In silico identification of oncogenic potential of fyn-related kinase in hepatocellular carcinoma

Oncogenes and tumor suppressor genes: functions and roles in cancers

Cancer, being the most formidable ailment, has had a profound impact on the human health. The disease is primarily associated with genetic mutations that impact oncogenes and tumor suppressor genes (TSGs). Recently, growing evidence have shown that X-linked TSGs have specific role in cancer progression and metastasis as well. Interestingly, our genome harbors around substantial portion of genes that function as tumor suppressors, and the X chromosome alone harbors a considerable number of TSGs. The scenario becomes even more compelling as X-linked TSGs are adaptive to key epigenetic processes such as X chromosome inactivation. Therefore, delineating the new paradigm related to X-linked TSGs, for instance, their crosstalk with autosome and involvement in cancer initiation, progression, and metastasis becomes utmost importance. Considering this, herein, we present a comprehensive discussion of X-linked TSG dysregulation in various cancers as a consequence of genetic variations and epigenetic alterations. In addition, the dynamic role of X-linked TSGs in sex chromosome-autosome crosstalk in cancer genome remodeling is being explored thoroughly. Besides, the functional roles of ncRNAs, role of X-linked TSG in immunomodulation and in gender-based cancer disparities has also been highlighted. Overall, the focal idea of the present article is to recapitulate the findings on X-linked TSG regulation in the cancer landscape and to redefine their role toward improving cancer treatment strategies.

CancerMHL: the database of integrating key DNA methylation, histone modifications and lncRNAs in cancer

The discovery of key epigenetic modifications in cancer is of great significance for the study of disease biomarkers. Through the mining of epigenetic modification data relevant to cancer, some researches on epigenetic modifications are accumulating. In order to make it easier to integrate the effects of key epigenetic modifications on the related cancers, we established CancerMHL (http://www.positionprediction.cn/), which provide key DNA methylation, histone modifications and lncRNAs as well as the effect of these key epigenetic modifications on gene expression in several cancers. To facilitate data retrieval, CancerMHL offers flexible query options and filters, allowing users to access specific key epigenetic modifications according to their own needs. In addition, based on the epigenetic modification data, three online prediction tools had been offered in CancerMHL for users. CancerMHL will be a useful resource platform for further exploring novel and potential biomarkers and therapeutic targets in cancer. Database URL: http://www.positionprediction.cn/.

Identification and validation of disulfidptosis-associated molecular clusters in non-alcoholic fatty liver disease

Objective: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease in the world, and its pathogenesis is not fully understood. Disulfidptosis is the most recently reported form of cell death and may be associated with NAFLD progression. Our study aimed to explore the molecular clusters associated with disulfidptosis in NAFLD and to construct a predictive model. Methods: First, we analyzed the expression profile of the disulfidptosis regulators and immune characteristics in NAFLD. Using 104 NAFLD samples, we investigated molecular clusters based on differentially expressed disulfidptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were then identified by using the WGCNA method. We also evaluated the performance of four machine learning models before choosing the optimal machine model for diagnosis. Nomogram, calibration curves, decision curve analysis, and external datasets were used to confirm the prediction effectiveness. Finally, the expression levels of the biomarkers were assessed in a mouse model of a high-fat diet. Results: Two differentially expressed DRGs were identified between healthy and NAFLD patients. We revealed the expression profile of DRGs in NAFLD and the correlation with 22 immune cells. In NAFLD, two clusters of molecules connected to disulfidptosis were defined. Significant immunological heterogeneity was shown by immune infiltration analysis among the various clusters. A significant amount of immunological infiltration was seen in Cluster 1. Functional analysis revealed that Cluster 1 differentially expressed genes were strongly linked to energy metabolism and immune control. The highest discriminatory performance was demonstrated by the SVM model, which had a higher area under the curve, relatively small residual and root mean square errors. Nomograms, calibration curves, and decision curve analyses were used to show how accurate the prediction of NAFLD was. Further analysis revealed that the expression of three model-related genes was significantly associated with the level of multiple immune cells. In animal experiments, the expression trends of DDO, FRK and TMEM19 were consistent with the results of bioinformatics analysis. Conclusion: This study systematically elucidated the complex relationship between disulfidptosis and NAFLD and developed a promising predictive model to assess the risk of disease in patients with disulfidptosis subtypes and NAFLD.

Isolation of a Human Betaretrovirus from Patients with Primary Biliary Cholangitis

A human betaretrovirus (HBRV) has been linked with the autoimmune liver disease, primary biliary cholangitis (PBC), and various cancers, including breast cancer and lymphoma. HBRV is closely related to the mouse mammary tumor virus, and represents the only exogenous betaretrovirus characterized in humans to date. Evidence of infection in patients with PBC has been demonstrated through the identification of proviral integration sites in lymphoid tissue, the major reservoir of infection, as well as biliary epithelium, which is the site of the disease process. Accordingly, we tested the hypothesis that patients with PBC harbor a transmissible betaretrovirus by co-cultivation of PBC patients’ lymph node homogenates with the HS578T breast cancer line. Because of the low level of HBRV replication, betaretrovirus producing cells were subcloned to optimize viral isolation and production. Evidence of infection was provided by electron microscopy, RT-PCR, in situ hybridization, cloning of the HBRV proviral genome and demonstration of more than 3400 integration sites. Further evidence of viral transmissibility was demonstrated by infection of biliary epithelial cells. While HBRV did not show a preference for integration proximal to specific genomic features, analyses of common insertion sites revealed evidence of integration proximal to cancer associated genes. These studies demonstrate the isolation of HBRV with features similar to mouse mammary tumor virus and confirm that patients with PBC display evidence of a transmissible viral infection.

A robust and interpretable gene signature for predicting the lymph node status of primary T1/T2 oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC) affects more than 30 000 individuals in the United States annually, with smoking and alcohol consumption being the main risk factors. Management of early-stage tumors usually includes surgical resection followed by postoperative radiotherapy in certain cases. The cervical lymph nodes (LNs) are the most common site for local metastasis, and elective neck dissection is usually performed if the primary tumor thickness is greater than 3.5 mm. However, postoperative histological examination often reveals that many patients with early-stage disease are negative for neck nodal metastasis, posing a pressing need for improved risk stratification to either avoid overtreatment or prevent the disease progression. To this end, we aimed to identify a primary tumor gene signature that can accurately predict cervical LN metastasis in patients with early-stage OSCC. Using gene expression profiles from 189 samples, we trained K-top scoring pairs models and identified six gene pairs that can distinguish primary tumors with nodal metastasis from those without metastasis. The signature was further validated on an independent cohort of 35 patients using real-time polymerase chain reaction (PCR) in which it achieved an area under the receiver operating characteristic (ROC) curve and accuracy of 90% and 91%, respectively. These results indicate that such signature holds promise as a quick and cost effective method for detecting patients at high risk of developing cervical LN metastasis, and may be potentially used to guide the neck treatment regimen in early-stage OSCC.

Multivariate competing endogenous RNA network characterization for cancer MicroRNA biomarker discovery: a novel bioinformatics model with application to prostate cancer metastasis

Background

MicroRNAs (miRNAs) are post-transcriptional regulators with potential as biomarkers for cancer management. Data-driven competing endogenous RNA (ceRNA) network modeling is an effective way to decipher the complex interplay between miRNAs and spongers. However, there are currently no general rules for ceRNA network-based biomarker prioritization.

Methods and results

In this study, a novel bioinformatics model was developed by integrating gene expression with multivariate miRNA-target data for ceRNA network-based biomarker discovery. Compared with traditional methods, the structural vulnerability in the human long non-coding RNA (lncRNA)–miRNA–messenger RNAs (mRNA) network was comprehensively analyzed, and the single-line regulatory or competing mode among miRNAs, lncRNAs, and mRNAs was characterized and quantified as statistical evidence for miRNA biomarker identification. The application of this model to prostate cancer (PCa) metastasis identified a total of 12 miRNAs as putative biomarkers from the metastatic PCa-specific lncRNA–miRNA–mRNA network and nine of them have been previously reported as biomarkers for PCa metastasis. The receiver operating characteristic curve and cell line qRT-PCR experiments demonstrated the power of miR-26b-5p, miR-130a-3p, and miR-363-3p as novel candidates for predicting PCa metastasis. Moreover, PCa-associated pathways such as prostate cancer signaling, ERK/MAPK signaling, and TGF-β signaling were significantly enriched by targets of identified miRNAs, indicating the underlying mechanisms of miRNAs in PCa carcinogenesis.

