Bioinformatics analysis of key genes and latent pathway interactions based on the anaplastic thyroid carcinoma gene expression profile

NF-κB in Thyroid Cancer: An Update

The dysregulated NF-κB basal activity is a common feature of human thyroid carcinomas, especially in poorly differentiated or undifferentiated forms that, even if rare, are often resistant to standard therapies, and, therefore, are uncurable. Despite the molecular mechanisms leading to NF-κB activation in thyroid cancer being only partially understood, during the last few years, it has become clear that NF-κB contributes in different ways to the oncogenic potential of thyroid neoplastic cells. Indeed, it enhances their proliferation and viability, promotes their migration to and colonization of distant organs, and fuels their microenvironment. In addition, NF-κB signaling plays an important role in cancer stem cells from more aggressive thyroid carcinomas. Interfering with the different upstream and/or downstream pathways that drive NF-κB activity in thyroid neoplastic cells is an attractive strategy for the development of novel therapeutic drugs capable of overcoming the therapy resistance of advanced thyroid carcinomas. This review focuses on the recent findings about the key functions of NF-κB in thyroid cancer and discusses the potential implications of targeting NF-κB in advanced thyroid carcinomas.

Selected using bioinformatics and molecular docking analyses, PHA-793887 is effective against osteosarcoma

To identify novel prognostic and therapeutic targets for osteosarcoma patients, we compared the gene expression profiles of osteosarcoma and control tissues from the GSE42352 dataset in the Gene Expression Omnibus. Differentially expressed genes were subjected to Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment and protein-protein interaction network analyses. Survival curve analyses indicated that osteosarcoma patients with lower mRNA levels of cyclin-dependent kinase 1 (CDK1) and topoisomerase II alpha had better prognoses. Various computer-aided techniques were used to identify potential CDK1 inhibitors for osteosarcoma patients, and PHA-793887 was predicted to be a safe drug with a high binding affinity for CDK1. In vitro, MTT and colony formation assays demonstrated that PHA-793887 reduced the viability and clonogenicity of osteosarcoma cells, while a scratch assay suggested that PHA-793887 impaired the migration of these cells. Flow cytometry experiments revealed that PHA-793887 dose-dependently induced apoptosis in osteosarcoma cells. Western blotting and enzyme-linked immunosorbent assays indicated that CDK1 expression in osteosarcoma cells declined with increasing PHA-793887 concentrations. These results suggest that PHA-793887 could be a promising new treatment for osteosarcoma.

Identification of the EMT-Related Genes Signature for Predicting Occurrence and Progression in Thyroid Cancer

BACKGROUND

The detection rate of thyroid cancer (TC) has been continuously improved due to the development of detection technology. Epithelial-mesenchymal transition (EMT) is thought to be closely related to the malignant progression of tumors. However, the relationship between EMT-related genes (ERGs) characteristics and the diagnosis and prognosis of TC patients has not been studied.

METHODS

Four datasets from Gene Expression Omnibus (GEO) were used to perform transcriptomic profile analysis. The overlapping differentially expressed ERGs (DEERGs) were analyzed using the R package "limma". Then, the hub genes, which had a higher degree, were identified by the protein-protein interaction (PPI) network. Gene expression analysis between the TC and normal data, the disease-free survival (DFS) analysis of TC patients from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort, function analysis, and immunohistochemistry (IHC) were performed to verify the importance of the hub genes. Finally, a prognostic risk scoring was constructed to predict DFS in patients with the selected genes.

RESULTS

A total of 43 DEERGs were identified and 10 DEERGs were considered hub ERGs, which had a high degree of connectivity in the PPI network. Then, the differential expressions of FN1, ITGA2, and KIT between TC and normal tissues were verified in the TCGA-THCA cohort and their protein expressions were also verified by IHC. DFS analysis indicated upregulations of FN1 expression (P<0.01) and ITGA2 expression (P<0.01) and downregulation of KIT expression (P=0.01) increased risks of decreased DFS for TCGA-THCA patients. Besides, by building a prognostic risk scoring model, we found that the DFS of TCGA-THCA patients was significantly worse in high-risk groups.

CONCLUSION

In summary, these hub ERGs were potential biomarkers for diagnosis and prognosis of TC, which can provide a basis for further exploring the efficacy of EMT in patients with TC.

