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ORIGINAL RESEARCH ARTICLE

A Spatial Transcriptome-Based Perspective on Highly Variable Genes Associated with the Tumour Microenvironment in Hepatocellular Carcinoma

Hang Yang1* QiNian Jiang1
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1 Guizhou Medical University, Guiyang, 550004, China
CP 2023, 5(4), 1917
Submitted: 26 August 2023 | Accepted: 2 November 2023 | Published: 18 November 2023
© 2023 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

Background: Hepatocellular carcinoma is a common pathologic and histologic subtype of primary liver cancer and a common cause of cancer-related death. The tumor microenvironment is involved in the composition and progression of the cancer pathological environment, and understanding the components and mechanisms of the complex tumor microenvironment of hepatocellular carcinoma will aid in the inhibition of hepatocellular carcinoma progression and metastasis. Methods: The spatial transcriptome data were used to discover specific cell subclusters based on the seurat process, followed by monocle to do pseudo-temporal analysis, spatial gene pathway analysis based on the GSVA package process, single cell sequencing data process based on seurat, and gene sets were scored using the AddModuleScore approach.QPCR and immunohistochemistry as well as molecular docking assays were used to determine the biological effects of S100A6. Results: The tumor tissue region revealed a specific subpopulation cluster 4 rich in CAF cell types, particularly myofibroblasts. GSVA analysis suggested that this subpopulation was involved in the epithelial mesenchymal transition process, and KEGG analysis explained its involvement in the composition of extracellular matrix components. Pathological sections of the spatial transcriptome revealed that this subpopulation was specifically expressed at the tumor's broad envelope boundary and in stroma-rich locations, which was confirmed by subsequent sections. The most prognostically relevant gene, S100A6, was found using TCGA sequencing, and expression patterns and tissue locations were consistent with trends in this subpopulation. Conclusions: We identified subgroups with particular tissue regional expression patterns and marker genes that are most substantially associated with cancer prognosis, allowing us to gain a more comprehensive understanding of the complicated compositional alterations in the tumor microenvironment. 

Keywords
Spatial transcriptome
Hepatocellular carcinoma
Multidimensional integrated analysis
S100A6
Funding
Not applicable.
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Conflict of interest
Not applicable.
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Cancer Plus, Electronic ISSN: 2661-3840 Print ISSN: 2661-3832, Published by AccScience Publishing