Conclusions

A novel ceRNA-based bioinformatics model was proposed and applied to screen candidate miRNA biomarkers for PCa metastasis. Functional validations using human samples and clinical data will be performed for future translational studies on the identified miRNAs.

Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

S100A8/S100A9 cytokine acts as a transcriptional coactivator during breast cellular transformation

Cytokines are extracellular proteins that convey messages between cells by interacting with cognate receptors at the cell surface and triggering signaling pathways that alter gene expression and other phenotypes in an autocrine or paracrine manner. Here, we show that the calcium-dependent cytokines S100A8 and S100A9 are recruited to numerous promoters and enhancers in a model of breast cellular transformation. This recruitment is associated with multiple DNA sequence motifs recognized by DNA binding transcription factors that are linked to transcriptional activation and are important for transformation. The cytokines interact with these transcription factors in nuclear extracts, and they activate transcription when artificially recruited to a target promoter. Nuclear-specific expression of S100A8/A9 promotes oncogenic transcription and leads to enhanced breast transformation phenotype. These results suggest that, in addition to its classical cytokine function, S100A8/A9 can act as a transcriptional coactivator.

Emerging Kinase Therapeutic Targets in Pancreatic Ductal Adenocarcinoma and Pancreatic Cancer Desmoplasia

Kinase drug discovery represents an active area of therapeutic research, with previous pharmaceutical success improving patient outcomes across a wide variety of human diseases. In pancreatic ductal adenocarcinoma (PDAC), innovative pharmaceutical strategies such as kinase targeting have been unable to appreciably increase patient survival. This may be due, in part, to unchecked desmoplastic reactions to pancreatic tumors. Desmoplastic stroma enhances tumor development and progression while simultaneously restricting drug delivery to the tumor cells it protects. Emerging evidence indicates that many of the pathologic fibrotic processes directly or indirectly supporting desmoplasia may be driven by targetable protein tyrosine kinases such as Fyn-related kinase (FRK); B lymphoid kinase (BLK); hemopoietic cell kinase (HCK); ABL proto-oncogene 2 kinase (ABL2); discoidin domain receptor 1 kinase (DDR1); Lck/Yes-related novel kinase (LYN); ephrin receptor A8 kinase (EPHA8); FYN proto-oncogene kinase (FYN); lymphocyte cell-specific kinase (LCK); tec protein kinase (TEC). Herein, we review literature related to these kinases and posit signaling networks, mechanisms, and biochemical relationships by which this group may contribute to PDAC tumor growth and desmoplasia.

CENPE, PRC1, TTK, and PLK4 May Play Crucial Roles in the Osteosarcoma Progression

Osteosarcoma (OS) is a cancerous tumor in a bone. We aimed to identify the critical genes involved in OS progression, and then try to elucidate the molecular mechanisms of this disease. The microarray data of GSE32395 was used for the present study. We analyzed differentially expressed genes (DEGs) in OS cells compared with control group by Student’s t-test. The significant enriched gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathways were analyzed for upregulated genes and downregulated genes, respectively. In addition, a protein-protein interaction (PPI) network was constructed. GO and KEGG enrichment analyses were conducted for genes in the PPI network. In total, 183 DEGs, including 100 upregulated DEGs and 83 downregulated DEGs were screened. The upregulated DEGs were significantly enriched in 2 KEGG pathways, such as “Glycosaminoglycan biosynthesis-chondroitin sulfate” and the downregulated DEGs were significantly enriched in 12 pathways, including “cell adhesion molecules,” “pentose phosphate pathway” and “allograft rejection.” GO enrichment analysis indicated that the upregulated DEGs were significantly involved in biological process, such as “multicellular organismal metabolic process” and “limb morphogenesis,” while the downregulated DEGs were significantly enriched in biological process, such as “Positive regulation of pathway-restricted SMAD protein phosphorylation.” The PPI network included 84 interactions and 51 nodes. The “glycosaminoglycan biosynthesis-chondroitin sulfate pathway,” “microtubule motor activityfunction,” and “regulation of mitosis process” were significantly enriched by genes in PPI network. In particular, CENPE, PRC1, TTK, and PLK4 had higher degrees in the PPI network. The interactions between TTK and PLK4 as well as CENPE and PRC1 may involve in the OS development. These 4 genes might be possible biomarkers for the treatment and diagnosis of OS.

Src Family Kinases as Therapeutic Targets in Advanced Solid Tumors: What We Have Learned so Far

Src is the prototypal member of Src Family tyrosine Kinases (SFKs), a large non-receptor kinase class that controls multiple signaling pathways in animal cells. SFKs activation is necessary for the mitogenic signal from many growth factors, but also for the acquisition of migratory and invasive phenotype. Indeed, oncogenic activation of SFKs has been demonstrated to play an important role in solid cancers; promoting tumor growth and formation of distant metastases. Several drugs targeting SFKs have been developed and tested in preclinical models and many of them have successfully reached clinical use in hematologic cancers. Although in solid tumors SFKs inhibitors have consistently confirmed their ability in blocking cancer cell progression in several experimental models; their utilization in clinical trials has unveiled unexpected complications against an effective utilization in patients. In this review, we summarize basic molecular mechanisms involving SFKs in cancer spreading and metastasization; and discuss preclinical and clinical data highlighting the main challenges for their future application as therapeutic targets in solid cancer progression

Prediction of Epitope-Based Peptide Vaccine Against the Chikungunya Virus by Immuno-informatics Approach

BACKGROUND

Chikungunya is an arthropod-borne viral disease characterized by abrupt onset of fever frequently accompanied by joint pain, which has been identified in over 60 countries in Africa, the Americas, Asia, and Europe.

METHODS

Regardless of the availability of molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet. In the present study, a combination of B-cell and T-cell epitope predictions, followed by molecular docking simulation approach has been carried out to design a potential epitope-based peptide vaccine, which can trigger a critical immune response against the viral infections.

RESULTS

A total of 52 sequences of E1 glycoprotein from the previously reported isolates of Chikungunya outbreaks were retrieved and examined through in silico methods to identify a potential B-cell and T-cell epitope. From the two separate epitope prediction servers, five potential B-cell epitopes were selected, among them "NTQLSEAHVEKS" was found highly conserved across strains and manifests high antigenicity with surface accessibility, flexibility, and hydrophilicity. Similarly, two highly conserved, non-allergenic, non-cytotoxic putative T-cell epitopes having maximum population coverage were screened to bind with the HLA-C 12*03 molecule. Molecular docking simulation revealed potential T-cell based epitope "KTEFASAYR" as a vaccine candidate for this virus.

CONCLUSION

A combination of these B-cell and T-cell epitope-based vaccine can open up a new skyline with broader therapeutic application against Chikungunya virus with further experimental and clinical investigation.

Microarray Analysis for Differentially Expressed Genes Between Stromal and Epithelial Cells in Development and Metastasis of Invasive Breast Cancer

Both epithelium and stroma are involved in breast cancer invasion and metastasis. This study aimed at identifying the roles of the stroma in breast cancer tumorigenesis and metastasis. Gene expression profiling GSE10797 was downloaded from the Gene Expression Omnibus database, and it included 28-paired stroma and epithelium breast tissue samples from invasive breast cancer patients and 10 paired normal breast tissue samples. Differentially expressed genes (DEGs) between breast cancer and normal breast tissue samples were identified by using the limma package followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to seek the potential functions of DEGs. Moreover, a protein-protein interaction network was constructed based on the String database, and modules were selected through the BioNet tool. Further, functional annotations of DEGs were carried out by using tumor suppressor gene and tumor associated gene databases. Ultimately, KEGG pathway enrichment analysis for DEGs in modules was performed. A total of 38 and 156 DEGs were identified from normal invasive stromal cells and epithelial cells, respectively. DEGs in stromal and epithelial cells were significantly enriched in extracellular matrix (ECM)- and cell proliferation-related functions. COL1A2, a hub node in the stromal module, was mainly enriched in ECM-receptor interaction and focal adhesion pathways. JUN, a hub node in the epithelium module, was significantly enriched in cancer and ErbB signaling pathways. COL1A2, COL1A1, COL3A1, JUN, and FN1 might be vital for tumorigenesis and metastasis of invasive breast cancer. These genes might be potential therapeutic targets for breast cancer treatment.

Identification of key differentially expressed genes and gene mutations in breast ductal carcinoma in situ using RNA-seq analysis

BACKGROUND

The aim of this study was to identify the key differentially expressed genes (DEGs) and high-risk gene mutations in breast ductal carcinoma in situ (DCIS).

