Discriminating high-risk cervical Human Papilloma Virus infections with urinary biomarkers via non-targeted GC-MS-based metabolomics

Higher clearance rates of multiple HPV infections may explain their lower risk of HSIL: A retrospective study in Wenzhou, China

Persistent human papilloma virus (HPV) infection is known to be associated with cervical lesions. The chief object of the study is to investigate if the pathogenicity of multiple HPV infections is different from a single infection. Furthermore, we would like to corroborate the discrepancy with clearance rates. Between August 1, 2020, and September 31, 2021, 5089 women underwent a colposcopy-directed biopsy in our hospital. We divided the 2999 patients who met the criteria into multiple and single HPV infection groups. The HPV genotypes were identified using the flow cytometry fluorescence hybridization technology. Binary logistic regression and survival analysis were used to perform statistics. Among HPV-positive individuals, 34.78% (1043/2999) were positive for 2 or more HPV types. After adjusting for the main factors, compared with single infection, multiple infections were associated with a significantly decreased risk of high squamous intraepithelial lesions (HSIL) (odds ratio [OR]: 0.570; 95% confidence interval [CI]: 0.468-0.694). In the mean time, the clearance rates of multiple infections were significantly higher (OR: 2.240; 95% CI: 1.919-2.614). When analyzing specific types covered by the 9-valent HPV vaccine, consistency between the lower risk of HSIL and the higher clearance rate was found in the most groups. Compared with a single infection, multiple HPV infections have a lower risk of HSIL, which may be related to its higher clearance rate. It suggests that aggressive treatment of multiple HPV infections early in their detection may be beneficial.

Metabolomic profiling identifies hair as a robust biological sample for identifying women with cervical cancer

Metabolomics serves as a useful tool for identifying biomarkers of disease and uncovering pathogenic mechanisms. However, most metabolomic studies use biological fluids such as blood and urine as biospecimens, which could be dramatically influenced by daily activities and dietary variation, resulting in measurement fluctuations. In contrast, hair may serve as a robust source of stable longitudinal metabolite information. Here, we conducted a pilot study to investigate the possibility of using hair as a biospecimen for the metabolomic analysis of cervical cancer. Hair, plasma, urine, and cervical tissue samples from cervical cancer and benign tumor patients were collected. Biospecimens were then tested using a gas chromatography-mass spectrometry-based metabolomic platform. The expressions of enzymatic genes related to metabolic changes were validated using qPCR. Statistical analyses were calculated via the R-console platform. Metabolite profiles in both hair and cervical tissue samples were significantly different between cancer and control groups, while no difference was observed in plasma and urine samples. Further analysis showed that most of the altered metabolites in hair were upregulated, and they had a negative correlation with those in the cervical tissue. Eight common metabolites showed an area under the Receiver Operating Characteristic curve greater than 0.95. These metabolites primarily participated in amino acid metabolism, cofactor synthesis, ferroptosis, and glycolysis. The gene expressions (IDH1, OGDH, GLUD1, ENO1, GSS, and GPX4) associated with the shortlisted metabolic pathways were also upregulated. Our study is the first to reveal metabolomic changes of hair in cervical cancer patients and demonstrates the potential for the hair metabolome to be used for biomarker identification in cervical cancer.

Exploration of biomarkers for the diagnosis, treatment and prognosis of cervical cancer: a review

As the fourth most diagnosed cancer, cervical cancer (CC) is one of the major causes of cancer-related mortality affecting females globally, particularly when diagnosed at advanced stage. Discoveries of CC biomarkers pave the road to precision medicine for better patient outcomes. High throughput omics technologies, characterized by big data production further accelerate the process. To date, various CC biomarkers have been discovered through the advancement in technologies. Despite, very few have successfully translated into clinical practice due to the paucity of validation through large scale clinical studies. While vast amounts of data are generated by the omics technologies, challenges arise in identifying the clinically relevant data for translational research as analyses of single-level omics approaches rarely provide causal relations. Integrative multi-omics approaches across different levels of cellular function enable better comprehension of the fundamental biology of CC by highlighting the interrelationships of the involved biomolecules and their function, aiding in identification of novel integrated biomarker profile for precision medicine. Establishment of a worldwide Early Detection Research Network (EDRN) system helps accelerating the pace of biomarker translation. To fill the research gap, we review the recent research progress on CC biomarker development from the application of high throughput omics technologies with sections covering genomics, transcriptomics, proteomics, and metabolomics.

Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.

HPV-mediated Cervical Cancer: A Systematic review on Immunological Basis, Molecular Biology and Immune evasion mechanisms

BACKGROUND

Human papillomavirus (HPV), one of the most frequently transmitted viruses globally, causing several malignancies including cervical cancer.

