免疫浸润可作为食管鳞癌潜在的诊断和预后生物标志物。
Immune Infiltration Represents Potential Diagnostic and Prognostic Biomarkers for Esophageal Squamous Cell Carcinoma.
机构信息
School of Information Engineering of Henan University of Science and Technology, 263 Kaiyuan Road, Luoyang 471023, China.
Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China.
出版信息
Biomed Res Int. 2022 Jun 26;2022:9009269. doi: 10.1155/2022/9009269. eCollection 2022.
BACKGROUND
Immune infiltrates in the tumor microenvironment have established roles in tumor growth, invasion, and metastasis. However, the diagnostic and prognostic potential of immune cell signature in esophageal squamous cell carcinoma (ESCC) remains unclear.
RESULTS
The proportions of 22 subsets of immune cells from 331 samples including 205 ESCC and 126 normal esophageal mucosa retrieved from TCGA, GEO, and GTEx databases were deciphered by CIBERSORT. Nine overlapping subsets of immune cells were identified as important features for discrimination of ESCC from normal tissue in the training cohort by LASSO and Boruta algorithms. A diagnostic immune score (DIS) developed by XGBoost showed high specificities and sensitivities in the training cohort, the internal validation cohort, and the external validation cohort (AUC: 0.999, 0.813, and 0.966, respectively). Furthermore, the prognostic immune score (PIS) was developed based on naive B cells and plasma cells using Cox proportional hazards model. The PIS, an independent prognostic predictor, classified patients with ESCC into low- and high-risk subgroups in the internal validation cohort ( = 0.038) and the external validation cohort ( = 0.022). In addition, a nomogram model comprising age, N stage, TNM stage, and PIS was constructed and performed excellent (HR = 4.17, 95% CI: 2.22-7.69, < 0.0001) in all ESCC patients, with a time-dependent 5-year AUC of 0.745 (95% CI: 0.644 to 0.845), compared with PIS or TNM stage as a prognostic model alone.
CONCLUSION
Our DIS, PIS, and nomogram models based on infiltrated immune features may aid diagnosis and survival prediction for patients with ESCC.
背景
肿瘤微环境中的免疫浸润在肿瘤生长、侵袭和转移中具有重要作用。然而，免疫细胞特征在食管鳞状细胞癌（ESCC）中的诊断和预后潜力仍不清楚。
结果
通过 CIBERSORT 解析了来自 TCGA、GEO 和 GTEx 数据库的 331 个样本（包括 205 个 ESCC 和 126 个正常食管黏膜）中 22 个免疫细胞亚群的比例。通过 LASSO 和 Boruta 算法，确定了 9 个重叠的免疫细胞亚群，这些亚群是区分训练队列中 ESCC 与正常组织的重要特征。通过 XGBoost 开发的诊断免疫评分（DIS）在训练队列、内部验证队列和外部验证队列中具有较高的特异性和敏感性（AUC：0.999、0.813 和 0.966）。此外，基于幼稚 B 细胞和浆细胞的预后免疫评分（PIS）是通过 Cox 比例风险模型开发的。PIS 是一个独立的预后预测因子，可将 ESCC 患者在内部分验证队列（ = 0.038）和外部验证队列（ = 0.022）中分为低风险和高风险亚组。此外，构建了一个包含年龄、N 分期、TNM 分期和 PIS 的列线图模型，并在所有 ESCC 患者中表现出色（HR = 4.17，95%CI：2.22-7.69，<0.0001），与 PIS 或 TNM 分期作为单独的预后模型相比，其 5 年时间依赖性 AUC 为 0.745（95%CI：0.644 至 0.845）。
结论
我们基于浸润免疫特征的 DIS、PIS 和列线图模型可能有助于 ESCC 患者的诊断和生存预测。
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