Lai Qing, Feng Haifei
Department of Gastroenterology, The First People's Hospital of Xiaoshan Hangzhou, Hangzhou 311200, China.
Evid Based Complement Alternat Med. 2022 Aug 27;2022:3640589. doi: 10.1155/2022/3640589. eCollection 2022.
Colon cancer is one of the leading malignancies with poor prognosis worldwide. Immune cell infiltration has a potential prognostic value for colon cancer. This study aimed to establish an immune-related prognostic risk model for colon cancer by bioinformatics analysis. A total of 1670 differentially expressed genes (DEGs), including 177 immune-related genes, were identified from The Cancer Genome Atlas (TCGA) dataset. A prognostic risk model was constructed based on six critical immune-related genes (C-X-C motif chemokine ligand 1 (CXCL1), epiregulin (EREG), C-C motif chemokine ligand 24 (CCL24), fatty acid binding protein 4 (FABP4), tropomyosin 2 (TPM2), and semaphorin 3G (SEMA3G)). This model was validated using the microarray dataset GSE35982. In addition, Cox regression analysis showed that age and clinical stage were correlated with prognostic risk scores. Kaplan-Meier survival analysis showed that high risk scores correlated with low survival probabilities in patients with colon cancer. Downregulated TPM2, FABP4, and SEMA3G levels were positively associated with the activated mast cells, monocytes, and macrophages M2. Upregulated CXCL1 and EREG were positively correlated with macrophages M1 and activated T cells CD4 memory, respectively. Based on these results, we can conclude that the proposed prognostic risk model presents promising novel signatures for the diagnosis and prognosis prediction of colon cancer. This model may provide therapeutic benefits for the development of immunotherapy for colon cancer.
结肠癌是全球范围内预后较差的主要恶性肿瘤之一。免疫细胞浸润对结肠癌具有潜在的预后价值。本研究旨在通过生物信息学分析建立一种结肠癌免疫相关预后风险模型。从癌症基因组图谱（TCGA）数据集中共鉴定出1670个差异表达基因（DEG），其中包括177个免疫相关基因。基于六个关键免疫相关基因（C-X-C基序趋化因子配体1（CXCL1）、表皮调节素（EREG）、C-C基序趋化因子配体24（CCL24）、脂肪酸结合蛋白4（FABP4）、原肌球蛋白2（TPM2）和信号素3G（SEMA3G））构建了预后风险模型。使用微阵列数据集GSE35982对该模型进行了验证。此外，Cox回归分析表明年龄和临床分期与预后风险评分相关。Kaplan-Meier生存分析表明，高风险评分与结肠癌患者的低生存概率相关。TPM2、FABP4和SEMA3G水平下调分别与活化的肥大细胞、单核细胞和M2巨噬细胞呈正相关。CXCL1和EREG上调分别与M1巨噬细胞和活化的CD4记忆T细胞呈正相关。基于这些结果，我们可以得出结论，所提出的预后风险模型为结肠癌的诊断和预后预测提供了有前景的新特征。该模型可能为结肠癌免疫治疗的发展提供治疗益处。