AIM

Owing to their unique pathogenicity HPV viruses can persist in the host organism for a longer duration than other virus types, to complete their lifecycle. During its association with the host, HPV causes various pathological conditions affecting the immune system by evading the host immune- mechanisms leading to the progression of various diseases, including cancer.

METHOD

To date, ~ 150 serotypes were identified, and certain high-risk HPV types are known to be associated with genital warts and cervical cancer. As of now, two prophylactic vaccines are in use for the treatment of HPV infection, however, no effective antiviral drug is available for HPV-associated disease/infections. Numerous clinical and laboratory studies are being investigated to formulate an effective and specific vaccine again HPV infections and associated diseases.

RESULT

As the immunological basis of HPV infection and associated disease progress persist indistinctly, deeper insights on immune evasion mechanism and molecular biology of disease would aid in developing an effective vaccine.

CONCLUSION

Thus this review focuses, aiming a systematic review on the immunological aspects of HPV-associated cervical cancer by uncovering immune evasion strategies adapted by HPV.

Identification of volatile organic compounds in the urine of patients with cervical cancer. Test concept for timely screening

The objective of this research was to identify a global chemical pattern of volatile organic compounds (VOCs) in urine capable of discriminating between women with cervical cancer (CC) and control women using an electronic nose and to elucidate potential biomarkers by gas chromatography-mass spectrometry (GC-MS). A cross-sectional study was performed, with 12 control women, 5 women with CIN (Cervical Intraepithelial Neoplasia) and 12 women with CC. Global VOCs in urine were assessed using an electronic nose and specific by GC-MS. Multivariate analysis was performed: Principal Component Analysis (PCA), Canonical Principal Coordinate Analysis (CAP) and Partial Least Squares Discriminant Analysis (PLS-DA) and the test's diagnostic power was evaluated through ROC (Receiver Operating Characteristic) curves. Results from the PCA between the control group compared to the CC present variability of 98.4% (PC₁ = 93.9%, PC₂ = 2.3% and PC₃ = 2.1%). CAP model shows a separation between the overall VOCs profile of the control and CC group with a correct classification of 94.7%. PLS-DA indicated that 8 sensors have a higher contribution in the CC group. The sensitivity, specificity, value reached 91.6% (61.5%-99.7%) and 100% (73.5%-100%) respectively, according to the ROC curve. GC-MS analysis indicated that 33 compounds occur only in the CC group and some of them have been found in other types of cancer. In all, this study provides the basis for the development of an accessible, non-invasive, sensitive and specific screening platform for cervical cancer through the application of electronic nose and chemometric analysis.

Untargeted Metabolomics Reveals Species-Specific Metabolite Production and Shared Nutrient Consumption by Pseudomonas aeruginosa and Staphylococcus aureus

While bacterial metabolism is known to impact antibiotic efficacy and virulence, the metabolic capacities of individual microbes in cystic fibrosis lung infections are difficult to disentangle from sputum samples. Here, we show that untargeted metabolomic profiling of supernatants of multiple strains of Pseudomonas aeruginosa and Staphylococcus aureus grown in monoculture in synthetic cystic fibrosis media (SCFM) reveals distinct species-specific metabolic signatures despite intraspecies metabolic variability. We identify a set of 15 metabolites that were significantly consumed by both P. aeruginosa and S. aureus, suggesting that nutrient competition has the potential to impact community dynamics even in the absence of other pathogen-pathogen interactions. Finally, metabolites that were uniquely produced by one species or the other were identified. Specifically, the virulence factor precursor anthranilic acid, as well as the quinoline 2,4-quinolinediol (DHQ), were robustly produced across all tested strains of P. aeruginosa. Through the direct comparison of the extracellular metabolism of P. aeruginosa and S. aureus in a physiologically relevant environment, this work provides insight toward the potential for metabolic interactions in vivo and supports the development of species-specific diagnostic markers of infection. IMPORTANCE Interactions between P. aeruginosa and S. aureus can impact pathogenicity and antimicrobial efficacy. In this study, we aim to better understand the potential for metabolic interactions between P. aeruginosa and S. aureus in an environment resembling the cystic fibrosis lung. We find that S. aureus and P. aeruginosa consume many of the same nutrients, suggesting that metabolic competition may play an important role in community dynamics during coinfection. We further identify metabolites uniquely produced by either organism with the potential to be developed into species-specific biomarkers of infection in the cystic fibrosis lung.

The evolving landscape of untargeted metabolomics

AIMS

Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics.

