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Distribution of microbiota in cervical preneoplasia of racially disparate populations

Abstract

Backgrounds

Microbiome dysbiosis is an important contributing factor in tumor development and thus may be a risk predictor for human malignancies. In the United States, women with Hispanic/Latina (HIS) and African American (AA) background have a higher incidence of cervical cancer and poorer outcomes than Caucasian American (CA) women.

Methods

Here, we assessed the distribution pattern of microbiota in cervical intraepithelial neoplasia (CIN) lesions obtained from HIS (n = 12), AA (n = 12), and CA (n = 12) women, who were screened for CC risk assessment. We employed a 16S rRNA gene sequencing approach adapted from the NIH-Human Microbiome Project to identify the microbial niche in all CIN lesions (n = 36).

Results

We detected an appreciably decreased abundance of beneficial Lactobacillus in the CIN lesions of the AA and HIS women compared to the CA women. Differential abundance of potentially pathogenic Prevotella, Delftia, Gardnerella, and Fastidiosipila was also evident among the various racial groups. An increased abundance of Micrococcus was also evident in AA and HIS women compared to the CA women. The detection level of Rhizobium was higher among the AA ad CA women compared to the HIS women. In addition to the top 10 microbes, a unique niche of 27 microbes was identified exclusively in women with a histopathological diagnosis of CIN. Among these microbes, a group of 8 microbiota; Rubellimicrobium, Podobacter, Brevibacterium, Paracoccus, Atopobium, Brevundimonous, Comamonous, and Novospingobium was detected only in the CIN lesions obtained from AA and CA women.

Conclusions

Microbial dysbiosis in the cervical epithelium represented by an increased ratio of potentially pathogenic to beneficial microbes may be associated with increased CC risk disparities. Developing a race-specific reliable panel of microbial markers could be beneficial for CC risk assessment, disease prevention, and/or therapeutic guidance.

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Background

In the current setting, high-risk human papillomavirus (hrHPV) detection, Papanicolaou test (Pap test), and colposcopy-based screening have considerably reduced the overall rate of cervical cancer (CC) mortality in the USA [1]. However, significant racial health disparities exist in CC outcomes, posing a challenge to effective disease management [2,3,4,5]. Among various races, Hispanic/Latina (HIS) women have the highest rate of CC incidence and advanced staged diagnosis compared to other racial groups. The HIS women also have a higher mortality rate (9.5/100,000) compared to non-HIS women (7.5/100,000). Notably, the mortality rate among the HIS women is also slightly higher compared to the African American (AA) women [6]. On the other hand, CC associated mortality rate is double in AA women compared to Caucasian American (CA) women [7]. In terms of frequency, CC incidence is higher among AA compared to CA women (9/100,000 vs. 7.2/100,000). Similar to the HIS women, AA women have a higher incidence (60%) of CC, with an increased risk of advanced stage diagnosis compared to CA women.

Microbiota comprises a diverse population of bacteria, fungi, and viruses. It is an integral component of the human body, participating in various regulatory processes, including immune system function and metabolism. Loss of the beneficial components of the diverse microbiota and concomitant increase in their pathogenic counterpart may lead to chronic inflammation and transformation of the epithelial cells. The gastric epithelial cell resident Helicobacter pylori is an excellent example, whose increased accumulation is associated with a higher rate of gastric cancer [8, 9]. Diverse microbiota populations reside in the cervicovaginal canal of the female reproductive system. Changes in their composition may elicit inflammatory changes in the cervicovaginal epithelium, leading to an increased risk of cervical cancer. Notably, the cervicovaginal microbiota compositions may alter differentially in women of different racial backgrounds, posing a variable risk of CC development. In the present study, we examined the resident microbial compositions of the cervical intraepithelial lesions obtained from CA, AA, and HIS women, who were initially screened for CC risk assessment. We observed a lower abundance of the beneficial Lactobacillus and a concomitant increase in potentially pathogenic Prevotella and Leucobacter in AA and HIS groups compared to the CA women. A unique signature of twenty-seven microbes was identified exclusively in women with variable degrees of preneoplastic changes in their cervical epithelium (cervical intraepithelial neoplasia, grade 1–3), of which eight genera were detected only in the preneoplastic lesions obtained from the AA and HIS women.