METHODS

Raw data (GSE36863) were downloaded from the database of Gene Expression Omnibus (GEO), including three DCIS samples (DCIS cell lines MCF10.DCIS, Sum102, and Sum225) and one normal control sample (normal mammary epithelial cell line MCF10A). The DEGs were analyzed using NOIseq and annotated via DAVID. Motif scanning in the promoter region of DEGs was performed via SeqPos. Additionally, single nucleotide variations (SNVs) were identified via GenomeAnalysisTK and SNV risk was assessed via VarioWatch. Mutant genes with a high frequency and risk were validated by RT-PCR analyses.

RESULTS

Finally, 5391, 7073, and 7944 DEGs were identified in DCIS, Sum102, and Sum22 cell lines, respectively, when compared with MCF10A. VENN analysis of the three cell lines revealed 603 upregulated and 1043 downregulated DEGs, including 16 upregulated and 36 downregulated transcription factor (TF) genes. In addition, six TFs each (e.g., E2F1 and CREB1) were found to regulate the core up- and downregulated DEGs, respectively. Furthermore, SNV detection results revealed 1104 (MCF10.DCIS), 2833 (Sum102), and 1132 (Sum22) mutation sites. Four mutant genes (RWDD4, SDHC, SEPT7, and SFN) with high frequency and risk were identified. The results of RT-PCR analysis as well as bioinformatics analysis consistently demonstrated that the expression of RWDD4, SDHC, SEPT7, and SFN was downregulated in the tumor tissues as compared with that in adjacent non-tumor tissues.

CONCLUSIONS

The differentially expressed TFs, TFs regulating DEGs (e.g., E2F1 and CREB1), and high-frequency mutant genes (RWDD4, SDHC, SEPT7, and SFN) might play key roles in the pathogenesis of DCIS.

Prediction of progression of chronic atrophic gastritis with Helicobacter pylori and poor prognosis of gastric cancer by CYP3A4

BACKGROUND AND AIM

It has been well documented that Helicobacter pylori (H. pylori) infection is a risk factor for aggravating gastric mucosal atrophy. However, the exact molecular mechanism mediating this process is not fully elucidated. The purpose of this study was to identify biomarkers, which may predict the risk for progression of chronic atrophic gastritis (CAG) with H. pylori.

METHODS

GSE27411 was downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) between H. pylori-infected samples without CAG and H. pylori-infected CAG samples were analyzed. Gene Ontology and pathway enrichment analyses were performed, followed by protein-protein interaction network construction. We used immunohistochemistry analysis to identify DEGs in 20 chronic gastritis, 20 CAG, and 22 gastric cancer (GC) specimens.

RESULTS

A total of 303 upregulated and 26 downregulated DEGs were identified. The pathways enriched by upregulated DEGs were mainly related to fat digestion and absorption, peroxisome proliferator-activated receptor signaling pathway, and chemical carcinogenesis. Cytochrome P450, family 3, subfamily A, polypeptide 4 (CYP3A4) had the highest degrees in protein-protein interaction network. Moreover, the positive rates of CYP3A4 protein expression in chronic gastritis, CAG, and GC were 10% (2/20), 55% (11/20), and 77.3% (17/22), respectively (P < 0.001). The Kaplan-Meier analysis revealed that elevated expression of CYP3A4 was significantly associated with worse overall survival and first progression, respectively (P < 0.0001).

CONCLUSION

According to the findings of this study, the expression of CYP3A4 might be related to the potential carcinogenic transformation of CAG to GC. Therefore, CYP3A4 may be biomarkers to predict progression of CAG and poor prognosis of gastric cancer.

Evolutionarily novel genes are expressed in transgenic fish tumors and their orthologs are involved in development of progressive traits in humans

Abstract

Earlier we suggested a new hypothesis of the possible evolutionary role of hereditary tumors (Kozlov, Evolution by tumor Neofunctionalization, 2014), and described a new class of genes – tumor specifically expressed, evolutionarily novel (TSEEN) genes - that are predicted by this hypothesis (Kozlov, Infect Agents Cancer 11:34, 2016). In this paper we studied evolutionarily novel genes expressed in fish tumors after regression, as a model of evolving organs. As evolutionarily novel genes may not yet have organismal functions, we studied the acquisition of new gene functions by comparing fish evolutionarily novel genes with their human orthologs. We found that many genes involved in development of progressive traits in humans (lung, mammary gland, placenta, ventricular septum, etc.) originated in fish and are expressed in fish tumors and tumors after regression. These findings support a possible evolutionary role of hereditary tumors, and in particular the hypothesis of evolution by tumor neofunctionalization.

Research highlights

Earlier we described a new class of genes that are tumor-specifically expressed and evolutionarily novel (TSEEN). As the functions of TSEEN genes are often uncertain, we decided to study TSEEN genes of fishes so that we could trace the appearance of their new functions in higher vertebrates. We found that many human genes which are involved in development of progressive traits (placenta development, mammary gland and lung development etc.,) originated in fishes and are expressed in fish tumors.

Oncogenes, tumor suppressor and differentiation genes represent the oldest human gene classes and evolve concurrently

Earlier we showed that human genome contains many evolutionarily young or novel genes with tumor-specific or tumor-predominant expression. We suggest calling such genes Tumor Specifically Expressed, Evolutionarily New (TSEEN) genes. In this paper we performed a study of the evolutionary ages of different classes of human genes, using homology searches in genomes of different taxa in human lineage. We discovered that different classes of human genes have different evolutionary ages and confirmed the existence of TSEEN gene classes. On the other hand, we found that oncogenes, tumor-suppressor genes and differentiation genes are among the oldest gene classes in humans and their evolution occurs concurrently. These findings confirm non-trivial predictions made by our hypothesis of the possible evolutionary role of hereditary tumors. The results may be important for better understanding of tumor biology. TSEEN genes may become the best tumor markers.

The stromal loss of miR-4516 promotes the FOSL1-dependent proliferation and malignancy of triple negative breast cancer

Stroma-derived exosomal microRNA (exomiR) contributes to tumor progression, however, which remains poorly understood. In our study, we analyzed exomiRs from the cancer-associated fibroblast (CAF) and normal fibroblast (NF) isolated from an invasive ductal carcinoma (IDC) patient and found that the level of microRNA (miR)-4516 was approximately 5-fold lower in CAF-derived exosomes than NF-derived ones. In gene annotation analysis, miR-4516 target genes were mainly associated with the regulation of proliferation. miR-4516 overexpression or mimic treatment suppressed the proliferation of breast cancer cells, especially triple negative breast cancer (TNBC) cells. Among miR-4516 targets, FOSL1 was overexpressed in TNBC cells compared to non-TNBC cells and promoted tumor proliferation. The expression of miR-4516 and FOSL1 was reversely correlated in breast cancer patient tissues. Particularly, TNBC patients with high FOSL1 expression showed a significant poorer survival than those with low FOSL1 expression. Our results show that the loss of miR-4516 from CAF-derived exosomes is associated with FOSL1-dependent TNBC progression and suggest that miR-4516 can be used as an anti-cancer drug for TNBC.

Effect of a high-intensity interval training on serum microRNA levels in women with breast cancer undergoing hormone therapy. A single-blind randomized trial

BACKGROUND

The role of microRNAs (miRs) in hormone therapy (HT) is of keen interest in developing biomarkers and treatments for individuals with breast cancer. Although miRs are often moderate regulators under homeostatic conditions, their function is changed more in response to physical activity.

OBJECTIVE

This single-blind randomized trial aimed to explore the effect of high-intensity interval training (HIIT) on serum levels of miRs in individuals with early-stage breast cancer undergoing HT.

METHODS

Hormone receptor-positive women with breast cancer and healthy women were randomly assigned to a healthy control group (n=15), healthy group with HIIT (n=15), breast cancer group with HT (HT, n=26), and breast cancer group with HT and HIIT (HT+HIIT, n=26). The exercise groups underwent interval uphill walking training on a treadmill 3 times a week for 12weeks. At the end of the study, we analyzed changes in levels of cancer-related miRs (oncomiRs) and tumour suppressor miRs (TSmiRs) in response to the HT and HIIT.

RESULTS

In women with breast cancer versus healthy controls, the expression of some oncomiRs was significantly increased - miR-21 (P<0.001), miR-155 (P=0.001), miR-221 (P=0.008), miR-27a (P<0.001), and miR-10b (P=0.007) - and that of some TSmiRs was significantly decreased - miR-206 (P=0.048), miR-145 (P=0.011), miR-143 (P=0.008), miR-9 (P=0.020), and let-7a (P=0.005). Moreover, HT considerably downregulated oncomiRs and upregulated TSmiRs. HIIT for 12weeks with HT significantly decreased the expression of the oncomiRs and significantly increased that of the TSmiRs as compared with HT alone.

