Vaginal Microbiome-Based Bacterial Signatures for Predicting the Severity of Cervical Intraepithelial Neoplasia

Co-evolution of vaginal microbiome and cervical cancer

BACKGROUND

Exploration of adaptive evolutionary changes at the genetic level in vaginal microbial communities during different stages of cervical cancer remains limited. This study aimed to elucidate the mutational profile of the vaginal microbiota throughout the progression of cervical disease and subsequently establish diagnostic models.

METHODS

This study utilized a metagenomic dataset consisting of 151 subjects classified into four categories: invasive cervical cancer (CC) (n = 42), cervical intraepithelial neoplasia (CIN) (n = 43), HPV-infected (HPVi) patients without cervical lesions (n = 34), and healthy controls (n = 32). The analysis focused on changes in microbiome abundance and extracted information on genetic variation. Consequently, comprehensive multimodal microbial signatures associated with CC, encompassing taxonomic alterations, mutation signatures, and enriched metabolic functional pathways, were identified. Diagnostic models for predicting CC were established considering gene characteristics based on single nucleotide variants (SNVs).

RESULTS

In this study, we screened and analyzed the abundances of 18 key microbial strains during CC progression. Additionally, 71,6358 non-redundant mutations were identified, predominantly consisting of SNVs that were further annotated into 25,773 genes. Altered abundances of SNVs and mutation types were observed across the four groups. Specifically, there were 9847 SNVs in the HPV-infected group and 14,892 in the CC group. Furthermore, two distinct mutation signatures corresponding to the benign and malignant groups were identified. The enriched metabolic pathways showed limited similarity with only two overlapping pathways among the four groups. HPVi patients exhibited active nucleotide biosynthesis, whereas patients with CC demonstrated a significantly higher abundance of signaling and cellular-associated protein families. In contrast, healthy controls showed a distinct enrichment in sugar metabolism. Moreover, biomarkers based on microbial SNV abundance displayed stronger diagnostic capability (cc.AUC = 0.87) than the species-level biomarkers (cc.AUC = 0.78). Ultimately, the integration of multimodal biomarkers demonstrated optimal performance for accurately identifying different cervical statuses (cc.AUC = 0.86), with an acceptable performance (AUC = 0.79) in the external testing set.

CONCLUSIONS

The vaginal microbiome exhibits specific SNV evolution in conjunction with the progression of CC, and serves as a specific biomarker for distinguishing between different statuses of cervical disease.

Highly specific vaginal microbiome signature for gynecological cancers

To investigate the vaginal microbiota signature of patients with gynecologic cancer and evaluate its diagnostic biomarker potential. We incorporated vaginal 16S rRNA-seq data from 529 women and utilized VSEARCH to analyze the raw data. α-Diversity was evaluated utilizing the Chao1, Shannon, and Simpson indices, and β-diversity was evaluated through principal component analysis using Bray-Curtis distances. Linear discriminant analysis effect size (LEfSe) was utilized to determine species differences between groups. A bacterial co-abundance network was constructed utilizing Spearman correlation analysis. A random forest model of gynecologic tumor risk based on genus was constructed and validated to test its diagnostic efficacy. In gynecologic cancer patients, vaginal α-diversity was significantly greater than in controls, and vaginal β-diversity was significantly separated from that of controls; there was no correlation between these characteristics and menopause status among the subject women. Women diagnosed with gynecological cancer exhibited a reduction in the abundance of vaginal Firmicutes and Lactobacillus, while an increase was observed in the proportions of Bacteroidetes, Proteobacteria, Prevotella, Streptococcus, and Anaerococcus. A random forest model constructed based on 56 genus achieved high accuracy (area under the curve = 84.96%) in gynecological cancer risk prediction. Furthermore, there were discrepancies observed in the community complexity of co-abundance networks between gynecologic cancer patients and the control group. Our study provides evidence that women with gynecologic cancer have a unique vaginal flora structure and microorganisms may be involved in the gynecologic carcinogenesis process. A gynecological cancer risk prediction model based on characteristic genera has good diagnostic value.

