列中基因表达与临床病理特征及预后之间的相关性。
三个基因,即[此处原文缺失基因名称]、[此处原文缺失基因名称]和[此处原文缺失基因名称],被确定为与SREBF2和结肠癌相关的枢纽基因。使用TCGA数据集,受试者工作特征曲线分析显示,[此处原文缺失基因名称]、[此处原文缺失基因名称]和[此处原文缺失基因名称]的曲线下面积值分别为0.943、0.976和0.868。在CMU队列中,SREBF2和DHCR7表达水平与TNM分期和肿瘤浸润深度相关(P<0.05),且DHCR7高表达与结肠癌预后不良相关(P<0.05)。此外,[此处原文缺失基因名称]基因表达与M0和M1巨噬细胞丰度呈正相关,与M2巨噬细胞丰度呈负相关,这表明免疫微环境可能在结肠癌监测中发挥作用。在TCGA数据库中,不同癌症的[此处原文缺失基因名称]和[此处原文缺失基因名称]表达之间存在相关性。
本研究突出了[此处原文缺失基因名称]作为结肠癌诊断标志物和治疗靶点的潜力。