Identification of a Six Gene Prognosis Signature for Papillary Thyroid Cancer Using Multi-Omics Methods and Bioinformatics Analysis

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer. PTC is typically curable with an excellent survival rate; however, some patients experience disease recurrence or death. This study aimed to discover potential key genes and signaling pathways of PTC, which could provide new insights for thyroid lesions. Four GEO microarray datasets were integrated to screen for candidate genes involved in PTC progression. A total of 164 upregulated and 168 downregulated differentially expressed genes (DEGs) were screened. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes were used in pathway enrichment analyses for DEGs. A protein-protein interaction network was then built and analyzed utilizing STRING and Cytoscape, followed by the identification of 13 hub genes by cytoHubba. CDH3, CTGF, CYR61, OGN, FGF13, and CHRDL1 were selected through survival analyses. Furthermore, immune infiltration, mutations and methylation analysis indicated that these six hub genes played vital roles in immune surveillance and tumor progression. ROC and K-M plots showed that these genes had good prognostic values for PTC which was validated by TCGA dataset. Finally, GSEA for a single hub gene revealed that each candidate hub gene had close associations with PTC development. These findings provided new insights into PTC pathogenesis and identified six candidate gene prognosis signature for PTC.

TMEM158 May Serve as a Diagnostic Biomarker for Anaplastic Thyroid Carcinoma: An Integrated Bioinformatic Analysis

Anaplastic thyroid carcinoma (ATC) is a rare but extremely lethal malignancy. However, little is known about the pathogenesis of ATC. Given its high mortality, it is critical to improve our understanding of ATC pathogenesis and to find new diagnostic biomarkers. In the present study, two gene microarray profiles (GSE53072 and GSE65144), which included 17 ATC and 17 adjacent non-tumorous tissues, were obtained. Bioinformatic analyses were then performed. Immunohistochemistry (IHC) and receiver operating characteristic (ROC) curves were then used to detect transmembrane protein 158 (TMEM158) expression and to assess diagnostic sensitivity. A total of 372 differentially expressed genes (DEGs) were identified. Through protein-protein interaction (PPI) analysis, we identified a significant module with 37 upregulated genes. Most of the genes in this module were related to cell-cycle processes. After co-expression analysis, 132 hub genes were selected for further study. Nine genes were identified as both DEGs and genes of interest in the weighted gene co-expression network analysis (WGCNA). IHC and ROC curves confirmed that TMEM158 was overexpressed in ATC tissue as compared with other types of thyroid cancer and normal tissue samples. We identified 8 KEGG pathways that were associated with high expression of TMEM158, including aminoacyl-tRNA biosynthesis and DNA replication. Our results suggest that TMEM158 may be a potential oncogene and serve as a diagnostic indicator for ATC.

Identifying 8-mRNAsi Based Signature for Predicting Survival in Patients With Head and Neck Squamous Cell Carcinoma via Machine Learning

Cancer stem cells (CSCs) have been characterized by several exclusive features that include differentiation, self-renew, and homeostatic control, which allows tumor maintenance and spread. Recurrence and therapeutic resistance of head and neck squamous cell carcinomas (HNSCC) have been identified to be attributed to CSCs. However, the biomarkers led to the development of HNSCC stem cells remain less defined. In this study, we quantified cancer stemness by mRNA expression-based stemness index (mRNAsi), and found that mRNAsi indices were higher in HNSCC tissues than that in normal tissue. A significantly higher mRNAsi was observed in HPV positive patients than HPV negative patients, as well as in male patients than in female patients. The 8-mRNAsi signature was identified from the genes in two modules which were mostly related to mRNAsi screened by weighted gene co-expression network analysis. In this prognostic signatures, high expression of RGS16, LYVE1, hnRNPC, ANP32A, and AIMP1 focus in promoting cell proliferation and tumor progression. While ZNF66, PIK3R3, and MAP2K7 are associated with a low risk of death. The riskscore of eight signatures have a powerful capacity for 1-, 3-, 5-year of overall survival prediction (5-year AUC 0.77, 95% CI 0.69-0.85). These findings based on stemness indices may provide a novel understanding of target therapy for suppressing HNSCC stem cells.