Ecoinformatic Analysis of the Gut Ecological Diversity of Wild and Captive Long-Tailed Gorals Using Improved ITS2 Region Primers to Support Their Conservation

Ex situ conservation is used to protect endangered wildlife. As captive and wild long-tailed gorals are known to be similar, individuals under ex situ conservation can be reintroduced into nature. However, there is no appropriate indicator to evaluate them. Here, we amplified the internal transcribed spacer 2 (ITS2) region and compared the gut ecological information (eco-information) of captive and wild long-tailed gorals. We validated the existing ITS86F and ITS4 universal primers using reference sequences of the National Center for Biotechnology Information (NCBI) and improved their matching rates. We compared the gut eco-information of captive and wild long-tailed gorals obtained through experiments using the improved primer pair and found that the gut ecological diversity of captive gorals was low. Based on this, we suggested that the gut eco-information can be used as an evaluation index before reintroducing captive long-tailed gorals. Furthermore, we identified four plant types from the gut eco-information of wild long-tailed gorals, which can be the additional food sources to enhance the reduced intestinal ecological diversity of the captive animals.

Unlocking the microbial studies through computational approaches: how far have we reached?

The metagenomics approach accelerated the study of genetic information from uncultured microbes and complex microbial communities. In silico research also facilitated an understanding of protein-DNA interactions, protein-protein interactions, docking between proteins and phyto/biochemicals for drug design, and modeling of the 3D structure of proteins. These in silico approaches provided insight into analyzing pathogenic and nonpathogenic strains that helped in the identification of probable genes for vaccines and antimicrobial agents and comparing whole-genome sequences to microbial evolution. Artificial intelligence, more precisely machine learning (ML) and deep learning (DL), has proven to be a promising approach in the field of microbiology to handle, analyze, and utilize large data that are generated through nucleic acid sequencing and proteomics. This enabled the understanding of the functional and taxonomic diversity of microorganisms. ML and DL have been used in the prediction and forecasting of diseases and applied to trace environmental contaminants and environmental quality. This review presents an in-depth analysis of the recent application of silico approaches in microbial genomics, proteomics, functional diversity, vaccine development, and drug design.

Leveraging 16S rRNA data to uncover vaginal microbial signatures in women with cervical cancer

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.

Compositional Changes in the Vaginal Bacterial Microbiome of Healthy Pregnant Women across the Three Gestational Trimesters in Ismailia, Egypt

The composition of the vaginal microbiome may lead to adverse pregnancy outcomes. Normal pregnancy is associated with changes in the vaginal bacterial community composition, which tend to be more enriched with one or two Lactobacillus species promoting a healthy vagina and favorable birth outcomes. The aim of the current study was to determine compositional changes in the healthy vaginal microbiome composition during the three trimesters of pregnancy in Ismailia, Egypt using Illumina MiSeq sequencing of the V3-V4 region of the 16S rRNA. The phylum Firmicutes and the genus Lactobacillus dominated across the three trimesters of pregnancy. L. iners was the most abundant species. However, L. coleohominis and L. reuteri represented the least dominant vaginal lactobacilli. Core microbiome analyses showed the Lactobacillus genus and L. iners species to have the highest prevalence in all the samples of our study groups. The phylum Firmicutes was found to be negatively correlated with almost all other vaginal phyla during pregnancy. Likewise, a negative correlation between Lactobacillus and almost all other genera was detected, including significant negative correlations with Dialister and Prevotella. Furthermore, negative correlations of L. iners were detected with almost all other species, including a significant negative correlation with L. helveticus, G. vaginalis, S. anginosus, and S. agalactiae.