Methods

Human samples and ethical statement

Cervical intraepithelial neoplasia (CIN) tissues from various grades (CIN1-CIN3) were collected from 36 women. Twelve samples each were obtained from CA, AA, and HIS women. (Table 1). All archived biospecimens were collected from the de-identified subject under an IRB-approved protocol from the University of South Alabama (#20–222). This study was approved by the Ethics Committee of Medicine, University of South Alabama. Informed consent was obtained from all the de-identified subjects, and only relevant clinical information such as age, grade, stage, diagnosis, HPV status, race, etc., was collected for statistical comparison. All methods were performed following the relevant guidelines and regulations.

Table 1 Demographic information of the women detected with cervical intraepithelial neoplasia (CIN) from various races. The cervical intraepithelial neoplastic lesions from all these women were sequenced for detecting various microbiomes

16S rRNA gene sequencing for microbiome detection

Cervical intraepithelial neoplasia lesions from AA (n = 12), CA (n = 12), and HIS (n = 12) subjects were processed (n = 36) for the microbiome sequencing. The 16S rRNA gene sequencing methods were adapted from the NIH-Human Microbiome Project as described previously, and specific guidelines for sample processing and data analysis were followed [10,11,12]. Briefly, we isolated bacterial genomic DNA utilizing MO BIO PowerSoil DNA Isolation Kit (MO BIO Laboratories, (MoBIO PowerSoil v3.4). We then performed PCR amplification of the 16S rDNA V4 region (Illumina 16Sv4 v1.2) by PCR using a set of specific primers described earlier [13]. Sequencing was carried out on the MiSeq platform (Illumina MiSeq v2 2 × 250 v1.8) using the 2 × 250 bp paired-end protocol yielding pair-end reads that overlap almost completely. The primers used for the amplification contained adapters for MiSeq sequencing and single-end barcodes, allowing pooling and direct sequencing of the PCR products [14].

Quality control and compositional analysis

The pipeline data for the 16S rRNA gene assembles phylogenetic, and alignment-based approaches to maximize the data resolution described [13]. Based on the unique molecular barcodes, The read pairs were de-multiplexed. The resulting reads were merged using USEARCH v7.0.1090, equipped with a de novo built-in chimera filter. All singleton operational taxonomic units (OTUs) were discarded as described previously [13, 15,16,17]. To remove sequencing errors, Contig filters were employed as appropriate. The 16S rRNA gene sequences were clustered into Operational Taxonomic Units (OTUs), which were mapped to the SILVA database at 97% similarities to obtain phylum to genus taxonomies. The mapping of the OTUs was done utilizing an optimized version of the SILVA database, which exclusively contains the 16S v4 region for determining taxonomies. For abundance recovery, de-multiplexed mapping of the reads to the UPARSE OTUs was performed.

Data analysis

The distribution of the microbiome populations was assessed in alpha diversity (AD) and taxa abundances (TA) through heat maps and customizable box/hierarchical plots as applicable. As described, appropriate statistical annotations were added to infer significant correlations with the metadata outcomes [13]. Kruskal–Wallis and Mann–Whitney tests were conducted for all the statistical data analyses with an appropriate FDR application utilizing the Bonferroni correction method. All the samples with total read counts below the designated threshold levels were excluded from further analysis. We employed alpha diversity analysis to measure diversity within a sample. The different alpha diversity metrics use the counts (richness) and distribution (evenness) of the OTUs within a sample as the basic values for these calculations. All the sequencing data have been deposited in the NIH sequence read archive (SRA, # PRJNA824515).