TPX2 Promotes Metastasis and Serves as a Marker of Poor Prognosis in Non-Small Cell Lung Cancer

BACKGROUND Metastasis contributes to the high mortality rate of non-small cell lung cancer (NSCLC), and gaining a better understanding of its metastatic mechanisms would aid in initiating effective clinical treatment. MATERIAL AND METHODS In this study, bioinformatics analyses of the GEO database and TCGA-LUAD were first used to identify the key node gene regulating NSCLC malignant progression. Further in vitro experiments, including wound healing assay, invasion assay, Western blot assay, and luciferase report assay, were used to clarify the functions and mechanism of TPX2 in NSCLC. RESULTS Results of the TCGA analysis showed that TPX2 was significantly positively correlated with tumor metastasis and growth and the clinical stage of NSCLC. In addition, high levels of TPX2 significantly indicated a poor survival rate. In vitro experimental results also revealed that the upregulation of TPX2 significantly promoted NSCLC cell migration and invasion and could affect cell replasticity. Further results indicated that TPX2 significantly activated the epithelial-mesenchymal transition process and promoted the expression and activities of matrix metalloproteinase (MMP)2 and MMP9. CONCLUSIONS This study demonstrated that TPX2 promotes the metastasis and malignant progression of NSCLC and could thus serve as a marker of poor prognosis in NSCLC.

Transcriptome Analysis Reveals the Tolerance Mechanism of Mantis Shrimp (Oratosquilla oratoria) under a Lipopolysaccharide Challenge

Lipopolysaccharide (LPS), a major cell wall component of Gram-negative bacteria, is considered to lead to some disease development in commercial crustaceans. However, mantis shrimps Oratosquilla oratoria (Crustacea: Stomatopoda) have a strong vitality and ability to resist disease. To study the tolerance mechanism of mantis shrimp, transcriptome analyses were conducted in hepatopancreas of O. oratoria under LPS challenge investigation. Totally, 84 547 044 clean reads were obtained from transcriptomes (43 159 230 in OP (control), 41 387 814 in OL (treatment), respectively). Unigenes, the longest transcript of each gene, with a total length of 68 318 880 bp and the total number of 100 978 were obtained. 8369 (8.28%) of unigenes were successfully annotated in all databases and 54 888 (54.35%) were annotated in at least one database. Finally, 1012 differentially expressed genes (DEGs) including 439 and 573 showed significantly upregulated and downregulated were determined between OL and OP, respectively. Moreover, those DEGs only expressed in OL or OP accounted for 8.99%. The functional classification based on GO and KEGG indicated that the common enrichment categories for the DEGs are "amino sugar metabolic" and "cellular homeostasis" and that the progress of nutrient metabolic and homeostasis in cells is important in facing variable environmental conditions. Protein-protein interaction analysis elucidated proteins, β-actin (ACTB_G1), T-complex protein subunits (TCPs), heat shock proteins (HSPs), hydroxysteroid dehydrogenase-like protein 2 (HSDL2), kinesin family member 5 (KIF5), methylglutaconyl-CoA hydratase (AUH), and myosin heavy chain (MYH) may play key roles in response to an LPS challenge. This study laid a foundation to further investigate the possible adaptation way that O. oratoria survives in a bacterial challenge.

The clinical significance and potential molecular mechanism of integrin subunit beta 4 in laryngeal squamous cell carcinoma

The relationship between integrin beta 4 (ITGB4) expression and laryngeal squamous cell carcinoma (LSCC) remains unclarified. The object of the present study was to explore the clinical significance and potential molecular mechanism of ITGB4 in LSCC. The protein level of ITGB4 was significantly higher in 46 LSCC patients than in 26 non-LSCC tissues detected by in-house immunohistochemistry. Consistently, ITGB4 mRNA level was also greatly upregulated based on microarray and RNA-seq data (standard mean difference, SMD = 1.62, 95 % CI: 1.23-2.00). And the area under curves (AUC) of summary receiver operator characteristic (SROC) was 0.87 (95 % CI: 0.84-0.90) based on 172 cases of LSCC and 59 cases of non-cancerous controls. Ninety genes were intersected by the ITGB4 related genes and LSCC differential expressed genes (DEGs) from all available microarray and RNA-seq datasets. Based on Gene Ontology (GO) analysis, the top terms of biological process (BP), cellular component (CC) and molecular function (MF) for the 90 ITGB4 related DEGs were extracellular matrix organization, basement membrane and extracellular matrix structural constituent, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that ITGB4 related DEGs mainly participated in the pathways of ECM-receptor interaction, Focal adhesion and Small cell lung cancer. Moreover, the Protein-Protein Interaction (PPI) network indicated that ITGA3, ITGA5, ITGB4, MET, LAMA3, and COL4A1 might be the core genes of LSCC development related to ITGB4. In conclusion, high ITGB4 expression may lead to the occurrence and development of LSCC via various signaling pathways.

