Methods: RNA sequencing data was extracted from The Cancer Genome Atlas (TCGA), specifically from the hepatocellular carcinoma section (n = 366). CIBERSORT was utilized to organize the immune cell fractions present for each patient sample. Radiant by Shiny was used to perform a linear regression elucidating the relationship between overall survival and several other variables including: age, gender, tumor stage, race, ethnicity, B-cells naïve, B-cells memory, plasma cells, CD8 T-cells, CD4 T-cells, T-cells follicular, T-cells regulatory, natural killer activated and resting cells, monocytes, macrophages (M0, M1, M2), dendritic cells activated and resting, mast cells activated and resting, eosinophils, and neutrophils. Subgroup analyses were also performed via radiant regarding gender, race, and resting dendritic counts.
Results: Resting dendritic cells were independently prognostic of overall survival on multivariable analysis (p = 0.041). The coefficient of correlation was +164.53 showing a positive association between the number of resting dendritic cells and the overall survival. Subgroup analysis showed no difference in resting dendritic counts between males and females (p = 0.526). Also, there was no difference seen in resting dendritic counts between populations of Asians and African Americans (p = 0.873), Asians and Whites (p = 0.223), and between Whites and African Americans (p = 0.811).
Conclusions: Patients with a higher number of resting dendritic cells in their tumor immune microenvironment had a better overall survival. There was no difference between males and females in the resting dendritic counts. Likewise, there was no difference in the resting dendritic counts between Asian, African American, and white populations. Resting dendritic cells have been shown to be enriched in hepatocellular carcinomas with a low tumor mutational burden. This is a paradigm that should be explored further in the context of immunotherapy. Resting dendritic cells are also in a state of plasticity as they go from resting to active. Future genomic analysis of the tumor microenvironment regarding this plasticity could also lead to enhancing treatment options.
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