Department of Gastroenterology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325000, China.
Department of Pharmacy, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310000, China.
Dis Markers. 2020 May 11;2020:8974793. doi: 10.1155/2020/8974793. eCollection 2020.
A growing body of evidence has indicated that behaviors of cancers are defined by not only intrinsic activities of tumor cells but also tumor-infiltrating immune cells (TIICs) in the tumor microenvironment. However, it still lacks a well-structured and comprehensive analysis of TIICs and its therapeutic value in esophageal cancer (EC). The proportions of 22 TIICs were evaluated between 150 normal tissues and 141 tumor tissues of EC by the CIBERSORT algorithm. Besides, correlation analyses between proportions of TIICs and clinicopathological characters, including age, gender, histologic grade, tumor location, histologic type, LRP1B mutation, TP53 mutation, tumor stage, lymph node stage, and TNM stage, were conducted. We constructed a risk score model to improve prognostic capacity with 5 TIICs by least absolute shrinkage and selection operator (lasso) regression analysis. The risk score = -1.86∗plasma + 2.56∗T cell follicular helper - 1.37∗monocytes - 3.64∗activated dendritic cells - 2.24∗resting mast cells (immune cells in the risk model mean the proportions of immune cell infiltration in EC). Patients in the high-risk group had significantly worse overall survival than these in the low-risk group (HR: 2.146, 95% CI: 1.243-3.705, = 0.0061). Finally, we identified Semustine and Sirolimus as two candidate compounds for the treatment of EC based on CMap analysis. In conclusion, the proportions of TIICs may be important to the progression, prognosis, and treatment of EC.
越来越多的证据表明,癌症的行为不仅由肿瘤细胞的固有活性决定,还由肿瘤微环境中的肿瘤浸润免疫细胞(TIICs)决定。然而,目前仍然缺乏对 TIICs 及其在食管癌(EC)中的治疗价值的结构化和全面分析。通过 CIBERSORT 算法评估了 22 种 TIIC 在 150 份正常组织和 141 份 EC 肿瘤组织中的比例。此外,还进行了 TIIC 比例与临床病理特征(包括年龄、性别、组织学分级、肿瘤部位、组织学类型、LRP1B 突变、TP53 突变、肿瘤分期、淋巴结分期和 TNM 分期)之间的相关性分析。我们通过最小绝对收缩和选择算子(lasso)回归分析构建了一个风险评分模型,该模型使用 5 种 TIIC 来提高预后能力。风险评分= -1.86∗血浆+2.56∗T 细胞滤泡辅助-1.37∗单核细胞-3.64∗激活树突状细胞-2.24∗静止肥大细胞(风险模型中的免疫细胞是指 EC 中免疫细胞浸润的比例)。高风险组患者的总生存率明显低于低风险组(HR:2.146,95%CI:1.243-3.705, = 0.0061)。最后,我们通过 CMap 分析确定了司莫司汀和西罗莫司两种候选化合物用于治疗 EC。总之,TIICs 的比例可能对 EC 的进展、预后和治疗很重要。