Zhang Zizhen, Liu Shengde, Wang Zhenghang, Wang Shuo, Jiang Lei, Wang Xicheng, Li Jian, Shen Lin
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, China.
Cancer Cell Int. 2024 Mar 10;24(1):103. doi: 10.1186/s12935-024-03274-9.
Colorectal cancer (CRC) is a malignancy of remarkable heterogeneity and heightened morbidity. Cancer associated fibroblasts (CAFs) are abundant in CRC tissues and are essential for CRC growth. Here, we aimed to develop a CAF-related classifier for predicting the prognosis of CRC and identify critical pro-tumorigenic genes in CAFs.
The mRNA expression and clinical information of CRC samples were sourced from two comprehensive databases, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using a weighted gene co-expression network analysis (WGCNA) approach, CAF-related genes were identified and a CAF risk signature was developed through the application of univariate analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model. EdU cell proliferation assay, and transwell assay were performed to detect the oncogenic role of KCNE4 in CAFs.
We constructed a prognostic CAF model consisting of two genes (SFRP2 and KCNE4). CRC patients were classified into low- and high-CAF-risk groups using the median CAF risk score, and patients in the high-CAF-risk group had worse prognosis. Meanwhile, a higher risk score for CAFs was associated with greater stromal and CAF infiltrations, as well as higher expression of CAF markers. Furthermore, TIDE analysis indicated that patients with a high CAF risk score are less responsive to immunotherapy. Our further experiments had confirmed the strong correlation between KCNE4 and the malignant phenotypes of CAFs. Moreover, we had shown that KCNE4 could actively promote tumor-promoting phenotypes in CAFs, indicating its critical role in cancer progression.
The two-gene prognostic CAF signature was constructed and could be reliable for predicting prognosis for CRC patients. Moreover, KCNE4 may be a promising strategy for the development of novel anti-cancer therapeutics specifically directed against CAFs.
结直肠癌(CRC)是一种具有显著异质性且发病率不断上升的恶性肿瘤。癌症相关成纤维细胞(CAF)在CRC组织中大量存在,对CRC的生长至关重要。在此,我们旨在开发一种与CAF相关的分类器来预测CRC的预后,并鉴定CAF中关键的促肿瘤基因。
CRC样本的mRNA表达和临床信息来自两个综合数据库,即癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)。使用加权基因共表达网络分析(WGCNA)方法,鉴定与CAF相关的基因,并通过单变量分析和最小绝对收缩和选择算子(LASSO)Cox回归模型开发CAF风险特征。进行EdU细胞增殖试验和Transwell试验以检测KCNE4在CAF中的致癌作用。
我们构建了一个由两个基因(SFRP2和KCNE4)组成的预后CAF模型。使用中位CAF风险评分将CRC患者分为低CAF风险组和高CAF风险组,高CAF风险组的患者预后较差。同时,CAF的风险评分越高,与基质和CAF浸润程度越高以及CAF标志物的表达越高相关。此外,TIDE分析表明,CAF风险评分高的患者对免疫治疗的反应较小。我们的进一步实验证实了KCNE4与CAF的恶性表型之间存在强相关性。此外,我们已经表明KCNE4可以积极促进CAF中的促肿瘤表型,表明其在癌症进展中的关键作用。
构建了双基因预后CAF特征,可用于可靠地预测CRC患者的预后。此外,KCNE4可能是开发专门针对CAF的新型抗癌治疗药物的有前景的策略。