CONCLUSIONS

HITT could amplify the decrease and/or increase in expression of miRs associated with HT in women with breast cancer. A prospective trial could determine whether the use of circulating miRs for monitoring treatment can be useful in therapy decisions.

TRIAL REGISTRATION

Iranian Registry of Clinical Trials (No.: IRCT201202289171N1).

miRDRN-miRNA disease regulatory network: a tool for exploring disease and tissue-specific microRNA regulatory networks

BACKGROUND

MicroRNA (miRNA) regulates cellular processes by acting on specific target genes, and cellular processes proceed through multiple interactions often organized into pathways among genes and gene products. Hundreds of miRNAs and their target genes have been identified, as are many miRNA-disease associations. These, together with huge amounts of data on gene annotation, biological pathways, and protein-protein interactions are available in public databases. Here, using such data we built a database and web service platform, miRNA disease regulatory network (miRDRN), for users to construct disease and tissue-specific miRNA-protein regulatory networks, with which they may explore disease related molecular and pathway associations, or find new ones, and possibly discover new modes of drug action.

METHODS

Data on disease-miRNA association, miRNA-target association and validation, gene-tissue association, gene-tumor association, biological pathways, human protein interaction, gene ID, gene ontology, gene annotation, and product were collected from publicly available databases and integrated. A large set of miRNA target-specific regulatory sub-pathways (RSPs) having the form (T, G 1, G 2) was built from the integrated data and stored, where T is a miRNA-associated target gene, G 1 (G 2) is a gene/protein interacting with T (G 1). Each sequence (T, G 1, G 2) was assigned a p-value weighted by the participation of the three genes in molecular interactions and reaction pathways.

RESULTS

A web service platform, miRDRN (http://mirdrn.ncu.edu.tw/mirdrn/), was built. The database part of miRDRN currently stores 6,973,875 p-valued RSPs associated with 116 diseases in 78 tissue types built from 207 diseases-associated miRNA regulating 389 genes. miRDRN also provides facilities for the user to construct disease and tissue-specific miRNA regulatory networks from RSPs it stores, and to download and/or visualize parts or all of the product. User may use miRDRN to explore a single disease, or a disease-pair to gain insights on comorbidity. As demonstrations, miRDRN was applied: to explore the single disease colorectal cancer (CRC), in which 26 novel potential CRC target genes were identified; to study the comorbidity of the disease-pair Alzheimer's disease-Type 2 diabetes, in which 18 novel potential comorbid genes were identified; and, to explore possible causes that may shed light on recent failures of late-phase trials of anti-AD, BACE1 inhibitor drugs, in which genes downstream to BACE1 whose suppression may affect signal transduction were identified.

Exploration of Novel Biomarkers in Vasculitis by Integrated Bioinfomatic Approaches

Angiitis, also known as vasculitis, is a chronic inflammatory disease characterized by the infiltration of inflammatory cells in surroundings of blood vessels, accompanied by vascular damage including fibrin deposition, collagen fiber degeneration, myocyte, and endotheliocyte necrosis. This work aimed to perform an integrated bioinformatic analysis of three data sets concerning vasculitis to explore and examine the potential diagnostic and therapeutic makers contributing to illuminating the pathomechanisms of vasculitis. We collected three sets of gene expression data designed by dual-channel method from Gene Expression Omnibus, which were based on the same platform (Agilent-014850 Whole Human Genome Microarray 4x44K G4112F). The meta-analysis was used to analyze the gene expression profiles and screen the differentially expressed genes followed by functional features identification. Subsequently, a protein-protein interaction and transcriptional regulation network were conducted for further investigation of expression mechanisms of vasculitis. Totally, 73 consistently upregulated genes, 49 consistently downregulated genes, and 26 genes with different expression directions were identified. Functional enrichment and transcription regulation analysis suggested upregulated genes (PPBP, PLAU, and HIST1H2BH) and downregulated genes such as IL23A gene were predominately associated with immune responses and cytokine receptors function. In addition, specific cancer-related genes such as MRVI1 was also extracted and considered as promising biomarkers of the development and progression of vasculitis. This study established an integrated meta-analysis approach and identified novel biomarkers involved in vasculitis, which further facilitate to explore and unravel the etiopathogenesis of vasculitis.

FRK plays an oncogenic role in non-small cell lung cancer by enhancing the stemness phenotype via induction of metabolic reprogramming

The role of Fyn-related kinase (FRK) in malignant tumors remains controversial. Our study investigated the function of FRK in lung cancer. Immunohistochemistry staining and generating a knockout of FRK by CRISPR/Cas9 in H1299 (FRK-KO-H1299) cells were strategies used to explore the role of FRK. Immunohistochemistry staining indicated that FRK expression was elevated in 223 lung cancer tissues compared to 26 distant normal lung tissues. FRK contributed to poor survival status in lung cancer patients and acted as a predictor for poor prognosis of lung cancer. Knockout of FRK by CRISPR/Cas9 markedly inhibited proliferation, invasion, colony formation and epithelial-mesenchymal transition (EMT) process in the lung cancer cell line H1299. Further exploration indicated that FRK-KO damaged the stemness phenotype of H1299 by inhibiting CD44 and CD133 expression. Seahorse detection and a U-¹³ C flux assay revealed that FRK-KO induced metabolism reprogramming by inhibiting the Warburg effect and changing the energy type in H1299 cells. Epidermal growth factor stimulation recovered the expression of FRK and biological functions, metabolic reprogramming and stemness phenotype of H1299 cells. FRK plays an oncogenic role in lung cancer cells via a novel regulation mechanism of enhancing the stemness of H1299 cells by inducing metabolism reprogramming, which finally promotes EMT and metastasis. Our study also indicates that FRK could be used as a potential therapeutic target for drug development.

Protective potential of miR-146a-5p and its underlying molecular mechanism in diverse cancers: a comprehensive meta-analysis and bioinformatics analysis

Background/aims

Studies have shown that miR-146a-5p was differentially expressed in diverse cancers, but the associations between miR-146a-5p expression and prognosis across multiple types of cancer as well its potential targets and downstream pathways have not been comprehensively analyzed. In this study, we performed the first meta-analysis of the prognostic value of miR-146a-5p expression in diverse malignancies and explored prospective targets of miR-146a-5p and related signaling pathways.

Methods

A thorough search for articles related to miR-146a-5p was performed, and RNA-seq data from The Cancer Genome Atlas (TCGA) and microarray data from gene expression omnibus profiles were used to collect information about the prognostic value of miR-146a-5p. A comprehensive meta-analysis was conducted. Twelve platforms in miRWalk 2.0 were applied to predict targets of miR-146a-5p. TCGA RNA-seq data were used to validate the inverse relationships between miR-146a-5p and its likely targets. Subsequently, gene ontology and pathway analyses were conducted using Funrich version 3.1.3. Potential protein–protein interaction (PPI) networks were constructed. Potential target genes of miR-146a-5p in lung cancer were validated by RT-qPCR.

Results

We included 10 articles in the meta-analysis. In a pooled analysis, the high miR-146a-5p expression group showed a better overall survival in solid cancers, particularly in reproductive system cancers and digestive system cancers. A total of 120 predicted target genes were included in a bioinformatics analysis. Five pathways involving phospholipase C (PLC) and aquaporins (AQPs) were the most significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways. Moreover, the PPI network displayed the related signaling pathways and interactions among proteins. AQP1 and FYN were validated by RT-qPCR to be potential targets of miR-146a-5p in lung cancer.

Conclusion

There is a close link between high miR-146a-5p expression and better overall survival in 21 types of solid cancer, especially in reproductive system and digestive system cancers. Furthermore, miR-146a-5p could inhibit diverse malignancies by modulating pathways linked to PLC or AQPs. In summary, miR-146a-5p is a potential prognostic biomarker and therapeutic target for various cancers.

