Screening of hub genes and pathways in colorectal cancer with microarray technology

Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis

BACKGROUND

Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.

METHODS

The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency of Hub gene mutations, and the effects of mutation on the patients' prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes.

RESULTS

We identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle.

CONCLUSION

Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks

OBJECTIVE

This study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA.

METHODS

Microarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA.

RESULTS

The 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions.

CONCLUSION

The findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.

Exploring the molecular underpinning of psoriasis and its associated comorbidities through network approach: cross talks of genes and pathways

Patients with psoriasis often complain of several linked disorders including autoimmune and cardiometabolic diseases. Understanding of molecular link between psoriasis and associated comorbidities would be of great interest at the point of patient care management. Integrative unbiased network approach, indicates significant unidirectional gene overlap between psoriasis and its associated comorbid condition including obesity (31 upregulated and 26 downregulated), ischemic stroke (14 upregulated and 2 downregulated), dyslipidaemia (5 upregulated, 5 downregulated), atherosclerosis (8 upregulated and 1 downregulated) and type II diabetes (5 upregulated, 5 downregulated). The analysis revealed substantial gene sharing among the different psoriasis-associated comorbidities. Molecular comorbidity index determining the strength of the interrelation between psoriasis and its comorbidities indicates prevalence of dyslipidaemia followed by type II diabetes among psoriasis patients. The Jaccard coefficient indices revealed psoriasis shared maximum number of biological pathways with dyslipidaemia followed by type 2 diabetes, ischemic stroke, obesity and atherosclerosis. Moreover, pathway annotation highlighted nearly 45 shared pathways amongst psoriasis and its comorbidities and a substantial number of shared pathways was found among multi-morbidities. Overall, the present study established conceivable link between psoriasis and comorbid diseases. The shared genes and overlapped pathways may be explored as a common productive target for psoriasis and its comorbid conditions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03533-y.

Cancer and Alzheimer's Inverse Correlation: an Immunogenetic Analysis

Numerous studies have demonstrated an inverse link between cancer and Alzheimer's disease (AD), with data suggesting that people with Alzheimer's have a decreased risk of cancer and vice versa. Although other studies have investigated mechanisms to explain this relationship, the connection between these two diseases remains largely unexplained. Processes seen in cancer, such as decreased apoptosis and increased cell proliferation, seem to be reversed in AD. Given the need for effective therapeutic strategies for AD, comparisons with cancer could yield valuable insights into the disease process and perhaps result in new treatments. Here, through a review of existing literature, we compared the expressions of genes involved in cell proliferation and apoptosis to establish a genetic basis for the reciprocal association between AD and cancer. We discuss an array of genes involved in the aforementioned processes, their relevance to both diseases, and how changes in those genes produce varying effects in either disease.

Transcriptomic Signatures in Colorectal Cancer Progression

AIMS

Due to a large number of identified hub-genes encoding key molecular regulators, which are involved in signal transduction and metabolic pathways in cancers, it is relevant to systemize and update these findings.

BACKGROUND

Colorectal cancer (CRC) is the third leading cause of cancer death in the world, with high metastatic potential. Elucidating the pathogenic mechanisms and selection of novel biomarkers in CRC is of great clinical significance.

OBJECTIVE

This analytical review aims at the systematization of bioinformatics and experimental identification of hub-genes associated with CRC for a more consolidated understanding of common features in networks and pathways in CRC progression as well as hub-genes selection.

RESULTS

In total, 301 hub-genes were derived from 40 articles. The "core" consisted of 28 hub-genes (CCNB1, LPAR1, BGN, CXCL3, COL1A2, UBE2C, NMU, COL1A1, CXCL2, CXCL11, CDK1, TOP2A, AURKA, SST, CXCL5, MMP3, CCND1, TIMP1, CXCL8, CXCL1, CXCL12, MYC, CCNA2, GCG, GUCA2A, PAICS, PYY and THBS2) mentioned in not less than three articles and having clinical significance in cancerassociated pathways. Of them, there were two discrete clusters enriched in chemokine signaling and cell cycle regulatory genes. High expression levels of BGN and TIMP1 and low expression levels of CCNB1, CXCL3, CXCL2, CXCL2 and PAICS were associated with unfavorable overall survival of patients with CRC. Differently expressed genes such as LPAR1, SST, CXCL12, GUCA2A, and PYY were shown as down regulated, whereas BGN, CXCL3, UBE2C, NMU, CXCL11, CDK1, TOP2A, AURKA, MMP3, CCND1, CXCL1, MYC, CCNA2, PAICS were up regulated genes in CRC. It was also found that MMP3, THBS2, TIMP1 and CXCL12 genes were associated with metastatic CRC. Network analysis in ONCO.IO showed that upstream master regulators RELA, STAT3, SOX2, FOXM1, SMAD3 and NF-kB were connected with "core" hub-genes. Conclusión: Results obtained are of useful fundamental information on revealing the mechanism of pathogenicity, cellular target selection for optimization of therapeutic interventions, as well as transcriptomics prognostic and predictive biomarkers development.

ICAT promotes colorectal cancer metastasis via binding to JUP and activating the NF-κB signaling pathway

Background

The inhibitor of β‐catenin and T‐cell factor (ICAT) is a direct negative regulator of the canonical Wnt signaling pathway, which is an attractive therapeutic target for colorectal cancer (CRC). Accumulating evidence suggests that ICAT interacts with other proteins to exert additional functions, which are not yet fully elucidated.

Methods

The overexpression of ICAT of CRC cells was conducted by lentivirus infection and plasmids transfection and verified by quantitative real‐time reverse transcription‐polymerase chain reaction (real‐time RT‐PCR) and Western blotting. The effect of ICAT on the mobility of CRC cells was assessed by wound healing assay and transwell assay in vitro and lung metastasis in vivo. New candidate ICAT‐interacting proteins were explored and verified using the STRING database, silver staining, co‐immunoprecipitation mass spectrometry analysis (Co‐IP/MS), and immunofluorescence (IF) staining analysis.

