Tumor Hospital of Xinjiang Medical University

Exosomes serve as intercellular communication vectors and are involved in a broad range of physiological functions. Although exosome-based therapies have demonstrated diverse functional potential, the regulatory mechanisms underlying their biogenesis and secretion remain poorly understood. Here, we report that TEAD1 functions as a molecular switch, dramatically enhancing the synthesis and secretion of exosomes. Mechanistically, TEAD1 enhances exosome secretion by promoting the expression of exosome secretion-associated proteins RAB11, CD9, and SNAP23. We found that TEAD1 enhances exosome secretion from adipose-derived mesenchymal stem cells, thereby promoting skin wound healing in diabetic mice. Similarly, TEAD1 promotes the release of exosomes from bone marrow-derived mesenchymal stem cells, thereby facilitating spinal cord injury (SCI) repair. Our study elucidates a novel role for TEAD1 in driving exosome secretion in different cell types, highlighting the therapeutic potential of TEAD1 in enhancing tissue regeneration, particularly in diabetic wound healing and SCI repair.

The early and accurate diagnosis of cervical precancerous lesions is essential for mitigating the risk of cervical cancer. Given the limitations of traditional screening methods, such as inadequate sensitivity and low specificity, this study aims to assess the diagnostic performance of combined PAX1/JAM3 gene methylation testing for cervical intraepithelial neoplasia (CIN) and to explore its potential in triage management. Methylation testing serves as a tool for investigating the epigenetic alterations associated with diseases like cancer, thereby providing molecular biological evidence for diagnosis and prognosis. This study included 431 cervical exfoliated cell samples, which consisted of CIN1, CIN2/3, cervical cancer (CC), and control groups. The methylation levels of the PAX1/JAM3 genes were assessed using quantitative methylation-specific PCR. The diagnostic efficacy of these genes for high-grade lesions (CIN2+) was analyzed through receiver operating characteristic (ROC) curve analysis and was compared with HPV testing and cytological examination. Additionally, the diagnostic performance of PAX1/SOX1 methylation was preliminarily evaluated in a sub-cohort of 100 cases. Further evaluation was conducted on the triage referral rate and the impact of clinical intervention using this biomarker in HPV-positive patients. The area under the curve (AUC) for the PAX1/JAM3 methylation test in diagnosing CIN2+ was 0.89 (95% CI: 0.85-0.92), with a sensitivity of 83.1% and a specificity of 88.8%. In the sub-cohort, the PAX1/SOX1 combination also demonstrated high diagnostic potential for CIN3+ (AUC = 0.91), serving as a validation of methylation testing efficacy. In non-HPV16/18 positive patients, the sensitivity and specificity of methylation testing for CIN2+ were superior to those of cytology. Among patients undergoing colposcopy, 265 cases had results of ≤ASCUS, of which 51 were methylation positive, resulting in a colposcopy referral rate of 19.3%. PAX1/JAM3 gene methylation testing demonstrates strong diagnostic efficacy for cervical precancerous lesions and holds significant potential in triage diagnosis. The PAX1/SOX1 panel also shows promise as a complementary biomarker.

ObjectiveTo develop and validate an artificial intelligence (AI)-driven ultrasound radiomics model for predicting postoperative recurrence and metastasis in patients with triple-negative breast cancer (TNBC) receiving standardized therapies.MethodsWe conducted a retrospective study of 668 female TNBC patients (treated 2013-2018). Univariate and multivariate logistic regression were first used to screen significant clinicopathological variables for baseline assessment and to inform model development. Radiomic features were automatically extracted from pretreatment ultrasound images using PyRadiomics following tumor segmentation. A radiomics signature was constructed by integrating LASSO for feature selection with a support vector machine (SVM) classifier. The model’s performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, decision curve analysis (DCA), and confusion matrices.ResultsThe ultrasound radiomics model showed high predictive accuracy for any recurrence/metastasis, with an AUC of 0.9458 in the training cohort and 0.8983 in the validation cohort. For distinguishing between locoregional recurrence and distant metastasis, the model achieved AUCs of 0.9341 and 0.8824 in the training and validation cohorts, respectively. Calibration and decision curve analyses confirmed the model’s robust predictive capability and potential clinical utility.ConclusionThis study demonstrates that an AI-enhanced ultrasound radiomics model can effectively predict postoperative recurrence and metastasis patterns in TNBC, offering a promising non-invasive tool to support personalized prognosis assessment.

