Analyzing the role of TM4SF1 expression in pancreatic adenocarcinoma: understanding prognostic implications and therapeutic opportunities.

Background: Pancreatic adenocarcinoma (PAAD) is a highly lethal malignancy characterized by aggressive growth and poor prognosis. Understanding the molecular mechanisms underlying PAAD is crucial for developing effective therapies. This study aimed to explore the role of TM4SF1 and other key genes in PAAD progression, their prognostic implications, and therapeutic opportunities. Methods: Differential gene expression analysis was performed using PAAD and normal tissue samples to identify upregulated genes, with TM4SF1 emerging as significantly elevated in PAAD. Functional enrichment analysis elucidated associated signaling pathways. A prognostic model comprising BPIFB4, PLEKHN1, CPTP, DVL1, and DDR1 was developed using least absolute shrinkage and selection operator (LASSO) regression and validated in an independent cohort. Genetic mutation analysis provided insights into the functional significance of identified genes. Pharmacogenomic analysis examined associations between gene expression and drug sensitivity. Experimental validation included quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot analyses to confirm gene expression patterns and protein levels. Results: Lower TM4SF1 expression correlated with enhanced anti-tumor immune activity in PAAD, suggesting a complex interplay between genetic expression and immune response. The prognostic model showed robust associations with patient survival outcomes, validated across diverse patient cohorts. Genetic mutation analysis highlighted potential therapeutic targets. Pharmacogenomic analysis revealed correlations between gene expression profiles and drug responsiveness, suggesting personalized treatment strategies. Experimental validation confirmed elevated TM4SF1 levels in tumor tissues and demonstrated its role in promoting cancer cell proliferation and colony formation. Conclusions: This study advances understanding of the molecular landscape of PAAD, emphasizing TM4SF1 as a key regulator and potential therapeutic target. The integration of genetic expression, immune response dynamics, and pharmacogenomics offers a multifaceted approach to personalized treatment strategies for PAAD, paving the way for improved patient outcomes and novel therapeutic interventions. Further research is warranted to elucidate the clinical utility of targeting TM4SF1 and other identified genes in PAAD management.

Mir-382 Promotes Differentiation of Rat Liver Progenitor Cell WB-F344 by Targeting Ezh2.

BACKGROUND/AIMS: Liver progenitor cells (LPCs) were considered as a promising hepatocyte source of cell therapy for liver disease due to their self-renewal and differentiation capacities, while little is known about the mechanism of LPC differentiate into hepatocytes. This study aims to explore the effect of miR-382, a member of Dlk1-Dio3 microRNA cluster, during hepatic differentiation from LPCs. METHODS: In this study, we used rat liver progenitor cell WB-F344 as LPC cell model and HGF as inducer to simulate the process of LPCs hepatic differentiation, then microRNAs were quantified by qPCR. Next, WB-F344 cell was transfected with miR-382 mimics, then hepatocyte cell trait was characterized by multiple experiments, including that periodic acid schiff staining and cellular uptake and excretion of indocyanine green to evaluate the hepatocellular function, qPCR and Western Blotting analysis to detect the hepatocyte-specific markers (ALB, Ttr, Apo E and AFP) and transmission electron microscopy to observe the hepatocellular morphology. Moreover, Luciferase reporter assay was used to determine whether Ezh2 is the direct target of miR-382. RESULTS: We found that miR-382 increased gradually and was inversely correlated with the potential target, Ezh2, during WB-F344 hepatic differentiation. In addition, functional studies indicated that miR-382 increased the level of hepatocyte-specific genes. CONCLUSIONS: This study demonstrates that miR-382 may be a novel regulator of LPCs differentiation by targeting Ezh2.

Bioinformatics analysis of aggressive behavior of breast cancer via an integrated gene regulatory network.

BACKGROUND: Breast cancer is one of the most frequently diagnosed cancers in women. Though death from this disease is mainly caused by the metastases of the aggressive cancer cells, few studies have expounded the aggressive behavior of breast cancer. MATERIALS AND METHODS: We downloaded the gene expression profiles of GSE40057, including four aggressive and six less-aggressive breast cancer cell lines, from Gene Expression Omnibus and identified the differentially expressed genes (DEGs) between the aggressive and less-aggressive samples. An integrated gene regulatory network was built including DEGs, microRNAs (miRNAs), and transcription factors. Then, motifs and modules of the network were identified. Modules were further analyzed at a functional level using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to study the aggressive behavior of breast cancer. RESULTS: A total of 764 DEGs were found and two modules were filtered from the integrated gene regulatory network. Totally two motifs and modules for DEGs were identified. Significant GO terms associated with cell proliferation and hormone stimulus of the modules were found and the target genes identified were  CAV1, CD44, and TGFßR2. The KEGG pathway analysis discovered that CAV1 and FN1 were significantly enriched in focal adhesion, extracellular matrix (ECM)-receptor interaction, and pathways in cancer. CONCLUSION: Aggressive behavior of breast cancer was proved to be related to cell proliferation and hormone stimulus. Genes such as CAV1, CD44, TGFßR2, and FN1 might be potential targets to diagnose the aggressive behavior of breast cancer cells.