Proteomics analysis of intensive exercise-induced disorders of gametogenesis in the testis using isobaric tags for relative and absolute quantification (iTRAQ) analysis

In the present study we screened a panel of regulatory proteins associated with gametogenesis disorders in the testis that are induced by intensive exercise. Four-week-old Sprague-Dawley male rats were randomly divided into three groups: a control group, a no-load exercise group and an intensive exercise group. Rats in the control group were free to move in their cage. Rats in the no-load exercise and intensive exercise groups swam for 60minday-1, six times each week, for a total 9-week exercise regimen; rats in the intensive exercise group swam with a load of 6% body mass. After the last exercise session (or at the end of the 9-week period), a sperm count, reproductive hormone assays, histological analysis of the testis and proteomics analysis were performed for each rat. Mean (±s.d.) sperm concentration was significantly lower in the intensive exercise group than in the control and no-load exercise groups (1.36±0.63 vs 2.12±0.53 and 2.57±0.48×106 spermatozoa mL-1 respectively; P<0.05). Serum testosterone concentrations were also significantly lower in the intensive exercise group (P<0.01), whereas gonadotrophin-releasing hormone, LH and FSH concentrations were slightly decreased in the intensive exercise group, but not significantly (P>0.05). Histological analysis showed that the number of spermatogenic cells in the seminiferous tubules was lower in the intensive exercise group than in the control and no-load exercise groups. Proteomics analysis identified 54 proteins that were differentially expressed between the control and intensive exercise groups (31 downregulated, 23 upregulated). Pathway enrichment analysis showed that ribosome and extracellular matrix-receptor interaction pathways play an important role in the signal transduction of testicular gametogenic disorders. Four differentially expressed proteins that were involved in the regulation of reproduction were identified by bioinformatics analysis and validated by targeted mass spectrometry analysis, namely vimentin, collagen α-1(I) chain, fatty acid-binding protein 9 and 40S ribosomal protein S3a. The data suggest that changes in the abundance of differentially expressed proteins after long-term intensive exercise affect the cycle and progression of spermatogenesis, resulting in spermatogenic disorders.

Effects of resveratrol on reducing spermatogenic dysfunction caused by high-intensity exercise

BACKGROUND

Long-term high-intensity exercise can lead to reproductive endocrine and spermatogenic dysfunction. This research is to investigate the effect of resveratrol on the reduction of reproductive dysfunction induced by high-intensity exercise, and to screen relevant factors and signal transduction pathways.

METHODS

Rats were randomly divided into three groups, a control group, an intensive exercise group (IE group), and a resveratrol-treated group (RSV group). After 9 weeks of exercise, the sperm density and reproductive hormone concentrations were measured, along with antioxidation, inflammatory cytokine production, and histological analyses performed for each group. In addition, a proteomics analysis of the IE group and RSV group were conducted.