Results

Cervical cancer screening survey of the study population

We have examined microbiome diversity in 36 women from various ethnic groups with a primary diagnosis of cervical intraepithelial neoplasia (Table 1). The mean age of the HIS subjects was 32.92 ± 9.62; 35.25 ± 8.00 for the AA and 44.42 ± 12.32 for the CA subjects. Of the 12 CA cases, seven were positive for hrHPV infection, two were negative, and no information was available for the remaining three cases. Only two CA subjects exhibited mild (CIN1) to moderate (CIN2) dysplasia in their cervical epithelium. Seven of the 12 HIS cases were positive for hrHPV infection, and five were negative. Only two HIS subjects exhibited mild (CIN1) to moderate (CIN2) dysplasia in their cervical epithelium. Of the 12 AA cases, six were positive for hrHPV infection, five were hrHPV negative, and no information was available for one subject. All but four AA subjects exhibited mild (CIN1) to moderate (CIN2) dysplasia in the cervical epithelium.

Overall sequence reads in the samples

Thirty-six biopsied samples from the uterine cervix were extracted and processed for 16Sv3-4 amplification and sequencing to determine microbiome profiles. All samples were included in the final analysis. A total of 251,993 sequencing reads were obtained from the 36 samples. Of these, 92.1% completed the merging and the quality filtering steps, and 1.36% of the resulting filtered reads mapped to the SILVA database after a QC step to remove potential contaminants.

Nature and distribution of the microbiota in racially disparate population

Two hundred fifty-nine unique Operational Taxonomic Units (OTUs) were observed in the samples analyzed. The average and median number of OTUs per sample were 15 and 13, respectively. The OTUs were classified across 13 different phyla, 74 families, and 142 genera. Overall, in all three racial groups, a considerable abundance of microbiota was evident from 4 major phyla, including, Firmicutes, Fusobacteria, Bacteroidetes, and Actinobacteria (Fig. 1). Within these 4 phyla, we have identified a considerable and differential abundance of 10 genera in the various racial groups, including Lactobacillus, Gardnerella, Prevotella, Enhydrobacter, Rizhobium, Micrococcus, Alcaligenes, Delftia, Fastidiosipila and Bosea (Fig. 2). Notably, among these 10 genera, a lower abundance (twofold) of Lactobacillus, a common cervicovaginal microbe, was noted in both AA and HIS women compared to the CA women. On the other hand, a higher abundance (1.5–fourfold) of Gardnerella, Enhydrobacter, Bosea, Delftia, and Fastidiosipila was also evident in the CA group compared to the AA and HIS women. Of note, we observed a 2–threefold higher abundance of Prevotella in HIS women compared to CA and AA women. Considering the variable degree of abundance (high-low), we have identified a panel of 27 microbes, which are exclusively present in women with a primary diagnosis of CIN but not in women with histologically normal-appearing cervical epithelium (Fig. 3). In addition to the highly abundant 10 genera detected in various racial populations (Fig. 2), a comparatively lower abundance of a panel of 8 microbes; Rubellimicrobium, Podobacter, Brevibacterium, Paracoccus, Atopobium, Brevundimonous, Comamonous, and Novospingobium was detected exclusively in CIN lesions from AA and HIS subjects (Fig. 4). We also identified a differential abundance of a group of 9 microbes in HPV-positive and HPV-negative CIN lesions from various racial groups (Fig. 5). We determined alpha diversity for species richness and the evenness between various groups considering CIN and HPV positivity. However, we did not observe any significant difference in richness or evenness (Fig. 6).

Fig. 1
figure 1

Major microbial Phyla were identified in women with various racial backgrounds. The differential level of abundance was presented as the mean abundance of the operational taxonomical unit. The mean abundance of the operational taxonomical unit was presented in each box in the various racial groups. A minimum average of 0.05% was considered for calculating the overall abundance. AA: African American; CA: Caucasian American; HIS: Hispanic/Latino

Fig. 2
figure 2

Differential abundance of the top 10 microbial genera identified in various racial groups. The differential level of abundance was presented as the mean of the operational taxonomical unit. The mean abundance of the operational taxonomical unit was presented in each box in the various racial groups. A minimum average of 0.05% was considered for calculating the overall abundance. AA: African American; CA: Caucasian American; HIS: Hispanic/Latino