Result

Inhibitor of β‐catenin and T‐cell factor overexpression promoted in vitro cell migration and invasion and tumor metastasis in vivo. Co‐IP/MS analysis and STRING database analyses revealed that junction plakoglobin (JUP), a homolog of β‐catenin, was involved in a novel protein interaction with ICAT. Furthermore, JUP downregulation impaired ICAT‐induced migration and invasion of CRC cells. In addition, ICAT overexpression activated the NF‐κB signaling pathway, which led to enhanced CRC cell migration and invasion.

Conclusion

Inhibitor of β‐catenin and T‐cell factor promoted CRC cell migration and invasion by interacting with JUP and the NF‐κB signaling pathway. Thus, ICAT could be considered a protein diagnostic biomarker for predicting the metastatic ability of CRC.

VRK1 Predicts Poor Prognosis and Promotes Bladder Cancer Growth and Metastasis In Vitro and In Vivo

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system with growing morbidity and diagnostic rate in recent years. Therefore, identifying new molecular biomarkers that inhibit the progression of bladder cancer is needed for developing further therapeutics. This study found a new potential treatment target: vaccinia-related kinase 1 (VRK1) and explored the function and mechanism of VRK1 in the development of bladder cancer. First, TCGA database and tissue microarray analysis showed that VRK1 was significantly upregulated in bladder cancer. Kaplan-Meier survival analysis indicates that the OS and PFS of the VRK1 high expression group were significantly lower than the VRK1 low expression group (p = 0.002, p = 0.005). Cox multi-factor analysis results show that VRK1 expression is an independent risk factor affecting tumor progress. The maximum tumor diameter, staging, and adjuvant chemotherapy also have a certain impact on tumor progression (p < 0.05). In internal validation, the column C index is 0.841 (95% CI, 0.803-0.880). In addition, cell functional studies have shown that VRK1 can significantly inhibit the proliferation, migration, and invasiveness of bladder cancer cells. In vivo, nude mice transplanted tumors further prove that low VRK1 can significantly inhibit the proliferation capacity of bladder cancer cells. In summary, VRK1 expression is significantly related to the staging, grade, and poor prognosis of patients with bladder cancer. At the same time, in vivo and in vitro experiments have shown that downregulation of VRK1 can significantly inhibit the proliferation of bladder cancer cells. These findings provide a basis for using VRK1 as a potential therapeutic target for patients with bladder cancer.

A Novel Intercellular Communication-Associated Gene Signature for Prognostic Prediction and Clinical Value in Patients With Lung Adenocarcinoma

Background

Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. This study aimed to identify the key intercellular communication-associated genes (ICAGs) in LUAD.

Methods

Eight publicly available datasets were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The prognosis-related ICAGs were identified and a risk score was developed by using survival analysis. Machine learning models were trained to predict LUAD recurrence based on the selected ICAGs and clinical information. Comprehensive analyses on ICAGs and tumor microenvironment were performed. A single-cell RNA-sequencing dataset was assessed to further elucidate aberrant changes in intercellular communication.

Results

Eight ICAGs with prognostic potential were identified in the present study, and a risk score was derived accordingly. The best machine-learning model to predict relapse was developed based on clinical information and the expression levels of these eight ICAGs. This model achieved a remarkable area under receiver operator characteristic curves of 0.841. Patients were divided into high- and low-risk groups according to their risk scores. DNA replication and cell cycle were significantly enriched by the differentially expressed genes between the high- and the low-risk groups. Infiltrating immune cells, immune functions were significantly related to ICAGs expressions and risk scores. Additionally, the changes of intercellular communication were modeled by analyzing the single-cell sequencing dataset.

Conclusion

The present study identified eight key ICAGs in LUAD, which could contribute to patient stratification and act as novel therapeutic targets.

Novel diagnostic and prognostic biomarkers of colorectal cancer: Capable to overcome the heterogeneity-specific barrier and valid for global applications

INTRODUCTION

The heterogeneity-specific nature of the available colorectal cancer (CRC) biomarkers is significantly contributing to the cancer-associated high mortality rate worldwide. Hence, this study was initiated to investigate a system of novel CRC biomarkers that could commonly be employed to the CRC patients and helpful to overcome the heterogenetic-specific barrier.

METHODS

Initially, CRC-related hub genes were extracted through PubMed based literature mining. A protein-protein interaction (PPI) network of the extracted hub genes was constructed and analyzed to identify few more closely CRC-related hub genes (real hub genes). Later, a comprehensive bioinformatics approach was applied to uncover the diagnostic and prognostic role of the identified real hub genes in CRC patients of various clinicopathological features.

RESULTS

Out of 210 collected hub genes, in total 6 genes (CXCL12, CXCL8, AGT, GNB1, GNG4, and CXCL1) were identified as the real hub genes. We further revealed that all the six real hub genes were significantly dysregulated in colon adenocarcinoma (COAD) patients of various clinicopathological features including different races, cancer stages, genders, age groups, and body weights. Additionally, the dysregulation of real hub genes has shown different abnormal correlations with many other parameters including promoter methylation, overall survival (OS), genetic alterations and copy number variations (CNVs), and CD8+T immune cells level. Finally, we identified a potential miRNA and various chemotherapeutic drugs via miRNA, and real hub genes drug interaction network that could be used in the treatment of CRC by regulating the expression of real hub genes.

CONCLUSION

In conclusion, we have identified six real hub genes as potential biomarkers of CRC patients that could help to overcome the heterogenetic-specific barrier across different clinicopathological features.

