Identification of genes differentially expressed in menstrual breakdown and repair

Quantitative evaluation of endometrium-expressed mRNAs for the purpose of discriminating between menstruation and traumatic vaginal injury in sexual assault cases

In sexual assault cases, it is crucial to discriminate between peripheral blood and menstrual blood to provide evidence for vaginal intercourse with traumatic injury. In this study, the menstrual blood mRNA markers progestagen-associated endometrial protein (PAEP), matrix metallopeptidase 7 (MMP7), and left-right determination factor 2 (LEFTY2) were evaluated by quantitative RT-PCR (RT-qPCR) for the discrimination of menstrual blood from peripheral blood and vaginal fluid. As a result, all markers with cutoff delta cycle quantification (ΔCq) values were specifically determined in menstrual blood among forensically relevant body fluids. Even though the changes in the expression levels of each marker differed during the menstrual cycle, all markers were determined to be positive in most of the randomly collected menstrual blood samples that were analyzed. Additionally, the markers with proposed cutoff ΔCq values could discriminate between menstrual blood and peripheral blood-mixed vaginal fluid samples. The determination of positive markers was less affected by storage temperature under dry conditions than under wet conditions, while PAEP was detectable in samples stored below room temperature under wet conditions. The detectability of PAEP was considered to be the result of its higher expression level compared with MMP7 and LEFTY2. In conclusion, menstrual blood markers for the RT-qPCR procedure evaluated in this study were highly specific for menstrual blood. The proposed procedure could be useful for discriminating between menstruation and traumatic bleeding in the female genital tract. In particular, PAEP is expected to be applicable to forensic casework samples because of its high specificity and robustness.

Pancancer Analysis of NSUN2 with a Focus on Prognostic and Immunological Roles in Endometrial Cancer

The significance of NSUN2 in carcinogenesis is gradually being recognized, yet a comprehensive analysis across pan-cancer remains a pivotal void in existing research. In our investigation, we capitalized on the UCSC Xena platform to evaluate NSUN2 expression levels and their prognostic implications across a range of cancer types. Furthermore, we employed the cBioPortal database to delve into the genomic variations of NSUN2 within human cancers. Our study encompassed the use of molecular docking, genomic tumor profiling, and an assessment of the gene's responsiveness to pharmacological treatments. Additionally, we utilized algorithmic techniques to measure the relationship between NSUN2 expression and key clinical biomarkers, such as microsatellite instability (MSI), tumor mutational burden (TMB), and immune cell infiltration. Our results have established a notable association between NSUN2 and endometrial cancer (UCEC), thereby confirming its clinical significance through an analysis of tumoral expression patterns, mutational spectra, methylation profiles, and drug sensitivity. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were crucial tools in elucidating the biological roles of NSUN2 in endometrial cancer. Consistently, elevated NSUN2 expression was associated with unfavorable clinical outcomes and was primarily observed in the context of genetic amplifications. Across 22 distinct tumor types, our analysis revealed a notable correlation between NSUN2 expression and various metrics related to immune cell infiltration, tumor stroma, and immune scores. Notably, higher levels of NSUN2 expression have been linked to a reduced response to certain chemotherapeutic agents, including PHA-793887. In UCEC, a positive correlation between NSUN2 methylation and gene expression hints at a potential epigenetic regulatory mechanism underlying cancer progression. Our study highlights the potential of NSUN2 as a key oncogene and its promising role as a therapeutic target as well as a prognostic biomarker for endometrial cancer. This underscores its potential importance in predicting responses to immunotherapy.

Quantitative proteomic analysis and verification identify global protein profiling dynamics in pig during the estrous cycle

The current estrus detection method is generally time-consuming and has low accuracy. As such, a deeper understanding of the physiological processes during the estrous cycle accelerates the development of estrus detection efficiency and accuracy. In this study, the label-free acquisition mass spectrometry was used to explore salivary proteome profiles during the estrous cycle (day -3, day 0, day 3, and day 8) in pigs, and the parallel reaction monitoring (PRM) was applied to verify the relative profiles of protein expression. A total of 1,155 proteins were identified in the label-free analysis, of which 115 were identified as differentially expressed proteins (DEPs) among different groups (p ≤ 0.05). Functional annotation revealed that the DEPs were clustered in calcium ion binding, actin cytoskeleton, and lyase activity. PRM verified the relative profiles of protein expression, in which PHB domain-containing protein, growth factor receptor-bound protein 2, elongation factor Tu, carboxypeptidase D, carbonic anhydrase, and trefoil factor 3 were confirmed to be consistent in both label-free and PRM approaches. Comparative proteomic assays on saliva would increase our knowledge of the estrous cycle in sows and provide potential methods for estrus detection.

