bioRxivCancer BiologyPreprint
Important Role of Hematopoietic Proteoglycan Serglycin in Liver Hepatocellular Carcinoma Associated with Tumor Microenvironment
Abstract
BackgroundSerglycin (SRGN) is a prominent hematopoietic proteoglycan that regulates tumorigenesis; however, its role in tumor immunity is unclear. Materials and methodsWe investigated the expression and prognostic potential of SRGN in liver hepatocellular cancer (LIHC) in the context of pan-cancer (for showing the similarity and heterogeneity) using the PrognoScan, GEPIA, Kaplan-Meier Plotter, and TIMER bioinformatics databases. HepG2 cells were transfected with an SRGN over-expression vector, and their proliferation, invasion, sorafenib resistance, and vasculature were examined in vitro. A subcutaneous xenograft tumor model was created in nude mice. ResultsSRGN expression was prominent in M2 macrophages in LIHC. The Kaplan-Meier Plotter indicated that SRGN RNA was a favorable prognostic factor after correcting for clinical factors. TIMER 2.0 showed that the immune infiltrates of CD8+ T cells, M1 and M2 macrophages, and endothelial cells were strongly correlated with SRGN RNA expression (r=0.552, P=5.79e-29; r=0.517, P=5.84e-25; r=0.696, P=3.26e51; and r=0.522, P=1.67e-25, respectively), and had prognostic potential in LIHC in patients with low or high levels of SRGN, in addition to resting memory CD4+ T cells, hematopoietic stem cells (HSCs), and myeloid-derived suppressor cells (MDSCs). SRGN promoted the proliferation of HepG2 cells in vitro and in vivo, and was associated with weak sorafenib resistance, invasion, and vasculature. CD206 and CD80 were up-regulated and down-regulated, respectively, in subcutaneous tumor tissues. ConclusionsThe results comprehensively revealed relationships between SRGN and tumor microenvironment(TME)-infiltrating cells, especially monocyte/macrophage subsets. These may constitute an important TME because the pro-tumorigenicity of SRGN in liver cancer.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: protein folding & dynamics
- approach: statistical model
- approach: experimental assay
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