The aim is to investigate the value and mechanism of action of LINC00963 in septic cardiomyopathy (SCM). A total of 85 patients with cardiomyopathy (control group) and 108 SCM patients were enrolled. An in vitro model was created by treating cardiomyocytes with 1μg/mL of LPS. A sepsis mouse model was created using cecal ligation and puncture (CLP). Cox analysis was used to identify factors independently influencing mortality. Kaplan-Meier curves were used to record patient prognosis. RT-qPCR was used to detect gene expression. CCK8 and flow cytometry were employed to evaluate cell function. ELISA was used to detect inflammatory factor expression. Dual luciferase reporter and RIP validation were employed to confirm gene-targeted interactions. Upregulation of LINC00963 was observed in serum from patients with septic cardiomyopathy, heart tissue from septic mice, and LPS-infected cardiomyocytes, while miR-98-5p was downregulated. Patients with high LINC00963 expression had lower survival rates and were more likely to experience fatal outcomes. Both LINC00963 and BNP/NT-proBNP were both independent factors influencing patient mortality, and it was predicted that miR-98-5p was a target gene of LINC00963. Following si-LINC00963 transfection, apoptosis was reduced and inflammatory levels decreased in cardiomyocytes and myocardial tissue from sepsis-induced mice, and miR-98-5p was downregulated. However, the use of a miR-98-5p inhibitor reversed the cellular functional and inflammatory changes induced by LINC00963 knockdown. Knocking down LINC00963 reduces apoptosis and inflammation levels, and promotes cell proliferation by targeting miR-98-5p. This reduces the damage caused by sepsis to cardiomyocytes.

Lung adenocarcinoma is prone to brain metastasis, and the prognosis of patients is extremely poor. The inhibitor of apoptosis-stimulating protein of p53 (iASPP) protein, encoded by the protein phosphatase 1 regulatory subunit 13-like (PPP1R13L) gene, is a key inhibitor of the p53 pathway and promotes carcinogenesis in various tumors, but its role in brain metastasis of lung adenocarcinoma is unknown. This study aims to analyze the tumor microenvironment characteristics of patients with brain metastasis of lung adenocarcinoma and explore the expression of PPP1R13L in brain metastasis tissues and its clinical significance by single-cell sequencing and clinical sample analysis. Brain tissues from 4 patients with lung adenocarcinoma brain metastasis and 2 patients with oligodendroglioma (ODG) were collected from the Affiliated Tumor Hospital of Xinjiang Medical University from January 2014 to December 2024 for single-cell sequencing. The tumor microenvironment was analyzed by combining single-cell sequencing data from 4 lung adenocarcinoma samples and 4 normal lung tissue samples from public databases. Additionally, clinical data and paraffin sections of 50 patients with lung adenocarcinoma brain metastasis in this hospital were collected, and immunohistochemistry was used to assess iASPP expression and its association with clinicopathologic features and patient outcome. Compared with the ODG and lung adenocarcinoma groups, the specific epithelial cells in the lung adenocarcinoma brain metastasis group were mainly enriched in oxidative phosphorylation, apoptosis, hypoxia, and p53 pathways. PPP1R13L, as an upregulated differential gene, was highly expressed in the specific epithelial cell subpopulation of the brain metastasis group; the interaction between PPP1R13L-positive cells and fibroblasts was significant, activating cell-matrix adhesion related pathways, with the key ligand-receptor pair being collagen type I alpha 1 chain-cluster of differentiation 44 (COL1A1-CD44). Statistical evaluation revealed that smoking (HR=2.543, 95%CI: 1.159-5.583, P=0.020) and high expression of iASPP (HR=3.351, 95%CI: 1.310-8.575, P=0.012) were independent predictors of poor prognosis in lung adenocarcinoma patients with brain metastases. This study revealed the interaction between epithelial cells and fibroblasts in the microenvironment of lung adenocarcinoma brain metastasis and implicate PPP1R13L as a potential prognostic indicator and actionable target, offering rationale for precision therapy against lung adenocarcinoma brain metastases.