DNA methylation profiling identifies potentially significant epigenetically-regulated genes in glioblastoma multiforme

Glioblastoma multiforme (GBM) is one of the most lethal and damaging types of human cancer. The current study was conducted to identify differentially methylated genes (DMGs) between GBM and normal controls, and to improve our understanding of GBM at the epigenetic level. The DNA methylation profile of GBM was downloaded from the Gene Expression Omnibus (GEO) database using the accession number GSE50923. The MethyAnalysis package was applied to identify DMGs between GBM and controls, which were then analyzed by functional enrichment analysis. Protein-protein interaction (PPI) networks were constructed using the hypermethylated and hypomethylated genes. Finally, transcription factors (TFs) that can regulate the hypermethylated and hypomethylated genes were predicted, followed by construction of transcriptional regulatory networks. Furthermore, another relevant dataset, GSE22867, was downloaded from the GEO database for data validation. A total of 476 hypermethylated and 850 hypomethylated genes were identified, which were mainly associated with the functions of ‘G-protein-coupled receptors ligand binding’, ‘cytokine activity’, ‘cytokine-cytokine receptor interaction’, and ‘D-glutamine and D-glutamate metabolism’. The hypermethylated gene neuropeptide Y (NPY) and the hypomethylated gene tumor necrosis factor (TNF) demonstrated high degrees in the PPI network. Forkhead box protein A1 (FOXA1), potassium voltage-gated channel subfamily C member 3 (KCNC3) and caspase-8 (CASP8) exhibited high degrees in the transcriptional regulatory networks. In addition, the methylation profiles of NPY, TNF, FOXA1, KCNC3 and CASP8 were confirmed by another dataset. In summary, the present study systematically analyzed the DNA methylation profile of GBM using bioinformatics approaches and identified several abnormally methylated genes, providing insight into the molecular mechanism underlying GBM.

The Role of Long Non-coding RNA Prostate Cancer-Associated Transcript 1 in Prostate Cancer

This study aimed to investigate the role of prostate cancer associated transcript 1 (PCAT1) underlying the molecular mechanisms of prostate cancer. Using GSE29886 data set downloaded from Gene Expression Omnibus database, we screened the differentially expressed genes (DEGs) in PCAT1-siRNA interfering (PCAT1-siRNA) LNCaP cells compared with control-siRNA cells. Transcription factor (TF) and tumor-associated genes database were used to obtain oncogenes and tumor suppressor genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to investigate the function and pathways of DEGs. Subnetwork was further analyzed using BioNet. A total of 93 DEGs were identified. KEGG analysis showed downregulated TF genes (ID1 and ID3) were enriched in transforming growth factor-β pathway, whereas upregulated genes were involved in pathways associated with immune system, environmental sensing, and metabolism. GO analysis showed that downregulated genes were primarily enriched in cell cycle-related biological functions and upregulated DEGs were related to immune response, exogenous genetic material response, and viral response. Centromere protein F (CENPF) was identified as the central node of the regulatory subnetwork. In the PCAT1 knockdown LNCaP cells, the CENPF, ID1, and ID3 were obviously decreased based on the RT-PCR (quantitative real-time reverse transcription PCR) analysis. PCAT1 may be involved in cell cycle and proliferation of prostate cancers by mediating the expression of CENPF, ID1, and ID3.

miR-19 promotes the proliferation of clear cell renal cell carcinoma by targeting the FRK-PTEN axis

Background

The non-receptor tyrosine kinase Fyn-related kinase (FRK) has been reported to affect cell proliferation in several cancer types. However, its effect on the proliferation of clear cell renal cell carcinoma (ccRCC) remains largely unknown.

Purpose

The objective of this study was to investigate the expression pattern and function of FRK in ccRCC. We further determined how FRK interacted with other molecules to regulate ccRCC proliferation.

Patients and methods

The expression of FRK in ccRCC samples and paired normal renal tissues from 30 patients were analyzed by immunoblotting, immunohistochemistry and quantitative PCR. Then the role of FRK in ccRCC proliferation was analyzed by Cell Counting Kit-8, colony formation assay and EdU incorporation assay. In addition, the miRNA targeting FRK was predicted through a bioinformatic approach and validated by quantitative PCR, immunoblotting and luciferase reporter assay. Finally, the underlying mechanism of FRK regulation of ccRCC proliferation was also determined.

Results

Low expression of FRK was detected in ccRCC samples and predicted poor survival for ccRCC patients. FRK inhibited the proliferation of ccRCC cells via phosphorylating downstream PTEN. miR-19 was identified as a novel suppressor of FRK in renal cancer cells and it promoted the proliferation of ccRCC by inhibiting the FRK-PTEN axis.

Conclusion

Our results unravel a new regulatory mechanism involved in ccRCC proliferation and may be useful in the identification of therapeutic targets for ccRCC.

Diagnostic and prognostic value of CEP55 in clear cell renal cell carcinoma as determined by bioinformatics analysis

Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumor. Tumor recurrence and metastasis is the primary cause of cancer-associated mortality in patients with ccRCC. Therefore, identification of efficient diagnostic and prognostic molecular markers may improve survival times. The GSE46699, GSE36895, GSE53000 and GSE53757 gene datasets were downloaded from the Gene Expression Omnibus database and contained 196 ccRCC samples and 164 adjacent normal kidney samples. Bioinformatics analysis was used to integrate the four microarray datasets to identify and analyze differentially expressed genes. Functional analysis revealed that there were 12 genes associated with cancer, based on the tumor-associated gene database. Erb-B2 receptor tyrosine kinase 4, centrosomal protein 55 (CEP55) and vascular endothelial growth factor A are oncogenes, all of which were associated with tumor stage, whereas only CEP55 was significantly associated with survival time as determined by Gene Expression Profiling Interactive Analysis. The mRNA expression levels of CEP55 in ccRCC samples were significantly higher than those observed in adjacent normal kidney tissues based on The Cancer Genome Atlas data and reverse transcription-polymerase chain reaction results. The receiver operating characteristic curve analysis revealed that CEP55 may be considered a diagnostic biomarker for ccRCC with an area under the curve of >0.85 in the training and validation sets. High CEP55 expression was strongly associated with sex, histological grade, stage, T classification, N classification and M classification. Univariate and multivariate Cox proportional hazards analyses demonstrated that CEP55 expression was an independent risk factor for poor prognosis. In addition, gene set enrichment analysis indicated that high CEP55 expression was associated with immunization, cell adhesion, inflammation, the Janus kinase/signal transducer and activator of transcription signaling pathway and cell proliferation. In conclusion, CEP55 was increased in ccRCC samples, and may be considered a potential diagnostic and prognostic biomarker for ccRCC.

Proteogenomic Characterization of Human Early-Onset Gastric Cancer

We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune- and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.

Plasma miR-21, miR-155, miR-10b, and Let-7a as the potential biomarkers for the monitoring of breast cancer patients

There is a pressing need for further studies to categorize and validate circulating microRNAs (miRs) in breast cancer patients that can be one of the novel strategies for cancer screening and monitoring. The present study is aimed to investigate the expression of the circulating candidate microRNAs after the operation, chemotherapy, and radiotherapy in the non-metastatic breast cancer patients. Tumor tissue and plasma samples were collected from the 30 patients with recently diagnosed Luminal A breast cancer. Control plasma samples were collected from the 10 healthy subjects. A panel of four miRs including miR-21, miR-55, miR-10b, and Let-7a were selected and their expression levels were measured before and after the operation, chemotherapy, and radiotherapy by using Real-Time PCR technique. The plasma expression of the miR-21, miR-155, and miR-10b was significantly increased and the Let-7a plasma expression decreased in the breast cancer patients compromised to the control ones. There was a similar expression pattern of the miRs between the tissue and plasma samples. The plasma levels of the miR-21, miR-155, and miR-10b were significantly down-regulated and the Let-7a plasma level was up-regulated after the operation, chemotherapy, and radiotherapy compromised to the pre-treatment. There was a significant difference in the miR-155 plasma level after the operation, chemotherapy, and radiotherapy compromised with each other. Moreover, there was no significant difference between the plasma levels of the miRs after the radiotherapy compromised to the control cases. The operation, chemotherapy, and radiotherapy led to a more reduction in the oncomiRs and an increase in the tumor suppressor-miRs. It seems that monitoring miRs during treatment might be considered as a respectable diagnostic tool for monitoring of breast cancer patients.

