Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Aging (Albany NY). 2020 Jun 16;12(12):11398-11415. doi: 10.18632/aging.103199.
High-grade serous ovarian cancer (HGSOC) is a heterogeneous disease with diverse clinical outcomes, highlighting a need for prognostic biomarker identification. Here, we combined tumor microenvironment (TME) scores with HGSOC characteristics to identify immune-related prognostic genes through analysis of gene expression profiles and clinical patient data from The Cancer Genome Atlas and the International Cancer Genome Consortium public cohorts. We found that high TME scores (TMEscores) based on the fractions of immune cell types correlated with better overall survival. Furthermore, differential expression analysis revealed 329 differentially expressed genes between patients with high vs. low TMEscores. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that these genes participated mainly in immune-related functions and, among them, 48 TME-related genes predicted overall survival in HGSOC. Seven of those genes were associated with prognosis in an independent HGSOC database. Finally, the two genes with the lowest -values in the prognostic analysis (GBP1, ETV7) were verified through experiments. These findings reveal specific TME-related genes that could serve as effective prognostic biomarkers for HGSOC.
高级别浆液性卵巢癌(HGSOC)是一种具有不同临床结局的异质性疾病,这凸显了识别预后生物标志物的必要性。在这里,我们通过分析来自癌症基因组图谱和国际癌症基因组联合会公共队列的基因表达谱和临床患者数据,将肿瘤微环境(TME)评分与 HGSOC 特征相结合,以确定与免疫相关的预后基因。我们发现,基于免疫细胞类型分数的高 TME 评分(TMEscores)与更好的总生存率相关。此外,差异表达分析显示,高 TME 评分组与低 TME 评分组之间存在 329 个差异表达基因。基因本体论和京都基因与基因组百科全书分析表明,这些基因主要参与免疫相关功能,其中 48 个 TME 相关基因可预测 HGSOC 的总生存率。其中 7 个基因在独立的 HGSOC 数据库中与预后相关。最后,通过实验验证了预后分析中值最低的两个基因(GBP1、ETV7)。这些发现揭示了特定的 TME 相关基因,它们可以作为 HGSOC 的有效预后生物标志物。