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Identification and validation of prognostic genes related to glycolysis and M2 macrophage in hepatocellular carcinoma: an integrated analysis of bulk RNA sequencing and single-cell RNA sequencing.

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Frontiers in immunology 📖 저널 OA 100% 2021: 2/2 OA 2022: 13/13 OA 2023: 10/10 OA 2024: 62/62 OA 2025: 810/810 OA 2026: 522/522 OA 2021~2026 2026 Vol.17() p. 1710411
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Wang A, You L, Zuo M, He Z, Yang H, Huang W

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[BACKGROUND] The role of the crosstalk between glycolysis and M2 macrophages in hepatocellular carcinoma (HCC) progression remains incompletely understood.

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APA Wang A, You L, et al. (2026). Identification and validation of prognostic genes related to glycolysis and M2 macrophage in hepatocellular carcinoma: an integrated analysis of bulk RNA sequencing and single-cell RNA sequencing.. Frontiers in immunology, 17, 1710411. https://doi.org/10.3389/fimmu.2026.1710411
MLA Wang A, et al.. "Identification and validation of prognostic genes related to glycolysis and M2 macrophage in hepatocellular carcinoma: an integrated analysis of bulk RNA sequencing and single-cell RNA sequencing.." Frontiers in immunology, vol. 17, 2026, pp. 1710411.
PMID 41766871 ↗

Abstract

[BACKGROUND] The role of the crosstalk between glycolysis and M2 macrophages in hepatocellular carcinoma (HCC) progression remains incompletely understood. This study aimed to identify prognostic genes linked to both glycolysis and M2 macrophages in HCC and to elucidate their mechanistic underpinnings.

[METHODS] Single-cell RNA sequencing (scRNA-seq) and transcriptomic data (TCGA-LIHC) were obtained from public databases. M2 macrophage-related genes (MRGs) were integrated with differentially expressed genes (DEGs1) from immune infiltration analysis and macrophage polarization-related genes (MPRGs). Candidate genes were identified through the intersection of glycolysis-related genes (GRGs), MRGs, and HCC-control DEGs (DEGs2). Prognostic genes were selected regression analysis for the development of a risk model. Subsequent analyses included nomogram development, functional enrichment, immune characterization, and drug sensitivity assessment. Single-cell analysis highlighted key cell populations and prognostic gene expression profiles in HCC. RT-qPCR was performed to validate prognostic gene expression levels.

[RESULTS] Fifty-two candidate genes were identified from the intersection of GRGs, MRGs, and DEGs2. Eight genes-PFKFB4, ADH4, ADH1C, ME1, FOXK1, PFKP, ARL2, and TKTL1-were selected as prognostic genes. ADH4 and ADH1C exhibited significantly higher expression in the low-risk group, whereas the other genes were elevated in the high-risk group. A more accurate risk model and nomogram were developed. Further analyses indicated that the prognostic genes might contribute to HCC progression through pathways such as drug metabolism (cytochrome P450), immune cell infiltration (naive B cells and M2 macrophages), immune escape, and drug sensitivity (e.g., A.770041), potentially influencing cellular interactions and differentiation states of hepatocytes and M2 macrophages. RT-qPCR confirmed that PFKFB4, FOXK1, and TKTL1 were upregulated in HCC, while ADH4 and ADH1C were downregulated.

[CONCLUSION] Eight prognostic genes were identified, and a risk model was established, providing valuable insights for clinical prognostic prediction and immunotherapy in HCC.

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