Skin cancer, the most common global malignancy, is linked to ultraviolet (UV)-driven serum 25-hydroxyvitamin D (25(OH)D)synthesis, with its controversial role possibly reflecting cumulative UV exposure. This study aimed to assess the association and causality between 25(OH)D levels and skin cancer risk using the National Health and Nutrition Examination Survey (1999–2018) data and Mendelian randomization (MR) analyses, evaluating 25(OH)D as a screening biomarker.

We integrated data from the National Health and Nutrition Examination Survey (1999–2018; n = 21,357 U.S. adults, including 631 skin cancer cases) with MR analyses using genome-wide association study-derived genetic variants to assess the causal relationship between serum 25(OH)D levels and skin cancer risk.

Higher 25(OH)D levels were associated with increased risks of nonmelanoma skin cancer [odds ratio (OR) (95% confidence interval (CI)) = 2.94 (2.10, 4.20)], melanoma [OR (95% CI) = 2.94 (1.73, 5.28)], and other skin cancers [OR (95% CI) = 2.10 (1.36, 3.36)]. MR analyses supported a causal relationship for nonmelanoma skin cancer [OR (95% CI) = 1.01 (1.00, 1.02)] and melanoma [OR (95% CI) = 1.00 (1.00, 1.01)]. Risks were highest in males, older adults, and individuals with obesity.

Higher serum 25(OH)D levels are associated with increased skin cancer risk, likely reflecting cumulative UV exposure. Routine monitoring of 25(OH)D, combined with UV exposure management, is recommended for risk stratification in skin cancer screening, particularly among high-risk groups. Validation in multiethnic cohorts is needed to confirm these findings.

circPVT1 has emerged as a key regulator in disease progression and clinical outcomes. However, its prognostic relevance and association with clinicopathological parameters in solid malignancies remain to be fully elucidated. To address this, we conducted a meta-analysis to elucidate the clinical significance of circPVT1 in solid tumors.

A comprehensive literature search was conducted across multiple databases, including PubMed, Web of Science, Embase, the Cochrane Library, and CNKI, with a cutoff date of December 31, 2024. Statistical analyses were conducted using STATA 12.0 to calculate pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs), assessing the impact of circPVT1 expression on overall survival (OS) and its association with clinicopathological characteristics.

This analysis included 27 clinical studies encompassing a total of 2,219 patients. Elevated circPVT1 expression was significantly associated with poorer OS in patients with solid tumors (HR = 1.68, 95% CI: 1.39–2.02, P < 0.001). This association was particularly notable in lung cancer (HR = 2.08, 95% CI: 1.51–2.88, P < 0.001) and osteosarcoma (HR = 1.65, 95% CI: 1.38–1.97, P < 0.001), with similar trends observed in hepatocellular carcinoma, colorectal cancer, and papillary thyroid carcinoma. Furthermore, the increased circPVT1 level was correlated with larger tumor size (OR = 1.36, 95% CI: 1.11–1.67, P = 0.004), lymph node metastasis (OR = 1.56, 95% CI: 1.22–2.00, P < 0.001), distant metastasis (OR = 1.80, 95% CI: 1.10–2.92, P = 0.017), and advanced tumor-node-metastasis stage (OR = 1.84, 95% CI: 1.50–2.25, P < 0.001).

Aberrant circPVT1 expression is associated with adverse OS and unfavorable clinicopathological features in solid tumors, underscoring its potential utility as a prognostic biomarker and indicator of tumor aggressiveness.

Wilms tumor is the most common kidney tumor in children aged 0-14 years. MicroRNAs are small, noncoding RNAs linked to the development of malignant tumors. Several studies have shown the association between single nucleotide polymorphism in miR-27a and cancer risk. This study aimed to explore the potential impact of the miR-27a rs895819 T>C polymorphism on Wilms tumor susceptibility.

The rs895819 T>C polymorphism was genotyped using the TaqMan method in 145 patients with Wilms tumors and 531 controls. Logistic regression models were used to assess the association between this polymorphism and Wilms tumor risk. A stratified analysis was also performed based on age, sex, and clinical stage.

The rs895819 T>C polymorphism showed genotypic distribution consistent with Hardy-Weinberg equilibrium (P = 0.749). The differences were not statistically significant. The miR-27a rs895819 T>C polymorphism was not significantly associated with Wilms tumor susceptibility, and the stratified analysis did not yield any significant differences.

Our study provides evidence of a lack of association between the miR-27a rs895819 T>C polymorphism and Wilms tumor susceptibility. Further validation through larger sample sizes and additional genetic polymorphisms is warranted.

Prostate cancer is the second most diagnosed cancer in men worldwide and a significant cause of cancer-related death. Proteogenomic analysis offers insights into how genomic mutations influence protein expression and can identify novel biomarkers. This study aimed to investigate the impact of missense mutations on protein abundance in prostate cancer versus healthy tissues using SILAC-based quantitative proteomics.

Mass spectrometry data from prostate tumors and adjacent healthy tissues were analyzed using stable isotope labeling. Peptides were classified based on their abundance into RefSeq and Variant Abundant groups. Missense mutations were mapped via RefSeq and dbPepVar databases. Protein intensity metrics were compared, and Spearman’s correlation was used to evaluate the relationship between mutation presence and protein abundance.