A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma

Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

Ultrafine particles altered gut microbial population and metabolic profiles in a sex-specific manner in an obese mouse model

Emerging evidence has highlighted the connection between exposure to air pollution and the increased risk of obesity, metabolic syndrome, and comorbidities. Given the recent interest in studying the effects of ultrafine particle (UFP) on the health of obese individuals, this study examined the effects of gastrointestinal UFP exposure on gut microbial composition and metabolic function using an in vivo murine model of obesity in both sexes. UFPs generated from light-duty diesel engine combustion of petrodiesel (B0) and a petrodiesel/biodiesel fuel blend (80:20 v/v, B20) were administered orally. Multi-omics approaches, including liquid chromatography-mass spectrometry (LC-MS) based targeted metabolomics and 16S rRNA gene sequence analysis, semi-quantitatively compared the effects of 10-day UFP exposures on obese C57B6 mouse gut microbial population, changes in diversity and community function compared to a phosphate buffer solution (PBS) control group. Our results show that sex-specific differences in the gut microbial population in response to UFP exposure can be observed, as UFPs appear to have a differential impact on several bacterial families in males and females. Meanwhile, the alteration of seventy-five metabolites from the gut microbial metabolome varied significantly (ANOVA p < 0.05) across the PBS control, B0, and B20 groups. Multivariate analyses revealed that the fuel-type specific disruption to the microbial metabolome was observed in both sexes, with stronger disruptive effects found in females in comparison to male obese mice. Metabolic signatures of bacterial cellular oxidative stress, such as the decreased concentration of nucleotides and lipids and increased concentrations of carbohydrate, energy, and vitamin metabolites were detected. Furthermore, blood metabolites from the obese mice were differentially affected by the fuel types used to generate the UFPs (B0 vs. B20).

Analysis of the role of Frizzled 2 in different cancer types

Frizzled 2 (FZD2) is an important receptor in the Wnt pathway, which is highly expressed in malignant tumors and helps regulate multiple tumor behaviors. Its expression level is related to prognosis. Here, bioinformatic analysis was performed to understand the expression of FZD2 in different tumors. We examined FZD2 expression using pan‐cancer data of 33 cancer types from The Cancer Genome Atlas (TCGA). Differential expression analysis (Wilcoxon's test) was used to compare tumor and normal tissues. Univariate Cox proportional hazard regression was performed to compare gene expression and overall patient survival. COSMIC, cBioPortal, and CCLE were used to examine FZD2 mutations in human cancers. Dryness index was calculated using one‐class logistic regression (OCLR). Spearman's correlation was performed based on gene expression and dryness score and used to analyze the correlation between gene expression and stemness score, matrix score, immune score, estimated score, tumor mutation burden (TMB), microsatellite instability (MSI), and drug sensitivity. STRING website was used to construct an FZD2 protein interaction network and identify genes that interact with FZD2. We report that FZD2 is highly expressed in most tumors, differing between cancer types. Expression was related to patient overall survival (OS), disease‐specific survival, disease‐free interval (DFI), mutations, drug sensitivity, tumor microenvironment, immune cell infiltration, immune checkpoint gene expression, immunotherapy indicators (TMB, MSI), and tumor cell stemness. FZD2 influenced drug sensitivities, including cobimetinib (r = −0.553, P < 0.001), selumetinib (r = −0.539, P < 0.001), bafetinib (r = −0.538, P < 0.001), tamoxifen (r = −0.523, P < 0.001), alvespimycin (r = −0.520, P < 0.001), and nilotinib (r = −0.502, P < 0.001). FZD2 has the most significant correlation with ROR2 (r = 0.4, P < 0.001), Wnt2 (r = 0.37, P < 0.001), and Wnt4A (r = 0.34, P < 0.001). The results confirm the importance of FZD2 expression in cancer prognosis and treatment, and provide new clues for treatment strategies.

Integrated bioinformatics analysis for the identification of key genes and signaling pathways in thyroid carcinoma

Thyroid carcinoma (TC) is one of the most common types of endocrine neoplasm with poor prognosis due to its aggressive behavior. Biomarkers for early diagnosis and prevention of TC are in urgent demand. By using a bioinformatics analysis, the present study aimed to identify essential genes and pathways associated with TC. First, the GSE27155 and GSE50901 expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were obtained using the two microarray datasets and further subjected to integrated analysis. A gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed 45 common DEGs in the two datasets. GO and KEGG pathway analysis indicated that the biological functions of the DEGs included protein binding, cardiac muscle cell potential involved in contraction, aldehyde dehydrogenase activity, the TGF-β receptor signaling pathway and the canonical Wnt signaling pathway. A protein-protein interaction network was also constructed and visualized to display the nodes of the top 9 up- and 36 downregulated common DEGs. The integrated bioinformatics analysis indicated that potassium inwardly rectifying channel subfamily J member 2 (KCNJ2) was the most significantly upregulated DEG. The transcriptional levels of KCNJ2 were confirmed to be elevated in TC tissues compared with those in normal tissues using reverse transcription-quantitative PCR analysis. Furthermore, the expression level of KCNJ2 was significantly associated with the 5-year survival rate of patients with TC, which was determined using the Kaplan-Meier method. In TC cell lines, KCNJ2 was also upregulated as compared with that in a normal control cell line. Finally, small interfering RNA was used to knock down the expression of KCNJ2, which was demonstrated to inhibit cell proliferation, migration and invasion, while increasing apoptosis in TC cells. In conclusion, in the present study, KCNJ2 was screened as an oncogene with a crucial role in TC development and progression and may represent a promising candidate biomarker and therapeutic target for TC.

Low Expression of Keratin17 is Related to Poor Prognosis in Bladder Cancer

Objective

To investigate the association between KRT17 and the prognosis in bladder cancer patients.

Methods

The clinical data of 101 patients with bladder cancer from May 2013 to May 2015 were retrospectively analyzed. At the same time, the expression of KRT17 and its correlation with clinicopathological factors were examined by immunohistochemistry. We search the prognostic value of KRT17 in bladder cancer from the cancer genome map (TCGA) online database. To explore the possible cellular mechanism, gene set enrichment analysis (GSEA) was used. The patients were divided into two groups: high expression of KRT17 and low expression of KRT17. The patients were followed up for 5 years to observe the survival. Kaplan–Meier method and Log rank test were used for univariate survival analysis, and Cox regression analysis was used for multivariate analysis. Finally, a nomogram was constructed on this basis for internal verification.

