Integrated weighted gene coexpression network analysis identifies Frizzled 2 (FZD2) as a key gene in invasive malignant pleomorphic adenoma

Abstract

Background Invasive malignant pleomorphic adenoma (IMPA) is a highly malignant neoplasm of the oral salivary glands with a poor prognosis and a considerable risk of recurrence. Many disease-causing genes of IMPA have been identified in recent decades (e.g., P53, PCNA and HMGA2), but many of these genes remain to be explored. Weighted gene coexpression network analysis (WGCNA) is a newly emerged algorithm that can cluster genes and form modules based on similar gene expression patterns. This study constructed a gene coexpression network of IMPA via WGCNA and then carried out multifaceted analysis to identify novel disease-causing genes. Methods RNA sequencing (RNA-seq) was performed for 10 pairs of IMPA and normal tissues to acquire the gene expression profiles. Differentially expressed genes (DEGs) were screened out with the cutoff criteria of |log2 Fold change (FC)|> 1 and adjusted p value < 0.05. Then, WGCNA was applied to systematically identify the hidden diagnostic hub genes of IMPA. Results In this research, a total of 1970 DEGs were screened out in IMPA tissues, including 1056 upregulated DEGs and 914 downregulated DEGs. Functional enrichment analysis was performed for identified DEGs and revealed an enrichment of tumor-associated GO terms and KEGG pathways. We used WGCNA to identify gene module most relevant with the histological grade of IMPA. The gene FZD2 was then recognized as the hub gene of the selected module with the highest module membership (MM) value and intramodule connectivity in protein–protein interaction (PPI) network. According to immunohistochemistry (IHC) staining, the expression level of FZD2 was higher in low-grade IMPA than in high-grade IMPA. Conclusion FZD2 shows an expression dynamic that is negatively correlated with the clinical malignancy of IMPA and it plays a central role in the transcription network of IMPA. Thus, FZD2 serves as a promising histological indicator for the precise prediction of IMPA histological stages.

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

“…Initially, a total of 97 tissue samples were collected from nine tumor types, including brain tissue, lung tissue, liver tissue, endometrium, ovarian, blood, colon, salivary gland, and stomach [38][39][40][41][42][43][44][45][46][47][48] (Table S1). In addition, we used the cell lines m 6 A-seq collected in previous studies [13] to verify our results, these data include seven tumor cell lines (HEC1a, HEPG2, iSLK MOLM13, MonoMac6, MT4tCELL, NB4) and three normal cell lines (MSC, NHDF, TIME) (Table S2)…”

Weighted Gene Co-expression Network Analysis (WGCNA) of Wnt Signaling Related to Periodontal Ligament Formation: A Bioinformatics-Based Analysis

“…Weighted gene co-expression network analysis (WGCNA) is a bioinformatics tool that identifies gene modules or networks where genes share similar expression patterns. It differs from traditional methods like differential gene expression analysis, focusing on individual genes [ 8 ]. WGCNA constructs a gene coexpression network, allowing for the identification of modules with similar expression patterns.…”

“…A comprehensive analysis method like WGCNA can be employed to understand the molecular mechanisms underlying Wnt signaling in odontogenic tissue formation. This method can identify co-expressed gene modules and potential hub genes, which may be critical players in odontogenic tissue formation [ 8 , 9 , 14 ]. Functional enrichment analysis can provide insights into the biological processes and pathways associated with Wnt signaling in odontogenesis.…”

Extracellular matrix remodelling and stiffening contributes to tumorigenesis of salivary carcinoma ex pleomorphic adenoma——A study based on patient-derived organoids

“…For instance, tenascin, an extracellular matrix (ECM) glycoprotein, was found to be expressed in the stroma of CXPA, which may contribute to neoplastic proliferation [ 13 ]. In one of our previous studies, we conducted RNA-sequencing of fresh specimens of CXPA and adjacent normal tissues and found that ECM-related terms, such as ECM organization and collagen fibril organization, were highly enriched in the transcription network of CXPA [ 14 ]. These findings implied that disruption of the ECM may be part of the mechanisms driving CXPA tumorigenesis.…”

“…Since our findings [ 14 ] regarding ECM in CXPA were based on fresh samples, which may include mesenchymal tissues, thus RNA-sequencing and bioinformatic analysis may produce false positive results. Patient-derived organoids model predominantly consists of tumour cells.…”