Biomedical subjects

Xuan Zhou

Publications and source records attributed to Xuan Zhou.

4 recordsLinked to original sources

PubMed2026

Stratifying lung adenocarcinoma: a novel prognostic model based on mitochondrial outer membrane permeabilization activity.

UNLABELLED: Mitochondrial outer membrane permeabilization (MOMP) is a core apoptotic regulatory event that dictates mitochondrial integrity, where full activation drives cell death and sublethal dysregulation contributes to tumor genomic instability. We used the Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD) as the training cohort and the Gene Expression Omnibus dataset GSE42127 as the validation cohort to identify prognostic genes related to MOMP activity in lung adenocarcinoma (LUAD) and to evaluate their potential biological significance. By intersecting MOMP-related genes with differentially expressed genes, combined with survival analysis, Mendelian randomization analysis, and 101 machine-learning algorithm combinations, seven prognostic genes, namely BIRC5, PSMD11, TNFRSF13C, YWHAZ, YWHAG, CYCS, and LTB, were identified. Next, an optimal prognostic model was constructed based on the gradient boosting machine (GBM) algorithm. Based on the risk score, LUAD patients were stratified into high- and low-risk groups, and patients in the high-risk group exhibited poorer overall survival in both the training and validation cohorts. Furthermore, a nomogram integrating the risk score and clinicopathological factors was developed and showed favorable predictive performance for 1-, 3-, and 5-year survival. Meanwhile, functional and immune analyses revealed that the high-risk group was enriched in DNA replication-related pathways and demonstrated a higher tumor mutation burden (TMB). Correlation analysis indicated that TNFRSF13C was positively correlated with activated B cells, whereas BIRC5 was negatively correlated with eosinophils, suggesting that MOMP-related genes might be involved in remodeling the immune microenvironment of LUAD. Drug sensitivity analysis showed differences in predicted half-maximal inhibitory concentration (IC50) values between the risk groups, suggesting the potential value of this model in assisting therapeutic stratification. Single-cell RNA sequencing (scRNA-seq) further identified T lymphocytes as a key cell type, with numerous prognostic genes exhibiting differential expression in T cells or dynamic changes during differentiation. We suggest that the MOMP-related signature established in this study may provide a reference for prognostic stratification in LUAD and offers candidate prognostic genes for subsequent experimental and clinical validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13205-026-05058-6.

Lung adenocarcinoma↗

PubMed2026

Targeted sequencing reveals a distinct genetic alteration landscape in oral multiple primary squamous cell carcinomas.

OBJECTIVE: Oral multiple primary cancers (MPCs) are associated with poor clinical outcomes, yet their genomic characteristics remain insufficiently understood. DESIGN: Fifty-four formalin-fixed paraffin-embedded (FFPE) tumor samples from 30 patients with oral MPCs were analyzed using high-depth targeted sequencing of a customized 14-gene panel derived from prior whole-exome sequencing data. Detected alterations were analyzed after removal of synonymous mutations. RESULTS: Non-silent genomic alterations were identified in 59.3% (32/54) of samples, involving 19 patients. A total of 70 variant loci across 13 genes were detected. AKAP13 was the most frequently mutated gene at both the sample (22.2%, 12/54), with recurrent mutations observed across multiple patients. In contrast, TP53 mutations occurred at a substantially lower frequency (11.1%, 6/54). Marked inter- and intra-patient mutational heterogeneity was observed. CONCLUSIONS: FFPE-based targeted sequencing enabled an initial characterization of genomic alterations in oral MPCs. Recurrent alterations in AKAP13, GLI2, JMJD1C, and DNAH8, together with the relatively low frequency of TP53 alterations, identify candidate genomic features for further investigation and provide a basis for future studies of the molecular basis of oral MPCs.

Humans↗

PubMed2026

Comparing the Efficacy of Mechanochemical Ablation Versus Radiofrequency Ablation for Treating Great Saphenous Vein Incompetence: A Meta-Analysis.

BACKGROUND: The objective of this meta-analysis was to compare the efficacy of mechanochemical ablation (MOCA) and radiofrequency ablation (RFA) in the treatment of great saphenous vein (GSV) incompetence. METHODS: Online databases including PubMed, Cochrane Library, Embase, and Web of Science were searched to collect randomized controlled trials (RCTs) and cohort studies comparing MOCA and RFA in the treatment of varicose veins in lower extremities from database inception to October 2025. Primary outcome was anatomic success. Secondary outcomes were visual analog scale (VAS), Aberdeen Varicose Vein Questionnaire score (AVVQ), and complications. Two reviewers independently screened the retrieved literature, extracted data, and assessed the risk of bias in the included studies. Subsequent analysis was performed using RevMan 5.3. RESULTS: A total of four RCTs, one cohort study and retrospective cross-sectional study involving 737 patients (380 MOCA patients and 357 RFA patients) were included. The meta-analysis results showed that the RFA group was significantly better than the MOCA group in short term and long term of anatomical success rate [(odds ratio [OR] = 0.38; 95% confidence interval [CI] (0.20, 0.71), P = 0.003), (OR = 0.17, 95% CI (0.06, 0.45), P = 0.0003)], but patients in the MOCA group had significantly lower perioperative period pain (mean difference [MD] = -4.48, 95% CI (-7.58, -1.37), P = 0.005] and required fewer days to return to normal activities (MD = -0.76, 95% CI, (-0.95, -0.57), P < 0.001). No significant differences were observed between the two groups in minor and major complications [(OR = 0.93, 95% CI (0.66, 1.33), P = 0.70), (OR = 1.30, 95% CI (0.32, 5.28), P = 0.72)] or quality of life scores (MD = -0.45, 95% CI (-2.53 to 1.63), P = 0.67). CONCLUSION: MOCA of GSV incompetence is an effective and safe method. Compared with RFA, it has lower postoperative pain score and faster recovery time. However, the anatomical success rates were significantly lower with MOCA than with RFA. Therefore, long-term follow-up to evaluate the impact on clinical results is required.

Humans↗

PubMed2025

Deep learning guided programmable design of Escherichia coli core promoters from sequence architecture to strength control.

Core promoters are essential regulatory elements that control transcription initiation, but accurately predicting and designing their strength remains challenging due to complex sequence-function relationships and the limited generalizability of existing AI-based approaches. To address this, we developed a modular platform integrating rational library design, predictive modelling, and generative optimization into a closed-loop workflow for end-to-end core promoter engineering. Conserved and spacer region of core promoters exert distinct effects on transcriptional strength, with the former driving large-scale variation and the latter enabling finer gradation. Based on this insight, Mutation-Barcoding-Reverse Sequencing approach was used and constructed a synthetic promoter library comprising 112 955 variants with minimal redundancy and a 16 226-fold expression range. A Transformer-based model trained on this dataset achieved a Pearson correlation of 0.87 with experimentally measured promoter strengths. When combined with a conditional diffusion model, the system enabled de novo generation of promoter sequences with defined strengths, achieving a design-to-measurement correlation of 0.95 and maintaining high accuracy (R = 0.93) across varied sequence contexts. The designed promoters consistently preserved their intended strength gradients, demonstrating robust plug-and-play functionality. This work establishes a scalable and extensible platform (www.yudenglab.com) for deep learning-guided programmable design of Escherichia coli core promoters, enabling precise transcriptional control.

Promoter Regions, Genetic↗