Results

Among the 101 patients, 46 (45.5%) were in the KRT17 low expression group and 55 (54.5%) in the high KRT17 expression group. After 5 years of follow-up, 79 patients survived with a survival rate of 78.2% and 22 patients died with a mortality rate of 21.8%. Kaplan–Meier survival analysis showed that OS and PFS of patients with high expression of KRT17 were significantly higher than those of patients with low expression of KRT17 (p<0.001, p=0.005). Cox multivariate analysis showed that KRT17 expression was an independent risk factor for tumor progression (p=0.019). And tumor size, vascular tumor thrombus, and T stage also affected tumor progression (p<0.05). In the internal validation, the c-index of nomogram was 0.898 (95% CI: 0.854–0.941).

Conclusion

The decreased expression of KRT17 is associated with poor prognosis in patients with bladder cancer. KRT17 can be used as a novel predictive biomarker to provide a new therapeutic target for bladder cancer patients.

Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

BACKGROUND

Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive.

OBJECTIVE

To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis.

METHOD

The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE.

RESULTS

A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene.

CONCLUSION

The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.

Transcriptomic landscaping of core genes and pathways of mild and severe psoriasis vulgaris

Psoriasis is a common chronic inflammatory skin disease affecting >125 million individuals worldwide. The therapeutic course for the disease is generally designed upon the severity of the disease. In the present study, the gene expression profile GSE78097, was retrieved from the National Centre of Biotechnology (NCBI)‑Gene Expression Omnibus (GEO) database to explore the differentially expressed genes (DEGs) in mild and severe psoriasis using the Affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways of the DEGs were analysed using clusterProfiler, Bioconductor, version 3.8. In addition, the STRING database was used to develop DEG‑encoded proteins and a protein‑protein interaction network (PPI). Cytoscape software, version 3.7.1 was utilized to construct a protein interaction association network and analyse the interaction of the candidate DEGs encoding proteins in psoriasis. The top 2 hub genes in Cytohubba plugin parameters were validated using immunohistochemical analysis in psoriasis tissues. A total of 382 and 3,001 dysregulated mild and severe psoriasis DEGs were reported, respectively. The dysregulated mild psoriasis genes were enriched in pathways involving cytokine‑cytokine receptor interaction and rheumatoid arthritis, whereas cytokine‑cytokine receptor interaction, cell cycle and cell adhesion molecules were the most enriched pathways in severe psoriasis group. PL1N1, TLR4, ADIPOQ, CXCL8, PDK4, CXCL1, CXCL5, LPL, AGT, LEP were hub genes in mild psoriasis, whereas BUB1, CCNB1, CCNA2, CDK1, CDH1, VEGFA, PLK1, CDC42, CCND1 and CXCL8 were reported hub genes in severe psoriasis. Among these, CDC42, for the first time (to the best of our knowledge), has been reported in the psoriasis transcriptome, with its involvement in the adaptive immune pathway. Furthermore, the immunoexpression of CDK1 and CDH1 proteins in psoriasis skin lesions were demonstrated using immunohistochemical analysis. On the whole, the findings of the present integrated bioinformatics and immunohistochemical study, may enhance our understanding of the molecular events occurring in psoriasis, and these candidate genes and pathways together may prove to be therapeutic targets for psoriasis vulgaris.

Identification of feature risk pathways of smoking-induced lung cancer based on SVM

Objective

The present study aims to explore the role of smoking factors in the risk of lung cancer and screen the feature risk pathways of smoking-induced lung cancer.

Methods

The expression profiles of the patient data from GEO database were standardized, and differentially expressed genes (DEGs) were analyzed by limma algorithm. Samples and genes were analyzed by Unsupervised hierarchical clustering method, while GO and KEGG enrichment analyses were performed on DEGs. The data of the protein-protein interaction (PPI) network were downloaded from the BioGrid and HPRD databases, and the DEGs were mapped into the PPI network to identify the interaction relationship. The enriched significant pathways were used to calculate the anomaly score and RFE method was used to optimize the feature sets. The model was trained using the support vector machine (SVM) and the predicted results were plotted into ROC curves. The AUC value was calculated to evaluate the predictive performance of the SVM model.

Results

A total of 1923 DEGs were obtained, of which 826 were down-regulated and 1097 were up-regulated. Unsupervised hierarchical clustering analysis showed that the diagnosis accuracy of lung cancer smokers was 74%, and that of non-lung cancer smokers was 75%. Five optimal feature pathway sets were obtained by screening, the clinical diagnostic ability of which was detected by SVM model with the accuracy improved to 84%. The diagnostic accuracy was 90% after combining clinical information.

Conclusion

We verified that five signaling pathways combined with clinical information could be used as a feature risk pathway for identifying lung cancer smokers and non-lung cancer smokers and increased the diagnostic accuracy.

Rac1 Signaling: From Intestinal Homeostasis to Colorectal Cancer Metastasis

The small GTPase Rac1 has been implicated in a variety of dynamic cell biological processes, including cell proliferation, cell survival, cell-cell contacts, epithelial mesenchymal transition (EMT), cell motility, and invasiveness. These processes are orchestrated through the fine tuning of Rac1 activity by upstream cell surface receptors and effectors that regulate the cycling Rac1-GDP (off state)/Rac1-GTP (on state), but also through the tuning of Rac1 accumulation, activity, and subcellular localization by post translational modifications or recruitment into molecular scaffolds. Another level of regulation involves Rac1 transcripts stability and splicing. Downstream, Rac1 initiates a series of signaling networks, including regulatory complex of actin cytoskeleton remodeling, activation of protein kinases (PAKs, MAPKs) and transcription factors (NFkB, Wnt/β-catenin/TCF, STAT3, Snail), production of reactive oxygen species (NADPH oxidase holoenzymes, mitochondrial ROS). Thus, this GTPase, its regulators, and effector systems might be involved at different steps of the neoplastic progression from dysplasia to the metastatic cascade. After briefly placing Rac1 and its effector systems in the more general context of intestinal homeostasis and in wound healing after intestinal injury, the present review mainly focuses on the several levels of Rac1 signaling pathway dysregulation in colorectal carcinogenesis, their biological significance, and their clinical impact.

Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset

Background

To better understand the process of osteoarthritic degenerative meniscal lesions (DMLs) formation, this study analyzed the dataset GSE52042 using bioinformatics methods to identify the pivotal genes and pathways related to osteoarthritic DMLs.

Material/Methods

The GSE52042 dataset, comprising diseased meniscus samples and healthier meniscus samples, was downloaded and the differentially-expressed genes (DEGs) were extracted. The reactome pathways assessment and functional analysis were performed using the “ClusterProfiler” package and “ReactomePA” package of Bioconductor. The protein–protein interaction network was constructed, followed by the extraction of hub genes and modules.

Results

A set of 154 common DEGs, including 64 upregulated DEGs and 90 downregulated DEGs, were obtained. GO analysis suggested that the DEGs primarily participated in positive regulation of the mitotic cell cycle and extracellular matrix organization. Reactome pathway analysis showed that the DEGs were predominantly enriched in TP53, which regulates transcription of genes involved in G2 cell cycle arrest and extracellular matrix organization. The top 10 hub genes were TYMS, AURKA, CENPN, NUSAP1, CENPM, TPX2, CDK1, UBE2C, BIRC5, and CCNB1. The genes in the 2 modules were primarily associated with M Phase and keratan sulfate degradation.

Conclusions

A series of pivotal genes and reactome pathways were identified elucidate the molecular mechanisms involved in the formation of osteoarthritic DMLs and to discover potential therapeutic targets.

FZD2 regulates cell proliferation and invasion in tongue squamous cell carcinoma

Many studies have shown that FZD2 is significantly associated with tumor development and tumor metastasis. The purpose of the present study was to gain insight into the role of FZD2 in the cell proliferation and invasion of tongue squamous cell carcinoma. According to TCGA-HNSC dataset, among the 10 Frizzled receptors, FZD2 exhibited the highest degree of differential expression between cancer tissues and normal tissues, and the overall survival of patients with higher FZD2 levels was shown to be significantly shorter compared with those with lower FZD2 levels. The upregulation of FZD2 in clinical tongue cancer tissues was validated by real-time PCR. Knockdown of FZD2 inhibited the proliferation, migration and invasion of CAL-27 and TCA-8113 cells, whereas overexpression of FZD2 led to the opposite results. Further analysis revealed that FZD2 is positively correlated with WNT3A, WNT5B, WNT7A and WNT2 and is negatively correlated with WNT4. These results indicated that FZD2 may act as an oncogene in tongue squamous cell carcinoma. Therefore, FZD2 may be a target for the diagnosis, prognosis and gene therapy of tongue cancer.

Claudin7-dependent exosome-promoted reprogramming of nonmetastasizing tumor cells

Claudin7 (cld7) is a cancer-initiating cell (CIC) marker in gastrointestinal tumors, a cld7-knockdown (kd) being accompanied by loss of tumor progression. Tumor exosomes (TEX) restoring CIC activities, we explored the contribution of cld7. This became particularly interesting, as tight junction (TJ)- and glycolipid-enriched membrane domain (GEM)-derived cld7 is recruited into distinct TEX. TEXs were derived from CIC or cld7kd cells of a rat pancreatic and a human colon cancer line. TEX derived from pancreatic cancer cld7kd cells rescued with palmitoylation site-deficient cld7 (cld7mP) allowed selectively evaluating the contribution of GEM-derived TEX, only palmitoylated cld7 being integrated into GEM. Cld7 CIC-TEX promoted tumor cell dissemination and metastatic growth without a major impact on proliferation, apoptosis resistance and epithelial-mesenchymal transition. Instead, migration, invasion and (lymph)angiogenesis were strongly supported, only migration being selectively fostered by GEM-derived cld7 TEX. CIC-TEX coculture of cld7kd cells uncovered significant changes in the cld7kd cell protein and miRNA profiles. However, changes did not correspond to the CIC-TEX profile, CIC-TEX rather initiating integrin, protease and RTK, particularly lymphangiogenic receptor activation. CIC-TEX preferentially rescuing cld7kd-associated defects in signal transduction was backed up by an RTK inhibitor neutralizing the impact of CIC-TEX on tumor progression. In conclusion, cld7 contributes to selective steps of the metastatic cascade. Defects of cld7kd and cld7mP cells in migration, invasion and (lymph)angiogenesis are effaced by CIC-TEX that act by signaling cascade activation. Accordingly, RTK inhibitors are an efficient therapeutic defeating CIC-TEX.

Colonic Mucosal Transcriptomic Changes in Patients with Long-Duration Ulcerative Colitis Revealed Colitis-Associated Cancer Pathways

BACKGROUND AND AIMS

Patients with ulcerative colitis [UC] with long disease duration have a higher risk of developing colitis-associated cancer [CAC] compared with patients with short-duration UC. The aim of this study was to identify transcriptomic differences associated with the duration of UC disease.

METHODS

We conducted transcriptome profiling on 32 colonic biopsies [11 long-duration UC, ≥20 years; and 21 short-duration UC, ≤5 years] using Affymetrix Human Transcriptome Array 2.0. Differentially expressed genes [fold change > 1.5, p < 0.05] and alternative splicing events [splicing index > 1.5, p < 0.05] were determined using the Transcriptome Analysis Console. KOBAS 3.0 and DAVID 6.8 were used for KEGG and GO analysis. Selected genes from microarray analysis were validated using qPCR.