The Overexpression of CD80 and ISG15 Are Associated with the Progression and Metastasis of Breast Cancer by a Meta-Analysis Integrating Three Microarray Datasets

Breast cancer is a common cancer and could result in a substantial mortality. The study aimed to screen gene signatures associated with the development and metastasis of breast cancer and explore their regulation mechanisms. Three datasets of GSE10797, GSE8977 and GSE3744 were downloaded from GEO (Gene Expression Omnibus) database, containing 55 breast cancer samples and 27 normal samples. After data preprocessing using limma software and RMA (robust multi-array average) algorithm, DEGs (differentially expressed genes) between breast tumor and normal tissues in three individual experiments were identified using MADAM package. Function and pathway enrichment analyses were performed for the DEGs. Transcription factors and TAGs (tumor associated genes) among the DEGs were recognized and the PPI (protein-protein-interaction) network for the DEGs was constructed using Cytoscape software. The mRNA expression was analyzed via real-time quantitative PCR and protein expression was measured by western blotting. Totally, 100 DEGs were identified, including 33 up-regulated genes and 67 down-regulated genes. Among them, up-regulated DEGs such as CD80 was enriched in toll-like receptor (TLR) interaction pathway and the TAG, ISG15 was related to RIG-I-like receptor signaling pathway, while CXCL10 was involved in both of the two pathways. Whereas, the down-regulated DEG, CXCL12 was significantly associated with axon guidance pathway. Additionally, these DEGs were also pivotal nodes in the PPI network with high degrees. Besides, CXCL10 and CD80 were both interacted with IFNG. The mRNA expression of ISG15 was obviously enhanced in human breast cancer cells MCF-7, while no significant difference of CXCL10 mRNA level was found between MCF10A and MCF-7 cells. Moreover, the proteins expression levels of CD80 and ISG15 were significantly increased in MCF-7, MDA-MB-468 and MDA-MB-231 breast cancer cells than in normal MCF10A cells. CD80 might be responsible for the breast cancer's progression and metastasis via regulating innate immune system. In addition, ISG15 is identified as a crucial gene signature associated with breast cancer development and metastasis via RIG-I-like receptor signaling pathway.

Exploring the molecular pathogenesis associated with T-cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis

As a rare hematological malignancy, T-cell prolymphocytic leukemia (T-PLL) has a high mortality rate. However, the comprehensive mechanisms of the underlying pathogenesis of T-PLL are unknown. The purpose of the present study was to investigate the pathogenesis of T-PLL based on a comprehensive bioinformatics analysis. The differentially expressed genes (DEGs) between T-PLL blood cell samples and normal peripheral blood cell samples were investigated using the GSE5788 Affymetrix microarray data from the Gene Expression Omnibus database. To investigate the functional changes associated with tumor progression, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used on the identified DEGs, followed by protein-protein interaction (PPI) and sub-PPI analysis. Transcription factors and tumor-associated genes (TAGs) were investigated further. The results identified 84 upregulated genes and 354 downregulated genes in T-PLL samples when compared with healthy samples. These DEGs featured in various functions including cell death and various pathways including apoptosis. The functional analysis of DEGs revealed 17 dysregulated transcription factors and 37 dysregulated TAGs. Furthermore, the PPI network analysis based on node degree (a network topology attribute) identified 61 genes, including the core downregulated gene of the sub-PPI network, signal transducer and activator of transcription 3 (STAT3; degree, 13) and the core upregulated gene, insulin receptor substrate-1 (IRS1; degree, 5), that may have important associations with the progression of T-PLL. Alterations to cell functions, including cell death, and pathways, including apoptosis, may contribute to the process of T-PLL. Candidate genes identified in the present study, including STAT3 and IRS1, should be targets for additional studies.

Multiproteomic and Transcriptomic Analysis of Oncogenic β-Catenin Molecular Networks

The dysregulation of Wnt signaling is a frequent occurrence in many different cancers. Oncogenic mutations of CTNNB1/β-catenin, the key nuclear effector of canonical Wnt signaling, lead to the accumulation and stabilization of β-catenin protein with diverse effects in cancer cells. Although the transcriptional response to Wnt/β-catenin signaling activation has been widely studied, an integrated understanding of the effects of oncogenic β-catenin on molecular networks is lacking. We used affinity-purification mass spectrometry (AP-MS), label-free liquid chromatography-tandem mass spectrometry, and RNA-Seq to compare protein-protein interactions, protein expression, and gene expression in colorectal cancer cells expressing mutant (oncogenic) or wild-type β-catenin. We generate an integrated molecular network and use it to identify novel protein modules that are associated with mutant or wild-type β-catenin. We identify a DNA methyltransferase I associated subnetwork that is enriched in cells with mutant β-catenin and a subnetwork enriched in wild-type cells associated with the CDKN2A tumor suppressor, linking these processes to the transformation of colorectal cancer cells through oncogenic β-catenin signaling. In summary, multiomics analysis of a defined colorectal cancer cell model provides a significantly more comprehensive identification of functional molecular networks associated with oncogenic β-catenin signaling.

Exploring the molecular mechanisms of osteosarcoma by the integrated analysis of mRNAs and miRNA microarrays

Osteosarcoma (OS) is the most frequently occurring primary bone malignancy with a rapid progression and poor survival. In the present study, in order to examine the molecular mechanisms of OS, we analyzed the microarray of GSE28425. GSE28425 was downloaded from Gene Expression Omnibus, which also included the miRNA expression profile, GSE28423, and the mRNA expression profile, GSE28424. Each of the expression profiles included 19 OS cell lines and 4 normal bones. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) were screened using the limma package in Bioconductor. The DEGs associated with tumors were screened and annotated. Subsequently, the potential functions of the DEGs were analyzed by Gene Ontology (GO) and pathway enrichment analyses. Furthermore, the protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Furthermore, modules of the PPI network were screened using the ClusterOne plugin in Cytoscape. Additionally, the transcription factor (TF)-DEG regulatory network, DE-miRNA-DEG regulatory network and miRNA-function collaborative network were separately constructed to obtain key DEGs and DE-miRNAs. In total, 1,609 DEGs and 149 DE-miRNAs were screened. Upregulated FOS-like antigen 1 (FOSL1) also had the function of an oncogene. MAD2 mitotic arrest deficient-like 1 (MAD2L1; degree, 65) and aurora kinase A (AURKA; degree, 64) had higher degrees in the PPI network of the DEGs. In the TF-DEG regulatory network, the TF, signal transducer and activator of transcription 3 (STAT3) targeted the most DEGs. Moreover, in the DE-miRNA-DEG regulatory network, downregulated miR-1 targeted many DEGs and estrogen receptor 1 (ESR1) was targeted by several highly expressed miRNAs. Moreover, in the miRNA-function collaborative networks of upregulated miRNAs, miR-128 targeted myeloid dendritic associated functions. On the whole, our data indicate that MAD2L1, AURKA, STAT3, ESR1, FOSL1, miR-1 and miR-128 may play a role in the development and/or progressio of OS.

Identification of potential key genes and high-frequency mutant genes in prostate cancer by using RNA-Seq data

The aim of the present study was to identify potential key genes and single nucleotide variations (SNVs) in prostate cancer. RNA sequencing (RNA-seq) data, GSE22260, were downloaded from the Gene Expression Omnibus database, including 4 prostate cancer samples and 4 normal tissues samples. RNA-Seq reads were processed using Tophat and differentially-expressed genes (DEGs) were identified using the Cufflinks package. Gene Ontology enrichment analysis of DEGs was performed. Subsequently, Seqpos was used to identify the potential upstream regulatory elements of DEGs. SNV was analyzed using Genome Analysis Toolkit. In addition, the frequency and risk-level of mutant genes were calculated using VarioWatch. A total of 150 upregulated and 211 downregulated DEGs were selected and 25 upregulated and 17 downregulated potential upstream regulatory elements were identified, respectively. The SNV annotations of somatic mutations revealed that 65% were base transition and 35% were base transversion. At frequencies ≥2, a total of 17 mutation sites were identified. The mutation site with the highest frequency was located in the folate hydrolase 1B (FOLH1B) gene. Furthermore, 20 high-risk mutant genes with high frequency were identified using VarioWatch, including ribosomal protein S4 Y-linked 2 (RPS4Y2), polycystin 1 transient receptor potential channel interacting (PKD1) and FOLH1B. In addition, kallikrein 1 (KLK1) and PKD1 are known tumor suppressor genes. The potential regulatory elements and high-frequency mutant genes (RPS4Y2, KLK1, PKD1 and FOLH1B) may have key functions in prostate cancer. The results of the present study may provide novel information for the understanding of prostate cancer development.

Bioinformatics analysis of the CDK2 functions in neuroblastoma

The present study aimed to elucidate the potential mechanism of cyclin-dependent kinase 2 (CDK2) in neuroblastoma progression and to identify the candidate genes associated with neuroblastoma with CDK2 silencing. The microarray data of GSE16480 were obtained from the gene expression omnibus database. This dataset contained 15 samples: Neuroblastoma cell line IMR32 transfected with CDK2 shRNA at 0, 8, 24, 48 and 72 h (n=3 per group; total=15). Significant clusters associated with differentially expressed genes (DEGs) were identified using fuzzy C‑Means algorithm in the Mfuzz package. Gene ontology and pathway enrichment analysis of DEGs in each cluster were performed, and a protein‑protein interaction (PPI) network was constructed. Additionally, functional annotation of DEGs in clusters was performed for the detection of transcription factors and tumor‑associated genes. A total of 4 clusters with significant change tendency and 1,683 DEGs were identified. The hub nodes of the PPI network constructed by DEGs in Cluster 1, Cluster 2, Cluster 3 and Cluster 4 were MDM2 oncogene, E3 ubiquitin protein ligase (MDM2), cyclin‑dependent kinase 1 (CDK1), proteasome (prosome, macropain) 26S subunit, non‑ATPase, 14 (PSMD14) and translocator protein (18 kDa) (TSPO) respectively. These genes were significantly enriched in the p53 signaling pathway, cell cycle, proteasome and systemic lupus erythematosus pathways. MDM2, CDK1, PSMD14 and TSPO may be key target genes of CDK2. CDK2 may have key functions in neuroblastoma progression by regulating the expression of these genes.

