Novel prognostic matrisome-related gene signature of head and neck squamous cell carcinoma

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy of the mucosal epithelium of the oral cavity, pharynx, and larynx. Laryngeal squamous cell carcinoma (LSCC) and oral squamous cell carcinoma are common HNSCC subtypes. Patients with metastatic HNSCC have a poor prognosis. Therefore, identifying molecular markers for the development and progression of HNSCC is essential for improving early diagnosis and predicting patient outcomes.Methods: Gene expression RNA-Seq data and patient clinical traits were obtained from The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma (TCGA-HNSC) and Gene Expression Omnibus databases. Differentially expressed gene (DEG) screening was performed using the TCGA-HNSC dataset. Intersection analysis between the DEGs and a list of core matrisome genes obtained from the Matrisome Project was used to identify differentially expressed matrisome genes. A prognostic model was established using univariate and multivariate Cox regression analyses, least absolute shrinkage, and selection operator (LASSO) regression analysis. Immune landscape analysis was performed based on the single-sample gene set enrichment analysis algorithm, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, prognostic value, receiver operating characteristic curve analysis, and gene mutation analyses. Immunohistochemical results regarding prognostic protein levels were obtained from the Human Protein Atlas. Single-gene RNA-sequencing data were obtained from GSE150321 and GSE172577 datasets. CCK-8 and Transwell assays were used to confirm cell proliferation and migration.Results: A total of 1,779 DEGs, including 939 upregulated and 840 downregulated genes, between tumor and normal samples were identified using the TCGA-HNSC microarray data. Intersection analysis revealed 52 differentially expressed matrisome-related genes. After performing univariate and multivariate Cox regression and LASSO analyses, a novel prognostic model based on six matrisome genes (FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1) for HNSCC was established. This risk model can successfully predict HNSCC survival. The high-risk group had worse prognoses and higher enrichment of pathways related to cancer development than the low-risk group. Silencing LAMB4 in HNSCC cell lines promoted cell proliferation and migration.Conclusion: This study provides a novel prognostic model for HNSCC. Thus, FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1 may be the promising biomarkers for clinical practice.

Functional CRISPR-Cas9 knockout screening of the genetic determinants of human fibroblast migration propensity

“…LAMB4 belongs to the laminin family, constituents of the extracellular matrix, however it is still poorly characterized, and it is currently not known to take part into any laminin heterotrimers 26,27 . The only study on its relation to migration reported that LAMB4 silencing in head and neck squamous cell carcinoma promotes migration, in agreement with what we found in fibroblasts 28 . GORASP1, also known as GRASP65, is a Golgi structural protein critical in establishing polarity in migrating cells once regulated by phosphorylation 29 .…”

Identification of S1PR4 as an immune modulator for favorable prognosis in HNSCC through machine learning

“…Furthermore, we compared the previous GPCR-based model with other models from previous studies. 23 , 24 , 25 , 26 As indicated by C-index comparison, the GPCR-based model outperformed them in predicting OS for HNSCC patients ( Figure S4 ). Moreover, we constructed a nomogram based on GPR87, S1PR4, and S1PR5 expressions ( Figure 4 D).…”

The value of basement membrane-associated genes in the prognosis and immune regulation of glioma

“…Huang et al determined that LAMB4 is overexpressed in head and neck squamous cell carcinoma, and knockdown of LAMB4 expression can effectively delay tumor progression. [58] Therefore, it can be inferred that BMGs participate in the regulation of TME, and produce corresponding pathological changes to promote tumor progression. According to this study, the high-risk group with glioma expressed more HLA, immunological checkpoints, chemokines, and chemokine receptors.…”