HPV-related cervical diseases: Alteration of vaginal microbiotas and promising potential for diagnosis

Vaginal microbiota is closely associated with women's health, however, the correlation between HPV-related cervical disease (HRCD) and vaginal microbiota is still obscure. In this study, patients with HRCD (n = 98) and healthy controls (n = 58) in Hangzhou were recruited, and their vaginal microbiota were collected and analyzed. The composition of the vaginal microbial community was explored, and a disease classification model was developed by random forest algorithm. The results suggested that the diversity of vaginal microbiota was significantly higher in HRCDs than that in healthy controls (p < 0.05). Firmicutes is the dominant phylum in vaginal microbiota, and Lactobacillus was identified as the most altered genus between two groups (p < 0.01). Kyoto Encyclopedia of Genes and Genomes analysis suggested the difference in vaginal microbial community functions between two groups. Furthermore, we identified 10 biomarkers as the optimal marker sets for the random forest model and found a higher probability of disease values in HRCD group in discovery cohort (p < 0.0001), with an area under the receiver operating characteristic curve reaching 89.7% (95% confidence interval: 78.3%-100%). We further validated the model in both validation and independent diagnosis cohorts, confirming its accuracy in the prediction of HRCD. In conclusion, this study revealed the community composition of vaginal microbiota in HRCDs and successfully constructed a diagnostic model for HRCD.

Updates on Group B Streptococcus Infection in the Field of Obstetrics and Gynecology

Group B Streptococcus (GBS, Streptococcus agalactiae) is a Gram-positive bacterium that is commonly found in the gastrointestinal and urogenital tracts. However, its colonization during pregnancy is an important cause of maternal and neonatal morbidity and mortality worldwide. Herein, we specifically looked at GBS in relation to the field of Obstetrics (OB) along with the field of Gynecology (GY). In this review, based on the clinical significance of GBS in the field of OBGY, topics of how GBS is being detected, treated, and should be prevented are addressed.

Novel Vaccine Strategies and Factors to Consider in Addressing Health Disparities of HPV Infection and Cervical Cancer Development among Native American Women

Cervical cancer is the 4th most common type of cancer in women world-wide. Many factors play a role in cervical cancer development/progression that include genetics, social behaviors, social determinants of health, and even the microbiome. The prevalence of HPV infections and cervical cancer is high and often understudied among Native American communities. While effective HPV vaccines exist, less than 60% of 13- to 17-year-olds in the general population are up to date on their HPV vaccination as of 2020. Vaccination rates are higher among Native American adolescents, approximately 85% for females and 60% for males in the same age group. Unfortunately, the burden of cervical cancer remains high in many Native American populations. In this paper, we will discuss HPV infection, vaccination and the cervicovaginal microbiome with a Native American perspective. We will also provide insight into new strategies for developing novel methods and therapeutics to prevent HPV infections and limit HPV persistence and progression to cervical cancer in all populations.

Association of Cervical Dysbacteriosis, HPV Oncogene Expression, and Cervical Lesion Progression

As the fourth most common gynecological cancer, cervical cancer has resulted in more than 300,000 deaths worldwide in 2020. The expression of the human papillomavirus (HPV) oncogenes E6 and E7 is significantly involved in the initiation and progression of cervical neoplasia. Additionally, the composition of the vaginal microbiome was also closely associated with the ability of HPV to induce cervical cancer. However, the relationship between the expression of HPV E6/E7 oncogene and the composition of the vaginal microbiome has not been clearly explored. In our present study, to investigate the relationship between the HPV E6/E7 oncogene and vaginal microbiome, cervical swabs from 115 patients were collected, and their vaginal microbiomes were analyzed by using metagenomics sequencing. Along with the progression of cervical lesions, the diversity of cervical flora increased gradually, and the abundance of Lactobacillus decreased. Compared with the HPV group, the prevalence of HPV E6/E7 and oncogene expression level were significantly upregulated in cervical intraepithelial neoplasia (CIN) and cervical cancer (CC) groups. Additionally, a positive correlation between the expression of the HPV oncogene and the genera Sneathia, Salmonella, Leptotrichia, Pseudomonas, and Roseovarius in the HPV group was observed. In the CIN group, the enrichment of the genera Sneathia and Megasphaera was weakly linked with HPV oncogene overexpression. In the CC group, a strong association between the overabundance of the genera Peptostreptococcus and Enterococcus and the high expression of HPV oncogene was also found. The increased diversity of the vaginal microbiota and the decreased Lactobacillus abundance were significantly associated with the severity of cervical disease, and the expression of the HPV oncogene could also be regulated by certain pathogens in different stages of cervical lesions.