Genome-Wide Transcriptome Analysis of Estrogen Receptor-Positive and Human Epithelial Growth Factor Receptor 2-Positive Breast Cancers by Ribonucleic Acid Sequencing

AIM

The aim is to identify complex pathogenesis of breast cancer subtypes and disclose the whole landscape of altered transcriptional activities in these cancers.

METHODS

We downloaded raw expression data from public database, and performed transcriptome analysis of 8 estrogen receptor-positive (ER+) breast cancer tissue samples, 8 human epithelial growth factor receptor 2-positive (HER2+) breast cancer tissue samples, and 3 normal breast tissues by identification, functional annotation, and prediction of upstream regulators and cell-surface biomarkers of differentially expressed genes (DEGs).

RESULTS

We identified over 5,000 DEGs in each of ER+ and HER2+ breast cancers compared to normal tissues. Functional enrichment analysis of shared DEGs indicated significant changes in the regulation of immune -systems in the 2 subtypes. We further identified 1,871 DEGs between the 2 subtypes and disclosed great tumor heterogeneity. We identified 533 shared upregulated genes and predicted 17 upstream transcription factors, as well as identified differentially expressed cell-surface biomarkers for distinguishing our ER+ and HER2+ breast cancers. Further analysis also highlighted the limitation of the usage of HER2 alone in breast cancer classification.

CONCLUSION

Our findings in ER+ and HER2+ breast cancers provided novel insights into heterogeneous transcriptional activities underlying complex mechanisms of oncogenesis in breast cancers.

FRK inhibits breast cancer cell migration and invasion by suppressing epithelial-mesenchymal transition

The human fyn-related kinase (FRK) is a non-receptor tyrosine kinase known to have tumor suppressor activity in breast cancer cells. However, its mechanism of action has not been fully characterized. We generated FRK-stable MDA-MB-231 breast cancer cell lines and analyzed the effect on cell proliferation, migration, and invasiveness. We also used kinome analysis to identify potential FRK-regulated signaling pathways. We employed both immunoblotting and RT-PCR to identify/validate FRK-regulated targets (proteins and genes) in these cells. Finally, we interrogated the TCGA and GENT gene expression databases to determine the correlation between the expression of FRK and epithelial/mesenchymal markers. We observed that FRK overexpression suppressed cell proliferation, migration, and invasiveness, inhibited various JAK/STAT, MAPK and Akt signaling pathways, and suppressed the expression of some STAT3 target genes. Also, FRK overexpression increased the expression of epithelial markers including E-cadherin mRNA and down-regulated the transcript levels of vimentin, fibronectin, and slug. Finally, we observed an inverse correlation between FRK expression and mesenchymal markers in a large cohort of breast cancer cells. Our data, therefore, suggests that FRK represses cell proliferation, migration and invasiveness by suppressing epithelial to mesenchymal transition.

Identification of key genes associated with bladder cancer using gene expression profiles

The aim of the present study was to further investigate the molecular mechanisms of bladder cancer. The microarray data GSE52519 were downloaded from Gene Expression Omnibus, comprising 9 bladder cancer and 3 normal bladder tissue samples. Differentially expressed genes (DEGs) were identified using Limma package analysis. Subsequently, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses were performed for down- and upregulated DEGs. Transcription factors and genes associated with cancer from DEGs were identified. Protein-protein interaction (PPI) networks were constructed using STRING, and pathway enrichment analysis was also conducted for genes in the core sub-network that was identified using BioNet. In total, 420 downregulated and 335 upregulated DEGs were identified. Functional and pathway enrichment analyses identified that a number of DEGs, including AURKA, CCNA2, CCNE1, CDC20 and CCNB2, were enriched in the cell cycle. Furthermore, a total of 12 upregulated proto-oncogenes were identified, including AURKA and CCNA2. In the PPI sub-network, a number of DEGs (e.g., CCNB2, CDC20, CCNA2 and MCM6) with higher degrees were enriched in the KEGG pathway of the cell cycle. In conclusion, the DEGs associated with the cell cycle (e.g., CDC20, CCNA2, CCNB2 and AURKA) may serve pivotal roles in the pathogenesis of bladder cancer.

Co-expression network analysis of long noncoding RNAs (IncRNAs) and cancer genes revealsSFTA1P and CASC2abnormalities in lung squamous cell carcinoma

Lung squamous cell carcinoma(LSCC) is the most common and aggressive lung tumor with poor clinical outcome. Previously studies showed that deregulation of long noncoding RNAs (lncRNAs) were involved in LSCC. We intended to figure out the role of lncRNAs in the regulation process of cancer-related genes and pathways they are involved. Data of 552 samples, including 501 cancer samples and 51 normal ones, were extracted from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DEIs) were screened out (FDR<0.05, |logFC|>1) and then followed by GO ontology and KEGG annotation analysis. Oncogenes from COSMIC data set and Tumor suppressor genes (TSGs) from TSGene data set were collected and analyzed by gene Set Enrichment Analysis (GSEA) . The differentially expressed oncogenes and tumor supressor gene (TSGs) were obtained and co-expression analysis was conducted to generate co-expression lncRNA-gene pairs, which can be helpful in figuring out the role of lncRNA in the regulation of oncogenes and tumor suppressor genes. A total of 31 lncRNAs with low expression levels and 37 lncRNAs with high expression levels were screened out and most of them were enriched in pathways such as meiosis, male gamete generation, defensins. Of note, SFTA1P and CASC2 were found to be related with most of the oncogenes and TSGs by co-expression analysis. We suggested SFTA1P and CASC2 played important role in the regulation of both oncogene and TSGs during the carcinogenesis of LSCC and have the potential to be applied in future diagnosis, prognostic process and target therapy of LSCC.

Proteomic profiling of human HepG2 cells treated with hesperidin using antibody array

Protein array technology not only identifies a large number of proteins but also determines their expression levels. In the present study, antibody array analysis is used to decipher the proteins involved in hesperidin-induced cell death in HepG2 cells. Altered proteins in hesperidin treated cells were compared with that of untreated control cells by using a RayBio® Label‑based (L series) human antibody array kit. The identified proteins were further confirmed using western blot analysis. STRING software based analysis was used to determine the protein‑protein interactions. Many proteins related to signal transduction, cellular mechanisms, cell growth and proliferation regulatory proteins were identified. Among the proteins identified Hsp90, Smac/DIABLO, Prdx6 and FRK were significantly reduced in hesperidin treated cells. To the best of the authors' knowledge, the present study is the first to use antibody array for identifying proteins marker in hesperidin‑induced cell death in HepG2 cells. The present study provides a novel insight into the anticancer mechanism of hesperidin.

Molecular mechanisms of breast cancer metastasis by gene expression profile analysis

Metastasis is the main cause of breast cancer‑related mortalities. The present study aimed to uncover the relevant molecular mechanisms of breast cancer metastasis and to explore potential biomarkers that may be used for prognosis. Expression profile microarray data GSE8977, which contained 22 stroma samples (15 were from normal breast and 7 were from invasive ductal carcinoma tumor samples), were obtained from the Gene Expression Omnibus database. Following data preprocessing, differentially expressed genes (DEGs) were selected based on analyses conducted using the linear models for microarray analysis package from R and Bioconductor software. The resulting data were used in subsequent function and pathway enrichment analyses, as well as protein‑protein interaction (PPI) network and subnetwork analyses. Transcription factors (TFs) and tumor‑associated genes were also identified among the DEGs. A total of 234 DEGs were identified, which were enriched in immune response, cell differentiation and cell adhesion‑related functions and pathways. Downregulated DEGs included TFs, such as the proto‑oncogene SPI1, pre‑B‑cell leukemia homeobox 3 (PBX3) and lymphoid enhancer‑binding factor 1 (LEF1), as well as tumor suppressors (TSs), such as capping actin protein, gelsolin like (CAPG) and tumor protein p53‑inducible nuclear protein 1 (TP53INP1). Upregulated DEGs also included TFs and tumor suppressors, consisting of transcription factor 7‑like 2 (TCF7L2) and pleiomorphic adenoma gene‑like 1 (PLAGL1). DEGs that were identified at the hub nodes in the PPI network and the subnetwork were epidermal growth factor receptor (EGFR) and spleen‑associated tyrosine kinase (SYK), respectively. Several genes crucial in the metastasis of breast cancer were identified, which may serve as potential biomarkers, many of which were associated with cell adhesion, proliferation or immune response, and may influence breast cancer metastasis by regulating these function or pathways.

