Microarray analyses reveal genes related to progression and prognosis of esophageal squamous cell carcinoma

Highly Expressing SCARA5 Promotes Proliferation and Migration of Esophageal Squamous Cell Carcinoma

Background

Thrombospondin type 1 domain-containing 7A (THSD7A) was reported to play a procancer role in esophageal squamous cell carcinoma (ESCC). The aim of the study was to screen the downstream functional genes of THSD7A and explore their functions in ESCC, based on the reported research into THSD7A function and on gene microarrays.

Methods

We adopted quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Celigo high-content screening (HCS) technology to screen the downstream genes of THSD7A. The expression level of target genes was examined by PCR, western blot, and immunohistochemistry (IHC). The effects of these target genes on ESCC malignant biological behavior were performed in vivo and in vitro. The Kaplan-Meier (K-M) survival analysis and Cox regression were used to analyze the prognostic significance of target genes in ESCC patients. Experiments in the literature on liver cancer (LC) were repeated to verify the functions of these genes in different tumors. We further explored the cancer-promoting mechanism of target genes in ESCC by sequencing of the genes' exons.

Results

Scavenger receptor class A member 5 (SCARA5) was proved to be the downstream driving gene of THSD7A. SCARA5 promoted cell proliferation and migration but inhibited apoptosis in ESCC. IHC results confirmed that SCARA5 expression in ESCC exceeded that in normal tissues. The K-M survival analysis indicated that SCARA5 expression quantity was not related to prognosis, but tumor volume and T classification were both the independent prognostic factors. Repetition of experiments in LC in the literature confirmed that SCARA5 had exactly opposite functions in EC and LC.

Conclusion

SCARA5 was related to the development and occurrence of ESCC. Our findings suggested that it was a potentially diagnostic individualized therapeutic target for ESCC in the future and that its application could possibly be combined with that of upstream THSD7A gene.

A glycolysis-related gene signature predicts prognosis of patients with esophageal adenocarcinoma

Background: Esophageal adenocarcinoma (EAC) is a growing problem with a rapidly rising incidence and carries a poor prognosis. We aimed to develop a glycolysis-related gene signature to predict the prognostic outcome of patients with EAC.

Results: Five genes (CLDN9, GFPT1, HMMR, RARS and STMN1) were correlated with prognosis of EAC patients. Patients were classified into high-risk and low-risk groups calculated by Cox regression analysis, based on the five gene signature risk score. The five-gene signature was an independent biomarker for prognosis and patients with low risk scores showed better prognosis. Nomogram incorporating the gene signature and clinical prognostic factors was effective in predicting the overall survival.

Conclusion: An innovative identified glycolysis-related gene signature and an effective nomogram reliably predicted the prognosis of EAC patients.

Methods: The Cancer Genome Atlas database was investigated for the gene expression profile of EAC patients. Glycolytic gene sets difference between EAC and normal tissues were identified via Gene set enrichment analysis (GSEA). Univariate and multivariate Cox analysis were utilized to construct a prognostic gene signature. The signature was evaluated by receiver operating characteristic curves and Kaplan–Meier curves. A prognosis model integrating clinical parameters with the gene signature was established with nomogram.

CYP3A5 suppresses metastasis of lung adenocarcinoma through ATOH8/Smad1 axis

Cytochrome P450 3A5 (CYP3A5) maintains primary roles in toxic metabolism, catalyzes redox reaction, and contributes to chemotherapeutic resistance. However, the mechanism of CYP3A5 in carcinogenesis remains largely undefined. Here, we investigated a novel role of CYP3A5 inhibiting the metastasis in lung adenocarcinoma (LUAD) via ATOH8/Smad1 axis. We found that CYP3A5 was generally down-regulated in LUAD by RT-PCR, western blot and immunohistochmeistry (IHC) in tissues and cell lines. Low expression of CYP3A5 was significantly associated with poor prognosis of LUAD patients. Functionally, ectopic expression of CYP3A5 could substantially inhibit the migration and invasion in vitro. Consistently, up-regulation of CYP3A5 dramatically suppressed metastatic ability in vivo. Mechanistically, high-throughput phosphorylation chip indicated that CYP3A5 significantly decreased the phosphorylation of Smad1, resulting in suppression of metastasis. Furthermore, bioinformatics analysis and co-immunoprecipitation (Co-IP) experiments uncovered that CYP3A5 interacted with ATOH8, and the interaction, in turn, mediated in-activation in the Smad1 pathway. The combined IHC panel, including CYP3A5 and phosphorylation of Smad1, exhibited a better prognostic value for LUAD patients than any of these components individually. Taken together, CYP3A5 repressed activation of Smad1 to inhibit LUAD metastasis via interacting with ATOH8, indicating a novel potential mechanism of CYP3A5 in LUAD progression.

