Ovarian cancer has a high death rate and is often not detected until late stages. While some studies found high expressions of MMPs correlated with cancer invasion, metastasis, and poor prognosis, however, several other studies indicated MMPs might inhibit cancer rather than promote cancer in certain situations. Thus, the role of different MMPs in different cancer types needs a systematic re-evaluation. In this study, we used RNA-Seq and corresponding clinical data downloaded from TCGA and analyzed the correlations between MMP expressions and the clinicopathologic characteristics and outcome in ovarian serous cystadenocarcinoma (OSC) patients. Among the MMPs investigated, MMP-3 was significantly increased in high-grade and high-stage tumors compared with low-grade and low-stage ones. Using univariate analysis and multivariate Cox model, high expressions of MMP-19 and -20 were found to associate with poor overall survival independent of clinicopathologic characteristics. Moreover, using in vitro studies, we found ovarian cancer cell lines with higher MMP-19 and -20 protein expressing levels were associated with anti-cancer drugs resistance, while knockdown of MMP-19 or -20 increased ovarian cancer cell sensitivities to several clinical using chemotherapy agents. Finally, knockdown of MMP-19 or -20 also decreased the invasion abilities of several ovarian cancer cell lines. These in vitro studies provided potential mechanisms of high MMP-19 and -20 expressions in the poor prognosis of ovarian cancer.

Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell‐free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer‐specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome‐wide methylation profiling of cfDNA using cell‐free methylated DNA immunoprecipitation and high‐throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA‐derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.

Cell-free DNA is a promising source of biomarkers for early cancer detection and carries tumor-driven methylation and fragmentation features that have achi

As a key tool for assessing aging, DNA methylation clocks are mostly constructed based on European and American populations and rely on the high-cost Infinium MethylationEPIC microarray. These factors limit their widespread application in the Chinese population. This study included two independent cohorts: the Fuyang cohort (n = 610, age range 2-89 years) for model development, and the Hefei cohort (n = 188, age range 15-86 years) for external validation. Using a multiplex PCR-based targeted capture sequencing technology, we examined 74 CpG sites located in seven age-associated genes, including ELOVL2, FHL2, C1orf132, KLF14, TRIM59, CCDC102B and PDE4C, to construct a DNA methylation-based age prediction model suitable for the Chinese population. The performance of our model was consistent with that reported in the literature for this field. In the Fuyang cohort, the training set achieved R²=0.95, MAE = 3.39 years; the test set achieved R² = 0.93, MAE = 4.04 years. External validation yielded R² = 0.89, MAE = 4.11 years. Compared with age-prediction models based on biochemical markers, our methylation clock demonstrated superior performance. Further analysis revealed non-linear aging rates and sex-specific differences. In addition, blood samples from cancer patients displayed DNA methylation patterns distinct from those associated with physiological aging, suggesting that they are associated with epigenetic alterations that lead to an overestimation of DNA methylation age. This study developed a cost-effective, targeted methylation clock for the full age spectrum in the Chinese population. Its strong response to both physiological aging and tumor status underscores its potential for large-scale aging assessment and for translational applications.

Objectives: Investigate the predictive value of Vasculogenic mimicry (VM) related genes for the survival and prognosis of Hepatocellular carcinoma (HCC) patients and its role in the tumor microenvironment (TME).Methods: VM-related genes were obtained from previous literature, the expression profiles, single-cell data and clinical information of HCC patients were downloaded from public databases. The HCC patients were divided into different clusters by unsupervised clustering, the differences in prognosis and immune characteristics of VM-related clusters were analyzed. A prognostic model related to VM (VM Score) was constructed based on LASSO regression and univariate and multivariate Cox regression, the correlation between this model and chemotherapy drugs and immunotherapy was studied. Seurat package was used to standardize single-cell data for single-cell level analysis. The expression of risk factors in VM Score was verified by RT-qPCR.Results: VM Score composed of SPP1, ADAMTS5 and ZBP1 was constructed and validated. VM Score was an independent prognostic factor for HCC. Through the analysis of single cell data further reveals the VM Score influence on TME. In addition, VM Score could provide ideas for the selection of immunotherapy and chemotherapy drugs. RT-qPCR showed that the expression of risk factors was different in HCC cell lines.Conclusion: Our results suggest that VM Score may serve as a promising prognostic biomarker for HCC and provide new ideas for immunotherapy in HCC patients.