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Abstract：
The identification of immune-related prognostic biomarkers opens up the possibility of developing new immunotherapy strategies against tumors. In this study, we investigated immune-related biomarkers in the tumor microenvironment to predict the prognosis of cervical cancer (CC) patients. ESTIMATE and CIBERSORT algorithms were used to calculate the abundance of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal components in cervical samples (n = 309) from The Cancer Genome Atlas. Ten immune-related differentially expressed genes associated with CC survival were identified via intersection analyses of multivariate Cox regression and protein-protein interactions. CD79B was chosen for further study, and its prognostic value and role in anti-CC immune functions were analyzed. Differential expression analysis and qRT-PCR validation both revealed that CD79B expression was down-regulated in CC tissues. Survival analysis suggested that a high level of CD79B expression was associated with good prognosis. In the clinical correlation analysis, CD79B expression was found to be related to primary therapy outcome, race, histological type, degree of cell differentiation, disease-specific survival, and progression-free interval. GSEA showed that the function and pathway of CD79B were mainly related to immune activities. Meanwhile, CD79B expression was correlated with 10 types of TICs. Based on CD79B-associated immunomodulators, a novel immune prognostic signature consisting of 10 genes (CD96, LAG3, PDCD1, TIGIT, CD27, KLRK1, LTA, PVR, TNFRSF13C, and TNFRSF17) was established and validated as possessing good independent prognostic value for CC patients. Finally, a nomogram to predict personalized 3- and 5-year overall survival probabilities in CC patients was built and validated. In summary, our findings demonstrated that CD79B might be a potential prognostic biomarker for CC. The 10-gene prognostic signature independently predicted the overall survival of patients with CC, which could improve individualized treatment and aid clinical decision-making.
摘要：
与免疫相关的预后生物标志物的鉴定为开发针对肿瘤的新的免疫疗法策略开辟了可能性。在这项研究中,我们研究了肿瘤微环境中免疫相关的生物标志物,以预测宫颈癌(CC)患者的预后.使用ESTIMATE和CIBERSORT算法计算来自癌症基因组图谱的宫颈样品（n=309）中肿瘤浸润免疫细胞（TIC）的丰度以及免疫和基质成分的量。通过多变量Cox回归和蛋白质-蛋白质相互作用的交叉分析，鉴定了10个与CC存活相关的免疫相关差异表达基因。选择CD79B进行进一步研究。并分析其预后价值和在抗CC免疫功能中的作用。差异表达分析和qRT-PCR验证均显示CD79B表达在CC组织中下调。生存分析提示高水平的CD79B表达与良好的预后相关。在临床相关分析中,发现CD79B表达与主要治疗结果有关，种族,组织学类型,细胞分化程度，疾病特异性生存，和无进展间隔。GSEA显示CD79B的功能和途径主要与免疫活性有关。同时,CD79B表达与10种类型的TIC相关。基于CD79B相关免疫调节剂，一个由10个基因组成的新的免疫预后标签(CD96，LAG3，PDCD1，TIGIT，CD27,KLRK1,LTA,PVR,TNFRSF13C,建立并验证TNFRSF17）对CC患者具有良好的独立预后价值。最后,我们构建并验证了预测CC患者个性化3年和5年总生存概率的列线图.总之,我们的研究结果表明,CD79B可能是CC的潜在预后生物标志物.10个基因的预后特征独立地预测了CC患者的总体生存率。这可以改善个性化治疗并帮助临床决策。
