Bioinformatics analysis of gene expression profiles of esophageal squamous cell carcinoma

COL11A1 promotes esophageal squamous cell carcinoma proliferation and metastasis and is inversely regulated by miR-335-5p

Background

Esophagus squamous cell carcinoma (ESCC) is a sort of cancer that occurs in the esophageal epithelial tissue. This study performed integrated bioinformatics analysis of Gene Expression Omnibus (GEO) datasets GSE32424, GSE29968, and GSE130078. Collagen type XI alpha 1 (COL11A1) was identified as the hub gene in ESCC progression. The involvement of COL11A1 in ESCC development was next determined using in vitro functional tests.

Methods

Hub genes were identified through integrated bioinformatics analysis. The real-time reverse transcription-polymerase chain reaction was implemented for detecting the expression of COL11A1 mRNA in esophageal cancer cells. KYSE-30 cells were transfected using a vector encoding COL11A1. The proliferation of cells was determined using the Cell Counting Kit-8 (CCK-8) assay. Detection of the cell migration and invasion was made through making use of the transwell test. The development of ESCC cells in vivo was evaluated in naked mice. The interplay among COL11A1 and microRNA-335-5p (miR-335-5p) was discovered using a luciferase reporter experiment.

Results

In vitro studies showed the upregulation of COL11A1 in ESCC cell lines obtained from ESCC patients and upregulation of COL11A1 was correlated with poor disease-free survival of ESCC patients, thereby implying an oncogenic involvement of COL11A1 in ESCC. Overexpression of COL11A1 enhanced the proliferation of ESCC cells, invasion, and migration; whereas COL11A1 knockdown impeded the proliferation of ESCC cells, invasion, and migration. Additionally, miRNA pathway analysis in combination with TargetScan’s online prediction and the luciferase reporter assay suggested miR-335-5p targeting and negatively regulating the COL11A1 3' untranslated region (3'UTR) within ESCC cells. MiR-335-5p overexpression diminished the development of ESCC cells. Additionally, co-expression of COL11A1 ameliorated the repressive influence of miR-335-5p overexpression on the growth and metastasis of ESCC cells.

Conclusions

Using comprehensive bioinformatics analysis, the current study identified COL11A1 as an oncogene in ESCC. The mechanistic studies indicated that COL11A1 promoted ESCC cell progression and that miR-335-5p negatively regulated the expression of COL11A1 in ESCC.

Collagen XI alpha 1 chain, a potential therapeutic target for cancer

Extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and it is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) has been found to be upregulated in a variety of cancers including ovarian cancer, breast cancer, thyroid cancer, pancreatic cancer, non-small-cell lung cancer, and transitional cell carcinoma of the bladder. High levels of COL11A1 usually predict poor prognosis, while COL11A1 is related to angiogenesis, invasion, and drug resistance of cancer. However, little is known about the specific mechanism by which COL11A1 regulates tumor progression. Here, we have organized and summarized the recent developments regarding elucidation of the relationship between COL11A1 and various cancers, as well as the interaction between COL11A1 and intracellular signaling pathways. In addition, we have selected therapeutic agents targeting COL11A1. All these indicate the possibility of using COL11A1 as a target for cancer treatment.

ECM Remodeling in Squamous Cell Carcinoma of the Aerodigestive Tract: Pathways for Cancer Dissemination and Emerging Biomarkers

Squamous cell carcinomas (SCC) include a number of different types of tumors developing in the skin, in hollow organs, as well as the upper aerodigestive tract (UADT) including the head and neck region and the esophagus which will be dealt with in this review. These tumors are often refractory to current therapeutic approaches with poor patient outcome. The most important prognostic determinant of SCC tumors is the presence of distant metastasis, significantly correlating with low patient survival rates. Rapidly emerging evidence indicate that the extracellular matrix (ECM) composition and remodeling profoundly affect SSC metastatic dissemination. In this review, we will summarize the current knowledge on the role of ECM and its remodeling enzymes in affecting the growth and dissemination of UADT SCC. Taken together, these published evidence suggest that a thorough analysis of the ECM composition in the UADT SCC microenvironment may help disclosing the mechanism of resistance to the treatments and help defining possible targets for clinical intervention.