Tumor immune checkpoints and their associated inhibitors

Immunological evasion is one of the defining characteristics of cancers, as the immune modification of an immune checkpoint (IC) confers immune evasion capabilities to tumor cells. Multiple ICs, such as programmed cell death protein-1 (PD-1) and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), can bind to their respective receptors and reduce tumor immunity in a variety of ways, including blocking immune cell activation signals. IC blockade (ICB) therapies targeting these checkpoint molecules have demonstrated significant clinical benefits. This is because antibody-based IC inhibitors and a variety of specific small molecule inhibitors can inhibit key oncogenic signaling pathways and induce durable tumor remission in patients with a variety of cancers. Deciphering the roles and regulatory mechanisms of these IC molecules will provide crucial theoretical guidance for clinical treatment. In this review, we summarize the current knowledge on the functional and regulatory mechanisms of these IC molecules at multiple levels, including epigenetic regulation, transcriptional regulation, and post-translational modifications. In addition, we provide a summary of the medications targeting various nodes in the regulatory pathway, and highlight the potential of newly identified IC molecules, focusing on their potential implications for cancer diagnostics and immunotherapy.

Covid-19 vaccination and menstrual cycle length in the Apple Women’s Health Study.. [PMID: 35860226 PMCID: PMC9298140 DOI: 10.1101/2022.07.07.22277371]

Background

COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination.

Methods

We conducted a longitudinal analysis within a subgroup of 14,915 participants in the Apple Women’s Health Study (AWHS) who enrolled between November 2019 and December 2021 and met the following eligibility criteria: were living in the U.S., met minimum age requirements for consent, were English speaking, actively tracked their menstrual cycles, and responded to the COVID-19 Vaccine Update survey. In the main analysis, we included tracked cycles recorded when premenopausal participants were not pregnant, lactating, or using hormonal contraceptives. We used conditional linear regression and multivariable linear mixed-effects models with random intercepts to estimate the covariate-adjusted difference in mean cycle length, measured in days, between pre-vaccination cycles, cycles in which a vaccine was administered, and post-vaccination cycles within vaccinated participants, and between vaccinated and unvaccinated participants. We further compared associations between vaccination and menstrual cycle length by the timing of vaccine dose within a menstrual cycle (i.e., in follicular or luteal phase). We present Bonferroni-adjusted 95% confidence intervals to account for multiple comparisons.

Results

A total of 128,094 cycles (median = 10 cycles per participant; interquartile range: 4-22) from 9,652 participants (8,486 vaccinated; 1,166 unvaccinated) were included. The average within-individual standard deviation in cycle length was 4.2 days. Fifty-five percent of vaccinated participants received Pfizer-BioNTech’s mRNA vaccine, 37% received Moderna’s mRNA vaccine, and 7% received the Johnson & Johnson/Janssen vaccine (J&J). We found no evidence of a difference between mean menstrual cycle length in the unvaccinated and vaccinated participants prior to vaccination (0.24 days, 95% CI: −0.34, 0.82).

Among vaccinated participants, COVID-19 vaccination was associated with a small increase in mean cycle length (MCL) for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimates for pre vs post cycle lengths were 0.14 days (95% CI: −0.13, 0.40) in the first cycle following vaccination, 0.13 days (95% CI: −0.14, 0.40) in the second, −0.17 days (95% CI: −0.43, 0.10) in the third, and −0.25 days (95% CI: −0.52, 0.01) in the fourth cycle post-vaccination. Follicular phase vaccination was associated with an increase in MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles.

Conclusions

COVID-19 vaccination was associated with an immediate short-term increase in menstrual cycle length overall, which appeared to be driven by doses received in the follicular phase. However, the magnitude of this increase was small and diminished in each cycle following vaccination. No association with cycle length persisted over time. The magnitude of change associated with vaccination was well within the natural variability in the study population. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.