RESULTS

There were 640 differentially expressed genes between both groups. The top ten upregulated genes were HMGCS2, UGT2A3 isoforms, B4GALNT2, MEP1B, GUCA2B, ADH1C, OTOP2, SLC9A3, and LYPD8; the top ten downregulated genes were PI3, DUOX2, VNN1, SLC6A14, GREM1, MMP1, CXCL1, TNIP3, TFF1, and LCN2. Among the 123 altered KEGG pathways, the most significant were metabolic pathways; fatty acid degradation; valine, leucine, and isoleucine degradation; the peroxisome proliferator-activated receptor signalling pathway; and bile secretion, which were previously linked with CAC. Analysis showed that 3560 genes exhibited differential alternative splicing between long- and short-duration UC. Among them, 374 were differentially expressed, underscoring the intrinsic relationship between altered gene expression and alternative splicing.

CONCLUSIONS

Long-duration UC patients have altered gene expressions, pathways, and alternative splicing events as compared with short-duration UC patients, and these could be further validated to improve our understanding of the pathogenesis of CAC.

Up-regulation of fibroblast growth factor receptor 1 due to prenatal tobacco exposure can lead to developmental defects in new born

Introduction: Tobacco-smoking is one of the most important risk factor for preterm delivery, pregnancy loss, low birth weight, and fetal growth restriction. It is estimated that approximately 30% of growth-restricted neonates could be independently associated with maternal smoking.Methods: In this study, gene expression profile, GSE11798, was chosen from GEO database with an aim to perceive change in gene expression signature in new born due to maternal smoking. Enrichment analysis was performed to annotate differentially expressed genes (DEGs) through gene ontology and pathway analysis using DAVID. Protein-protein interactions and module detection of these DEGs were carried out using cytoscape v3.6.0. Thirty umbilical cord tissue samples from 15 smokers and 15 non-smokers pregnant women were included in this analysis.Results: Twenty-six differentially expressed genes (DEGs) between two groups were selected using GEO2R tool. The DEGs were observed to be participating in biological processes/pathways related to growth releasing hormone, angiogenesis, embryonic skeletal, and cardiac development. Fibroblast growth factor receptor-1 (FGFR1) was identified to be the hub node with 348 interacting partners, which regulates transcription, cell growth, differentiation, and apoptosis. The up-regulation of FGFR1 in umbilical cord tissue may lead to reproductive and developmental complications such as encephalocraniocutaneous lipomatosis, osteoglophonic dysplasia, and Pfeiffer syndrome in new-borns.Conclusion: The findings manifests the possibility of overcoming these adverse health effects in new born through FGFR1 modulating treatments during pregnancy.

Long non-coding RNA NEAT1 promotes colorectal cancer progression by competitively binding miR-34a with SIRT1 and enhancing the Wnt/β-catenin signaling pathway

In recent years, accumulating evidence has indicated that long non-coding RNAs (lncRNAs) are powerful factors influencing the progression of multiple malignancies. Although a relationship between the lncRNA NEAT1 (nuclear enriched abundant transcript 1) and colorectal cancer has previously been reported, the functional mechanism underlying the involvement of NEAT1 in colorectal cancer remains unknown. In this study, we report that NEAT1 expression is up-regulated in colorectal cancer tissues, which correlates with advanced clinical features, poor overall survival and disease free survival. Up-regulated NEAT1 promotes cell proliferation and metastasis of colorectal cancer both in vitro and in vivo. Moreover, NEAT1 functions as an oncogene influencing cell viability and invasion in part by serving as a competing endogenous RNA (ceRNAs) modulating miRNA-34a expression, leading to subsequent repression of the miR-34a/SIRT1 axis and activation of the Wnt/β-catenin signaling pathway. Taken together, our study demonstrates that the lncRNA NEAT1 may serve as a prognostic biomarker and a potential therapeutic target in colorectal cancer.

Identification of Key Pathways and Genes in Anaplastic Thyroid Carcinoma via Integrated Bioinformatics Analysis

BACKGROUND To provide a better understanding of anaplastic thyroid carcinoma (ATC) at the molecular level, this study aimed to identify the genes and key pathways associated with ATC by using integrated bioinformatics analysis. MATERIAL AND METHODS Based on the microarray data GSE9115, GSE65144, and GSE53072 derived from the Gene Expression Omnibus, the differentially expressed genes (DEGs) between ATC samples and normal controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein-protein interaction (PPI) network was constructed and visualized, with which the hub gene nodes were screened out. Finally, modules analysis for the PPI network was performed to further investigate the potential relationships between DEGs and ATC. RESULTS A total of 537 common DEGs were screened out from all 3 datasets, among which 247 genes were upregulated and 275 genes were downregulated. GO analysis indicated that upregulated DEGs were mainly involved in cell division and mitotic nuclear division and the downregulated DEGs were significantly enriched in ventricular cardiac muscle cell action potential. KEGG pathway analysis showed that the upregulated DEGs were mainly enriched in cell cycle and ECM-receptor interaction and the downregulated DEGs were mainly enriched in thyroid hormone synthesis, insulin resistance, and pathways in cancer. The top 10 hub genes in the constructed PPI network were CDK1, CCNB1, TOP2A, AURKB, CCNA2, BUB1, AURKA, CDC20, MAD2L1, and BUB1B. The modules analysis showed that genes in the top 2 significant modules of PPI network were mainly associated with mitotic cell cycle and positive regulation of mitosis, respectively. CONCLUSIONS We identified a series of key genes along with the pathways that were most closely related with ATC initiation and progression. Our results provide a more detailed molecular mechanism for the development of ATC, shedding light on the potential biomarkers and therapeutic targets.

Development of a computational promoter with highly efficient expression in tumors

Background

Gene therapy is a potent method to increase the therapeutic efficacy against cancer. However, a gene that is specifically expressed in the tumor area has not been identified. In addition, nonspecific expression of therapeutic genes in normal tissues may cause side effects that can harm the patients’ health. Certain promoters have been reported to drive therapeutic gene expression specifically in cancer cells; however, low expression levels of the target gene are a problem for providing good therapeutic efficacy. Therefore, a specific and highly expressive promoter is needed for cancer gene therapy.

