Shanxi Traditional Chinese Medicine Institute

Cervical cancer (CC) is a gynaecological malignancy tumour that seriously threatens women's health. Recent evidence has identified that interferon regulatory factor 5 (IRF5), a nucleoplasm shuttling protein, is a pivotal transcription factor regulating the growth and metastasis of various human tumours. This study aimed to investigate the function and molecular basis of IRF5 in CC development. IRF5, protein phosphatase 6 catalytic subunit (PPP6C) and methyltransferase‐like 3 (METTL3) mRNA levels were evaluated by quantitative real‐time (qRT)‐polymerase chain reaction (PCR). IRF5, PPP6C, METTL3, B‐cell lymphoma 2 and Bax protein levels were detected using western blot. Cell proliferation, migration, invasion, angiogenesis and apoptosis were determined by using colony formation, 5‐ethynyl‐2′‐deoxyuridine (EdU), transwell, tube formation assay and flow cytometry assay, respectively. Glucose uptake and lactate production were measured using commercial kits. Xenograft tumour assay in vivo was used to explore the role of IRF5. After JASPAR predication, binding between IRF5 and PPP6C promoter was verified using chromatin immunoprecipitation and dual‐luciferase reporter assays. Moreover, the interaction between METTL3 and IRF5 was verified using methylated RNA immunoprecipitation (MeRIP). IRF5, PPP6C and METTL3 were highly expressed in CC tissues and cells. IRF5 silencing significantly inhibited cell proliferation, migration, invasion, angiogenesis and glycolytic metabolism in CC cells, while induced cell apoptosis. Furthermore, the absence of IRF5 hindered tumour growth in vivo. At the molecular level, IRF5 might bind with PPP6C to positively regulate the expression of PPP6C mRNA. Meanwhile, IRF5 was identified as a downstream target of METTL3‐mediated m6A modification. METTL3‐mediated m6A modification of mRNA might promote CC malignant progression by regulating PPP6C, which might provide a promising therapeutic target for CC treatment.

To determine whether or not a decoction made from Qigu Zhushui has a suppressive impact on malignant ascites in mice.

Malignant ascites are one of the common complications of advanced malignant tumors. Patients with malignant ascites typically have a poor prognosis, with only 12 to 20 weeks of survival. Currently, the standard treatments for malignant ascites are systemic chemotherapy, which is ineffective in eradicating the disease and is associated with issues such as safety, short duration of sustained high-level drug concentration in localised regions, and drug resistance.

To clarify the effect of Qigu Zhushui decoction on inhibiting malignant ascites in mice and provide the experimental basis for further research.

The ascites model of liver cancer in mice was established by intraperitoneal injection of the H22-H8D8 cell line of liver cancer. ELISA detected the content of CEA, VEGF and TNF-α in ascites.

Qigu Zhushui decoction combined with cisplatin group and Qigu Zhushui decoction highdose group could significantly reduce the weight, abdominal circumference and ascites volume of mice, and their survival days and survival rate were also greatly improved; The levels of CEA and VEGF in the combination group decreased significantly, while the level of TNF-α increased; The level of TNF-a in the high dose group of Qigu Zhushui decoction was significantly increased, while the level of CEA and VEGF in the moderate dose group was decreased.

Qigu Zhushui decoction can reduce the malignant ascites in mice, and the combination of Qigu Zhushui decoction and cisplatin has a significant anti-malignant ascites effect, which can significantly prolong the survival time and improve the survival rate.

In the realm of clinical practice, there is currently an insufficiency of distinct biomarkers available for the detection of breast cancer. It is of utmost importance to promptly employ bioinformatics methodologies to investigate prospective biomarkers for breast cancer, with the ultimate goal of achieving early diagnosis of the disease. The initial phase of this investigation involved the identification of 2 breast cancer gene chips meeting the specified criteria within the gene expression omnibus database. Subsequently, paired data analysis was conducted on these datasets, leading to the identification of differentially expressed genes (DEGs). In addition, this study executed Gene Ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. The subsequent stage involved the construction of a protein-protein interaction network graph using the STRING website and Cytoscape software, facilitating the calculation of Hub genes. Lastly, the UALCAN database and Kaplan–Meier survival plots were utilized to perform differential expression and survival analysis on the selected Hub genes. A total of 733 DEGs were identified from the combined analysis of 2 datasets. Among these DEGs, 441 genes were found to be downregulated, while 292 genes were upregulated. The selected DEGs underwent comprehensive analysis, including gene ontology enrichment analysis, Kyoto encyclopedia of genes and genomes pathway enrichment analysis, and establishing a protein-protein interaction network. As a result, 10 Hub genes closely associated with early diagnosis of breast cancer were identified: PDZ-binding kinase, cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, BIRC5, cell cycle protein B2, hyaluronan-mediated motility receptor, mitotic arrest deficient 2-like 1, and protein regulator of cytokinesis 1. The findings of this study unveiled the significant involvement of the identified 10 Hub genes in facilitating the growth and proliferation of cancer cells, particularly cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, hyaluronan-mediated motility receptor, and protein regulator of cytokinesis 1, which demonstrated a more pronounced connection with the onset and progression of breast cancer. Further analysis through differential expression and survival analysis reaffirmed their strong correlation with the incidence of breast cancer. Consequently, the investigation of these 10 pertinent Hub genes presents novel prospects for potential biomarkers and valuable insights into the early diagnosis of breast cancer.