RESULTS

We found that compared with the control group, the average sperm density (P < 0.05) and testosterone concentration (P < 0.05) in the IE group decreased significantly. Additionally, in testis tissue the concentration of the inflammatory cytokines IL-6 (P < 0.01) and TNF-α (P < 0.01) increased significantly. Also, a significant decrease in superoxide dismutase (SOD) activity (P < 0.01) and a significant increase in the malondialdehyde (MDA) concentration (P < 0.01) were noted. In the RSV group, the average sperm density (P < 0.01), testosterone (P < 0.01) and follicle stimulating hormone (FSH) levels (P < 0.01) all increased in comparison to the IE group, and the concentration of IL-6 (P < 0.01) and TNF-α (P < 0.01) were found to be significantly decreased. Compared with the IE group, the SOD activity in the RSV group was significantly increased (P < 0.01), while the MDA content decreased (P < 0.01). Furthermore, histological analysis showed that the number of spermatogenic epithelial cells in the RSV group was higher than that of the IE group. There were a number of spermatogenic regulatory proteins identified in the proteomics analysis, including Clusterin, Piwi like homolog 1 (Piwil1), Zona pellucida binding protein (Zpbp), Heat shock-related 70 kDa protein 2 (Hspa2), Centrin 1, and Bardet-Biedl syndrome 2 protein (Bbs2). It was found that the proteins that differed between the two groups were mainly involved in pathways such as complement and coagulation cascades, the extracellular matrix-receptor interactions, etc. CONCLUSIONS: The present study demonstrates that after high-intensity exercise, the inflammatory cascade in the tissue of the testis increases with decreased resistance to oxidation and disordered spermatogenic function. Resveratrol can improve the reproductive dysfunction of rats that was induced by high-intensity exercise. It mostly promotes reproductive function by increasing testosterone secretion, reducing the inflammatory response, improving the antioxidant capacity, affecting the expression of spermatogenic regulatory proteins, and enhancing the signal transduction pathway of spermatogenesis.

CCL28 Is Involved in Mucosal IgA Responses, Olfaction, and Resistance to Enteric Infections

CCL28 is a mucosal chemokine that has been involved in various responses, including IgA production. We have analyzed its production in human tissues using a comprehensive microarray database. Its highest expression is in the salivary gland, indicating that it is an important component of saliva. It is also expressed in the trachea, bronchus, and in the mammary gland upon onset of lactation. We have also characterized a Ccl28-/- mouse that exhibits very low IgA levels in milk, and the IgA levels in feces are also reduced. These observations confirm a role for the CCL28/CCR10 chemokine axis in the recruitment of IgA plasmablasts to the lactating mammary gland. CCL28 is also expressed in the vomeronasal organ. We also detected olfactory defects (anosmia) in a Ccl28-/- mouse suggesting that CCL28 is involved in the function/development of olfaction. Importantly, Ccl28-/- mice are highly susceptible to Salmonella enterica serovar Typhimurium in an acute model of infection, indicating that CCL28 plays a major role in innate immunity against Salmonella in the gut. Finally, microbiome studies revealed modest differences in the gut microbiota between Ccl28-/- mice and their cohoused wild-type littermates. The latter observation suggests that under homeostatic conditions, CCL28 plays a limited role in shaping the gut microbiome.

Integrated Bioinformatics Analysis of Hub Genes and Pathways in Anaplastic Thyroid Carcinomas

Anaplastic thyroid carcinoma (ATC) is a very rare malignancy; the pathogenesis of which is still not fully understood. The aim of the present study was to identify hub genes and pathways in ATC by microarray expression profiling. Two independent datasets (GSE27155 and GSE53072) were downloaded from GEO database. The differentially expressed genes (DEGs) between ATC tissues and normal thyroid tissues were screened out by the limma package and then enriched by gene ontology (GO) and KEGG pathway analysis. The hub genes were selected by protein-protein interaction (PPI) analysis. A total of 141 common upregulated and 87 common downregulated genes were screened out. These DEGs were significantly enriched in the phagosome and NF-kappa B signaling pathway. Through PPI analysis, TOP2A, TYMS, CCNB1, RACGAP1, FEN1, PRC1, and UBE2C were selected as hub genes, which were highly expressed in ATC tissues. TCGA data suggested that the expression levels of TOP2A, TYMS, FEN1, and PRC1 genes were also upregulated in other histological subtypes of thyroid carcinoma. High expression of TOP2A, TYMS, FEN1, PRC1, or UBE2C gene significantly decreased disease-free survival of patients with other thyroid carcinomas. In conclusion, the present study identified several hub genes and pathways, which will contribute to elucidating the pathogenesis of ATC and providing therapeutic targets for ATC.

Prediction of novel target genes and pathways involved in tall cell variant papillary thyroid carcinoma

BACKGROUND

Tall cell variant papillary thyroid carcinoma (TCPTC) is reportedly associated with aggressive clinicopathological parameters and poor outcomes; however, the molecular mechanisms underlying TCPTC remain poorly understood.

