Identification of key genes and pathways associated with esophageal squamous cell carcinoma development based on weighted gene correlation network analysis

Single-cell transcriptomics reveals heterogeneity in esophageal squamous epithelial cells and constructs models for predicting patient prognosis and immunotherapy

Background

Esophageal squamous cell carcinoma (ESCC), characterized by its high invasiveness and malignant potential, has long been a formidable challenge in terms of treatment.

Methods

A variety of advanced analytical techniques are employed, including single-cell RNA sequencing (scRNA-seq), cell trajectory inference, transcription factor regulatory network analysis, GSVA enrichment analysis, mutation profile construction, and the inference of potential immunotherapeutic drugs. The purpose is to conduct a more comprehensive exploration of the heterogeneity among malignant squamous epithelial cell subgroups within the ESCC microenvironment and establish a model for predicting the prognosis and immunotherapy outcomes of ESCC patients.

Results

An analysis was conducted through scRNA-seq, and three Cluster of malignant epithelial cells were identified using the infer CNV method. Cluster 0 was found to exhibit high invasiveness, whereas Cluster 1 displayed prominent characteristics associated with epithelial-mesenchymal transition. Confirmation of these findings was provided through cell trajectory analysis, which positioned Cluster 0 at the initiation stage of development and Cluster 1 at the final developmental stage. The abundance of Cluster 0-2 groups in TCGA-LUAD samples was assessed using ssGSEA and subsequently categorized into high and low-expression groups. Notably, it was observed that Cluster 0-1 had a significant impact on survival (p<0.05). Furthermore, GSVA enrichment analysis demonstrated heightened activity in hallmark pathways for Cluster 0, whereas Cluster 1 exhibited notable enrichment in pathways related to cell proliferation. It is noteworthy that a prognostic model was established utilizing feature genes from Cluster 0-1, employing the Lasso and stepwise regression methods. The results revealed that in TCGA and GSE53624 cohorts, the low-risk group demonstrated significantly higher overall survival and increased levels of immune infiltration. An examination of four external immunotherapy cohorts unveiled that the low-risk group exhibited improved immunotherapeutic efficacy. Additionally, more meaningful treatment options were identified for the low-risk group.

Conclusion

The findings revealed distinct interactions between malignant epithelial cells of ESCC and subgroups within the tumor microenvironment. Two cell clusters, strongly linked to survival, were pinpointed, and a signature was formulated. This signature is expected to play a crucial role in identifying and advancing precision medicine approaches for the treatment of ESCC.

Predicting and Understanding the Pathology of Single Nucleotide Variants in Human COQ Genes

Coenzyme Q (CoQ) is a vital lipid that functions as an electron carrier in the mitochondrial electron transport chain and as a membrane-soluble antioxidant. Deficiencies in CoQ lead to metabolic diseases with a wide range of clinical manifestations. There are currently few treatments that can slow or stop disease progression. Primary CoQ₁₀ deficiency can arise from mutations in any of the COQ genes responsible for CoQ biosynthesis. While many mutations in these genes have been identified, the clinical significance of most of them remains unclear. Here we analyzed the structural and functional impact of 429 human missense single nucleotide variants (SNVs) that give rise to amino acid substitutions in the conserved and functional regions of human genes encoding a high molecular weight complex known as the CoQ synthome (or Complex Q), consisting of the COQ3-COQ7 and COQ9 gene products. Using structures of COQ polypeptides, close homologs, and AlphaFold models, we identified 115 SNVs that are potentially pathogenic. Further biochemical characterizations in model organisms such as Saccharomyces cerevisiae are required to validate the pathogenicity of the identified SNVs. Collectively, our results will provide a resource for clinicians during patient diagnosis and guide therapeutic efforts toward combating primary CoQ₁₀ deficiency.

Upregulation of Centromere Proteins as Potential Biomarkers for Esophageal Squamous Cell Carcinoma Diagnosis and Prognosis