ECM Remodeling in Squamous Cell Carcinoma of the Aerodigestive Tract: Pathways for Cancer Dissemination and Emerging Biomarkers

Simple Summary

Local and distant metastasis of patients affected by squamous cell carcinoma of the upper aerodigestive tract predicts poor prognosis. In the latest years, the introduction of new therapeutic approaches, including targeted and immune therapies, has improved the overall survival. However, a large number of these patients do not benefit from these treatments. Thus, the identification of suitable prognostic and predictive biomarkers, as well as the discovery of new therapeutic targets have emerged as a crucial clinical need. In this context, the extracellular matrix represents a suitable target for the development of such therapeutic tools. In fact, the extracellular matrix is composed by complex molecules able to interact with a plethora of receptors and growth factors, thus modulating the dynamic crosstalk between cancer cells and the tumor microenvironment. In this review, we summarize the current knowledge of the role of the extracellular matrix in affecting squamous cell carcinoma growth and dissemination. Despite extracellular matrix is known to affect the development of many cancer types, only a restricted number of these molecules have been recognized to impact on squamous cell carcinoma progression. Thus, we consider that a thorough analysis of these molecules may be key to develop new potential therapeutic targets/biomarkers.

Abstract

Squamous cell carcinomas (SCC) include a number of different types of tumors developing in the skin, in hollow organs, as well as the upper aerodigestive tract (UADT) including the head and neck region and the esophagus which will be dealt with in this review. These tumors are often refractory to current therapeutic approaches with poor patient outcome. The most important prognostic determinant of SCC tumors is the presence of distant metastasis, significantly correlating with low patient survival rates. Rapidly emerging evidence indicate that the extracellular matrix (ECM) composition and remodeling profoundly affect SSC metastatic dissemination. In this review, we will summarize the current knowledge on the role of ECM and its remodeling enzymes in affecting the growth and dissemination of UADT SCC. Taken together, these published evidence suggest that a thorough analysis of the ECM composition in the UADT SCC microenvironment may help disclosing the mechanism of resistance to the treatments and help defining possible targets for clinical intervention.

Time series expression pattern of key genes reveals the molecular process of esophageal cancer

Background: Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease is still elusive. Aim: To investigate the molecular process of esophageal cancer comprehensively and deeply. Methods: Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer. Then exacting gene interaction modules and hub genes were identified in module interaction network. Further, though survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related function or pathway were identified to elucidate potential mechanism in esophageal cancer. Results: A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding and other biological processes (BPs), as well as p53 signaling pathway, ERBB signaling pathway and epidermal growth factor receptor (EGFR) signaling pathway. Then, transcription factors (TFs) (including HIF1A) and ncRNAs (including CRNDE and hsa-mir-330-3p) significantly regulate dysfunction modules were identified. Further, survival analysis showed that GNGT2 was closely related to survival of esophageal cancer. And DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Conclusion: These works not only help us to reveal the potential regulatory factors in the development of disease, but also deepen our understanding of its deterioration mechanism.

Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis

Breast cancer is one of the most common malignant tumors among women worldwide and has a high morbidity and mortality. This research aimed to identify hub genes and small molecule drugs for breast cancer by integrated bioinformatics analysis. After downloading multiple gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, 283 overlapping differentially expressed genes (DEGs) significantly enriched in different cancer-related functions and pathways were obtained using LIMMA, VennDiagram and ClusterProfiler packages of R. We then analyzed the topology of protein–protein interaction (PPI) network with overlapping DEGs and further obtained six hub genes (RRM2, CDC20, CCNB2, BUB1B, CDK1, and CCNA2) from the network via STRING and Cytoscape. Subsequently, we conducted genes expression verification, genetic alterations evaluation, immune infiltration prediction, clinicopathological parameters analysis, identification of transcriptional and post-transcriptional regulatory molecules, and survival analysis for these hub genes. Meanwhile, 29 possible drug candidates (e.g., Cladribine, Gallium nitrate, Alvocidib, 1β-hydroxyalantolactone, Berberine hydrochloride, Nitidine chloride) were identified from the DGIdb database and the GSE85871 dataset. In addition, some transcription factors and miRNAs (e.g., E2F1, PTTG1, TP53, ZBTB16, hsa-miR-130a-3p, hsa-miR-204-5p) targeting hub genes were identified as key regulators in the progression of breast cancer. In conclusion, our study identified six hub genes and 29 potential drug candidates for breast cancer. These findings may advance understanding regarding the diagnosis, prognosis and treatment of breast cancer.

