Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and the Berlin Institute of Health, Berlin, Germany.
Klinik für Augenheilkunde, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
PLoS One. 2020 Nov 16;15(11):e0242263. doi: 10.1371/journal.pone.0242263. eCollection 2020.
Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Many previous studies have demonstrated that the infiltrating of immune and stromal cells in the tumor microenvironment contributes significantly to prognosis.
Dataset TCGA-UVM, download from TCGA portal, was taken as the training cohort, and GSE22138, obtained from GEO database, was set as the validation cohort. ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to initial screen for potential prognostic genes. Then these genes entered into the validation cohort for validation using the same methods as that in the training cohort. Moreover, we conducted correlation analyses between the genes obtained in the validation cohort and the status of chromosome 3, chromosome 8q, and tumor metastasis to get prognosis genes. At last, the immune infiltration analysis was performed between the prognostic genes and 6 main kinds of tumor-infiltrating immune cells (TICs) for understanding the role of the genes in the tumor microenvironment.
959 intersection DEGs were found in the UM microenvironment. Kaplan-Meier and Cox analysis was then performed in the training and validation cohorts on these DEGs, and 52 genes were identified with potential prognostic value. After comparing the 52 genes to chromosome 3, chromosome 8q, and metastasis, we obtained 21 genes as the prognostic genes. The immune infiltration analysis showed that Neutrophil had the potential prognostic ability, and almost every prognostic gene we had identified was correlated with abundances of Neutrophil and CD8+ T Cell.
Identifying 21 prognosis genes (SERPINB9, EDNRB, RAPGEF3, HFE, RNF43, ZNF415, IL12RB2, MTUS1, NEDD9, ZNF667, AZGP1, WARS, GEM, RAB31, CALHM2, CA12, MYEOV, CELF2, SLCO5A1, ISM1, and PAPSS2) could accurately identify patients' prognosis and had close interactions with Neutrophil in the tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.
葡萄膜黑色素瘤（UM）是成人中最常见的原发性眼内恶性肿瘤。许多先前的研究表明，肿瘤微环境中免疫细胞和基质细胞的浸润对预后有重要贡献。
从 TCGA 数据库下载 TCGA-UVM 数据集作为训练队列，从 GEO 数据库下载 GSE22138 数据集作为验证队列。应用 ESTIMATE 算法在肿瘤微环境中寻找交集差异表达基因（DEGs）。对交集 DEGs 进行 Kaplan-Meier 分析和单因素 Cox 回归模型，初步筛选潜在的预后基因。然后，使用与训练队列相同的方法，将这些基因输入验证队列进行验证。此外，我们对验证队列中获得的基因与染色体 3、8q 染色体和肿瘤转移的状态进行相关性分析，以获得预后基因。最后，对预后基因与 6 种主要肿瘤浸润免疫细胞（TICs）之间的免疫浸润进行分析，以了解基因在肿瘤微环境中的作用。
在 UM 微环境中发现了 959 个交集 DEGs。然后在训练和验证队列中对这些 DEGs 进行 Kaplan-Meier 和 Cox 分析，确定了 52 个具有潜在预后价值的基因。将 52 个基因与染色体 3、8q 染色体和转移进行比较后，我们获得了 21 个预后基因。免疫浸润分析表明，中性粒细胞具有潜在的预后能力，我们确定的几乎每个预后基因都与中性粒细胞和 CD8+T 细胞的丰度相关。
确定了 21 个预后基因（SERPINB9、EDNRB、RAPGEF3、HFE、RNF43、ZNF415、IL12RB2、MTUS1、NEDD9、ZNF667、AZGP1、WARS、GEM、RAB31、CALHM2、CA12、MYEOV、CELF2、SLCO5A1、ISM1 和 PAPSS2）可以准确识别患者的预后，并与肿瘤环境中的中性粒细胞密切相互作用，这可能为 UM 患者提供个性化的预后预测和新的治疗见解。