Esophageal squamous cell carcinoma (ESCC) has a high incidence and low survival rate, necessitating the identification of novel specific biomarkers. Centromere-associated proteins (CENPs) have been reported to be biomarkers for many cancers, but their roles in ESCC have seldom been investigated. Here, the potential clinical roles of CENPs in ESCC patients were demonstrated by a systematic bioinformatics analysis. Most CENP-encoding genes were differentially expressed between tumor and normal tissues. CENPA, CENPE, CENPF, CENPI, CENPM, CENPN, CENPQ, and CENPR were upregulated universally in the three datasets. Survival analysis demonstrated that high expression of CENPE and CENPQ was positively correlated with the outcomes of ESCC patients. The CENPE-based forecast model was more accurate than the tumor-node-metastasis (TNM) staging-based model, which was classified as stage I/II vs. III/IV. More importantly, the forecast model based on the commonly upregulated CENPs exhibited a much higher area under the curve (AUC) value (0.855) than the currently known TTL, ZNF750, AC016205.1, and BOLA3 biomarkers. The nomogram model integrating the CENPs, TNM stage, and sex was highly accurate in the prognosis of ESCC patients ( $\text{AUC}=0.906$ ). Besides, gene set enrichment analysis (GSEA) demonstrated that CENPE expression is significantly correlated with cell cycle, G2/M checkpoint, mitotic spindle, p53, etc. Finally, in validation experiments, we also found that CENPE and CENPQ were significantly overexpressed in esophageal cancer cells. Taken together, these results clearly suggest that CENPs are clinically promising diagnostic and prognostic biomarkers for ESCC patients.

Levels of Coenzyme Q10 and Several COQ Proteins in Human Astrocytoma Tissues Are Inversely Correlated with Malignancy

In a previous study, we reported the alterations of primary antioxidant enzymes and decreased citrate synthase (CS) activities in different grades of human astrocytoma tissues. Here, we further investigated coenzyme Q₁₀ (CoQ₁₀) levels and protein levels of polyprenyl diphosphate synthase subunit (PDSS2) and several COQ proteins required for CoQ₁₀ biosynthesis in these tissues. We found that the level of endogenous CoQ₁₀, but not of exogenous α-tocopherol, was higher in nontumor controls than in all grades of astrocytoma tissues. The levels of COQ3, COQ5, COQ6, COQ7, COQ8A, and COQ9, but not of COQ4, were lower in Grade IV astrocytoma tissues than in controls or low-grade (Grades I and II) astrocytomas, but PDSS2 levels were higher in astrocytoma tissues than in controls. Correlation analysis revealed that the levels of CoQ₁₀ and COQ proteins were negatively correlated with malignancy degree and positively correlated with CS activity, whereas PDSS2 level was positively correlated with malignancy. Moreover, lower level of mitochondrial DNA-encoded cytochrome c oxidase subunit 2 was not only associated with a higher malignancy degree but also with lower level of all COQ proteins detected. The results revealed that mitochondrial abnormalities are associated with impaired CoQ₁₀ maintenance in human astrocytoma progression.

Identification and Validation of a Dysregulated miRNA-Associated mRNA Network in Temporal Lobe Epilepsy

Objectives

This study is aimed at exploring the relationships between miRNAs and mRNAs and to characterize their biological functions in temporal lobe epilepsy (TLE).

Methods

Novel clinical significant miRNAs and target genes and their potential underlying mechanisms have been discovered and explored by mining miRNAs and mRNA expression data of TLE patients using various bioinformatics methods. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the bioinformatic analysis results.

Results

A total of 6 dysregulated miRNAs and 442 differentially expressed genes (DEGs) related to TLE were obtained from GEO database (GSE114701 and GSE127871 datasets). A protein-protein interaction (PPI) network containing the 442 DEGs was established. mRNA response elements from the 6 dysregulated miRNAs were predicted using the miRDB and TargetScan bioinformatic tools. By merging the identified targets of the dysregulated miRNAs and the 247 downregulated DEGs, a miRNA-mRNA network was constructed revealing the interaction of miR-484 with eight mRNAs (ABLIM2, CEP170B, CTD-3193O13.9, EFNA5, GAP43, PRKCB, FXYD7, and NCAN). A weighted correlation network analysis (WGCNA) based on the eight genes was established and demonstrated that these mRNAs, except FXYD7 and NCAN, were hub genes in the network. Gene Oncology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the six hub genes were mainly involved in cellular-related biological functions and the neurotransmitter synapse pathway. The differences in expression levels of the miR-484 and the three hub genes (CTD-3193O13.9, EFNA5, and PRKCB) observed experimentally in TLE patients compared to those of healthy controls were consistent with the WGCNA prediction.

Conclusion

Our study suggests that understanding the miRNA-mRNA interactions will provide insights into the epilepsy pathogenesis. In addition, our results indicate that miR-484 may be a promising novel biomarker for TLE.

CircAGFG1 acts as a sponge of miR-4306 to stimulate esophageal cancer progression by modulating MAPRE2 expression

OBJECTIVE

This work aims to determine the role of circular RNA (circRNA) AGFG1 and related molecular mechanism in esophageal squamous cell carcinoma (ESCC) cells.

