Both electrical properties and biomarkers of biological tissues can be used to distinguish between normal and diseased tissues, and the correlations between them are critical for clinical applications of conductivity (σ) and permittivity (ε); however, these correlations remain unknown. This study aimed to investigate potential correlations between electrical characteristics and biomarkers of breast cancer cells (BCC). Changes in σ and ε of different components in suspensions of normal cells and BCC were analyzed in the range of 200 kHz–5 MHz. Pearson's correlation coefficient heatmap was used to investigate the correlation between σ and ε of the cell suspensions at different stages and biomarkers of cell growth and microenvironment. σ and ε of the cell suspensions closely resembled those of tissues. Further, the correlations between Na⁺/H⁺ exchanger 1 and ε and σ of cell suspensions were extremely significant among all biomarkers (p_ε < 0.001; p_σ < 0.001). There were significant positive correlations between cell proliferation biomarkers and ε and σ of cell suspensions (p_ε/σ < 0.05). The microenvironment may be crucial in the testing of cellular electrical properties. ε and σ are potential parameters to characterize the development of breast cancer.

Although colorectal cancer is the leading cause of death in patients with liver metastases, there are no efficient treatments available. Oncolytic virus therapy, a new type of tumor therapy, has become a potential solution. With the goal of improving the treatment of advanced colorectal cancer, we applied oncolytic herpes simplex virus type 2 (oHSV2) in a mouse model of colorectal cancer with liver metastasis. Compared with the control, oHSV2 effectively inhibited the growth of subcutaneous primary tumors, significantly reduced the number and size of liver metastases, and prolonged the median survival time of the mice. In addition, neutrophils, natural killer (NK) cells, T cells, B cells, and cytokines in the tumor microenvironment and the body were all activated, and their frequencies increased significantly. Moreover, the proportion of immunosuppressive myeloid-derived suppressor cells decreased. oHSV2 treatment, which establishes an effective long-term antitumor immune response, is strongly resistant to rechallenge by the same tumor. Our data show that oHSV2 can effectively kill the primary tumor and attack distal and metastatic tumors by inducing immune responses, resulting in lasting antitumor efficacy and preventing tumor recurrence. It is believed that oHSV2 has good clinical application prospects.

Gynecological malignancies, particularly ovarian cancer, pose a formidable challenge to women's wellbeing, as evidenced by the global incidence and mortality rates, emphasizing the pressing need for advanced diagnostic and treatment modalities. The heterogeneity of ovarian cancer poses challenges for traditional therapeutic approaches, necessitating the exploration of novel, precision medicine techniques. This study leveraged multi-dataset analysis to construct and validate an Artificial Intelligence-Derived Prognostic Index (AIDPI) for ovarian cancer. Transcriptome data from the TCGA, ICGC, and GEO databases were utilized, encompassing bulk and single-cell RNA sequencing. The AIDPI model was developed and refined using univariate Cox regression analysis and an ensemble of machine learning algorithms. Functional analysis, immunoprofiling, and the role of the MFAP4 gene were investigated to elucidate the biological mechanisms underlying the model. The AIDPI model demonstrated superior accuracy in predicting ovarian cancer prognosis compared to existing models. It correlated with clinical treatment outcomes, including chemotherapy responsiveness, and was integrated into a nomogram for improved prognostic stratification. Functional analysis revealed the influence of AIDPI genes on tumor immune infiltration and cell cycle regulation. Single-cell analysis exposed cell type-specific expression patterns, and the MFAP4 gene was identified as a potential therapeutic target due to its association with patient prognosis and modulation of cellular behavior. In clinical samples of ovarian cancer patients, MFAP4 is highly expressed in metastatic lesions and is associated with poor prognosis. In vitro and in vivo experiments, knockdown of MFAP4 reduces the metastasis of ovarian cancer cells. The AIDPI model offers a highly accurate tool for ovarian cancer prognosis and treatment decision-making, underscored by the integration of multi-omics data and artificial intelligence. The model's performance and biological insights provide a foundation for advancing precision medicine in ovarian cancer. MFAP4′s functionality and the influence of DNA methylation present opportunities for prospective research endeavors and potential therapeutic interventions.

The von Hippel-Lindau (VHL) protein (pVHL) functions as a potent tumor suppressor by mediating the degradation or inactivation of various substrates, including HIFα and Akt. However, pVHL is frequently downregulated in numerous cancers harboring wild-type VHL , and underlying mechanisms remains elusive. Aberrant glucose metabolism is a hallmark of cancer, driving tumor progression and therapeutic resistance. Despite this, the connection between glucose homoeostasis and pVHL turnover and functions has yet to be defined. In this study, we demonstrate that dysregulated glucose metabolism destabilizes pVHL in pancreatic ductal adenocarcinoma (PDAC), colorectal, and ovarian cancer cells. Mechanistically, energy stress induced by glucose starvation, 2-deoxyglucose (2-DG), or metformin activates AMP-activated protein kinase (AMPK), which subsequently phosphorylates and activates BAP1, a deubiquitinase whose specific function in targeting pVHL for deubiquitination and stabilization had not been previously characterized. Specifically, AMPKα phosphorylates BAP1 at residues S123, S469, and S583, enhancing the interaction between BAP1 and pVHL and promoting pVHL stabilization and tumor-suppressive function both in vitro and in vivo. Conversely, disrupting BAP1 phosphorylation through AMPKα depletion or reconstitution with a phosphorylation-defective BAP1 mutant (S123A/S469A/S583A) abolishes the BAP1-pVHL interaction, leading to impaired pVHL stabilization and accelerated tumor progression in cancer cell lines and patient-derived xenograft models. Clinically, our analysis reveals a positive correlation between levels of phosphorylated AMPKα (p-AMPKα), phosphorylated Ser123-BAP1 (pSer123-BAP1), and pVHL levels in PDAC, colorectal cancer, and ovarian cancer specimens. Collectively, these findings elucidate a novel mechanism linking dysregulated glucose metabolism to compromised function of the BAP1-pVHL tumor-suppressive axis. Our results suggest that therapeutic strategies designed to activate this pathway may represent a promising approach for treating cancers characterized by downregulated wild-type VHL and aberrant glucose metabolism.