Methods

Bioinformatics approaches were utilized to analyze transcription factors (TFs) from high-throughput data. Reverse transcription polymerase chain reaction, western blotting and cell transfection were applied for the measurement of mRNA, protein expression and activity. C57BL/6JNarl mice were injected with pD5-hrGFP to evaluate the expression of TFs.

Results

We analyzed bioinformatics data and identified three TFs, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), cyclic AMP response element binding protein (CREB), and hypoxia-inducible factor-1α (HIF-1α), that are highly active in tumor cells. Here, we constructed a novel mini-promoter, D5, that is composed of the binding sites of the three TFs. The results show that the D5 promoter specifically drives therapeutic gene expression in tumor tissues and that the strength of the D5 promoter is directly proportional to tumor size.

Conclusions

Our results show that bioinformatics may be a good tool for the selection of appropriate TFs and for the design of specific mini-promoters to improve cancer gene therapy.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4421-7) contains supplementary material, which is available to authorized users.

Keratin17 Promotes Tumor Growth and is Associated with Poor Prognosis in Gastric Cancer

Krt17 is a 48kDa protein member of keratin family. Previous literatures have demonstrated Krt17 may play a promotive role in the progression of various malignancies. However, the exact function of Krt17 in the carcinogenesis and the progression of gastric cancer (GC) remains unknown. In the present study, the expression of Krt17 in 20 fresh GC and matched normal tissues were detected and Krt17 was found to be significantly increased in GC tissues compared to normal tissues. And then the immunochemistry was performed to investigate the Krt17 expression in 569 GC tissue specimens, we found that the expression of Krt17 was remarkably positively correlated with the tumor size (P < 0.01), depth of invasion (T) (P < 0.001), lymph node metastasis (N) (P < 0.001), tumor node metastasis (TNM) stage (P < 0.001) and vascular invasion (P < 0.05). High expression of Krt17 predicted a poor prognosis of GC patients. In addition, we showed silencing of Krt17 inhibited GC cell proliferation, migration and invasion, and induced cell apoptosis by altering Bcl2 family protein expression and cleaved caspase3 upregulation. Moreover, silencing of Krt17 led to cell cycle arrest at G1/S stage by decreasing cyclin E1 and cyclin D expression. In conclusion, our findings revealed Krt17 can be used as a novel predictive biomarker, thus providing a novel therapeutic target for GC patients.

Altered expression profiles of circular RNA in colorectal cancer tissues from patients with lung metastasis

The lung is the most common extra-abdominal site of metastasis in colorectal cancer (CRC), in which circular RNA (circRNA) may have a crucial role. Therefore, the present study detected circRNA expression to identify novel targets to further study lung metastasis in CRC. In the present study, total RNA was extracted from CRC tissues of patients with and without lung metastasis to perform high-throughput microarray assay in order to detect differentially expressed circRNA. Following this, gene ontology (GO) and pathway analyses of the genes producing differentially expressed circRNA were performed to predict the function of circRNA using standard enrichment computational methods. Additionally, the circRNA/microRNA (miRNA) interactions were constructed with bioinformatics methods to predict the binding of miRNA with circRNA. In the CRC tissues from patients with lung metastasis, 431 circRNA were detected to be differentially expressed, including 192 upregulated and 239 downregulated over 2-fold compared with the CRC tissues without metastasis. Furthermore, GO analysis revealed that the genes producing upregulated circRNA were involved in DNA repair, while the genes producing downregulated circRNA were enriched in signal transduction. By pathway analysis, it was identified that the genes producing downregulated circRNA were involved in the nuclear factor-κB and Wnt signaling pathway in the CRC tissues from patients with lung metastasis compared with the CRC tissues without metastasis. In addition, it was demonstrated that hsa_circRNA_105055, hsa_circRNA_086376 and hsa_circRNA_102761 could commonly bind with miR-7 regulating target genes PRKCB, EPHA3, BRCA1 and ABCC1. The findings of the present study may provide a novel perspective on circRNA and lay a foundation for future research of potential roles of circRNA in CRC with lung metastasis.

Gene expression profile comparison between colorectal cancer and adjacent normal tissues

The present study aimed to compare gene expression profiles between colorectal cancer and adjacent normal tissues, and to perform a preliminarily analysis of the key genes and underlying molecular mechanisms implicated in colorectal cancer development. Gene expression microarray chips were used to screen genes that were differently expressed between colorectal cancer and adjacent normal tissues. Approximately 1,183 genes were differentially expressed in cancer tissues compared with adjacent normal tissues (P≤0.05; fold difference, >2.0), of which 570 genes were upregulated and 613 genes were downregulated. In total, 6 upregulated genes, including keratin 23, collagen type X α1, collagen type XI α1, cell migration-inducing hyaluronan-binding protein, transforming growth factor-β1 and V-Myc avian myelocytomatosis viral oncogene homolog, and 2 downregulated genes, including channel α subunit 7 and EPH receptor A7, were selected and validated using reverse transcription-quantitative polymerase chain reaction, which exhibited results that were consistent with the microarray analysis. These 1,183 differentially expressed genes were further classified into 71 groups based on their functions using gene ontology and pathway analyses. Kyoto Encyclopedia of Genes and Genomes analysis of these upregulated or downregulated genes suggested that 23 signaling pathways were involved. The present study preliminarily screened for and identified key genes and signaling pathways that may be closely associated with colorectal cancer development. However, subsequent gene function studies are required to verify these findings.