Identification of methylated-differentially expressed genes and pathways in esophageal squamous cell carcinoma

Methylation, as an epigenetic modification, can affect gene expression and play a role in the occurrence and development of cancer. This research is devoted to discover methylated-differentially expressed genes (MDEGs) in esophageal squamous cell carcinoma (ESCC) and explore special associated pathways. We downloaded GSE51287 methylation profiles and GSE26886 expression profiles from GEO DataSets, and performed a comprehensive bioinformatics analysis. Totally, 19 hypermethylated, lowly expressed genes (Hyper-LGs) were identified, and involved in regulation of cell proliferation, phosphorus metabolic process and protein kinase activity. Meanwhile, 17 hypomethylated, highly expressed genes (Hypo-HGs) were participated in collagen catabolic process, metallopeptidase and cytokine activity. Pathway analysis determined that Hyper-LGs were enriched in arachidonic acid metabolism pathway, while Hypo-HGs were primarily associated with the cytokine-cytokine receptor interaction pathway. IL 6, MMP3, MMP9, SPP1 were identified as hub genes based on the PPI network that combined 7 ranked methods included in cytoHubba, and verification was performed in human tissues. Our integrated analysis identified many novel genetic lesions in ESCC and provides a crucial molecular foundation to improve our understanding of ESCC. Hub genes, including IL 6, MMP3, MMP9 and SPP1, could be considered for use as aberrant methylation-based biomarkers to facilitate the accurate diagnosis and therapy of ESCC.

The Oncogene ECT2 Contributes to a Hyperplastic, Proliferative Lung Epithelial Cell Phenotype in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) and lung cancer are progressive lung diseases with a poor prognosis. IPF is a risk factor for the development of lung cancer, and the incidence of lung cancer is increased in patients with IPF. The disease pathogenesis of IPF and lung cancer involves common genetic alterations, dysregulated pathways, and the emergence of hyperplastic and metaplastic epithelial cells. Here, we aimed to identify novel, common mediators that might contribute to epithelial cell reprogramming in IPF. Gene set enrichment analysis of publicly available non-small cell lung cancer and IPF datasets revealed a common pattern of misregulated genes linked to cell proliferation and transformation. The oncogene ECT2 (epithelial cell transforming sequence 2), a guanine nucleotide exchange factor for Rho GTPases, was highly enriched in both IPF and non-small cell lung cancer compared with nondiseased controls. Increased expression of ECT2 was verified by qPCR and Western blotting in bleomycin-induced lung fibrosis and human IPF tissue. Immunohistochemistry demonstrated strong expression of ECT2 staining in hyperplastic alveolar epithelial type II (ATII) cells in IPF, as well as its colocalization with proliferating cell nuclear antigen, a well-known proliferation marker. Increased ECT2 expression coincided with enhanced proliferation of primary mouse ATII cells as analyzed by flow cytometry. ECT2 knockdown in ATII cells resulted in decreased proliferation and collagen I expression in vitro. These data suggest that the oncogene ECT2 contributes to epithelial cell reprogramming in IPF, and further emphasize the hyperplastic, proliferative ATII cell as a potential target in patients with IPF and lung cancer.

Identification of novel cell glycolysis related gene signature predicting survival in patients with endometrial cancer

BACKGROUND

Endometrial cancer (EC) is one of the three major gynecological malignancies. Numerous biomarkers that may be associated with survival and prognosis have been identified through database mining in previous studies. However, the predictive ability of single-gene biomarkers is not sufficiently specific. Genetic signatures may be an improved option for prediction. This study aimed to explore data from The Cancer Genome Atlas (TCGA) to identify a new genetic signature for predicting the prognosis of EC.

METHODS

mRNA expression profiling was performed in a group of patients with EC (n = 548) from TCGA. Gene set enrichment analysis was performed to identify gene sets that were significantly different between EC tissues and normal tissues. Cox proportional hazards regression models were used to identify genes significantly associated with overall survival. Quantitative real-time-PCR was used to verify the reliability of the expression of selected mRNAs. Subsequent multivariate Cox regression analysis was used to establish a prognostic risk parameter formula. Kaplan-Meier survival estimates and the log-rank test were used to validate the significance of risk parameters for prognosis prediction.

RESULT

Nine genes associated with glycolysis (CLDN9, B4GALT1, GMPPB, B4GALT4, AK4, CHST6, PC, GPC1, and SRD5A3) were found to be significantly related to overall survival. The results of mRNA expression analysis by PCR were consistent with those of bioinformatics analysis. Based on the nine-gene signature, the 548 patients with EC were divided into high/low-risk subgroups. The prognostic ability of the nine-gene signature was not affected by other factors.

CONCLUSION

A nine-gene signature associated with cellular glycolysis for predicting the survival of patients with EC was developed. The findings provide insight into the mechanisms of cellular glycolysis and identification of patients with poor prognosis in EC.

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer

Gastric cancer (GC) is one of the most fatal cancers in the world. Thousands of biomarkers have been explored that might be related to survival and prognosis via database mining. However, the prediction effect of single gene biomarkers is not specific enough. Increasing evidence suggests that gene signatures are emerging as a possible better alternative. We aimed to develop a novel gene signature to improve the prognosis prediction of GC. Using the messenger RNA (mRNA)-mining approach, we performed mRNA expression profiling in a large GC cohort (n = 375) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and we recovered genes related to the G2/M checkpoint, which we identified with a Cox proportional regression model. We identified a set of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A), which were significantly associated with overall survival (OS) in the test series. Based on this five-gene signature, the test series patients could be classified into high-risk or low-risk subgroups. Multivariate Cox regression analysis indicated that the prognostic power of this five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature related to the cell cycle that can predict survival for GC. Our findings provide novel insight that is useful for understanding cell cycle mechanisms and for identifying patients with GC with poor prognoses.