Fig. 3
figure 3

Microbial genera were identified exclusively in the cervical intraepithelial neoplasia (CIN) lesions from African American (AA) and Hispanic/Latina (HIS) women. The differential level of abundance was presented as the mean of the operational taxonomical unit. A minimum average of 0.05% was considered for calculating the overall abundance. CA: Caucasian American

Fig. 4
figure 4

Microbes detected only in the cervical intraepithelial neoplasia (CIN) lesion (lower abundance) from African American (AA) and Hispanic/Latina (HIS) women. The differential level of abundance was presented as the mean of the operational taxonomical unit. The mean abundance of the operational taxonomical unit was presented in each box in the various racial groups. A minimum average of 0.05% was considered for calculating the overall abundance. CA: Caucasian American

Fig. 5
figure 5

The pattern of distribution of the operational taxonomic units (OTUs) in the cervical intraepithelial neoplasia lesions across HPV positive and negative women with diverse racial backgrounds. A minimum average of 0.05% was considered for calculating the overall abundance. HPV-NA: No information on HPV status

Fig. 6
figure 6

Ordination plots for alpha diversity to measure intra-sampler diversity. For these calculations, the alpha diversity metrics use both counts (richness) and distribution (evenness, Shannon Index) of the operational taxonomic units (OTUs) within a sample as the basic values. A minimum average of 0.05% was considered for calculating the overall abundance in all cases. CIN: cervical intraepithelial neoplasia; NIL: No detection of cervical intraepithelial neoplasia; HPV-NA: no information on HPV status; HPV + : women positive for HPV infection; HPV-: women negative for HPV infection

Discussion

Microbiota represents a collective composition of bacteria, viruses, and fungi residing in the human body that participate in various metabolic processes [18,19,20]. An imbalance, commonly known as dysbiosis in the microbiota through an increased accumulation of pathogenic microbes and/or a decrease in the beneficial ones may initiate several pathobiological changes, including genomic instability, cellular proliferation, chronic inflammation, metabolic reprogramming, and immunosuppression leading to various diseases, including cancer [21,22,23,24].

Despite appreciable advancement in disease prevention strategies, women of diverse racial backgrounds carry a disproportionate burden of CC, warranting a deeper understanding of the underlying contributing factors, followed by refinement of current risk assessment strategies. Cervical carcinomas often develop through precursor cervical intraepithelial neoplastic lesions and are primarily driven by HPV oncogenesis [25, 26]. Interestingly, recent studies suggest that altered residential patterns of the microbiota in the cervicovaginal environment could be associated with the development of various diseases, including malignant transformation [27]. However, the compendium of microbiota adherent during early transformative changes of the cervical epithelium in populations with variable CC risk remains less well explored. Our pilot study identified the diverse microbiome in cervical intraepithelial neoplasia specimens obtained from HIS, AA, and CA women. It determined their correlation with preneoplastic changes and HPV status in various racial groups. This is the first study undertaking a comparative analysis of microbiota in CA, AA, and HIS women with a primary diagnosis of cervical intraepithelial neoplasia.

The most abundantly found and the beneficial resident microbe in the female genital tract is Lactobacillus [28]. Lactobacillus species appear to exert their protective function by metabolizing available glycogen from the vaginal epithelial cells undergoing periodic changes. The metabolization of glycogen by Lactobacillus creates a low pH environment, which aids in preventing the accumulation and adherence of pathogenic microbes therein [29]. Moreover, Lactobacillus is one of the microbes capable of altering the host’s microbiome, improving the immune response, reducing inflammation, and promoting HPV clearance [30]. Detection of the decreased abundance of Lactobacillus in the HIS and AA women compared to the CA women suggests an increased risk of colonization of the pathogenic microbes facilitating immunosuppression and subsequent HPV-mediated cervical carcinogenesis.

