Screening and Identification of Novel Biomarkers Associated with Cutaneous Squamous Cell Carcinoma

Abstract Background: Cutaneous squamous cell carcinoma (cSCC) is the leading cause of death in patients with non-melanoma skin cancers (NMSC). However, unclear pathogenesis of cSCC limits the application of molecular targeted therapy. Results: To identify the hub genes in the pathogenesis and progression of cSCC, we downloaded the microarray data sets GSE2503, GSE45164 and GSE66359 from the Gene Expression Omnibus (GEO) database, and identified differentially expressed genes (DEGs) between tumor and non-tumor tissues. Functional enrichment analysis was performed using DAVID. The STRING online website was used to construct a protein-protein interaction network (PPI), and then Cytoscape performed module analysis and degree calculation. 146 DEGs were identified with significant differences, including 113 up-regulated genes and 33 down-regulated genes. The enriched functions and pathways of the DEGs include microtubule-based movement, ATP binding, cell cycle, p53 signaling pathway, oocyte meiosis and PLK1 signaling events. Nine hub genes were identified, namely CDK1, AURKA, RRM2, CENPE, CCNB1, KIAA0101, ZWINT, TOP2A, ASPM. The differential expression of these genes has been verified in other data sets. In addition, the ROC curve also confirmed their ability to predict disease. Conclusion: By integrated bioinformatic analysis, the DEGs and hub genes identified in this study elucidated the molecular mechanism of the pathogenesis and progression of cSCC, and are expected to become future biomarkers or therapeutic targets.

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Screening and Identification of Potential Biomarkers Associated with Cutaneous Squamous Cell Carcinoma

10.21203/rs.3.rs-823635/v1 ◽

2021 ◽

Author(s):

Wenxing Su ◽

Biao Huang ◽

Qingyi Zhang ◽

Wei Han ◽

Lu An ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Bioinformatic Analysis ◽

Cutaneous Squamous Cell Carcinoma ◽

Functional Enrichment ◽

Hub Genes

Abstract Cutaneous squamous cell carcinoma (cSCC) is the leading cause of death in patients with non-melanoma skin cancers (NMSC). However, unclear pathogenesis of cSCC limits the application of molecular targeted therapy. We downloaded three microarray data (GSE2503, GSE45164 and GSE66359) from Gene Expression Omnibus (GEO) and screened out their common difference genes between tumor and non-tumor tissues. Functional enrichment analysis was performed using DAVID. The STRING online website was used to construct a protein-protein interaction network (PPI), and then Cytoscape performed module analysis and degree calculation.A total of 146 DEGs was identified with significant differences, including 113 up-regulated genes and 33 down-regulated genes. The enriched functions and pathways of the DEGs include microtubule-based movement, ATP binding, cell cycle, p53 signaling pathway, oocyte meiosis and PLK1 signaling events. Nine hub genes were identified, namely CDK1, AURKA, RRM2, CENPE, CCNB1, KIAA0101, ZWINT, TOP2A, ASPM. The differential expression of these genes has been verified in other data sets. By integrated bioinformatic analysis, the hub genes identified in this study elucidated the molecular mechanism of the pathogenesis and progression of cSCC, and are expected to become future biomarkers or therapeutic targets.

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Mine TCGA Database for Tumor Microenvironment-Related Genes of Prognostic value in lung squamous cell carcinoma

10.21203/rs.3.rs-28076/v1 ◽

2020 ◽

Author(s):

Xiao Chen ◽

Rui Li ◽

Yun-Hong Yin ◽

Xiao Liu ◽

Xi-Jia Zhou ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Tumor Microenvironment ◽

Cell Carcinoma ◽

Squamous Cell ◽

Immune Cells ◽

Lung Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Hub Genes

Abstract Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.

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Bioinformatics-based analysis of the lncRNA–miRNA–mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma

Bioscience Reports ◽

10.1042/bsr20201727 ◽

2020 ◽

Vol 40 (8) ◽

Author(s):

Zhimin Ye ◽

Jun Fang ◽

Zhun Wang ◽

Lei Wang ◽

Bin Li ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Regulatory Networks ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Diagnostic Efficiency ◽