IMPORTANCE The main findings of this study were that we clarified the associations of the different bacterial species with the expression of human papillomavirus (HPV) oncogenes at different stages of cervical cancer. Along with the severity of cervical lesions, the abundance of the genus and species of Lactobacillus obviously declined, while the aerobic and anaerobic bacteria, as well as the prevalence and expression of HPV E6/E7 oncogene, were increased dramatically.

Disturbances of Vaginal Microbiome Composition in Human Papillomavirus Infection and Cervical Carcinogenesis: A Qualitative Systematic Review

Background

Emerging evidence has demonstrated a close association between perturbations in vaginal microbiota composition in women and human papillomavirus (HPV) infection, cervical lesions, and cervical cancer (Ca); however, these findings are highly heterogeneous and inconclusive.

Aim

To perform a comprehensive systematic review of the global disturbance in the vaginal microbiota, specifically in women with HPV-associated cervical diseases, and to further conduct within- and across-disease comparisons.

Method

Twenty-two records were identified in a systematic literature search of PubMed, Web of Science, and Embase up to February 28, 2022. We extracted microbial changes at the community (alpha and beta diversity) and taxonomic (relative abundance) levels. Within- and across-disease findings on the relative abundance of taxonomic assignments were qualitatively synthesized.

Results

Generally, significantly higher alpha diversity was observed for HPV infection, cervical lesions, and/or cancer patients than in controls, and significant differences within beta diversity were observed for the overall microbial composition across samples. In within-disease comparisons, the genera Gardnerella, Megasphaera, Prevotella, Peptostreptococcus, and Streptococcus showed the greatest abundances with HPV infection; Sneathia and Atopobium showed inconsistent abundance with HPV infection, and Staphylococcus was observed in Ca. Across diseases, we find increased levels of Streptococcus and varying levels of Gardnerella were shared across HPV infections, high-grade squamous intraepithelial lesions, and Ca, whereas Lactobacillus iners varied depending on the HPV-related disease subtype.

Conclusions

This systematic review reports that vaginal microbiome disturbances are correlated to the depletion of Lactobacillus, enrichment of anaerobes, and increased abundance of aerobic bacteria in HPV infection and related cervical diseases. Moreover, L. iners may exert either protective or pathogenic effects on different HPV-related diseases.

Comparative measurement of D- and L-lactic acid isomers in vaginal secretions: association with high-grade cervical squamous intraepithelial lesions

PURPOSE

Identification of low-cost protocols to identify women at elevated susceptibility to develop cervical intra-epithelial abnormalities would aid in more individualized monitoring. We evaluated whether quantitation of the D- and L-lactic acid isomers in vaginal secretions could differentiate women with normal cervical epithelia from those with a low (LSIL) or high (HSIL) grade squamous intraepithelial lesion or with cervical cancer.

METHODS

Vaginal samples, collected from 78 women undetgoing cervical colposcopy and biopsy, were tested for pH, bacterial composition by Gram stain (Nugent score) and concentrations of D- and L-lactic acid by a colorimetric assay.

RESULTS

Subsequent diagnosis was 23 women with normal cervical epithelium, 10 with LSIL, 43 with HSIL and 2 with cervical cancer. Vaginal pH and Nugent score were comparable in all subject groups. The concentration of L-lactic acid, but not D-lactic acid, as well as the L/D-lactic acid ratio, were significantly elevated (p < 0.01) in women with HSIL and cervical cancer.

CONCLUSION

Comparative measurement of vaginal D- and L-lactic acid isomers may provide a low-cost alternative to identification of women with an elevated susceptibility to cervical abnormalities.