Wen Huakai, Zhang Yumeng, Liu Yongwei, Long Haixia, Yao Yuhua
School of Mathematics and Statistics, Hainan Normal University, Haikou 570100, China.
College of Information Science Technology, Hainan Normal University, Haikou 571158, China.
Int J Mol Sci. 2025 May 1;26(9):4293. doi: 10.3390/ijms26094293.
An increasing body of research indicates that the circulating microbiome plays a significant role in cancer initiation and progression and the treatment response. The genomic characteristics of circulating microorganisms may influence the tumor immune microenvironment, thereby affecting cancer progression and therapeutic outcomes. However, whether the circulating microbiome can serve as a prognostic biomarker for cervical cancer patients and its mechanistic role in the tumor immune microenvironment still requires further investigation. Univariate, Lasso, and multivariate Cox regression analyses were utilized to identify the circulating microbial signatures associated with overall survival (OS) in patients with cervical cancer. A circulating Microbial Abundance Prognostic Score (MAPS) model was constructed based on these findings. A nomogram that integrated clinical features and MAPSs was developed to predict the OS rates in patients with cervical cancer. Blood microbiome data were combined with matched tumor RNA-seq data to analyze the differences in the tumor microenvironment between high- and low-MAPS groups, elucidating the impact of the MAPS on the tumor immune microenvironment. Finally, the potential application of the circulating MAPS to predicting the efficacy of immunotherapy and chemotherapy was assessed. The MAPS predictive model, which includes 15 circulating microorganisms, has shown independent prognostic value for patients with cervical cancer. Integrating the MAPS into a nomogram improved the accuracy of the prognostic predictions. Combined microbial and gene analyses revealed potential interactions between prognostic tumor microbiomes and the tumor immune microenvironment. The drug sensitivity analysis indicated the potential of MAPS as a predictor of chemotherapy's efficacy. Our findings suggest that circulating microbial signatures hold promise as novel prognostic biomarkers and may inform personalized treatment strategies in cervical cancer. Further large-scale and multicenter studies are warranted to validate the clinical utility of the MAPS.
越来越多的研究表明，循环微生物群在癌症的发生、发展以及治疗反应中发挥着重要作用。循环微生物的基因组特征可能会影响肿瘤免疫微环境，从而影响癌症进展和治疗结果。然而，循环微生物群是否可作为宫颈癌患者的预后生物标志物及其在肿瘤免疫微环境中的作用机制仍需进一步研究。我们利用单因素、套索和多因素Cox回归分析来确定与宫颈癌患者总生存期（OS）相关的循环微生物特征。基于这些发现构建了循环微生物丰度预后评分（MAPS）模型。开发了一个整合临床特征和MAPS的列线图，以预测宫颈癌患者的OS率。将血液微生物组数据与匹配的肿瘤RNA测序数据相结合，分析高MAPS组和低MAPS组之间肿瘤微环境的差异，阐明MAPS对肿瘤免疫微环境的影响。最后，评估了循环MAPS在预测免疫治疗和化疗疗效方面的潜在应用。包含15种循环微生物的MAPS预测模型已显示出对宫颈癌患者具有独立的预后价值。将MAPS纳入列线图提高了预后预测的准确性。微生物和基因联合分析揭示了预后肿瘤微生物群与肿瘤免疫微环境之间的潜在相互作用。药物敏感性分析表明MAPS有潜力作为化疗疗效的预测指标。我们的研究结果表明，循环微生物特征有望成为新型预后生物标志物，并可能为宫颈癌的个性化治疗策略提供参考。有必要开展进一步的大规模多中心研究来验证MAPS的临床实用性。