METHODS

CircAGFG1 expression in ESCC cell lines was probed with qRT-PCR. ESCC cells were transfected/cotransfected with si-circAGFG1, pcDNA3.1-circAGFG1, si-Microtubule Associated Protein RP/EB Family Member 2 (MAPRE2), pcDNA3.1-circAGFG1 + miR-4306 mimic or pcDNA3.1-circAGFG1 + si-MAPRE2. The interactions between circAGFG1 and miR-4306 as well as miR-4306 and MAPRE2 were confirmed by dual-luciferase reporter assay. Cell proliferation, migration and invasion were detected by CCK-8, cell scratch and Transwell assays, respectively. Relative RNA expression levels of circAGFG1, miR-4306 and MAPRE2 in ESCC cells were measured by qRT-PCR. The protein level of MAPRE2 in ESCC cells was monitored by Western blot.

RESULTS

CircAGFG1 was observably upregulated in ESCC cell lines. Besides, circAGFG1 silencing hindered ESCC cell development in vitro, and these effects were enhanced by miR-4306 overexpression or MAPRE2 silencing. Mechanistic analysis evidenced that circAGFG1 might act as a competitive endogenous RNA of miR-4306 to relieve the repressive effect of miR-4306 on its target MAPRE2.

CONCLUSION

CircAGFG1 facilitates ESCC progression via the miR-4306/MAPRE2 axis, and it may act as a possible biomarker for therapy and diagnosis in ESCC treatment.

Systematic identification of key functional modules and genes in esophageal cancer

BACKGROUND

Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods.

METHODS

The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan-Meier plotter, and TIMER databases.

RESULTS

We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 'might not play an important role in immune cell infiltration.

CONCLUSIONS

Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

A Prognostic Signature Based on Immunogenomic Profiling Offers Guidance for Esophageal Squamous Cell Cancer Treatment

Our study aimed to develop an immune prognostic signature that could provide accurate guidance for the treatment of esophageal squamous cell cancer (ESCC). By implementing Single-Sample Gene Set Enrichment Analysis (ssGSEA), we established two ESCC subtypes (Immunity High and Immunity Low) in GSE53625 based on immune-genomic profiling of twenty-nine immune signature. We verified the reliability and reproducibility of this classification in the TCGA database. Immunity High could respond optimally to immunotherapy due to higher expression of immune checkpoints, including PD1, PDL1, CTLA4, and CD80. We used WGCNA analysis to explore the underlying regulatory mechanism of the Immunity High group. We further identified differentially expressed immune-related genes (CCR5, TSPAN2) in GSE53625 and constructed an independent two-gene prognostic signature we internally validated through calibration plots. We established that high-risk ESCC patients had worse overall survival (P=0.002, HR=2.03). Besides, high-risk ESCC patients had elevated levels of infiltrating follicle-helper T cells, naïve B cells, and macrophages as well as had overexpressed levels of some immune checkpoints, including B3H7, CTLA4, CD83, OX40L, and GEM. Moreover, through analyzing the Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk group demonstrated drug resistance to some chemotherapy and targeted drugs such as paclitaxel, gefitinib, erlotinib, and lapatinib. Furthermore, we established a robust nomogram model to predict the clinical outcome in ESCC patients. Altogether, our proposed immune prognostic signature constitutes a clinically potential biomarker that will aid in evaluating ESCC outcomes and promote personalized treatment.

Analysis of Differentially Expressed Genes in a Chinese Cohort of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a leading malignancy in China with both high incidence and mortality. Towards improving outcomes, clinically-relevant biomarkers are urgently needed for use as prognostic and treatment targets. Herein we applied RNA-seq for deep sequencing of ten matched pairs of ESCC and adjacent non-cancerous tissues (NT) from Chinese patients. Transcriptomic data mapped to approximately 64% of all annotated genes with 2,047 and 708 unigenes being differentially up-regulated and down-regulated, respectively, between ESCCs and NT samples (p<0.05). Dividing cases by pathological grade revealed significant differentially expressed genes (DEG) between ESCC and NT in both low and high differentiation cases (p<0.05) whereas gene expression differences were not significantly different between high and low differentiation ESCC tissues (p=0.053). Moreover, the majority of ESCC and NT tissues formed clusters in principal component analyses. The veracity of the DEG list was validated in a larger cohort of 45 patient samples, with down-regulated CLIC3, up-regulated CLIC4 and unchanged expression of CLIC2 confirmed in ESCC using quantitative PCR and Western blotting. Our data reveal both previously identified ESCC biomarkers along with novel candidates and represent a ready resource of DEGs in ESCC for further investigation.