This notion is further supported by detecting a higher abundance of CC-associated pathogenic microbe Prevotella in HIS women [31]. Notably, Prevotella is a unique microbe harboring estrobolome with β-glucaronidase and/or β-galactosidase activity, which is known to promote breast tumorigenesis [13]. Considering the CC facilitating role of estrogen [32, 33]. Prevotella may contribute to augmenting estrogen metabolism through its estrobolome activity. Along with Prevotella, Gardnerella and Fastidiosipila are emerging as potential risk factors and/or biomarkers for developing moderate CC development [34, 35]. Thus, an increased abundance of Gardnerella and Fastidiosipila, as identified in our study in racially disparate populations, may potentially be associated with the development of an immunosuppressive environment, thereby increasing the risk of HPV-mediated oncogenic transformation of the cervical epithelium. In a recent study, Delftia has been suggested as a microbiological hallmark of cervical preneoplasia due to its remarkable enrichment in both low and high-grade CIN lesions [36]. Detection of an increased abundance of Delftia in CIN lesions obtained from AA and HIS women further supports this notion.

Detection of a unique niche of a potentially pathogenic group of microbiota, exclusively in women with CIN lesions, further suggests that these microbiomes may play a critical role in cervical epithelial cells’ transformation alone and/or in concert with hrHPV integration. In addition, the detection of certain pathogenic microbes exclusively in AA and HIS women indicates the adherence to distinct microbiota niches in these women, which could be associated with disparate risks of CC development. Detection of Atopobium was reported in CIN2/3 lesions [37]. In this context, exclusive detection of Atopobium in CIN lesions from AA and HIS women suggests their role in transforming the normal cervical epithelium. Similarly, Brevibacterium and Novosphingobium were detected in CIN lesions from Mexican women [38], which were also seen exclusively in the AA women derived CIN lesions and HIS women in our study. Findings from this pilot study rationally instigate the development of a consensus panel of altered microbiome signatures through a comprehensive analysis of a large number of samples, which is our immediate goal. In the longer run, in concert with the standard risk assessment practice [39], routine screening of racially disparate populations for “microbiome dysbiosis” using a pre-defined marker panel may be helpful to improve the current disease prevention strategies further and reduce the disparity gaps.

In summary, we detected a differential abundance of a group of microbiota in various racial groups of women with a primary diagnosis of cervical preneoplasia, which may be associated with disparate CC risk outcomes and subsequent development and progression. The development of a race-specific reliable panel of microbial markers could be beneficial for better CC risk stratification and disease prevention and/or therapeutic guidance.

Availability of data and materials

All the sequencing data have been deposited in the NIH sequence read archive (SRA, # PRJNA824515). This Sequence Read Archive (SRA) submission has been released on 2022–08-25 and is available at https://submit.ncbi.nlm.nih.gov/subs/bioproject/SUB11231366/overview

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7.

    Article  Google Scholar 

  2. Dalton HJ, Farley JH. Racial disparities in cervical cancer: worse than we thought. Cancer. 2017;123:915.

    Article  Google Scholar 

  3. Rafiqullah Khan HM, Gabbidon K, Abdool-Ghany F, Saxena A, Gomez E, Stewart TSJ. Health disparities between black hispanic and black non-hispanic cervical cancer cases in the USA. Asian Pacific J Cancer Prev. 2014;15:9719.

    Article  Google Scholar 

  4. Chatterjee S, Gupta D, Caputo TA, Holcomb K. Disparities in gynecological malignancies. Front Oncol. 2016;6:36.

    Article  Google Scholar 

  5. Owusu GA, Eve SB, Cready CM, Koelln K, Trevino F, Urrutia-Rojas X, et al. Race and ethnic disparities in cervical cancer screening in a safety-net system. Matern Child Health J. 2005;9:285.

    Article  Google Scholar 

  6. Miller KD, Goding Sauer A, Ortiz AP, Fedewa SA, Pinheiro PS, Tortolero-Luna G, et al. Cancer statistics for hispanics/Latinos, 2018. CA Cancer J Clin. 2018;68:425.

    Article  Google Scholar 

  7. DeSantis CE, Miller KD, Goding Sauer A, Jemal A, Siegel RL. Cancer statistics for African Americans, 2019. CA Cancer J Clin. 2019;69:211.