METHODS

The gene mutation types and mRNA expression profiles of patients with TCPTC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified. Pathways in the interaction network and the diagnostic approaches of candidate markers for TCPTC were investigated.

RESULTS

BRAF mutation was particularly prevalent in TCPTC with a mutation frequency of 78%. TCPTC was associated with a patient age >45 years, tumor multifocality, extrathyroidal extension, a higher T stage, advanced AJCC TNM stages, BRAF V600E mutation, and poor disease-free survival. We identified 4138 TCPTC-related DEGs and 301 TCPTC-specific DEGs. Intriguingly, the gene expression pattern revealed that the dysregulated levels of both putative oncogenes and tumor suppressors in TCPTC were higher than those in classical/conventional variant PTC (cPTC). Functional enrichment analyses revealed that these DEGs were involved in several cancer-related pathways. A protein-protein interaction (PPI) network was constructed from the 301 TCPTC-specific DEGs, and 3 subnetworks, and 8 hub genes were verified. Receiver operating characteristic (ROC) analyses revealed that 6 hub genes, including COL5A1, COL1A1, COL10A1, COL11A1, CCL20, and CXCL5, could be used not only for the differential diagnosis of PTC from normal samples, but also for the differential diagnosis of TCPTC from cPTC samples.

CONCLUSIONS

Our study might provide further insights into the investigations of the tumorigenesis mechanism of TCPTC and assists in the discovery of novel candidate diagnostic markers for TCPTC.

Genetic expression profile-based screening of genes and pathways associated with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer; however, the specific genes and signaling pathways involved in this cancer remain largely unclear. The present study analyzed three profile datasets, GSE6004, GSE29265 and GSE60542, which were comprised of 47 PTC and 41 normal thyroid tissue samples, to identify key genes and pathways associated with PTC. Initially, differentially-expressed genes (DEGs) between PTC and normal thyroid tissue were screened using R 3.4.0 (2017-04-21, R Foundation, Vienna, Austria, http://www.R-project.org/). These DEGs were then clustered by gene ontology functional terms and representative signaling pathways. Additionally, specific key gene nodes were filtered out from a constructed protein-protein interaction (PPI) network. The results identified a total of 423 shared DEGs associated with PTC, including 211 upregulated and 212 downregulated genes. These 423 genes were primarily enriched in glycosaminoglycan binding, sulfur compound binding, heparin binding, enzyme activator activity, peptidase activator activity and hsa04512: Extracellular matrix (ECM)-receptor interaction. A total of 21 central node genes were identified as key genes in the PTC disease process including complement factor D (CFD), Collagen Type I α 1 Chain (COL1A1), Extracellular Matrix Protein 1 (ECM1) and Fibronectin 1 (FN1). These genes are involved in protease binding, G-protein coupled receptor binding, extracellular matrix structural constituent and peptidase regulator activity. To conclude, using bioinformatics analysis, the present study identified candidate DEGs and critical pathways in PTC that may improve the current understanding regarding the underlying mechanisms of PTC. These genes and pathways may be used as potential therapeutic targets of PTC in the future.

Fold change based approach for identification of significant network markers in breast, lung and prostate cancer

Cancer belongs to a class of highly aggressive diseases and a leading cause of death in the world. With more than 100 types of cancers, breast, lung and prostate cancer remain to be the most common types. To identify essential network markers (NMs) and therapeutic targets in these cancers, the authors present a novel approach which uses gene expression data from microarray and RNA-seq platforms and utilises the results from this data to evaluate protein-protein interaction (PPI) network. Differentially expressed genes (DEGs) are extracted from microarray data using three different statistical methods in R, to produce a consistent set of genes. Also, DEGs are extracted from RNA-seq data for the same three cancer types. DEG sets found to be common in both platforms are obtained at three fold change (FC) cut-off levels to accurately identify the level of change in expression of these genes in all three cancers. A cancer network is built using PPI data characterising gene sets at log-FC (LFC)>1, LFC>1.5 and LFC>2, and interconnection between principal hub nodes of these networks is observed. Resulting network of hubs at three FC levels highlights prime NMs with high confidence in multiple cancers as validated by Gene Ontology functional enrichment and maximal complete subgraphs from CFinder.