Proliferating cell nuclear antigen clamp associated factor, a potential proto-oncogene with increased expression in malignant gastrointestinal tumors

Gastrointestinal (GI) cancers, including malignancies in the gastrointestinal tract and accessory organs of digestion, represent the leading cause of death worldwide due to the poor prognosis of most GI cancers. An investigation into the potential molecular targets of prediction, diagnosis, prognosis, and therapy in GI cancers is urgently required. Proliferating cell nuclear antigen (PCNA) clamp associated factor (PCLAF), which plays an essential role in cell proliferation, apoptosis, and cell cycle regulation by binding to PCNA, is a potential molecular target of GI cancers as it contributes to a series of malignant properties, including tumorigenesis, epithelial-mesenchymal transition, migration, and invasion. Furthermore, PCLAF is an underlying plasma prediction target in colorectal cancer and liver cancer. In addition to GI cancers, PCLAF is also involved in other types of cancers and autoimmune diseases. Several pivotal pathways, including the Rb/E2F pathway, NF-κB pathway, and p53-p21 cascade, are implicated in PCLAF-mediated diseases. PCLAF also contributes to some diseases through dysregulation of the p53 pathway, WNT signal pathway, MEK/ERK pathway, and PI3K/AKT/mTOR signal cascade. This review mainly describes in detail the role of PCLAF in physiological status and GI cancers. The signaling pathways involved in PCLAF are also summarized. Suppression of the interaction of PCLAF/PCNA or the expression of PCLAF might be potential biological therapeutic strategies for GI cancers.

Role of GSTM1 and GSTT1 genotypes in differentiated thyroid cancer and interaction with lifestyle factors: Results from case-control studies in France and New Caledonia

Background

GSTM1 and GSTT1 are involved in detoxification of xenobiotics, products of oxidative stress and in steroid hormones metabolism. We investigated whether GSTM1 and GSTT1 gene deletion was associated with DTC risk and explored interaction with non-genetic risk factors of DTC.

Methods

The study included 661 DTC cases and 736 controls from two case-control studies conducted in France and New Caledonia. Odds ratios (OR) and their confidence interval (CI) for DTC associated with GST genotypes, alcohol drinking, tobacco smoking, body mass index and hormonal factors were calculated using logistic regression models.

Results

Results are presented for Europeans and Melanesians combined, as no heterogeneity between groups was detected. We found that DTC risk increased with obesity and decrease with alcohol drinking. After stratification by gene deletion status, the OR for obesity was 5.75, (95%CI 2.25–14.7) among individuals with GSTT1 and GSTM1-deleted genotype, and 1.26, (95%CI 0.89–1.77) in carriers of both genes (p-interaction = 0.02). The OR for drinking ≥1 glass/week was 0.33 (95%CI 0.15–0.74) in GSTT1-null individuals while it was 1.01 (95%CI 0.67–1.52) in non-null carriers of the gene (p-interaction = 0.01). No interaction between GST genotypes and other non-genetic risk factors was detected.

Conclusion

GSTM1 and GSTT1 genotypes may modulate the DTC risk associated with BMI and alcohol consumption.

Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues

Genome-wide association studies in the fields of reproductive medicine and endocrinology are yielding robust genetic variants associated with disease. Integrated genomic, transcriptomic, and epigenomic molecular profiling studies are common methodologies used to understand the biologic pathways perturbed by these variants. However, molecular profiling resources do not include the tissue most relevant to many female reproductive traits, the endometrium, while the parameters influencing variability of results from its molecular profiling are unclear. We investigated the sources of DNA methylation and RNA expression profile variability in endometrium (n = 135), endometriotic disease tissue (endometriosis), and subcutaneous abdominal fat samples from 24 women, quantifying between-individual, within-tissue (cellular heterogeneity), and technical variation. DNA samples (n = 96) were analyzed using Illumina HumanMethlylation450 BeadChip arrays; RNA samples (n = 39) were analyzed using H12-expression arrays. Variance-component analyses showed that, for the top 10–50% variable DNA methylation/RNA expression sites, between-individual variation far exceeded within-tissue and technical variation. Menstrual-phase accounted for most variability in methylation/expression patterns in endometrium (P_m = 7.8 × 10⁻³, P_e = 8.4 × 10⁻⁵) but not in fat and endometriotic tissue; age was significantly associated with DNA methylation profile of endometrium (P_m = 9 × 10⁻⁵) and endometriotic disease tissue (P_m = 2.4 × 10⁻⁵); and smoking was significantly associated with DNA methylation in adipose tissue (P_m = 1.8 × 10⁻³). Hierarchical cluster analysis showed significantly different methylation signatures between endometrium and endometriotic tissue enriched for WNT signaling, angiogenesis, cadherin signaling, and gonadotropin-releasing-hormone-receptor pathways. Differential DNA methylation/expression analyses suggested detection of a limited number of sites with large fold changes (FC > 4), but power calculations accounting for different sources of variability showed that for robust detection >500 tissue samples are required. These results enable appropriate study design for large-scale expression and methylation tissue-based profiling relevant to many reproductive and endocrine traits.