Anoikis classification of lung squamous cell carcinoma reveals correlation with clinical prognosis and immune characteristics
Background Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains poorly studied.Methods The differentially expressed ARGs and candidate genes were selecte...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2514944 |
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| Summary: | Background Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains poorly studied.Methods The differentially expressed ARGs and candidate genes were selected by the differential analysis to construct a predictive model. Independent prognostic gene was determined by Cox and LASSO analysis and we used the HCC95 and NCI H520 cell line to verify the gene function. We used the data from TCGA, GEO, GeneCards, and Harmonizome databases to analyze the immune microenvironment, functional enrichment, and drug sensitivity analysis.Results We identified 717 differentially expressed and selected 3 ARGs (FADD, SNAI1, and BAG4) to construct a predictive model. We found that SNAI1 is an independent prognostic gene and confirmed that knocking out the SNAI1 inhibited the HCC95/NCI H520 cell proliferation. We used single-sample gene-set enrichment analysis (ssGSEA) to evaluate the immune infiltration based on the 3 ARG expression levels. We constructed a risk score and provided a visual representation of the prophetic implications of the ARGs-based signature through a nomogram. We found 15 susceptible drugs in the high-risk group and 15 sensitive drugs in the low-risk group by the drug sensitivity analysis.Conclusion We used ARGs to construct a prognosis model for LUSC that can accurately predict the prognosis of LUSC patients. ARGs, especially SNAI1, play an essential role in developing LUSC. These findings could provide individualized treatment plans and new research ideas for LUSC patients. |
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| ISSN: | 0785-3890 1365-2060 |