Reanalysis of public bulk and single-nucleus transcriptomes identifies widespread tumor-normal dysregulation and a cross-layer cell-cycle signal in sinonasal squamous cell carcinoma
Year: 2026
Type: article
Abstract: Background Sinonasal squamous cell carcinoma (SNSCC) is a rare malignancy affecting the nasal cavity and paranasal sinuses, with human papillomavirus (HPV) infection identified as a critical etiological factor in a subset of cases. HPV-positive and HPV-negative SNSCC exhibit distinct clinical behaviors, with HPV-positive tumors generally demonstrating better prognosis and treatment response. However, the cellular composition and transcriptomic landscape of SNSCC tumor versus normal tissue remain incompletely characterized. Multi-layer transcriptomic reanalysis of publicly available single-nucleus and bulk RNA sequencing data provides an opportunity to systematically identify tumor-normal gene expression changes and nominate candidate biomarkers for prospective validation. Methods We reanalyzed publicly available single-nucleus RNA sequencing data (GSE277797: one healthy nasal mucosa library, HC1; one SNSCC tumor library, CA5) together with bulk RNA-seq data from 14 SNSCC and normal nasal mucosa samples (GSE278145), microarray data from five matched tumor-adjacent-normal pairs (GSE138809), and a 21-sample sinonasal cancer tumor-only context cohort (GSE118386). Following rigorous quality control, doublet detection, cell-type annotation using canonical markers, and program scoring, we integrated findings across data layers. Candidate genes were further assessed by in vitro experiments in two SNSCC cell lines (RPMI 2650 and Detroit 562) compared with normal bronchial epithelial BEAS-2B cells, using quantitative real-time PCR (qRT-PCR) to evaluate mRNA expression levels (2 −ΔΔCT method, GAPDH reference) and enzyme-linked immunosorbent assay (ELISA) to quantify secreted and intracellular protein concentrations. Results Single-nucleus analysis resolved 14,479 nuclei into 11 biological cell types, with the largest observed compositional shift being an increase in Epithelial cells (+44.7 percentage points) and a decrease in Secretory epithelial cells (−56.2 percentage points) in the tumor library relative to the healthy library. Bulk RNA-seq differential expression testing across 17,677 genes identified 5,732 genes at FDR <0.05, with cell-cycle genes showing the largest program-level shift (+1.727 standardized units). Cross-layer integration yielded a Spearman correlation of 0.543 between bulk fold-changes and single-nucleus pseudobulk shifts. Candidate genes including CD74, CCL5, IL32, and HLA-DRA showed concordant upregulation across data layers. In vitro qRT-PCR confirmed significant mRNA upregulation of CD74 (4.27-fold), CCL5 (3.15-fold), IL32 (3.68-fold), and HLA-DRA (3.82-fold) in RPMI 2650 cells compared to normal BEAS-2B cells (all p < 0.01), with elevated protein levels further corroborated by enzyme-linked immunosorbent assay. Conclusion This multi-layer transcriptomic reanalysis of publicly available SNSCC datasets identifies consistent tumor-versus-normal dysregulation across single-nucleus and bulk platforms, and nominates CD74, CCL5, IL32, and HLA-DRA as candidate biomarkers warranting prospective clinical validation. These findings are exploratory and should be interpreted within the constraints of the available single-sample single-nucleus data.
Source: Frontiers in Genetics
Authors: Jiongcong Yuan, Ying Wang, Kaisheng Lin, Lingli Sun
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7223170585