Functional enrichment revealed that RefSeq Abundant proteins are involved in normal metabolic and structural functions, while Variant Abundant proteins are enriched in tumor-related pathways such as immune evasion and apoptosis suppression. A significant negative correlation was found between protein intensity difference and ratio (p < 0.05), indicating that missense mutations contribute to altered protein expression. Mutation hotspot analysis identified recurrent alterations in genes such as PPIF and ACTB. PROVEAN was used to evaluate the functional impact of variants, identifying several as deleterious to protein stability and function.

Missense mutations are associated with altered protein abundance and may promote oncogenic processes in prostate cancer. These findings enhance the understanding of genome-proteome interactions and could support the development of targeted biomarkers and therapies.

Emerging evidence implicates immune dysregulation and neuroinflammation in the pathogenesis of epilepsy, yet the causal mechanisms remain unclear. This study aimed to investigate the causal effects of immune cells and inflammatory proteins on epilepsy and evaluate the mediating role of inflammatory proteins.

This study utilized the largest available genome-wide association study data on immune cell phenotypes and inflammatory proteins as exposures, and epilepsy genome-wide association study data from the FinnGen dataset as outcomes. Five Mendelian randomization (MR) methods were applied within a two-sample MR framework to assess causal effects. Furthermore, a two-step MR analysis was conducted to quantify the proportion of epilepsy and its subtypes influenced by immune cells through inflammatory proteins.

The two-sample MR analysis identified 32 immune cell phenotypes associated with epilepsy risk (19 risk-increasing, e.g., CD19+ B cells; 13 protective, e.g., regulatory T cell subsets). Subtype analyses revealed 30 immune phenotypes associated with generalized epilepsy and 26 with focal epilepsy. Eight inflammatory proteins showed suggestive causal effects on epilepsy: C-C chemokine ligand 23, C-X-C motif chemokine ligand 6, C-X-C motif chemokine ligand 11, and vascular endothelial growth factor A increased epilepsy risk, while interleukin-13 (IL-13), leukemia inhibitory factor receptor, tumor necrosis factor, and osteoprotegerin conferred protection. Mediation analysis indicated that inflammatory proteins mediated 6.3–13.5% of the immune effects on epilepsy. Specifically, CD14+CD16+ monocytes increased epilepsy risk through elevated C-C chemokine ligand 23 levels (8.5% mediation), while effector memory double-negative (CD4−CD8−) T cells reduced epilepsy risk via upregulation of IL-13 (6.3%). Sensitivity analyses confirmed the robustness of these findings (P heterogeneity/pleiotropy > 0.05). Although no associations reached Bonferroni-corrected significance, the findings implicate B cells, monocytes, regulatory T cells, and cytokines (e.g., IL-13, leukemia inhibitory factor receptor) in the pathogenesis of epilepsy, with inflammatory proteins acting as partial mediators.

These results enhance our understanding of immune-inflammatory pathways in epilepsy and highlight potential therapeutic targets. Future studies should validate these findings across diverse populations and further elucidate the molecular mechanisms underlying the identified associations.

Characteristic signs of alopecia are gradual thinning, disruption of structural features, and the hair development cycle (anagen, catagen, telogen) against the background of miniaturization of hair follicles, which leads to baldness and psychological stress in patients. Despite the rapid development and clinical application of synthetic pharmacological, cellular/acellular, and molecular drugs, no effective therapeutic agent against alopecia has yet been developed. Great hopes are pinned on the improvement of therapeutic strategies with the introduction of exosomes into practical application, which contain a wide array of active substances for the targeted stimulation of hair follicle activity (anagen inducers) through the regulation of intracellular signaling cascades, growth factors, and microRNAs. The review discusses in detail the microRNAs and their intracellular targets that control hair follicle morphogenesis. It also focuses on the prospects of using stem cell exosomes from various sources for the treatment of alopecia, providing a clinical rationale for potential benefits and risks.

Human papillomavirus (HPV) infection is the primary cause of cervical, anogenital, and oropharyngeal cancers in the United States. These cancers are preventable through HPV vaccination. Research is critically needed to identify effective strategies for promoting HPV vaccination among high-risk groups. This study develops a risk prediction model to identify patients who are unlikely to complete HPV vaccination, with the goal of using the model to direct resources and increase vaccination rates.

We assessed vaccination status along with patient, provider, and clinic characteristics that predict vaccination completion. We then developed a predictive model to assess the likelihood of completing HPV vaccination, which can be used to target interventions based on patient needs. We used a retrospective cohort from a large integrated delivery system in Oregon. Using logistic regression with data available in the electronic health record, we created a risk model to determine the likelihood of vaccination completion among patients aged 11–17 years.

In a cohort of 61,788 patients, 40,570 (65.7%) had received at least one dose of the HPV vaccine. The full model included 17 demographic, clinical, provider, and community characteristics, achieving a bootstrap-corrected C-statistic of 0.67 with adequate calibration. The reduced model, which retained five demographic and clinical characteristics (age, language, race, ethnicity, and prior vaccinations), had a bootstrap-corrected C-statistic of 0.65 and adequate calibration.

Our findings suggest that a risk prediction model can guide the implementation of targeted interventions and the intensity of those interventions based on the likelihood of vaccination completion.