Xu Wei, Zhao Dongxu, Huang Xiaowei, Zhang Man, Zhu Wenxin, Xu Chunfang
Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Front Oncol. 2022 Nov 21;12:1001307. doi: 10.3389/fonc.2022.1001307. eCollection 2022.
Gastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.
Based on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.
Monocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.
In conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.
胃癌仍是世界上最致命的肿瘤疾病之一。尽管有一些改善，但胃癌患者的预后仍无法准确预测。
基于单细胞测序数据，我们对胃癌患者和正常组织进行了详细分析，以确定单核细胞在胃癌进展中的作用。加权基因共表达网络分析（WCGA）有助于我们在癌症基因组图谱（TCGA）中寻找与分级相关的基因。然后，根据单核细胞的标记基因和细胞分化基因，我们确定了单核细胞的促癌基因。基于套索回归，我们使用TCGA数据库建立了一个预后模型。通过主成分分析（PCA）、ROC曲线、生存分析和预后分析验证了该模型的准确性。最后，我们通过观察不同风险组患者的药物敏感性、免疫微环境和免疫检查点表达，评估了该模型在临床诊断和治疗中的意义。
单核细胞在肿瘤微环境中分化较差。它主要通过两种方式发挥促癌作用。一种是通过与其他肿瘤基质细胞相互作用间接促进肿瘤进展。另一种是通过巨噬细胞移动抑制因子（MIF）和肿瘤坏死因子（TNF）途径直接与肿瘤细胞连接发挥促癌作用。在这两种方式中，前者更为重要。共获得292个单核细胞促癌基因，最终12个基因被纳入预后模型的构建。多种验证方法表明我们的模型具有准确的预测能力。药物敏感性分析可为患者的临床用药提供指导。免疫微环境和免疫检查点的结果也表明了高危患者预后不良的原因。
总之，我们为胃癌患者提供了一个包含12个基因的风险评分公式和列线图，以协助临床药物治疗和预后预测。该模型具有良好的准确性和临床意义。