Hub Genes

Abstract Esophageal squamous cell carcinoma (ESCC) is a 5-year survival rate unsatisfied malignancies. The study aimed to identify the novel diagnostic and prognostic targets for ESCC. Expression profiling (GSE89102, GSE97051, and GSE59973) data were downloaded from the GEO database. Then, differentially expressed (DE) lncRNAs, DEmiRNAs, and genes (DEGs) with P-values < 0.05, and |log2FC| ≥ 2, were identified using GEO2R. Functional enrichment analysis of miRNA-related mRNAs and lncRNA co-expressed mRNA was performed. LncRNA–miRNA–mRNA, protein–protein interaction of miRNA-related mRNAs and DEGs, co-expression, and transcription factors-hub genes network were constructed. The transcriptional data, the diagnostic and prognostic value of hub genes were estimated with ONCOMINE, receiver operating characteristic (ROC) analyses, and Kaplan–Meier plotter, respectively. Also, the expressions of hub genes were assessed through qPCR and Western blot assays. The CDK1, VEGFA, PRDM10, RUNX1, CDK6, HSP90AA1, MYC, EGR1, and SOX2 used as hub genes. And among them, PRDM10, RUNX1, and CDK6 predicted worse overall survival (OS) in ESCC patients. Our results showed that the hub genes were significantly up-regulated in ESCA primary tumor tissues and cell lines, and exhibited excellent diagnostic efficiency. These results suggest that the hub genes may server as potential targets for the diagnosis and treatment of ESCC.

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Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586v1 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

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Significance of mucin type glucosaminyl (N-acetyl) transferase 3 expression in lung squamous cell carcinoma

10.21203/rs.3.rs-142867/v1 ◽

2021 ◽

Author(s):

Yu-Jun Chen ◽

Li Gao ◽

Rui Zhang ◽

Gang Chen ◽

Zhen-bo Feng ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Methylation Level ◽

Lung Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Progression Free Survival ◽

Genetic Mutation ◽

Functional Enrichment ◽

Standard Mean Difference

Abstract Background: The clinical significance and role of glycan synthase glucosamine (N-acetyl) transferase 3 (GCNT3) has not been investigated in lung squamous cell carcinoma (LUSC).Materials & Methods: In the present study, multiple detection technologies including tissue microarrays, external microarrays and RNA-seq were adopted for evaluating the clinic-pathological significance of GCNT3 in 1632 LUSC samples and 1478 non-cancer samples. Standard mean difference and hazard ratio value were calculated from all included datasets for assessing differential expression and prognostic value of GCNT3 in LUSC. The molecular basis underlying GCNT3 in LUSC was also explored through methylation level, genetic mutation and functional enrichment analysis of GCNT3-correlated genes in LUSC. Results: GCNT3 was obviously upregulated in LUSC samples. GCNT3 overexpression exerted unfavorable impact on the progression-free survival and overall survival of LUSC patients from GSE29013. The mRNA expression of GCNT3 was negatively correlated with methylation level of GCNT3 in LUSC and the predominant type of genetic alteration for GCNT3 in LUSC was mRNA high. Genes correlated with GCNT3 in LUSC mainly assembled in pathways such as adherens junction, p53 signaling pathway, protein digestion and absorption pathway. Conclusions: In conclusion, overexpressed GCNT3 had clinical potential as therapeutic target for LUSC.

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Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

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Identification of novel prognostic biomarkers in head and neck squamous cell carcinoma using bioinformatics analysis

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323666201027120855 ◽

2020 ◽

Vol 23 ◽

Author(s):

Yi Ding ◽

Min Li ◽

Tuersong Tayier ◽

Long Chen ◽

ShuMei Feng

Keyword(s):

Cell Cycle ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Interaction Network ◽

Tumor Grade ◽

Neck Squamous Cell Carcinoma ◽

Hub Genes ◽

Key Genes

Background: : Head and neck squamous cell carcinoma (HNSCC) is a common cancer that is characterized by a complex pathogenesis. Only limited data are available on the primary pathogenic genes and pathways in HNSCC. Objective: This study aimed to identify potential biomarkers of HNSCC and explore its underlying mechanisms. Methods: We screened differentially expressed genes (DEGs) using the Gene Expression Omnibus(GEO) database. Gene Ontology (GO) and Reactome pathway enrichment were analyzed using the STRING database. The protein-protein interaction network of the DEGs was reconstructed using Cytoscape software in STRING. The ONCOMINE and UNLCAN databases were used to identify the expression of hub genes. In addition, we employed UNLCAN to correlate tumor grade with key genes. Results: Finally, the effect of hub genes on overall survival (OS) was analyzed using the Kaplan-Meier method. In total, 22 DEGs were identified, These were related to the mitotic cell cycle, mitotic G1-G1, and S phases, G2/M transition, NOTCH signaling, and regulation of TP53 activity. Seven hub genes were screened with Cytoscape. Increased expression of five hub genes (AURKA, BIRC5, MKI67, UBE2C, and TOP2A) was related to a higher tumor grade and worse OS. Conclusion: We have identified five key genes that may help us understand the carcinogenic mechanisms related to the cell cycle in HNSCC. These genes may be used as biomarkers for survival and treatment of HNSCC.

