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BCG 治疗后膀胱癌患者尿液微生物组及其代谢特征的差异。

Differential Urinary Microbiome and Its Metabolic Footprint in Bladder Cancer Patients Following BCG Treatment.

机构信息

Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.

Department of Urology, Chungbuk National University College of Medicine, Cheongju 28644, Republic of Korea.

出版信息

Int J Mol Sci. 2024 Oct 17;25(20):11157. doi: 10.3390/ijms252011157.

Abstract

Recent studies have identified a urinary microbiome, dispelling the myth of urine sterility. Intravesical bacillus Calmette-Guérin (BCG) therapy is the preferred treatment for intermediate to high-risk non-muscle-invasive bladder cancer (BCa), although resistance occurs in 30-50% of cases. Progression to muscle-invasive cancer necessitates radical cystectomy. Our research uses 16S rRNA gene sequencing to investigate how the urinary microbiome influences BCa and its response to BCG therapy. Urine samples were collected via urethral catheterization from patients with benign conditions and non-muscle-invasive BCa, all of whom underwent BCG therapy. We utilized 16S rRNA gene sequencing to analyze the bacterial profiles and metabolic pathways in these samples. These pathways were validated using a real metabolite dataset, and we developed predictive models for malignancy and BCG response. In this study, 87 patients participated, including 29 with benign diseases and 58 with BCa. We noted distinct bacterial compositions between benign and malignant samples, indicating the potential role of the toluene degradation pathway in mitigating BCa development. Responders to BCG had differing microbial compositions and higher quinolone synthesis than non-responders, with two species being prevalent among responders, associated with prolonged recurrence-free survival. Additionally, we developed highly accurate predictive models for malignancy and BCG response. Our study delved into the mechanisms behind malignancy and BCG responses by focusing on the urinary microbiome and metabolic pathways. We pinpointed specific beneficial microbes and developed clinical models to predict malignancy and BCG therapy outcomes. These models can track recurrence and facilitate early predictions of treatment responses.

摘要

最近的研究已经确定了尿微生物组,打破了尿液无菌的神话。膀胱内卡介苗(BCG)治疗是中高危非肌肉浸润性膀胱癌(BCa)的首选治疗方法,尽管在 30-50%的病例中会出现耐药性。进展为肌肉浸润性癌症需要根治性膀胱切除术。我们的研究使用 16S rRNA 基因测序来研究尿微生物组如何影响 BCa 及其对 BCG 治疗的反应。通过尿道导管术从良性疾病和非肌肉浸润性 BCa 患者中收集尿液样本,所有患者均接受 BCG 治疗。我们利用 16S rRNA 基因测序来分析这些样本中的细菌谱和代谢途径。使用真实代谢物数据集验证了这些途径,并为恶性肿瘤和 BCG 反应开发了预测模型。在这项研究中,87 名患者参与了研究,其中 29 名患有良性疾病,58 名患有 BCa。我们注意到良性和恶性样本之间存在明显的细菌组成差异,表明甲苯降解途径在减轻 BCa 发展方面具有潜在作用。BCG 治疗的应答者与非应答者的微生物组成不同,喹诺酮合成能力更高,两种细菌在应答者中更为普遍,与延长无复发生存期相关。此外,我们还为恶性肿瘤和 BCG 反应开发了高度准确的预测模型。我们的研究通过关注尿微生物组和代谢途径,深入研究了恶性肿瘤和 BCG 反应的机制。我们确定了特定的有益微生物,并开发了临床模型来预测恶性肿瘤和 BCG 治疗的结果。这些模型可以跟踪复发情况,并有助于早期预测治疗反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b430/11508893/3a41efdb47bc/ijms-25-11157-g001.jpg

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