Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma
Abstract Background Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with poor prognosis. Neutrophil infiltration has been associated with unfavorable outcomes in OSCC, but the underlying molecular mechanisms remain unclear. Methods This study integrated single-cell transcriptomics (s...
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BMC
2024-12-01
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| Series: | Human Genomics |
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| Online Access: | https://doi.org/10.1186/s40246-024-00712-7 |
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| author | Jinhang Wang Zifeng Cui Qiwen Song Kaicheng Yang Yanping Chen Shixiong Peng |
| author_facet | Jinhang Wang Zifeng Cui Qiwen Song Kaicheng Yang Yanping Chen Shixiong Peng |
| author_sort | Jinhang Wang |
| collection | DOAJ |
| description | Abstract Background Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with poor prognosis. Neutrophil infiltration has been associated with unfavorable outcomes in OSCC, but the underlying molecular mechanisms remain unclear. Methods This study integrated single-cell transcriptomics (scRNA-seq) with bulk RNA-seq data to analyze neutrophil infiltration patterns in OSCC and identify key gene modules using weighted gene co-expression network analysis (hdWGCNA). A prognostic model was developed based on univariate and Lasso-Cox regression analyses, stratifying patients into high- and low-risk groups. Immune landscape and drug sensitivity analyses were conducted to explore group-specific differences. Additionally, Mendelian randomization analysis was employed to identify genes causally related to OSCC progression. Results Several key pathways associated with neutrophil interactions in OSCC progression were identified, leading to the construction of a prognostic model based on significant module genes. The model demonstrated strong predictive performance in distinguishing survival rates between high- and low-risk groups. Immune landscape analysis revealed significant differences in cell infiltration patterns and TIDE scores between the groups. Drug sensitivity analysis highlighted differences in drug responsiveness between high- and low-risk groups. Conclusion This study elucidates the critical role of neutrophils and their associated gene modules in OSCC progression. The prognostic model provides a novel reference for patient stratification and targeted therapy. These findings offer potential new targets for OSCC diagnosis, prognosis, and immunotherapy. |
| format | Article |
| id | doaj-art-bd5fa63856bc4be39fc52273922250ff |
| institution | DOAJ |
| issn | 1479-7364 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
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| series | Human Genomics |
| spelling | doaj-art-bd5fa63856bc4be39fc52273922250ff2025-08-20T02:39:38ZengBMCHuman Genomics1479-73642024-12-0118112110.1186/s40246-024-00712-7Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinomaJinhang Wang0Zifeng Cui1Qiwen Song2Kaicheng Yang3Yanping Chen4Shixiong Peng5Department of Stomatology, The Second Hospital of ShijiazhuangDepartment of Stomatology, The Fourth Hospital of Hebei Medical UniversityDepartment of Stomatology, The Third Hospital of Hebei Medical UniversityDepartment of Stomatology, The Fourth Hospital of Hebei Medical UniversityDepartment of Stomatology, The Fourth Hospital of Hebei Medical UniversityDepartment of Stomatology, The Fourth Hospital of Hebei Medical UniversityAbstract Background Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with poor prognosis. Neutrophil infiltration has been associated with unfavorable outcomes in OSCC, but the underlying molecular mechanisms remain unclear. Methods This study integrated single-cell transcriptomics (scRNA-seq) with bulk RNA-seq data to analyze neutrophil infiltration patterns in OSCC and identify key gene modules using weighted gene co-expression network analysis (hdWGCNA). A prognostic model was developed based on univariate and Lasso-Cox regression analyses, stratifying patients into high- and low-risk groups. Immune landscape and drug sensitivity analyses were conducted to explore group-specific differences. Additionally, Mendelian randomization analysis was employed to identify genes causally related to OSCC progression. Results Several key pathways associated with neutrophil interactions in OSCC progression were identified, leading to the construction of a prognostic model based on significant module genes. The model demonstrated strong predictive performance in distinguishing survival rates between high- and low-risk groups. Immune landscape analysis revealed significant differences in cell infiltration patterns and TIDE scores between the groups. Drug sensitivity analysis highlighted differences in drug responsiveness between high- and low-risk groups. Conclusion This study elucidates the critical role of neutrophils and their associated gene modules in OSCC progression. The prognostic model provides a novel reference for patient stratification and targeted therapy. These findings offer potential new targets for OSCC diagnosis, prognosis, and immunotherapy.https://doi.org/10.1186/s40246-024-00712-7Oral squamous cell carcinomaNeutrophilsImmune landscapeRisk modelBiomarkers |
| spellingShingle | Jinhang Wang Zifeng Cui Qiwen Song Kaicheng Yang Yanping Chen Shixiong Peng Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma Human Genomics Oral squamous cell carcinoma Neutrophils Immune landscape Risk model Biomarkers |
| title | Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| title_full | Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| title_fullStr | Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| title_full_unstemmed | Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| title_short | Integrating single-cell RNA-seq and bulk RNA-seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| title_sort | integrating single cell rna seq and bulk rna seq to construct a neutrophil prognostic model for predicting prognosis and immune response in oral squamous cell carcinoma |
| topic | Oral squamous cell carcinoma Neutrophils Immune landscape Risk model Biomarkers |
| url | https://doi.org/10.1186/s40246-024-00712-7 |
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