Identification of Autophagy-Related Genes and Small-Molecule Drugs in Esophageal Carcinoma

Background

Esophageal carcinoma (ESCA) is associated with a poor prognosis and high mortality rate. Autophagy plays important roles in promoting or suppressing tumor cell survival at different stages of cancer development. However, the roles of autophagy-related genes (ARGs) during ESCA progression and in patient prognosis remain unclear. Accordingly, in this study, we aimed to identify the relationships of ARGs with ESCA progression and patient prognosis.

Material/Methods

Clinicopathological information for patients with ESCA was downloaded from The Cancer Genome Atlas (TCGA) database. Transcriptome expression profiles were downloaded from TCGA and GTEx databases, and ARGs were downloaded from the Human Autophagy Database. We investigated the functions of ARGs by bioinformatics analysis. Moreover, statistical analysis of these genes was performed to identify independent prognostic markers.

Results

Differentially expressed genes between normal and tumor tissues were detected and identified. GO and KEGG analyses of differentially expressed ARGs were performed. Moreover, we derived a risk signature based on the identified independent prognostic markers. The identified genes also could predict the clinicopathological features of ESCA.

Conclusions

ARGs were key participants in the tumorigenesis and development of ESCA. Our findings may be useful for developing improved therapeutic approaches for ESCA.

Integrated Bioinformatics Analysis Identifies Hub Genes Associated with the Pathogenesis and Prognosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, using bioinformatics analyses, we attempted to identify potential biomarkers and therapeutic targets for ESCC. Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained through comprehensive analysis of three publicly available gene expression profile datasets from the Gene Expression Omnibus database. The biological roles of the DEGs were identified by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Moreover, the Cytoscape 3.7.1 platform and subsidiary tools such as Molecular Complex Detection (MCODE) and CytoHubba were used to visualize the protein-protein interaction (PPI) network of the DEGs and identify hub genes. A total of 345 DEGs were identified between normal esophageal and ESCC samples, which were enriched in the KEGG pathways of the cell cycle, endocytosis, pancreatic secretion, and fatty acid metabolism. Two of the highest scoring models were selected from the PPI network using Molecular Complex Detection. Moreover, CytoHubba revealed 21 hub genes with a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of five genes-SPP1, SPARC, BGN, POSTN, and COL1A2-were associated with poor disease-free survival of ESCC patients, as indicated by survival analysis. Taken together, we identified that elevated expression of five hub genes, including SPP1, is associated with poor prognosis in ESCC patients, which may serve as potential prognostic biomarkers or therapeutic target for ESCC.

Immunohistochemical analysis of the expression of cancer-associated fibroblast markers in esophageal cancer with and without neoadjuvant therapy

Esophageal carcinoma (EC) is one of the most aggressive human malignancies with high rates of resistance to conventional anticancer treatment. Cancer-associated fibroblasts (CAFs) are an important part of the tumor microenvironment and associated with tumor progression. COL11A1, SPARC, and CD90 have been identified as rather specific CAF markers, with COL11A1 expression particularly shown to influence response to chemotherapy. We investigated the impact of CAFs in esophageal cancer with a special focus on response to neoadjuvant treatment (nTX). Two collections of esophageal carcinomas were investigated: 164 cases treated with primary resection and 256 cases receiving nTX before resection. The expression of CAF markers was determined using next-generation tissue microarray (ngTMA®) technology and immunohistochemistry. The presence of COL11A1 and SPARC in fibroblasts within both primary resected cases and nTX-treated cases was associated with unfavorable clinicopathological variables such as higher (y)pT category and lymphatic invasion (p<0.001 each). The presence of COL11A1-positive CAFs was associated with worse overall survival in primary resected cases (HR: 2.162, p = 0.004, CI 95% 1.275-3.686). While in tumors showing regression after nTX, COL11A1-positive CAFs were detected less frequently, SPARC-positive CAFs were enriched after nTX, in both responding and non-responding patients (p < 0.001). Our results support the concept of CAFs as an important factor of tumor promotion and maintenance in EC. The population of CAFs increases with tumor progression and decreases, partly depending on the subtype, after regression following nTX. CAFs may serve as potential target for future therapeutic approaches for these highly aggressive tumors.

The prognostic role of FZD6 in esophageal squamous cell carcinoma patients

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a kind of cancer with heterogeneous biological characteristics, which is affected by a complex network of gene interactions. Identification of molecular biomarkers paves the way for individualized therapy based on gene expression profiles, which can overcome the heterogeneity of ESCC.

