Genomic and immune landscape in hepatocellular carcinoma: Implications for personalized therapeutics

Integrated spatial and single cell transcriptomics identifies PRKDC as a dual prognostic biomarker and therapeutic target in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with a pressing need for effective biomarkers and therapeutic targets. Despite the clinical use of alpha-fetoprotein (AFP) as a diagnostic biomarker, its limitations in sensitivity and specificity necessitate the identification of novel markers. In this study, we investigated the role of Protein Kinase, DNA-Activated, Catalytic Subunit (PRKDC) in HCC prognosis and its potential as a therapeutic target. Utilizing spatial transcriptomics and single-cell RNA sequencing (scRNA-seq), we dissected the cellular composition of PRKDC in HCC tissue samples, revealing its high expression in malignant cell subpopulations and its association with the tumor immune microenvironment. Through clinical signature analysis, we observed widespread PRKDC expression in HCC tissues, particularly in immune cells, highlighting its link to immune cell infiltration. Further analyses confirmed high PRKDC expression in malignant cells and its inhibitory effect on immune cell infiltration. Copy number variation (CNV) analysis revealed significant genomic instability, with PRKDC exhibiting both amplifications and deletions across chromosomal regions, underscoring its role in tumorigenesis. Functional overexpression of PRKDC in HCC cell lines enhanced cell proliferation, migration, and altered cell cycle dynamics, with a notable increase in the G2/S phase. Taken together, we first to integrate spatial transcriptomics and single-cell transcriptomics and bulk RNA-seq to reveal that PRKDC is a reliable prognostic biomarker and a potential therapeutic target. High PRKDC expression is associated with shorter survival times and an abnormal tumor microenvironment, highlighting its impact on immune cell infiltration and HCC prognosis. Targeting PRKDC could selectively inhibit its expression in tumor cells, providing new strategies for HCC treatment.

Integrative bioinformatics analysis of miRNA and mRNA expression profiles and identification of associated miRNA-mRNA network in intracranial aneurysms

Background

Intracranial aneurysms (IAs) represent protrusions in the vascular wall, with their growth and wall thinning influenced by various factors. These processes can culminate in the rupture of the aneurysm, leading to subarachnoid hemorrhage (SAH). Unfortunately, over half of the patients prove unable to withstand SAH, succumbing to adverse outcomes despite intensive therapeutic interventions, even in premier medical facilities. This study seeks to discern the pivotal microRNAs (miRNAs) and genes associated with the formation and progression of IAs.

Methods

The investigation gathered expression data of miRNAs (from GSE66240) and mRNAs (from GSE158558) within human aneurysm tissue and superficial temporal artery (STA) samples, categorizing them into IA and normal groups. This classification was based on the Gene Expression Omnibus (GEO) database.

Results

A total of 70 differentially expressed microRNAs (DEMs) and 815 differentially expressed mRNAs (DEGs) were pinpointed concerning IA. Subsequently, a miRNA-mRNA network was constructed, incorporating 9 significantly upregulated DEMs and 211 significantly downregulated DEGs. Simultaneously, functional enrichment and pathway analyses were conducted on both DEMs and DEGs. Through protein-protein interaction (PPI) network analysis and functional enrichment, 9 significantly upregulated DEMs (hsa-miR-188-5p, hsa-miR-590-5p, hsa-miR-320b, hsa-miR-423-5p, hsa-miR-140-5p, hsa-miR-486-5p, hsa-miR-320a, hsa-miR-342-3p, and hsa-miR-532-5p) and 50 key genes (such as ATP6V1G1, KBTBD6, VIM, PA2G4, DYNLL1, METTL21A, MDH2, etc.) were identified, suggesting their potential significant role in IA. Among these genes, ten were notably negatively regulated by at least two key miRNAs.

Conclusions

The findings of this study provide valuable insights into the potential pathogenic mechanisms underlying IA by elucidating a miRNA-mRNA network. This comprehensive approach sheds light on the intricate interplay between miRNAs and genes, offering a deeper understanding of the molecular dynamics involved in IA development and progression.