621 Background: Hepatocellular carcinoma (HCC), the predominant form of primary liver cancer, is the sixth most prevalent cancer globally and a leading cause of cancer-related mortality. The tumor microenvironment (TME) in HCC, characterized by complex interactions between immune and tumor cells, significantly influences tumor progression and immune suppression. Understanding the immune landscape across the different stages of HCC can inform prognosis and therapeutic strategies. Methods: We analyzed RNA seq data from 333 HCC patients (disease stages I-III), from The Cancer Genome Atlas (TCGA), using the immune deconvolution algorithms CIBERSORT and xCell. Differential gene expression analysis was performed using the DESeq2 package in R. Immune cell abundance across various HCC stages was imputed, and survival analyses was conducted using Kaplan-Meier curves and log-rank tests. Results: Of the 19,514 genes analyzed, 2,774 were up-regulated and 947 were down-regulated in stage II and III in comparison to stage I. CIBERSORT and xCell analyses revealed significant variability in the immune cell composition between HCC stages. Notable differences were observed in the T cells (CD4 and CD8 subsets), B cells, plasma cells, and stromal components. ANOVA and post hoc tests identified significant stage-specific differences in several immune cell types. For the survival analysis, we categorized patients into low and high groups based on median cell abundances. Overall survival showed no statistically significant differences among the various groups for common myeloid and lymphoid progenitor cells. In contrast, disease-free survival demonstrated statistically significant differences across the groups for both cell types. Conclusions: This study emphasizes the tumor microenvironment's pivotal role in HCC, revealing that immune cell composition significantly influences disease-free survival, despite limited effects on overall survival. These findings advocate for further exploration into targeted immunotherapies and the development of predictive models that integrate immune landscape characteristics, ultimately aiming to enhance patient outcomes in HCC. Cell type xCell Cibersort Mean SD Mean SD T cell CD4 naive 0.00466 0.01994 1.31e-5 1.69e-4 T cell CD8 0.01368 0.03253 0.03161 0.04947 Eosinophil 3.96e-5 3.41e-4 1.67e-4 8.69e-4 Macrophage 0.02323 0.02441 0.02924 0.04345 Macrophage.M1 0.00914 0.01526 0.01806 0.02054 Macrophage.M2 0.02303 0.01697 0.05439 0.04815 B cell memory 0.00196 0.01418 0.00107 0.00733 B cell naive 0.00163 0.01034 0.01319 0.02148 Neutrophil 2.14e-4 0.00137 0.00112 0.00539 Immune score 0.04621 0.06817 - - Table presents various cell type abundances for each algorithm used.
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