Department of Gynecology and Obstetrics, The People's Hospital of China Three Gorges University, Hubei, China/The First Hospital Of Yichang.
Department of Gynecology and Obstetrics, The People's Hospital of China Three Gorges University, Hubei, China/The First Hospital Of Yichang.
Gene. 2022 Sep 5;838:146701. doi: 10.1016/j.gene.2022.146701. Epub 2022 Jun 28.
BACKGROUND: Serous ovarian cancer (SOC) is the most common type of ovarian cancer (OC), with bad outcomes. To improve the prognosis of SOC patients, a novel risk signature was developed by combining immunity- and ferroptosis-related genes. METHODS: By means of comparing SOC tissues with normal tissues, we screened the differential expression of immunity-related genes (DE-IRGs) and ferroptosis-related genes(DE-FRGs) with the standards of |logfold change| > 1 and false discovery rate (FDR) < 0.05. After obtaining the meaningful differentially expressed genes from immune and ferroptosis (DEGs), we established a prognostic risk signature by utilizing Cox regression analyses in TCGA training set, which was validated in TCGA testing set and GSE26712 dataset. Besides, the differential expression of immune-related markers, immunophenoscore (IPS), TIDE score,T cell dysfunction score and T cell exclusion score were also analyzed. We further verified the expression of target genes in ovarian tumor cells lines by QRT-PCR. RESULTS: A risk signature constructed by totally four immunity- and ferroptosis-related DEGs (CXCL11, CX3CR1, FH, and DNAJB6) was developed, which distinguished the SOC patients as high-risk and low-risk groups. Patients in the high-risk group showed a lower overall survival (OS) than those in the low-risk group. Furthermore, the risk score was independent when analyzed with clinical augments, which was significantly associated with 13 KEGG signaling pathways. The gene signature showed favorable predictive performance according to Receiver operating characteristic (ROC) curves. Notably, the expression of immune-related markers or IPS indicated a negative connection with the risk score. SOC patients had a lower score of TIDE and T cell dysfunction than Whom had a higher score. Nonetheless, there were no significant differences in T cell exclusion scores between the two groups.Compared with normal ovarian cell line IOSE-80,QRT-PCR experiments exhibited that CXCL11, CX3CR1and FH were up-regulated in ovarian tumor cells lines(SK-OV-3,COC1,A2780),while DNAJB6 was down-regulated. CONCLUSION: Four-biomarker signature formed by immunity- and ferroptosis-related genes may be clinically used as risk stratifcation tool in serous ovarian cancer,which can help further clinical decision-making regarding prognostic prediction,individualized treatment and follow-up scheduling.
背景：浆液性卵巢癌（SOC）是最常见的卵巢癌（OC）类型，预后较差。为了改善 SOC 患者的预后，通过结合免疫和铁死亡相关基因，开发了一种新的风险特征。
方法：通过比较 SOC 组织与正常组织，我们筛选出免疫相关基因（DE-IRGs）和铁死亡相关基因（DE-FRGs）的差异表达，标准为|logfold change|>1 和错误发现率（FDR）<0.05。从免疫和铁死亡（DEGs）中获得有意义的差异表达基因后，我们利用 TCGA 训练集的 Cox 回归分析建立了一个预后风险特征，并在 TCGA 测试集和 GSE26712 数据集进行了验证。此外，还分析了免疫相关标志物、免疫评分（IPS）、TIDE 评分、T 细胞功能障碍评分和 T 细胞排斥评分的差异表达。我们进一步通过 QRT-PCR 验证了靶基因在卵巢肿瘤细胞系中的表达。
结果：构建了一个由 4 个免疫和铁死亡相关 DEGs（CXCL11、CX3CR1、FH 和 DNAJB6）组成的风险特征，该特征将 SOC 患者分为高危和低危组。高危组患者的总生存期（OS）明显低于低危组。此外，在与临床指标进行分析时，风险评分是独立的，与 13 个 KEGG 信号通路显著相关。基因特征根据接收者操作特征（ROC）曲线显示出良好的预测性能。值得注意的是，免疫相关标志物或 IPS 的表达与风险评分呈负相关。SOC 患者的 TIDE 和 T 细胞功能障碍评分低于风险评分较高的患者。然而，两组之间 T 细胞排斥评分没有显著差异。与正常卵巢细胞系 IOSE-80 相比，QRT-PCR 实验显示 CXCL11、CX3CR1 和 FH 在卵巢肿瘤细胞系（SK-OV-3、COC1、A2780）中上调，而 DNAJB6 下调。
结论：由免疫和铁死亡相关基因组成的四标志物特征可能在浆液性卵巢癌中作为临床风险分层工具，有助于进一步进行预后预测、个体化治疗和随访计划的临床决策。
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