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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Main Authors: Jinhang Wang, Zifeng Cui, Qiwen Song, Kaicheng Yang, Yanping Chen, Shixiong Peng
Format: Article
Language:English
Published: BMC 2024-12-01
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.
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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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