Overexpression of collagen type V α1 chain in human breast invasive ductal carcinoma is mediated by TGF-β1

Collagen type V α1 chain (COL5A1) is a minor fibrillar collagen in mammals that co-polymerizes with type I collagen to adjust the diameter of collagen molecules. However, the function of COL5A1 in invasive ductal carcinoma (IDC) of the human breast remains unknown. In the present study, our group examined the expression of COL5A1 in IDC compared with its adjacent normal tissue and fibroadenoma of the breast. COL5A1 was revealed to be overexpressed in IDC compared with benign tumor and adjacent normal control tissues, and was associated with the expression of estrogen receptor and progesterone receptor. No association between COL5A1 expression and tumor size, lymph node metastasis, clinical stage, age, or Her2 expression was identified. High expression of COL5A1 mRNA was associated with distant metastasis free survival in patients with breast cancer. Knockdown of COL5A1 led to a decrease of cell viability, as detected by the WST-1 assay, and an inhibition of migration and invasion, as detected by wound healing and Transwell assays, respectively, in the breast cancer cell line MCF-7. The expression of COL5A1 in MCF-7 cells was downregulated by transforming growth factor (TGF)‑β1, which was abolished in the presence of SB-431542, an inhibitor of TGF-β type I receptor. In conclusion, these data indicated that COL5A1 is overexpressed in IDC and regulated by TGF-β1, suggesting that an increase of COL5A1 reflects tumor progression and may serve as a novel biomarker and therapeutic target for the treatment of breast IDC.

In silico analysis of the potential mechanism of telocinobufagin on breast cancer MCF-7 cells

BACKGROUNDS AND AIMS

The extractives from a ChanSu, traditional Chinese medicine, have been discovered to possess anti-inflammatory and tumor-suppressing abilities. However, the molecular mechanism of telocinobufagin, a compound extracted from ChanSu, on breast cancer cells has not been clarified. The aim of this study is to investigate the underlying mechanism of telocinobufagin on breast cancer cells.

METHODS AND MATERIALS

The differentially expressed genes after telocinobufagin treatment on breast cancer cells were searched and downloaded from Gene Expression Omnibus (GEO), ArrayExpress and literatures. Bioinformatics tools were applied to further explore the potential mechanism of telocinobufagin in breast cancer using the Kyoto Encyclopedia of genes and genomes (KEGG) pathway, Gene ontology (GO) enrichment, panther, and protein-protein interaction analyses. To better comprehend the role of telocinobufagin in breast cancer, we also queried the Connectivity Map using the gene expression profiles of telocinobufagin treatment.

RESULTS

One GEO accession (GSE85871) provided 1251 differentially expressed genes after telocinobufagin treatment on MCF-7 cells. The pathway of neuroactive ligand-receptor interaction, cell adhesion molecules (CAMs), intestinal immune network for IgA production, hematopoietic cell lineage and calcium signaling pathway were the key pathways from KEGG analysis. IGF1 and KSR1, owning to higher protein levels in breast cancer tissues, IGF1 and KSR1 could be the hub genes related to telocinobufagin treatment. It was indicated that the molecular mechanism of telocinobufagin resembled that of fenspiride.

CONCLUSIONS

Telocinobufagin might regulate neuroactive ligand-receptor interaction pathway to exert its influences in breast cancer MCF-7 cells, and its molecular mechanism might share some similarities with fenspiride. This study only presented a comprehensive picture of the role of telocinobufagin in breast cancer MCF-7 cells using big data. However, more thorough and deeper researches are required to add to the validity of this study.

Identification of common key genes in breast, lung and prostate cancer and exploration of their heterogeneous expression