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Differences in Gene Expression Between High- and Low-Grade Serous Ovarian Cancers: Implications for Diagnosis and Prognosis

10.21203/rs.3.rs-963632/v1 ◽

2021 ◽

Author(s):

Jianhao Xu ◽

Qian Wang ◽

Fang Cao ◽

Zhiyong Deng ◽

Xiaojiao Gao ◽

...

Keyword(s):

Ovarian Cancer ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Low Grade ◽

Serous Ovarian Cancer ◽

Hub Genes ◽

Diagnosis And Prognosis ◽

Potential Marker

Abstract Background The clinical presentations of high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC) differ. In this study, we aimed to identify the essential molecules for the diagnosis and prognosis of these OC subtypes. Methods Differentially expressed genes (DEGs) between HGSOC and LGSOC were identified using three GEO series. The functional enrichment analysis was performed to investigate different biological processes and pathways. The protein–protein interaction network was constructed, and hub genes were screened to narrow the focus of the study. The discovered hub genes were frequently validated using prognostic correlation, co-expression, and immunohistochemistry (IHC) in GTEx, Oncomine, GEPIA, cBioportal, HPA, and other databases. Results In comparison with LGSOC, 79 upregulated genes and 85 downregulated genes were identified in HGSOC, and the biological roles of these genes were mostly centered on the cell cycle process and chromosomal segregation. Among the 10 hub genes chosen, BIRC5 was favorably linked with overall survival of patients with ovarian cancer (p = 0.014), whereas RRM2 was negatively correlated with the ovarian cancer stage (p = 0.0251). In IHC studies, the intensity of BIRC5 expression in ovarian cancer was greater than that in normal ovarian tissues; however, RRM2 was not substantially expressed in either ovarian cancer tissues or normal ovarian tissues. Conclusions BIRC5 is a potential marker that can distinguish HGSOC from LGSOC, guide prognosis, and be utilized in clinical IHC.

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Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

BMC Medical Genomics ◽

10.1186/s12920-021-00928-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Mingdi Liu ◽

Faping Li ◽

Bin Liu ◽

Yongping Jian ◽

Dan Zhang ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

High Risk ◽

Tumor Microenvironment ◽

Cell Carcinoma ◽

Squamous Cell ◽

Risk Model ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment

Abstract Background As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC). Methods ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. Conclusions Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

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Identification of Differential Methylation Regions and Correspondence Targeted Genes in Oral Squamous Cell Carcinoma

10.21203/rs.3.rs-27701/v1 ◽

2020 ◽

Author(s):

Yan Niu ◽

Qiusheng Shan ◽

Yuanling Guo

Keyword(s):

Squamous Cell Carcinoma ◽

Oral Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Biological Process ◽

Enrichment Analysis ◽

Differential Methylation ◽

Differentially Expressed ◽

Hub Genes ◽

R Software

Abstract Background The differential methylation included hypermethylation and hypomethylation plays significant role in the progression of many kind of cancers but study little in oral squamous cell carcinoma (OSCC). Methods GSE123781 and GSE87053 was used to analysis the differential methylation regions (DMRs) and predict the target genes in OSCC by R software and wANNOVAR respectively. the biological process and cell pathways of common targeted genes between GSE123781 and GSE87053 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis. The hub genes (hub genes 1) in common targeted genes associated with cancer biological process was identified by protein to protein interaction network (PPI). In addition, GSE74530 and GSE30784 was used to identify common differentially expressed genes (DEGs) in OSCC by R software. The biological process and cell pathways of common DEGs was analyzed by GO and KEGG enrichment analysis. The hub genes (hub genes 2) in common DEGs associated with cancer biological process was identified by PPI network. The significant hub genes between hub genes 1 and hub genes 2 were identified by Venn picture. Finally, the expression level of significant hub genes and correspondence relationship with head and neck squamous cell carcinoma (HNSCC) patient survival were confirmed by The Cancer Genome Atlas (TCGA) dataset. Results There are 2146 common targeted genes regulated by DMRs between GSE123781 and GSE87053 and 278 hub genes in common targeted genes associated with cancer biological process. In addition, there are 895 common DEGs between GSE74530 and GSE30784 and 144 hub genes in common DEGs associated with cancer biological process. There are 9 significant hub genes between hub genes 1 and hub genes 2. Finally, these 9 significant hub genes differentially expressed in HNSCC tissues except CCR7 and quite associated with the survival of HNSCC patients. Conclusions CCR7, ETS1, RUNX3, CCR1, C3AR1, LAMB1, IRF7, LGALS3 and CDKN3 both are DEGs and regulated by DMRs in OSCC, which are quite associated with the progression of OSCC and the survival of HNSCC patients. All of these genes have much potential to be new biomarkers in targeted therapy of OSCC.

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