Paired box 8 facilitates the c-MYC related cell cycle progress in TP53-mutation uterine corpus endometrial carcinoma through interaction with DDX5

Zengmian Yiliu formula suppresses cell cycle in immune-rich ovarian cancer patient-derived organoids

BACKGROUND

Ovarian cancer, often diagnosed at advanced stages, has a 5-year survival rate below 50%, indicating a critical need for innovative treatments. The Zengmian Yiliu (ZMYL) formula, a Traditional Chinese Medicine (TCM) prescription, has shown potential in enhancing chemotherapy efficacy and improving patients' quality of life, PURPOSE: To investigate the effects of the ZMYL formula on ovarian cancer organoids, focusing on its impact on organoid phenotypes and underlying mechanisms, and to explore its potential as an immunotherapeutic agent.

METHODS

Ovarian cancer organoids were established from surgical tissues and treated with the ZMYL formula at varying concentrations. Network pharmacology was utilized to predict the formula's therapeutic targets and pathways, and molecular docking was conducted to validate ingredient-target interactions. Phenotypic changes were monitored, and RNA sequencing was performed post-treatment to analyze gene expression alterations.

RESULTS

A total of 34 overlapping targets of 10 compounds in the ZMYL formula and ovarian cancer were predicted by Network pharmacology analysis. The ZMYL formula induced dose-dependent morphological changes in organoids, including a reduction in size and structural sparsity at higher concentrations. RNA sequencing revealed significant modulation of cell cycle and immune response pathways, with a particular focus on immunomodulatory effects. The formula's treatment targeted key genes involved in these processes, reshaping the tumor's molecular landscape.

CONCLUSIONS

This study establishes ZMYL's capacity to simultaneously target oncogenic drivers (e.g., cell cycle regulators) and immune checkpoints (e.g., CXCL10-mediated T cell recruitment) in ovarian cancer organoids. Unlike conventional monotherapy-focused approaches, ZMYL's multi-component mechanism offers a synergistic framework for integrating TCM with modern immunotherapies. These findings provide a foundation for future clinical evaluation of ZMYL as a precision medicine strategy to enhance treatment efficacy and mitigate chemoresistance in ovarian cancer.

Independent organelle and organelle-organelle interactions: essential mechanisms for malignant gynecological cancer cell survival

Different eukaryotic cell organelles (e.g., mitochondria, endoplasmic reticulum, lysosome) are involved in various cancer processes, by dominating specific cellular activities. Organelles cooperate, such as through contact points, in complex biological activities that help the cell regulate energy metabolism, signal transduction, and membrane dynamics, which influence survival process. Herein, we review the current studies of mechanisms by which mitochondria, endoplasmic reticulum, and lysosome are related to the three major malignant gynecological cancers, and their possible therapeutic interventions and drug targets. We also discuss the similarities and differences of independent organelle and organelle-organelle interactions, and their applications to the respective gynecological cancers; mitochondrial dynamics and energy metabolism, endoplasmic reticulum dysfunction, lysosomal regulation and autophagy, organelle interactions, and organelle regulatory mechanisms of cell death play crucial roles in cancer tumorigenesis, progression, and response to therapy. Finally, we discuss the value of organelle research, its current problems, and its future directions.

Epstein-Barr Virus: Human Interactome Reveals New Molecular Insights into Viral Pathogenesis for Potential Therapeutics and Antiviral Drug Discovery

Host-virus Protein-Protein Interactions (PPIs) play pivotal roles in biological processes crucial for viral pathogenesis and by extension, inform antiviral drug discovery and therapeutics innovations. Despite efforts to develop the Epstein-Barr virus (EBV)-host PPI network, there remain significant knowledge gaps and a limited number of interacting human proteins deciphered. Furthermore, understanding the dynamics of the EBV-host PPI network in the distinct lytic and latent viral stages remains elusive. In this study, we report a comprehensive map of the EBV-human protein interactions, encompassing 1752 human and 61 EBV proteins by integrating data from the public repository HPIDB (v3.0) as well as curated high-throughput proteomic data from the literature. To address the stage-specific nature of EBV infection, we generated two detailed subset networks representing the latent and lytic stages, comprising 747 and 481 human proteins, respectively. Functional and pathway enrichment analysis of these subsets uncovered the profound impact of EBV proteins on cancer. The identification of highly connected proteins and the characterization of intrinsically disordered and cancer-related proteins provide valuable insights into potential therapeutic targets. Moreover, the exploration of drug-protein interactions revealed notable associations between hub proteins and anticancer drugs, offering novel perspectives for controlling EBV pathogenesis. This study represents, to the best of our knowledge, the first comprehensive investigation of the two distinct stages of EBV infection using high-throughput datasets. This makes a contribution to our understanding of EBV-host interactions and provides a foundation for future drug discovery and therapeutic interventions.

DDX5 Functions as a Tumor Suppressor in Tongue Cancer

DEAD-box polypeptide 5 (DDX5), a DEAD-box RNA helicase, is a multifunctional protein that plays important roles in many physiological and pathological processes. Contrary to its documented oncogenic role in a wide array of cancers, we herein demonstrate that DDX5 serves as a tumor suppressor in tongue cancer. The high expression of DDX5 is correlated with better prognosis for clinical tongue cancer patients. DDX5 downregulates the genes associated with tongue cancer progression. The knockdown of DDX5 promotes, while the overexpression of DDX5 inhibits, tongue cancer proliferation, development, and cisplatin resistance. Furthermore, the expression of DDX5 in tongue cancer is associated with immune cell infiltration in the tumor microenvironment. Specifically, the expression of DDX5 is associated with the reduced infiltration of M2 macrophages and increased infiltration of T cell clusters, which may contribute to anticancer effects in the tumor microenvironment. In this study, we establish DDX5 as a valuable prognostic biomarker and an important tumor suppressor in tongue cancer.

Identification of novel key genes associated with uterine corpus endometrial carcinoma progression and prognosis

Background

Uterine corpus endometrial carcinoma (UCEC) is a common malignant cancer type which affects the health of women worldwide. However, its molecular mechanism has not been elucidated.

Methods

To identify the hub modules and genes in UCEC associated with clinical phenotypes, the RNA sequencing data and clinical data of 543 UCEC samples were obtained from The Cancer Genome Atlas (TCGA) database and then subjected to weighted gene co-expression network analysis (WGCNA). To explore the potential biological function of the hub modules, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Genes differentially expressed in UCEC were screened according to TCGA data using the "gdcDEAnalysis" package in R (The R Foundation for Statistical Computing). After intersecting with hub genes, the shared genes were used for further survival analyses. The relationship between gene expression level and clinical phenotype was analyzed in the TCGA-UCEC cohort in The University of ALabama at Birmingham CANcer data analysis Portal and the Human Protein Atlas. The microarray data set GSE17025 was also analyzed to validate the gene expression profiles.

Results

There were 19 coexpression modules generated by WGCNA. Among them, 2 modules with 198 hub genes were highly correlated with clinical features (especially histologic grade and clinical stage). Meanwhile, 4,003 differentially expressed genes (DEGs) were screened out, and 164 DEGs overlapped with hub genes. Survival analyses revealed that high expression of GINS4 and low expression of ESR1 showed a trend of poor prognosis. Further analyses demonstrated that both messenger RNA (mRNA) and protein expression profiles of GINS4 and ESR1 were significantly associated with UCEC development and progression in TCGA and GSE17025 cohorts.

Conclusions

Based on the integrated bioinformatic analyses, our data indicated that GINS4 and ESR1 might serve as potential prognostic markers and targets for UCEC therapy.