DATA SYNTHESIS

Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available.

CONCLUSIONS

Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.

HPV post-infection microenvironment and cervical cancer

Human papillomavirus (HPV) is the most common sexually transmitted virus worldwide. More than 99% of cervical cancer cases are associated with certain types of HPVs, termed high-risk types. In addition to the well-known transformative properties, HPVs-infected cells actively instruct the local milieu and create a supportive post-infection microenvironment (PIM), which is becoming recognized as a key factor for the viral persistence, propagation, and malignant progression. The PIM is initiated and established via a complex interplay among virus-infected cells, immune cells, and host stroma, as well as their derived components including chemokines, cytokines, extracellular vesicles, and metabolites. In this review, we summarize the current understanding of these key components, characteristics, and effects of the PIM, and highlights the prospect of targeting the PIM as a potential strategy to improve therapeutic outcomes for cervical cancer.

Crocodylus porosus: a potential source of anticancer molecules

Background

Cancer remains a global threat resulting in significant morbidity and mortality despite advances in therapeutic interventions, suggesting urgency for identification of anticancer agents. Crocodiles thrive in polluted habitat, feed on germ-infested meat, are exposed to carcinogenic heavy metals, are the very few species to survive the catastrophic Cretaceous–Paleogene extinction event, yet have a prolonged lifespan and rarely been reported to develop cancer. Therefore, we hypothesised that animals living in polluted environments such as crocodiles possess anticancer molecules/mechanisms.

Methods

Crocodylus porosus was procured, blood collected, dissected and lysates prepared from internal organs. Organ lysates and sera were tested for growth inhibition, cytotoxic effects and cell survival against HeLa, PC3 and MCF7 cells and subjected to liquid chromatography mass spectrometry. RNA transcriptome analysis and differential gene analysis were performed using Galaxy Bioinformatics.

Results

Sera exhibited potent growth inhibition and cytotoxic effects against cancer cells. 80 molecules were detected from C. porosus and 19 molecules were putatively identified. Additionally, more than 100 potential anticancer peptides were identified from sera using bioinformatics based on peptide amino acid composition, binary profile, dipeptide composition and pseudo-amino acid composition. Following transcriptome analysis, 14 genes in treated HeLa cells, 51 genes in treated MCF7 cells and 2 genes in treated PC3 cells, were found to be expressed, compared with untreated controls.

Conclusion

Animals residing in polluted milieus are an unexploited source for prospective pharmaceutical drugs, and could lead to identification of novel antitumour compound(s) and/or further understanding of the mechanisms of cancer resistance.

Paper Spray Ionization Mass Spectrometry as a Potential Tool for Early Diagnosis of Cervical Cancer

Squamous intraepithelial lesion is an abnormal growth of epithelial cells on the surface of the cervix that may lead to cervical cancer. Analytical protocols for the determination of squamous intraepithelial lesions are in high demand, since cervical cancer is the fourth most diagnosed cancer among women in the world. Here, paper spray ionization mass spectrometry (PSI-MS) is used to distinguish between healthy (negative for intraepithelial lesion or malignancy) and diseased (high-grade squamous intraepithelial lesion) blood plasmas. A total of 86 blood samples of different women (49 healthy samples, 37 diseased samples) were collected, and the plasmas were prepared. Then, 10 μL of each plasma sample was deposited onto triangular papers for PSI-MS analysis. No additional step of sample preparation was necessary. The interval-successive projection algorithm linear discriminant analysis (iSPA-LDA) was applied to the PSI mass spectra, showing six ions (mostly phospholipids) that were predictive of healthy and diseased plasmas. Values of 77% accuracy, 86% sensitivity, 80% positive predictive value (PPV), and 75% negative predictive value (NPV) were achieved. This study provides evidence that PSI-MS may potentially be used as a fast and simple analytical technique for the early diagnosis of cervical cancer.

A Protocol for the Multi-Omic Integration of Cervical Microbiota and Urine Metabolomics to Understand Human Papillomavirus (HPV)-Driven Dysbiosis

The multi-omic integration of microbiota data with metabolomics has gained popularity. This protocol is based on a human multi-omics study, integrating cervicovaginal microbiota, HPV status and neoplasia, with urinary metabolites. Indeed, to understand the biology of the infections and to develop adequate interventions for cervical cancer prevention, studies are needed to characterize in detail the cervical microbiota and understand the systemic metabolome. This article is a detailed protocol for the multi-omic integration of cervical microbiota and urine metabolome to shed light on the systemic effects of cervical dysbioses associated with Human Papillomavirus (HPV) infections. This methods article suggests detailed sample collection and laboratory processes of metabolomics, DNA extraction for microbiota, HPV typing, and the bioinformatic analyses of the data, both to characterize the metabolome, the microbiota, and joint multi-omic analyses, useful for the development of new point-of-care diagnostic tests based on these approaches.

