一种新型的肿瘤纯度和免疫浸润相关模型，用于预测前列腺癌的无远处转移生存。
A novel tumor purity and immune infiltration-related model for predicting distant metastasis-free survival in prostate cancer.
机构信息
School of Engineering Medicine, Beihang University, Beijing, 100191, China.
Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology, People's Republic of China, Beijing, 100191, China.
出版信息
Eur J Med Res. 2023 Nov 28;28(1):545. doi: 10.1186/s40001-023-01522-8.
BACKGROUND
umor cells, immune cells and stromal cells jointly modify tumor development and progression. We aim to explore the potential effects of tumor purity on the immune microenvironment, genetic landscape and prognosis in prostate cancer (PCa).
METHODS
Tumor purity of prostate cancer patients was extracted from The cancer genome atlas (TCGA). Immune cellular proportions were calculated by the CIBERSORT. To identify critical modules related to tumor purity, we used weighted gene co-expression network analysis (WGCNA). Using STRING and Cytoscape, protein-protein interaction (PPI) networks were constructed and analyzed. A Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) enrichment analysis of identified modules was conducted. To identify the expression of key genes at protein levels, we used the Human Protein Atlas (HPA) platform.
RESULTS
A model of tumor purity score (TPS) was constructed in the gene expression omnibus series (GSE) 116,918 cohort. TCGA cohort served as a validation set and was employed to validate the TPS. TPS model, as an independent prognostic factor of distant metastasis-free survival (DMFS) in PCa. Patients had higher tumor purity and better prognosis in the low-TPS group. Tumor purity was related to the infiltration of mast cells and macrophage cells positively, whereas related to the infiltration of dendritic cells, T cells and B cells negatively in PCa. The nomogram based on TPS, Age, Gleason score and T stage had a good predictive value and could evaluate the prognosis of PCa metastasis. GO and KEGG enrichment analyses showed that hub genes mainly participate in T cell activation and T-helper lymphocytes (TH) differentiation. Hub genes were mainly enriched in primary immunodeficiency disease, according to DO analysis. SLAMF8 was identified as the most critical gene by Cytoscape and HPA analysis.
CONCLUSIONS
Dynamic changes in the immune microenvironment associated with tumor purity could correlate with a poor DMFS of low-purity PCa. The TPS can predict the DMFS of PCa. In addition, prostate cancer metastases may be related to immunosuppression caused by a disorder of the immune microenvironment.
背景
肿瘤细胞、免疫细胞和基质细胞共同改变肿瘤的发生和发展。我们旨在探索肿瘤纯度对前列腺癌（PCa）免疫微环境、遗传景观和预后的潜在影响。
方法
从癌症基因组图谱（TCGA）中提取前列腺癌患者的肿瘤纯度。通过 CIBERSORT 计算免疫细胞比例。为了确定与肿瘤纯度相关的关键模块，我们使用加权基因共表达网络分析（WGCNA）。使用 STRING 和 Cytoscape 构建和分析蛋白质-蛋白质相互作用（PPI）网络。对鉴定模块进行基因本体论（GO）、京都基因与基因组百科全书（KEGG）通路、疾病本体论（DO）和基因集富集分析（GSEA）富集分析。为了鉴定关键基因在蛋白质水平上的表达，我们使用了人类蛋白质图谱（HPA）平台。
结果
在基因表达综合数据集（GSE）116918 队列中构建了肿瘤纯度评分（TPS）模型。TCGA 队列作为验证集，用于验证 TPS。TPS 模型作为 PCa 远处无转移生存（DMFS）的独立预后因素。在低 TPS 组中，患者的肿瘤纯度更高，预后更好。在 PCa 中，肿瘤纯度与肥大细胞和巨噬细胞浸润呈正相关，而与树突状细胞、T 细胞和 B 细胞浸润呈负相关。基于 TPS、年龄、Gleason 评分和 T 分期的列线图具有良好的预测价值，可以评估 PCa 转移的预后。GO 和 KEGG 富集分析表明，枢纽基因主要参与 T 细胞激活和 T 辅助淋巴细胞（TH）分化。根据 DO 分析，枢纽基因主要富集在原发性免疫缺陷病中。通过 Cytoscape 和 HPA 分析，发现 SLAMF8 是最关键的基因。
结论
与肿瘤纯度相关的免疫微环境的动态变化可能与低纯度 PCa 的 DMFS 不良相关。TPS 可以预测 PCa 的 DMFS。此外，前列腺癌转移可能与免疫微环境紊乱引起的免疫抑制有关。
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