Metabolomics variation profiling of vaginal discharge identifies potential targets for cervical cancer early warning

Rapid prediction of cervical cancer and high-grade precursor lesions: An integrated approach using low-field 1H NMR and chemometric analysis

Cervical cancer (CC) is a significant cause of morbidity and mortality in women, often preceded by high-grade cervical intraepithelial lesions (HSIL). Although conventional cytology (Pap smear) is widely used for screening, its sensitivity limitations and high false-positive rate reinforce the need for complementary methods. This study investigated the feasibility of low-field 1H NMR spectroscopy combined with chemometric modeling to differentiate healthy individuals (CON) from patients with HSIL and CC. Principal Component Analysis (PCA) was applied to explore metabolic patterns and identify relevant spectral variables in group differentiation. PCA1 highlighted the separation between CC and the other groups, while PCA2 and PCA3 evidenced intermediate metabolic characteristics in HSIL, reinforcing its role as a transition stage. Three classification scenarios were evaluated using Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA): (1) CON as target class, HSIL/CC as outclass classes; (2) HSIL as target class, CON as outclass class; and (3) CC as target class, CON as outclass class. Calibration was optimal (100 % SEN, SPE, ACC, MCC), and prediction showed higher efficacy in detecting CC (SPE = 100 %, MCC = 70 %), indicating that the model was more efficient in screening cervical cancer cases. Furthermore, low-field 1H NMR has demonstrated potential as a metabolomic screening tool. It is a promising alternative due to its greater accessibility, lower operational cost, and non-invasive nature, complementing traditional methods of early detection of tumors and cervical lesions.

NAD+ Metabolism Reprogramming Drives SIRT1-Dependent Deacetylation Inducing PD-L1 Nuclear Localization in Cervical Cancer

Cervical cancer (CC) is a major health threat to women, with immunotherapies targeting the programmed death receptor 1/programmed death ligand 1(PD-1/PD-L1) axis showing promise but encountering resistance in a significant patient population. This resistance has driven a critical quest to uncover the underlying mechanisms. This study uncovers a novel metabolic axis involving the nicotinamide adenine dinucleotide (NAD+) salvage pathway enzyme nicotinamide phosphoribosyltransferase (NAMPT) and the deacetylase Sirtuin 1 (SIRT1), which regulates PD-L1 expression and nuclear localization in CC. This axis may be a key factor contributing to the resistance observed in immunotherapy. This study reveals that PD-L1 overexpression in cancers is regulated by both transcriptional and post-transcriptional processes. Acetyl-proteomic analysis pinpoints SIRT1 as a central regulator in the deacetylation of histone H3 at lysines 27, which may influence PD-L1 subcellular distribution. This finding reveals the epigenetic control of immune checkpoint proteins by metabolic pathways, offering a new perspective on the regulation of PD-L1. The identification of the NAMPT/SIRT1 metabolic axis as a critical factor suggests that targeting this axis may enhance therapeutic responses.

The vaginal metabolomics profile with features of polycystic ovary syndrome: a pilot investigation in China

Background

Polycystic ovary syndrome (PCOS) is the most common metabolic disorder and reproductive endocrine disease, posing an elevated risk to women of reproductive age. Although metabolism differences in serum, amniotic fluid and urine have been documented in PCOS, there remains a paucity of evidence for vaginal fluid. This study aimed to identify the metabolic characteristics and potential biomarkers of PCOS in Chinese women of reproductive age.

Methods

We involved ten newly diagnosed PCOS women who attended gynecology at Zhongda Hospital and matched them with ten healthy controls who conducted health check-up programs at Gulou Maternal and Child Health Center in Nanjing, China from January 1st, 2019 to July 31st, 2020. Non-targeted metabolomics based on ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) was applied to differentially screen vaginal metabolites between PCOS group and healthy controls. Principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA) and enrichment analysis were used to observe differences, search for potential biomarkers and enrich related pathways.

Results

Among the 20 participants, a total of 195 different metabolites were detected between PCOS group and healthy control group. PCOS and control groups were effectively separated by vaginal fluid. Lipids and lipid-like molecules constituted the majority of differential metabolites. Notably, dopamine exhibited an increased trend in PCOS group and emerged as the most significant differential metabolite, suggesting its potential as a biomarker for identifying PCOS. The application of UHPLC-MS/MS based vaginal metabolomics methods showed significant differences between PCOS and non-PCOS healthy control groups, especially linoleic acid metabolism disorder. Most differential metabolites were enriched in pathways associated with linoleic acid metabolism, phenylalanine metabolism, tyrosine metabolism, nicotinate and nicotinamide metabolism or arachidonic acid metabolism.

Conclusions

In this pilot investigation, significant metabolomics differences could be obtained between PCOS and healthy control groups. For PCOS women of reproductive age, vaginal metabolism is a more economical, convenient and harmless alternative to provide careful personalized health diagnosis and potential targets for therapeutic intervention.

The human vaginal microbiota: from clinical medicine to models to mechanisms

The composition of the vaginal microbiota is linked to numerous reproductive health problems, including increased susceptibility to infection, pregnancy complications, and impaired vaginal tissue repair; however, the mechanisms contributing to these adverse outcomes are not yet fully defined. In this review, we highlight recent clinical advancements associating vaginal microbiome composition and function with health outcomes. Subsequently, we provide a summary of emerging models employed to identify microbe-microbe interactions contributing to vaginal health, including metagenomic sequencing, multi-omics approaches, and advances in vaginal microbiota cultivation. Last, we review new in vitro, ex vivo, and in vivo models, such as organoids and humanized microbiota murine models, used to define and mechanistically explore host-microbe interactions at the vaginal mucosa.