    Article  Google Scholar 

  8. Dickson IH. pylori elimination reduces gastric cancer risk. Nat Rev Gastroenterol Hepatol. 2020;17:194.

    PubMed  Google Scholar 

  9. Mladenova I. Clinical relevance of helicobacter pylori infection. J Clin Med. 2021;10:3473.

    Article  CAS  Google Scholar 

  10. Peterson J, Garges S, Giovanni M, McInnes P, Wang L, Schloss JA, et al. The NIH human microbiome project. Genome Res. 2009;19:2317.

    Article  CAS  Google Scholar 

  11. Methé BA, Nelson KE, Pop M, Creasy HH, Giglio MG, Huttenhower C, et al. A framework for human microbiome research. Nature. 2012;486:215.

    Article  CAS  Google Scholar 

  12. Curtis Huttenhower, Dirk Gevers, Rob Knight, Sahar Abubacker, Jonathan H. Badger, Asif T. Chinwalla. Structure, function and diversity of the healthy human microbiome - The Human Microbiome Project Consortium. Nature. 2012.

  13. Philley JV, Kannan A, Olusola P, McGaha P, Singh KP, Samten B, et al. Microbiome diversity in sputum of nontuberculous mycobacteria infected women with a history of breast cancer. Cell Physiol Biochem. 2019;52:263.

    Article  CAS  Google Scholar 

  14. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621.

    Article  CAS  Google Scholar 

  15. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460.

    Article  CAS  Google Scholar 

  16. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335.

    Article  CAS  Google Scholar 

  17. Lahti L, Shetty S, Blake T. Tools for microbiome analysis in R. Microbiome Package Version 0.99. 2017.

  18. Rowland I, Gibson G, Heinken A, Scott K, Swann J, Thiele I, et al. Gut microbiota functions: metabolism of nutrients and other food components. Eur J Nutr. 2018;57:1.

    Article  CAS  Google Scholar 

  19. Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol. 2021;19:55.

    Article  CAS  Google Scholar 

  20. Martin AM, Sun EW, Rogers GB, Keating DJ. The influence of the gut microbiome on host metabolism through the regulation of gut hormone release. Front Physiol. 2019;10:428.

    Article  Google Scholar 

  21. Karwowska Z, Szemraj J, Karwowski B. Microbiota alterations in gastrointestinal cancers. Applied Sciences (Switzerland). 2020.

  22. Chen J, Domingue JC, Sears CL. Microbiota dysbiosis in select human cancers: evidence of association and causality. Semin Immunol. 2017;32:25.

    Article  CAS  Google Scholar 

  23. Meng C, Bai C, Brown TD, Hood LE, Tian Q. Human Gut Microbiota and Gastrointestinal Cancer. Genomics, Proteomics Bioinformatics. 2018;16:33.

    Article  Google Scholar 

  24. Zhou H, Suo J, Zhu J. Therapeutic relevance of human microbiota and lung cancer. Chinese J Lung Cancer. 2019.

  25. Eckhardt M, Zhang W, Gross AM, Von Dollen J, Johnson JR, Franks-Skiba KE, et al. Multiple routes to oncogenesis are promoted by the human papillomavirus–host protein network. Cancer Discov. 2018;8:1474.

    Article  CAS  Google Scholar 

  26. Münger K, Baldwin A, Edwards KM, Hayakawa H, Nguyen CL, Owens M, et al. Mechanisms of human papillomavirus-induced oncogenesis. J Virol. 2004;78:11451.

    Article  CAS  Google Scholar 

  27. Kwasniewski W, Wolun-Cholewa M, Kotarski J, Warchol W, Kuzma D, Kwasniewska A, et al. Microbiota dysbiosis is associated with HPV-induced cervical carcinogenesis. Oncol Lett. 2018;16:7035.

    PubMed  PubMed Central  CAS  Google Scholar 

  28. Chee WJY, Chew SY, Than LTL. Vaginal microbiota and the potential of lactobacillus derivatives in maintaining vaginal health. Microb Cell Fact. 2020;19:203.

