Qin Xu, Zhou Jianglin, Wang Zizhuo, Feng Chenzhao, Fan Junpeng, Huang Jia, Hu Dianxing, Baban Babak, Wang Shengqi, Ma Ding, Sun Chaoyang, Zhou Zhe, Chen Gang
Cancer Biology Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Stomatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
EPMA J. 2022 Jun 23;13(3):487-498. doi: 10.1007/s13167-022-00286-1. eCollection 2022 Sep.
We investigated whether ovarian cancer could alter the genital microbiota in a specific way with clinical values. Furthermore, we proposed how such changes could be envisioned in a paradigm of predictive, preventive, and personalized medicine (PPPM).
The samples were collected using cotton swabs from the cervical, uterine cavity, fallopian tubes, and ovaries of patients subjected to the surgical procedures for the malignant/benign lesions. All samples were then analyzed by metagenomic shotgun sequencing. The distribution patterns and characteristics of the microbiota in the reproductive tract of subjects were analyzed and were interpreted in relation to the clinical outcomes of the subjects.
While the ovarian cancer was able to alter the genital microbiota, the bacteria were the dominant microorganisms in all samples across all cohorts in the study (median 99%). The microbiota of the upper female reproductive tract were mainly from the cervical, identified by low bacterial biomass and high bacterial diversity. Ovarian cancer had a distinct microbiota signature. The tubal ligation affects its microbial distribution. There were no different species on the surface of platinum-sensitive ovarian tissues compared to samples from platinum-resistant patients.
The ovarian cancer-induced changes in microbiota magnify the potential of microbiota as a biotherapeutic modality in the treatment of ovarian cancer in this study and very likely for several malignancies and other conditions. Our findings demonstrated, for the first time, that microbiota could be dissected and applied in more specific fashion based on a predictive, preventive, and personalized medicine (PPPM) model in the treatment of ovarian cancer. Utilizing microbiota portfolio in a PPPM system in ovarian cancer would provide a unique opportunity to a clinically intelligent and novel approach in the treatment of ovarian cancer as well as several other conditions and malignancies.
The online version contains supplementary material available at 10.1007/s13167-022-00286-1.
我们研究了卵巢癌是否会以具有临床价值的特定方式改变生殖微生物群。此外，我们提出了如何在预测、预防和个性化医学（PPPM）范式中设想这种变化。
使用棉签从接受恶性/良性病变手术的患者的宫颈、子宫腔、输卵管和卵巢采集样本。然后对所有样本进行宏基因组鸟枪法测序分析。分析受试者生殖道中微生物群的分布模式和特征，并结合受试者的临床结果进行解释。
虽然卵巢癌能够改变生殖微生物群，但细菌是研究中所有队列所有样本中的主要微生物（中位数为99%）。女性上生殖道的微生物群主要来自宫颈，其特点是细菌生物量低且细菌多样性高。卵巢癌有独特的微生物群特征。输卵管结扎会影响其微生物分布。与铂耐药患者的样本相比，铂敏感卵巢组织表面没有不同的物种。
卵巢癌引起的微生物群变化放大了微生物群作为生物治疗手段在本研究中治疗卵巢癌的潜力，很可能对几种恶性肿瘤和其他病症也有作用。我们的研究结果首次表明，基于预测、预防和个性化医学（PPPM）模型，微生物群可以以更具体的方式进行剖析并应用于卵巢癌的治疗。在卵巢癌的PPPM系统中利用微生物群组合将为卵巢癌以及其他几种病症和恶性肿瘤的临床智能和新颖治疗方法提供独特机会。
在线版本包含可在10.1007/s13167-022-00286-1获取的补充材料。
