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- Title
Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer.
- Authors
Ming Wu; Hongfei Yu; Yueqian Gao; Huanrong Li; Chen Wang; Huiyang Li; Xiaotong Ma; Mengting Dong; Bijun Li; Junyi Bai; Yalan Dong; Xiangqin Fan; Jintian Zhang; Ye Yan; Wenhui Qi; Cha Han; Aiping Fan; Fengxia Xue
- Abstract
Microbiota-relevant signatures have been investigated for human papillomavirus-related cervical cancer (CC), but lack consistency because of study- and methodology-derived heterogeneities. Here, four publicly available 16S rRNA datasets including 171 vaginal samples (51 CC versus 120 healthy controls) were analyzed to characterize reproducible CC-associated microbial signatures. We employed a recently published clustering approach called VAginaL community state typE Nearest CentroId clAssifier to assign the metadata to 13 community state types (CSTs) in our study. Nine subCSTs were identified. A random forest model (RFM) classifier was constructed to identify 33 optimal genus-based and 94 species-based signatures. Confounder analysis revealed confounding effects on both study- and hypervariable region-associated aspects. After adjusting for confounders, multivariate analysis identified 14 significantly changed taxa in CC versus the controls (P < 0.05). Furthermore, predicted functional analysis revealed significantly upregulated pathways relevant to the altered vaginal microbiota in CC. Cofactor, carrier, and vitamin biosynthesis were significantly enriched in CC, followed by fatty acid and lipid biosynthesis, and fermentation of short-chain fatty acids. Genus-based contributors to the differential functional abundances were also displayed. Overall, this integrative study identified reproducible and generalizable signatures in CC, suggesting the causal role of specific taxa in CC pathogenesis.
- Subjects
CERVICAL cancer; CANCER patients; SHORT-chain fatty acids; RIBOSOMAL RNA; CONFOUNDING variables; METADATA; RANDOM forest algorithms
- Publication
Frontiers in Cellular & Infection Microbiology, 2023, Vol 13, p1
- ISSN
2235-2988
- Publication type
Article
- DOI
10.3389/fcimb.2023.1024723