    Article  Google Scholar 

  29. Miller EA, Beasley DAE, Dunn RR, Archie EA. Lactobacilli dominance and vaginal pH: why is the human vaginal microbiome unique? Front Microbiol. 2016;7:1936.

    Article  Google Scholar 

  30. Curty G, de Carvalho PS, Soares MA. The role of the cervicovaginal microbiome on the genesis and as a biomarker of premalignant cervical intraepithelial neoplasia and invasive cervical cancer. Int J Mol Sci. 2019;21:222.

    Article  CAS  Google Scholar 

  31. Lam KC, Vyshenska D, Hu J, Rodrigues RR, Nilsen A, Zielke RA, et al. Transkingdom network reveals bacterial players associated with cervical cancer gene expression program. PeerJ. 2018;6: e5590.

    Article  CAS  Google Scholar 

  32. Chung S, Franceschi S, Lambert PF. Estrogen and eralpha: culprit in cervical cancer? Trends Endocrinol Metab. 2010;21:504.

    Article  CAS  Google Scholar 

  33. Brake T, Lambert PF. Estrogen contributes to the onset, persistence, and malignant progression of cervical cancer in a human papillomavirus-transgenic mouse model. Proc Natl Acad Sci U S A. 2005;102:2490.

    Article  CAS  Google Scholar 

  34. Usyk M, Zolnik CP, Castle PE, Porras C, Herrero R, Gradissimo A, et al. Cervicovaginal microbiome and natural history of HPV in a longitudinal study. PLoS Pathog. 2020;16: e1008376.

    Article  CAS  Google Scholar 

  35. Chen Y, Hong Z, Wang W, Gu L, Gao H, Qiu L, et al. Association between the vaginal microbiome and high-risk human papillomavirus infection in pregnant Chinese women. BMC Infect Dis. 2019;19:677.

    Article  CAS  Google Scholar 

  36. Wu M, Gao J, Wu Y, Li Y, Chen Y, Zhao F, et al. Characterization of vaginal microbiota in Chinese women with cervical squamous intra-epithelial neoplasia. Int J Gynecol Cancer. 2020;30:1500.

    Article  Google Scholar 

  37. So KA, Yang EJ, Kim NR, Hong SR, Lee JH, Hwang CS, et al. Changes of vaginal microbiota during cervical carcinogenesis in women with human papillomavirus infection. PLoS ONE. 2020;15: e0238705.

    Article  CAS  Google Scholar 

  38. Nieves-Ramírez ME, Partida-Rodríguez O, Moran P, Serrano-Vázquez A, Pérez-Juárez H, Pérez-Rodríguez ME, et al. Cervical squamous intraepithelial lesions are associated with differences in the vaginal microbiota of Mexican women. Microbiol Spectr. 2021;9: e0014321.

    Article  Google Scholar 

  39. Fontham ETH, Wolf AMD, Church TR, Etzioni R, Flowers CR, Herzig A, et al. Cervical cancer screening for individuals at average risk: 2020 guideline update from the American Cancer Society. CA Cancer J Clin. 2020;70:321.

    Article  Google Scholar 

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Acknowledgements

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Funding

This work is supported by funding from the Elsa U Pardee Foundation, Mitchell Cancer Institute, and the University of South Alabama (SD).

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Contributions

SD designed and supervised the study; SD, KSV, and SA analyzed data and prepared all the figures; SD, APS, SS, JYP, SA, and KSV Wrote the manuscript. All authors have approved the finalized manuscript.

Corresponding author

Correspondence to Santanu Dasgupta.

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The study was approved by the Ethics Committee of Medicine, University of South Alabama. Informed consent was signed by all participants in accordance with the Declaration of Helsinki.

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The authors have no competing interests.

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Vikramdeo, K.S., Anand, S., Pierce, J.Y. et al. Distribution of microbiota in cervical preneoplasia of racially disparate populations. BMC Cancer 22, 1074 (2022). https://doi.org/10.1186/s12885-022-10112-6

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Keywords

  • Cervix
  • Preneoplasia
  • Microbiome
  • HPV
  • Cancer risk