Cervicovaginal Microbiome and Urine Metabolome Paired Analysis Reveals Niche Partitioning of the Microbiota in Patients with Human Papilloma Virus Infections

In this study, we evaluate the association between vaginal and cervical human papillomavirus infections high-risk types (HPV+H), negative controls (HPV-), the bacterial biota, and urinary metabolites via integration of metagenomics, metabolomics, and bioinformatics analysis. We recently proposed that testing urine as a biofluid could be a non-invasive method for the detection of cervical HPV+H infections by evaluating the association between cervical HPV types and a total of 24 urinary metabolites identified in the samples. As a follow-up study, we expanded the analysis by pairing the urine metabolome data with vaginal and cervical microbiota in selected samples from 19 Puerto Rican women diagnosed with HPV+H infections and HPV- controls, using a novel comprehensive framework, Model-based Integration of Metabolite Observations and Species Abundances 2 (MIMOSA2). This approach enabled us to estimate the functional activities of the cervicovaginal microbiome associated with HPV+H infections. Our results suggest that HPV+H infections could induce changes in physicochemical properties of the genital tract through which niche partitioning may occur. As a result, Lactobacillus sp. enrichment coincided with the depletion of L. iners and Shuttleworthia, which dominate under normal physiological conditions. Changes in the diversity of microbial species in HPV+H groups influence the capacity of new community members to produce or consume metabolites. In particular, the functionalities of four metabolic enzymes were predicted to be associated with the microbiota, including acylphosphatase, prolyl aminopeptidase, prolyl-tRNA synthetase, and threonyl-tRNA synthetase. Such metabolic changes may influence systemic health effects in women at risk of developing cervical cancer. Overall, even assuming the limitation of the power due to the small sample number, our study adds to current knowledge by suggesting how microbial taxonomic and metabolic shifts induced by HPV infections may influence the maintenance of microbial homeostasis and indicate that HPV+H infections may alter the ecological balance of the cervicovaginal microbiota, resulting in higher bacterial diversity.

The vaginal metabolome and microbiota of cervical HPV-positive and HPV-negative women: a cross-sectional analysis

OBJECTIVE

Characterise the vaginal metabolome of cervical HPV-infected and uninfected women.

DESIGN

Cross-sectional.

SETTING

The Center for Health Behavior Research at the University of Maryland School of Public Health.

SAMPLE

Thirty-nine participants, 13 categorised as HPV-negative and 26 as HPV-positive (any genotype; HPV⁺ ), 14 of whom were positive with at least one high-risk HPV strain (hrHPV).

METHOD

Self-collected mid-vaginal swabs were profiled for bacterial composition by 16S rRNA gene amplicon sequencing, metabolites by both gas and liquid chromatography mass spectrometry, and 37 types of HPV DNA.

MAIN OUTCOME MEASURES

Metabolite abundances.

RESULTS

Vaginal microbiota clustered into Community State Type (CST) I (Lactobacillus crispatus-dominated), CST III (Lactobacillus iners-dominated), and CST IV (low-Lactobacillus, 'molecular-BV'). HPV⁺ women had higher biogenic amine and phospholipid concentrations compared with HPV^- women after adjustment for CST and cigarette smoking. Metabolomic profiles of HPV⁺ and HPV^- women differed in strata of CST. In CST III, there were higher concentrations of biogenic amines and glycogen-related metabolites in HPV⁺ women than in HPV^- women. In CST IV, there were lower concentrations of glutathione, glycogen, and phospholipid-related metabolites in HPV⁺ participants than in HPV^- participants. Across all CSTs, women with hrHPV strains had lower concentrations of amino acids, lipids, and peptides compared with women who had only low-risk HPV (lrHPV).

CONCLUSIONS

The vaginal metabolome of HPV⁺ women differed from HPV^- women in terms of several metabolites, including biogenic amines, glutathione, and lipid-related metabolites. If the temporal relation between increased levels of reduced glutathione and oxidised glutathione and HPV incidence/persistence is confirmed in future studies, anti-oxidant therapies may be considered as a non-surgical HPV control intervention.

TWEETABLE ABSTRACT

Metabolomics study: Vaginal microenvironment of HPV⁺ women may be informative for non-surgical interventions.

Translational Metabolomics: Current Challenges and Future Opportunities

Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.