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. 2024 Dec 28;14(1):31368.
doi: 10.1038/s41598-024-82815-8.

Integrative analysis of ASXL family genes reveals ASXL2 as an immunoregulatory molecule in head and neck squamous cell carcinoma

Affiliations

Integrative analysis of ASXL family genes reveals ASXL2 as an immunoregulatory molecule in head and neck squamous cell carcinoma

Qian Liu et al. Sci Rep. .

Abstract

Despite the progress in conventional treatments for head and neck squamous cell carcinoma (HNSCC), the 5-year survival rate remains below 70%. Enhancing immunotherapy outcomes through personalized treatment strategies, particularly by identifying immune-related biomarkers, is critical. The ASXL family are associated with malignancies, but their relationship with HNSCC has not been elucidated. In this study, we found that high expression of ASXL2 is associated with better prognosis in HNSCC patients. Analysis revealed a significant positive correlation between ASXL2 and immune infiltration. Functional analysis suggests that ASXL2 co-expressed genes in HNSCC patients are enriched in the JAK-STAT signaling pathway, and patients with high expression show an even greater enrichment in T cell and B cell receptor signaling pathways. Utilizing the NPC single-cell dataset, ASXL2's widespread expression in the tumor microenvironment was confirmed, and its co-expressed genes were found to be highly associated with immune cell function. Experimental validation showed a correlation between ASXL2 expression and T cell secretion of interferon-γ (IFNγ), confirming that high ASXL2 expression facilitates T cell activation. Overall, our findings underscore the important role of ASXL2 in immune activation, suggesting its potential as a promising biomarker for tailoring immunotherapy strategies in HNSCC patients.

Keywords: ASXL2; Head and neck squamous cell carcinoma; Immunoregulation; Immunotherapy; Prognosis.

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Conflict of interest statement

Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
ASXL family members and their clinical correlation with HNSCC. (A–C) Survival curves for ASXL family members in HNSCC patients. (D) Prognostic value of ASXL2 in multiple cancer types. (E–G) ASXL2 expression in TCGA-HNSC, KIRC and LGG cohort. HNSCC, Head and Neck Squamous Cell Carcinoma; KIRC, Kidney Renal Clear Cell Carcinoma; LGG, Low-Grade Glioma; num(T), number (Tumor); num(N), number (Normal).
Fig. 2
Fig. 2
Genetic alteration status of ASXL family members in HNSCC. (A–C) The genetic alteration status (mutation, amplification, deep deletion, and multiple alterations) for (A) ASXL1, (B) ASXL2, and (C) ASXL3 in multiple cancer types. (D) Top ten mutated genes with the most significant differences between patients with low and high expression of ASXL2.
Fig. 3
Fig. 3
ASXL2-associated immune landscape and signaling pathways (A–C). The scores of Estimate in HNSCC, KIRC and LGG patients. (D) Correlation between ASXL2 and the degree of infiltration of each immune cell in HNSCC patients. (E) Heatmaps of the top 50 genes that show positive (left) and negative (right) correlations with ASXL2 in the HNSCC cohort. (F) Enrichment analysis of ASXL2 related genes by KEGG pathways. (G, H) Gene set enrichment analysis (GSEA) demonstrates the difference between positively and negatively Correlated genes of ASXL2 in (G) B-cell receptor signaling and (H) T-cell receptor signaling pathways.
Fig. 4
Fig. 4
(A) The features of hallmarks between low- and high-risk score groups. (B) KEGG-based biological characteristics and immune landscape between low- and high-risk score groups. (C) Biocarta-based biological characteristics and immune landscape between low- and high-risk score groups. (D) The evaluation of Fges for immune. (E) The abundance of immune cells by ESTIMATE. (F) Correlation of risk score with immune cell abundance. Fges, functional gene expression signatures.
Fig. 5
Fig. 5
(A) The expression of ASXL2 in GSE12452, GSE13597 and GSE64634. (B) The distribution of cell type in NPC single-cell dataset. (C) The expression of ASXL2 in single cells. (D) Expression levels of ASXL2 in various cell types in the microenvironment of nasopharyngeal carcinoma tissues and normal control tissues. (E) The proportion of cells expressing ASXL2 within the tumor microenvironment of nasopharyngeal carcinoma across various cell types. (F) Co-expression analysis of the ASXL2 gene in a single-cell dataset of NPC. (G) KEGG enrichment analysis of ASXL2 co-expressed genes. NPC, nasopharyngeal carcinoma.
Fig. 6
Fig. 6
ASXL2 expression in NPC cell lines affects T cell activation. (A) Western blotting was performed to quantify the protein level of ASXL2 in NPE cell line HNE2, HONE1, HK1, CNE1, 5–8 F and OSCC cell line TSCCA and TCA8113. ACTIN was used as an internal control. B-D Detection of ASXL2 mRNA (B, C) and protein (D) levels in HK1 and CNE1 and their ASXL2 overexpressing cell lines by real-time fluorescence quantitative PCR and western blotting. E-F Relative levels of IFNγ secretion by T cells after co-culture with HK1 and CNE1 and their ASXL2 overexpressing cell lines respectively. G Western blotting was used to detect the protein level of ASXL2 in HNE2 and its ASXL2 knockdown cell lines. H Relative levels of IFNγ secretion by T cells after co-culture with HNE2 and its ASXL2 knockdown cell lines respectively. I-J Detection of mRNA levels of signature genes from the HNSCC prognostic model in HK1 (I) and CNE1 (J) and their ASXL2-overexpressing cell lines by real-time quantitative PCR. K Real-time quantitative PCR analysis of mRNA levels of signature genes from the HNSCC prognostic model in HNE2 and its ASXL2 knockdown cell lines.

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