METHODS

In this study, GSE20347, GSE23400 and GSE45670 datasets were retrieved from Gene Expression Omnibus (GEO) database, and the overlapping differentially expressed genes (DEGs) in three datasets were screened. Then the overlapping DEGs function was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-enrichment analysis. The prognostic value of the top five KEGG pathway-related genes were further validated in The Cancer Genome Atlas (TCGA) database. After extensive statistical analysis, four genes (CDC25B, CXCL8, FZD6 and MCM4) were identified as potential prognostic markers. Among the four candidate genes, the prognostic value of FZD6 in ESCC patients has not been evaluated. Therefore, we finally used immunohistochemistry method to evaluate the effect of FZD6 on the prognosis of patients with ESCC. Additionally, we detected the expression level of FZD6 in ESCC cell line and normal esophageal epithelial cell line, and observed the cell viability of ESCC cell line after FZD6 knockdown.

RESULTS

The results showed that the overexpression of FZD6 predicted poor overall survival (OS) (P = 0.005) and progression-free survival (PFS) (P = 0.004) in ESCC patients. COX regression analysis showed that N stage (P = 0.026) and FZD6 expression level (P = 0.001) were independent prognostic factors of OS for ESCC patients. Furthermore, compared with normal esophageal epithelial cell line, the up-regulation of FZD6 was detected in ESCC cell line. Knockdown of FZD6 could significantly inhibit the proliferation of ESCC cells (P < 0.001).

CONCLUSION

CDC25B, CXCL8, FZD6 and MCM4 were screened as candidate genes for prognosis assessment of patients with ESCC. The prognostic role of FZD6 in ESCC patients was confirmed in current study.

The clinical significance of collagen family gene expression in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a subtype of esophageal cancer with high incidence and mortality. Due to the poor 5-year survival rates of patients with ESCC, exploring novel diagnostic markers for early ESCC is emergent. Collagen, the abundant constituent of extracellular matrix, plays a critical role in tumor growth and epithelial-mesenchymal transition. However, the clinical significance of collagen genes in ESCC has been rarely studied. In this work, we systematically analyzed the gene expression of whole collagen family in ESCC, aiming to search for ideal biomarkers.

Methods

Clinical data and gene expression profiles of ESCC patients were collected from The Cancer Genome Atlas and the gene expression omnibus databases. Bioinformatics methods, including differential expression analysis, survival analysis, gene sets enrichment analysis (GSEA) and co-expression network analysis, were performed to investigate the correlation between the expression patterns of 44 collagen family genes and the development of ESCC.

Results

A total of 22 genes of collagen family were identified as differentially expressed genes in both the two datasets. Among them, COL1A1, COL10A1 and COL11A1 were particularly up-regulated in ESCC tissues compared to normal controls, while COL4A4, COL6A5 and COL14A1 were notably down-regulated. Besides, patients with low COL6A5 expression or high COL18A1 expression showed poor survival. In addition, a 7-gene prediction model was established based on collagen gene expression to predict patient survival, which had better predictive accuracy than the tumor-node-metastasis staging based model. Finally, GSEA results suggested that collagen genes might be tightly associated with PI3K/Akt/mTOR pathway, p53 pathway, apoptosis, cell cycle, etc.

Conclusion

Several collagen genes could be potential diagnostic and prognostic biomarkers for ESCC. Moreover, a novel 7-gene prediction model is probably useful for predicting survival outcomes of ESCC patients. These findings may facilitate early detection of ESCC and help improves prognosis of the patients.

Integrative genomics analysis of hub genes and their relationship with prognosis and signaling pathways in esophageal squamous cell carcinoma