Functional analysis of keratinocyte and fibroblast gene expression in skin and keloid scar tissue based on deviation analysis of dynamic capabilities

The aim of the present study was to select key genes that are associated with fibroblasts and keratinocytes during keloid scar progression and development. The gene expression profile of GSE44270, which includes 32 samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in case samples compared with control samples were screened using the Limma R package followed by hierarchical clustering analysis. Protein-protein interaction (PPI) networks of the total selected DEGs were constructed using Cytoscape. Moreover, the Gene Ontology biological processes and significant Kyoto Encyclopedia of Genes and Genomes pathways of the total selected DEGs were enriched using the Database for Annotation, Visualization and Integrated Discovery. Significant pathways that may be associated with keloid scar were analyzed using deviation analysis of dynamic capabilities. There were 658 DEGs in fibroblast keloid vs. normal, 112 DEGs in fibroblast non-lesion vs. normal, 439 DEGs in fibroblast keloid vs. non-lesion, 523 DEGs in keratocyte keloid vs. normal, 186 DEGs in keratocyte non-lesion vs. normal, and 963 DEGs in keratocyte keloid vs. non-lesion groups. HOXA9, BMP4, CDKN1A and SMAD2 in fibroblasts, and HOXA7, MCM8, PSMA4 and PSMB2 in keratinocytes were key genes in the PPI networks. Moreover, the amino sugar and nucleotide sugar metabolism pathway, cell cycle, and extracellular matrix (ECM)-receptor interaction pathway were significant pathways. This study suggests that several key genes (BMP4, HOXA9, SMAD2, CDKN1A, HOXA7, PSMA4 and PSMB2) that participate in some significant pathways (cell cycle and ECM-receptor interaction pathways) may be potential therapeutic targets for keloid scars.

Combined Analysis of ChIP Sequencing and Gene Expression Dataset in Breast Cancer

Breast cancer is a common malignancy in women and contribute largely to the cancer related death. The purpose of this study is to confirm the roles of GATA3 and identify potential biomarkers of breast cancer. Chromatin Immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) (GSM1642515) and gene expression profiles (GSE24249) were downloaded from the Gene Expression Omnibus (GEO) database. Bowtie2 and MACS2 were used for the mapping and peak calling of the ChIP-Seq data respectively. ChIPseeker, a R bioconductor package was adopted for the annotation of the enriched peaks. For the gene expression profiles, we used affy and limma package to do normalization and differential expression analysis. The genes with fold change >2 and adjusted P-Value <0.05 were screened out. Besides, BETA (Binding and Expression Target Analysis) was used to do the combined analysis of ChIP-Seq and gene expression profiles. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for the functional enrichment analysis of overlapping genes between the target genes and differential expression genes (DEGs). What's more, the protein-protein interaction (PPI) network of the overlapping genes was obtained through the Human Protein Reference Database (HPRD). A total of 46,487 peaks were identified for GATA3 and out of which, 3256 ones were found to located at -3000 ~ 0 bp from the transcription start sites (TSS) of their nearby gene. A total of 236 down- and 343 up-regulated genes were screened out in GATA3 overexpression breast cancer samples compared with those in control. The combined analysis of ChIP-Seq and gene expression dataset showed GATA3 act as a repressor in breast cancer. Besides, 68 overlaps were obtained between the DEGs and genes included in peaks located at -3000 ~ 0 bp from TSS. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cancer progression and gene regulation were found to be enriched in those overlaps. In the PPI network, NDRG1, JUP and etc. were found to directly interact with large number of genes, which might indicate their important roles in the progression of breast cancer.

Identification of gene markers in the development of smoking-induced lung cancer

Lung cancer is a malignant tumor with high mortality in both women and men. To study the mechanisms of smoking-induced lung cancer, we analyzed microarray of GSE4115. GSE4115 was downloaded from Gene Expression Omnibus including 78 and 85 bronchial epithelium tissue samples separately from smokers with and without lung cancer. Limma package in R was used to screen differentially expressed genes (DEGs). Hierarchical cluster analysis for DEGs was conducted using orange software and visualized by distance map. Using DAVID software, functional and pathway enrichment analyses separately were conducted for the DEGs. And protein-protein interaction (PPI) network was constructed using Cytoscape software. Then, the pathscores of enriched pathways were calculated. Besides, functional features were screened and optimized using the recursive feature elimination (RFE) method. Additionally, the support vector machine (SVM) method was used to train model. Total 1923 DEGs were identified between the two groups. Hierarchical cluster analysis indicated that there were differences in gene level between the two groups. And SVM analysis indicated that the five features had potential diagnostic value. Importantly, MAPK1 (degree=30), SRC (degree=29), SMAD4 (degree=23), EEF1A1 (degree=21), TRAF2 (degree=21) and PLCG1 (degree=20) had higher degrees in the PPI network of the DEGs. They might be involved in smoking-induced lung cancer by interacting with each other (e.g. MAPK1-SMAD4, SMAD4-EEF1A1 and SRC-PLCG1). MAPK1, SRC, SMAD4, EEF1A1, TRAF2 and PLCG1 might be responsible for the development of smoking-induced lung cancer.

FZD2 inhibits the cell growth and migration of salivary adenoid cystic carcinomas

Several studies have reported that FZD2 regulates tumor biology in a complex manner. The aim of the present study was to identify the role of FZD2 in the cell growth and metastasis of salivary adenoid cystic carcinomas (SACCs). The expression of FZD2 in ACC-83 and ACC-LM cells were measured with real-time PCR. Immunohistochemical staining was used to detect the expression of FZD2 in clinical SACC samples with or without metastasis. Cell proliferation and Transwell assays were performed to explore the effects of FZD2 on cell growth and migration following the silencing of FZD2 with small interference RNAs and the overexpression of FZD2 with plasmid. Our data showed that FZD2 was downregulated in ACC-LM cells, which are an adenoid cystic carcinoma cell line with high metastatic potential, compared to ACC-83 cells, which have low metastatic potential. Additionally, the expression of FZD2 was lower in SACC tissues with metastasis compared to SACC tissues without metastasis (P<0.05). Cell proliferation and migration of ACC-83 cells were increased after the knockdown of FZD2 and decreased following overexpression of FZD2. Knockdown of FZD2 downregulated the expression of PAI-1. Our results suggest that FZD2 may be a tumor suppressor gene in SACCs that inhibits cell growth and migration.