Cancer is one of the leading causes of mortality worldwide, and in particular, breast cancer in women, prostate cancer in men, and lung cancer in both women and men. The present study aimed to identify a common set of genes which may serve as indicators of important molecular and cellular processes in breast, prostate and lung cancer. Six microarray gene expression profile datasets [GSE45827, GSE48984, GSE19804, GSE10072, GSE55945 and GSE26910 (two datasets for each cancer)] and one RNA-Seq expression dataset (GSE62944 including all three cancer types), were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in each individual cancer type using the LIMMA statistical package in R, and then a comparison of the resulting gene lists was performed to identify common DEGs across cancer types. This analysis was performed for microarray and RNA-Seq datasets individually, revealing a set of 62 and 1,290 differentially expressed genes respectively, which may be associated with the three cancers. Out of these genes, 44 were common to both analyses, and hence termed key genes. Gene Ontology functional annotation, Kyoto Encyclopedia of Genes and Genomes pathway mapping and literature citations were used to confirm the role of the key genes in cancer. Finally, the heterogeneity of expression of the key genes was explored using the I² statistic (meta package in R). The results demonstrated non-heterogeneous expression of 6 out of the 44 key genes, whereas the remaining genes exhibited significant heterogeneity in expression across microarray samples. In conclusion, the identified DEGs may play important roles in the pathogenesis of breast, prostate and lung cancer and may be used as biomarkers for the development of novel diagnostic and therapeutic strategies.

Identification of Driver Genes and Key Pathways of Glioblastoma Shows JNJ-7706621 as a Novel Antiglioblastoma Drug

OBJECTIVE

The aim of this study is to identify novel targets of diagnosis, therapy, and prognosis for glioblastoma, as well as to verify the therapeutic effect of JNJ-7706621 regarding glioblastoma.

METHODS

The gene expression profiles of GSE42656, GSE50161, and GSE86574 were obtained respectively from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified with comparison between gene expression profiles of the glioblastoma tissues and normal tissues. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network analyses were performed. Quantitative reverse transcription polymerase chain reaction and survival curve analysis were also conducted to verify the correlation between expression of hub genes and prognosis. Moreover, in vitro, MTT assay, colony-forming assay, the scratch assay, and flow cytometry were performed to verify the therapeutic effect of JNJ-7706621.

RESULTS

AURKA, NDC80, KIF4A, and NUSAP1 were identified as hub genes after PPI network analysis. Differential expression of those genes was detected between human normal glial cells and glioblastoma cells by quantitative reverse transcription polymerase chain reaction (P < 0.05), and the survival curve analysis showed that the patients with low expression of gene AURKA, NDC80, KIF4A, and NUSAP1 had a significant favorable prognosis (P < 0.05). In vitro assays showed that JNJ-7706621 inhibited glioblastoma cellular viability, proliferation, and migration via inducing glioblastoma cells apoptosis.

CONCLUSIONS

AURKA, NDC80, KIF4A, and NUSAP1 were significantly more highly expressed in glioblastoma cells than in human normal glial cell. Patients with low expression of those 4 genes had a favorable prognosis. JNJ-7706621 was a potential drug in treatment of patients with glioblastoma.

Identification of Driver Genes and Key Pathways of Pediatric Brain Tumors and Comparison of Molecular Pathogenesis Based on Pathologic Types

OBJECTIVE

This study is to identify pediatric brain tumors (PBT) driver genes and key pathways to detect the expression of the driver genes and also to clarify the relationship between patients' prognosis and expression of driver genes.

METHODS

The gene expression profile of GSE50161 was analyzed to identify the differentially expressed genes (DEGs) between tumor tissue and the normal tissue. Gene ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and protein-protein interaction network analysis were conducted to identify the enrichment functions, pathways, and hub genes. After hub genes were identified, quantitative reverse transcription polymerase chain reaction was used to confirm the differential expression of these hub genes. Survival data of 325 patients' were analyzed to clarify the relationship between prognosis and expression levels of the mutual hub genes.

RESULTS

Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that there were 13 common functions and 3 common pathways which were upregulated or downregulated among the 4 groups. Mutual hub genes were somatostatin (SST), glutamate decarboxylase 2 (GAD2), and single copy human parvalbumin gene (PVALB). The expression of SST, GAD2, and PVALB in glioma cells significantly decreased compared with normal glial cells (P < 0.05). In addition, survival analysis showed a favorable progression-free and overall survival in patients with glioma with SST, GAD2, and PVALB high expression (P < 0.05).

CONCLUSIONS

SST, GAD2, and PVALB significantly decrease in glioma cells compared with normal glial cells. Survival analysis suggests that patients with high-expressed SST, GAD2, and PVALB have a longer overall and progression-free survival. The differential expressed genes identified in this study provide novel targets for diagnosis and treatment.