Qin Fei, Huan Lu, Shi Xia, Hua Yuanyuan, Wu Yi
Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Renji Hospital, School of Medicine, Chongqing University, Chongqing, China.
Front Oncol. 2025 Jul 3;15:1608597. doi: 10.3389/fonc.2025.1608597. eCollection 2025.
Cervical cancer remains a leading cause of cancer-related mortality among women worldwide. Despite advances in vaccination and early screening, late-stage diagnoses are common and associated with poor outcomes. This study aimed to identify novel prognostic biomarkers and therapeutic targets through a multi-omics approach, providing insights into the tumor immune microenvironment.
We integrated transcriptomic, mutational, and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to construct a prognostic model. Differential gene expression, enrichment analysis, immune infiltration profiling, and drug response prediction were performed to explore molecular features and therapeutic relevance.
Key high-risk biomarkers (EZH2, PCNA, BIRC5) and protective factors (CD34, ROBO4, CXCL12) were identified. The model effectively stratified patient survival in both cohorts and showed strong predictive performance. High-risk patients displayed distinct immune cell infiltration patterns and upregulated immune checkpoint expression, suggesting potential benefit from immunotherapy. Additionally, higher tumor mutational burden (TMB) was associated with improved survival. Drug sensitivity analysis indicated increased responsiveness of high-risk patients to agents such as Afuresertib and Venetoclax.
This study establishes a reliable prognostic model and identifies critical biomarkers associated with cervical cancer progression, offering valuable insights into personalized therapeutic strategies. The findings contribute to a more comprehensive understanding of the disease and provide a foundation for future clinical applications. Nevertheless, further large-scale validation is required to confirm these findings and enhance their clinical utility.
宫颈癌仍然是全球女性癌症相关死亡的主要原因。尽管在疫苗接种和早期筛查方面取得了进展，但晚期诊断仍然很常见，且预后较差。本研究旨在通过多组学方法识别新的预后生物标志物和治疗靶点，深入了解肿瘤免疫微环境。
我们整合了来自癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）的转录组、突变和临床数据，以构建一个预后模型。进行差异基因表达、富集分析、免疫浸润分析和药物反应预测，以探索分子特征和治疗相关性。
确定了关键的高危生物标志物（EZH2、PCNA、BIRC5）和保护因子（CD34、ROBO4、CXCL12）。该模型在两个队列中均有效地对患者生存进行了分层，并显示出强大的预测性能。高危患者表现出独特的免疫细胞浸润模式和免疫检查点表达上调，提示可能从免疫治疗中获益。此外，较高的肿瘤突变负荷（TMB）与生存改善相关。药物敏感性分析表明高危患者对阿福司他和维奈克拉等药物的反应性增加。
本研究建立了一个可靠的预后模型，并识别出与宫颈癌进展相关的关键生物标志物，为个性化治疗策略提供了有价值的见解。这些发现有助于更全面地了解该疾病，并为未来的临床应用提供了基础。然而，需要进一步的大规模验证来证实这些发现并提高其临床实用性。
