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Biomedical subjects

Elham Karimi

Publications and source records attributed to Elham Karimi.

2 recordsLinked to original sources

Key hub genes and pathways associated with HCV-related hepatocellular carcinoma as potential diagnostic biomarkers.

BACKGROUND: Hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) remains a major global health challenge, with high morbidity and mortality despite recent therapeutic advances. Early detection and identification of reliable molecular biomarkers are essential to improve patient outcomes. Therefore, the present study aimed to investigate key hub genes and pathways associated with HCV-related HCC as potential diagnostic biomarkers. METHODS: The datasets GSE69715 and GSE62232 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were recognized according to an adjusted p-value and a log fold change (logFC). The GEO2R tool facilitated the identification of common DEGs across the two datasets. Pathways were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Furthermore, protein-protein interactions (PPIs) were assessed through Cytoscape. The target genes were confirmed through a GEPIA analysis. RESULTS: A total of 421 common DEGs were identified, and 80 hub genes were subsequently determined through GEO and PPI network analyses, respectively. The GO and KEGG pathways analysis presented DEGs were enhanced in metabolic pathways, cellular components, extracellular exosome, detoxification of copper ion and monooxygenase activity. The GEPIA analysis indicated a notable variation in the expression levels of four specific genes -CDKN2A, CDK1, CCNB1, and TOP2A-when comparing normal samples to tumor samples. CONCLUSION: The present study discovered novel genes by expression variation in HCV-related hepatocellular carcinoma development. These findings suggest that CDKN2A, CDK1, CCNB1, and TOP2A are promising candidates for diagnostic biomarkers and present a valuable opportunity for the early identification of HCV-HCC, which could lead to improved treatment outcomes.

Bioinformatics

Distinct immune landscapes characterize highly versus minimally invasive brain metastases.

Brain metastases (BrMs) occur in approximately 30% of cancer patients, causing nearly one-fifth of cancer deaths. While immune checkpoint inhibitors (ICIs) benefit some BrM patients, responses remain highly variable. This variability partly reflects distinct histopathological growth patterns that include minimally invasive (MI) and highly invasive (HI) brain BrMs. Here we show that MI BrMs exhibit robust immune infiltration, whereas HI lesions are immunosuppressed. However, histological differentiation between MI and HI can be challenging because of subjective margin assessment. Here, using highly multiplexed spatial proteomics on 119 tumor sections from 46 patients with BrMs, we identify CHI3L1 as a key mediator of the immunosuppressive microenvironment in HI BrMs. In preclinical models, genetic deletion of CHI3L1 converts immune-cold metastases into lymphocyte-rich, ICI-responsive lesions infiltrated by granzyme B+ CD8+ T cells. In BrM patients treated with ICI, immunohistochemical quantification of CHI3L1 expression was a stronger predictor of ICI response than traditional MI/HI classification. Thus, CHI3L1 represents a promising biomarker and therapeutic target for BrMs.

Humans