The main purpose of the present study was to recognize the integrative genomics analysis of hub genes and their relationship with prognosis and signaling pathways in esophageal squamous cell carcinoma (ESCC). The mRNA gene expression profile data of GSE38129 were downloaded from the Gene Expression Omnibus database, which included 30 ESCC and 30 normal tissue samples. The differentially expressed genes (DEGs) between ESCC and normal samples were identified using the GEO2R tool. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify the functions and related pathways of the genes. The protein‑protein interaction (PPI) network of these DEGs was constructed with the Search Tool for the Retrieval of Interacting Genes and visualized with a molecular complex detection plug‑in via Cytoscape. The top five important modules were selected from the PPI network. A total of 928 DEGs, including ephrin‑A1 (EFNA1), collagen type IV α1 (COL4A1),  C‑X‑C chemokine receptor 2 (CXCR2), adrenoreceptor β2 (ADRB2), P2RY14, BUB1B, cyclin A2 (CCNA2), checkpoint kinase 1 (CHEK1), TTK, pituitary tumor transforming gene 1 (PTTG1) and COL5A1, including 498 upregulated genes, were mainly enriched in the 'cell cycle', 'DNA replication' and 'mitotic nuclear division', whereas 430 downregulated genes were enriched in 'oxidation‑reduction process', 'xenobiotic metabolic process' and 'cell‑cell adhesion'. The KEGG analysis revealed that 'ECM‑receptor interaction', 'cell cycle' and 'p53 signaling pathway' were the most relevant pathways. According to the degree of connectivity and adjusted P‑value, eight core genes were selected, among which those with the highest correlation were CHEK1, BUB1B, PTTG1, COL4A1 and CXCR2. Gene Expression Profiling Interactive Analysis in The Cancer Genome Atlas database for overall survival (OS) was applied among these genes and revealed that EFNA1 and COL4A1 were significantly associated with a short OS in 182 patients. Immunohistochemical results revealed that the expression of PTTG1 in esophageal carcinoma tissues was higher than that in normal tissues. Therefore, these genes may serve as crucial predictors for the prognosis of ESCC.

Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer

Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE63678 from the GEO database and then performed functional enrichment analyses, including gene ontology and pathway analysis. To further investigate the molecular mechanisms underlying the three types of gynecological cancer, protein-protein interaction (PPI) analysis was performed. A biological network was generated with the guidance of the Kyoto Encyclopedia of Genes and Genomes database and was presented in Cytoscape. A total of 1,219 DEGs were identified for the three types of cancer, and 25 hub genes were revealed. Pathway analysis and the PPI network indicated that four main types of pathway participate in the mechanism of gynecological cancer, including viral infections and cancer formation, tumorigenesis and development, signal transduction, and endocrinology and metabolism. A preliminary gynecological cancer biological network was constructed. Notably, following all analysis, the phosphoinositide 3-kinase (PI3K)/Akt pathway was identified as a potential biomarker pathway. Seven pivotal hub genes (CCNA2, CDK1, CCND1, FGF2, IGF1, BCL2 and VEGFA) of the three gynecological cancer types were proposed. The seven hub genes may serve as targets in gynecological cancer for prevention and early intervention. The PI3K/Akt pathway was identified as a critical biomarker of the three types of gynecological cancer, which may serve a role in the pathogenesis. In summary, the present study provided evidence that could support the treatment of gynecologic tumors in the future.

MiR-219-5p suppresses cell proliferation and cell cycle progression in esophageal squamous cell carcinoma by targeting CCNA2

Background

We investigated the potential regulatory role of miR-219-5p in esophageal squamous cell carcinoma (ESCC) and looked at the underlying mechanisms in ESCC.

Methods

Real-time PCR was used to determine the levels of miR-219-5p in ESCC tissues and cell lines. The effects of miR-219-5p and cyclin A2 (CCNA2) on cell proliferation and cell cycle progression were evaluated using MTT, colony formation and flow cytometry assays with ESCC cell lines EC9706 and TE-9. Bioinformatics techniques and the luciferase reporter assay were applied to validate CCNA2 as the miR-219-5p target in ESCC cells. The mRNA and protein levels of CCNA2 were measured using real-time PCR and western blotting.

Results

MiR-219-5p expression was significantly lower in ESCC tissues and cells than in healthy tissues. Upregulation of miR-219-5p repressed cell proliferation and induced cell cycle arrest at the G2/M phase. CCNA2 was identified and confirmed as a direct downstream target of miR-219-5p and its expression negatively correlated with miR-219-5p profiles in ESCC tissues. Knockdown of CCNA2 potentiated the effects of miR-219-5p on cell proliferation and cell cycle distribution.

Conclusions

Our results demonstrate that miR-219-5p might function as a tumor suppressor by directly targeting CCNA2 expression. It could serve as a new therapeutic target for ESCC.

CD109 and squamous cell carcinoma

Squamous cell carcinoma (SCC) is well-known for its high rate of metastasis with poor prognosis. CD109 is a glycosylphosphatidylinositol-anchored cell-surface glycoprotein. Recently, CD109 emerges as a potential biomarker and a therapeutic target for SCCs. Accumulating studies have reported that CD109 is highly expressed in human SCCs of multiple organs, and may contribute to the progression of SCCs. In this review, we summarized the findings on expression pattern of CD109 in SCCs, and discussed the molecular mechanisms underlying the roles of CD109 in pathogenesis of SCCs.