Bioinformatics analysis of transcription profiling of solid pseudopapillary neoplasm of the pancreas

Solid pseudopapillary neoplasm (SPN) of the pancreas is a low-grade malignant neoplasm that accounts for ~5% of cystic pancreatic tumors and ~0.9–2.7% of exocrine pancreatic tumors. The transcription profiling data (GSE43795) of 14 SPN and 6 control samples were downloaded from the Gene Expression Omnibus (GEO) database. Using the Limma package, Student's t-tests were performed to identify differentially expressed genes (DEGs) between SPN and control samples [with the following criterion: False discovery rate (FDR)<0.01 and log₂ fold-change (FC)≥3]. Pathway and functional enrichment analyses were performed to investigate the biological processes that the DEGs were involved in. Protein-protein interaction (PPI) network and sub-network analyses were conducted to comprehensively understand the interactions between DEGs. The screened DEGs were further annotated according to information relating to transcription factors and tumor associated genes (TAGs). A total of 710 upregulated and 710 downregulated DEGs were observed, including 74 transcriptional factors and 124 TAGs. Membrane metallo-endopeptidase (MME), matrix metalloproteinase (MMP)-2 and MMP-9 were also identified as key TAGs. Following PPI network analysis, hub nodes of epidermal growth factor receptor (EGFR), proto-oncogene tyrosine protein kinase Fyn (FYN), c-JUN (JUN), glucagon (GCG), c-Myc (MYC) and CD44 were identified, the majority of which participate in the epidermal growth factor receptor (ErbB) and gonadotropin-releasing hormone (GnRH) signaling pathways. A sub-network involving 70 gene nodes was also identified, with EGFR as the central gene. MME, MMP-2 and MMP-9 contribute to proliferative diabetic retinopathy and also involved in SPN. The genes EGFR, FYN, JUN, GCG, MYC and CD44 may therefore be key genes in SPN, and the ErbB and GnRH signaling pathways may be an important contributor to SPN progression.

An integrative analysis of DNA methylation in osteosarcoma

Background

The study aimed to analyze aberrantly methylated genes, relevant pathways and transcription factors (TFs) in osteosarcoma (OS) development.

Methods

Based on the DNA methylation microarray data GSE36002 that were downloaded from GEO database, the differentially methylated genes in promoter regions were identified between OS and normal samples. Pathway and function enrichment analyses of differentially methylated genes was performed. Subsequently, protein-protein interaction (PPI) network was constructed, followed by identification of cancer-associated differentially methylated genes and significant differentially methylated TFs.

Results

A total of 1379 hyper-methylation regions and 169 hypo-methylation regions in promoter regions were identified in OS samples compared to normal samples. The differentially hyper-methylated genes were significantly enriched in Neuroactive ligand-receptor interaction pathway, and Peroxisome proliferator activated receptor (PPAR) signaling pathway. The differentially hypo-methylated genes were significantly enriched in Toll-like receptor signaling pathway. In PPI network, signal transducers and activators of transcription (STAT3) had high degree (degree=21). MAX interactor 1, dimerization protein (MXI1), STAT3 and T-cell acute lymphocytic leukemia 1 (TAL1) were significant TFs enriched with target genes in OS samples. They were found to be cancer-associated and hyper-methylated in OS samples.

Conclusion

Neuroactive ligand-receptor interaction, PPAR signaling, Toll-like receptor signaling pathways are implicated in OS. MXI1, STAT3, and TAL1 may be important TFs involved in OS development.

Silencing TAK1 alters gene expression signatures in bladder cancer cells

The aim of the present study was to identify the differentially expressed genes (DEGs) that are induced by the silencing of transforming growth factor-β-activated kinase 1 (TAK1) in bladder cancer cells and to analyze the potential biological effects. Dataset GSE52452 from mutant fibroblast growth factor receptor 3 (FGFR3) bladder cancer cells transfected with control siRNA or TAK1-specific siRNA was downloaded from Gene Expression Omnibus. The DEGs between the two groups were identified using Limma package following data pre-processing by Affy in Bioconductor. Enrichment analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery, followed by functional annotation using TRANSFAC, TSGene and TAG databases. Integrated networks were constructed by Cytoscape and sub-networks were extracted employing BioNet, followed by enrichment analysis of DEGs in the sub-network. A total of 43 downregulated and 21 upregulated genes were obtained. The downregulated genes were enriched in five pathways, including NOD-like receptor signaling pathway and functions related to cellular response. The upregulated genes were associated with cellular developmental processes. Transcription factor EGR1 and 9 tumor-associated genes were screened from the DEGs. Among the DEGs, 10 hub nodes may represent important roles in the complex metabolic network, including EGFR, CYP3A5, MAP3K7, GSTA1, PTHLH, ALDH1A1, KCND2, EGR1, ARRB1 and ITPR1. Additionally, EGFR was correlated with ERBB2, GRB2 and PIK3R1, and these were enriched in ErbB signaling pathway and various cancer-associated pathways. Silencing TAK1 may decrease cellular response to chemical stimulus via downregulating CYP3A5, MAP3K7, GSTA1, ALDH1A1, ARRB1 and ITPR1; increase cancer cell development via upregulating EGFR, EGR1 and PTHLH; and regulate cancer metastasis through EGFR, ERBB2, GRB2 and PIK3R1.

Analysis of gene expression changes associated with human carcinoma-associated fibroblasts in non-small cell lung carcinoma

Background

This study aimed to investigate the gene expression changes associated with carcinoma-associated fibroblasts (CAFs) involving in non-small cell lung carcinoma (NSCLC).

Methods

We downloaded the GEO series GSE22862, which contained matched gene expression values for 15 CAF and normal fibroblasts samples, and series GSE27289 containing SNP genotyping for four matched NSCLC samples. The differentially expressed genes in CAF samples were identified using the limma package in R. Then we performed gene ontology (GO) and pathway enrichment analysis and protein–protein interaction (PPI) network construction using the identified DEGs. Moreover, aberrant cell fraction, ploidy, allele-specific copy number, and loss of heterozygosity (LOH) within CAF cells were analyzed using the allele-specific copy number analysis.

Results

We obtained 545 differentially expressed genes between CAF and normal fibroblasts samples. The up-regulated genes are mainly involved in GO terms such as positive regulation of cell migration and extracellular region, while the down-regulated genes participate in the lung development and extracellular region. Multiple genes including bone morphogenetic protein 4 (BMP4) and transforming growth factor, beta 3 (TGFB3) are involved in the TGF-β signaling pathway. Genes including BMP4, TGFBI and matrix Gla protein (MGP) were hub genes. Moreover, no LOH event for BMP4 and MGP was found, that for sphingosine kinase 1 (SPHK1) was 70%, and for TGFBI was 40%.

Conclusion

Our data suggested that BMP4, MGP, TGFBI, and SPHK1 may be important in CAFs-associated NSCLC, and the abnormal expression and high LOH frequency of them may be used as the diagnosis targets of CAFs in NSCLC.

Identification of molecular characteristics induced by radiotherapy in rectal cancer based on microarray data

The present study aimed to reveal the molecular characteristics induced by radiotherapy in rectal cancer at the transcriptome level. Microarray data (ID, GSE26027) downloaded from the Gene Expression Omnibus database were re-analyzed to identify differentially expressed genes (DEGs) between rectal cancer tissues during and prior to radiotherapy. The DEGs were then inputted into the database for annotation, visualization and integrated discovery, an online tool to perform enrichment analyses, and into the search tool for the retrieval of interacting genes/proteins database to identify protein-protein interactions (PPIs). Subsequently, a PPI network was constructed, which was screened for densely connected modules. Furthermore, protein domain enrichment analysis was performed. In total, 690 DEGs, including 179 upregulated and 511 downregulated DEGs, were found in rectal cancer tissues during and prior to radiotherapy. The upregulated DEGs were significantly enriched in 'positive regulation of transport' and 'regulation of cardiac muscle contraction', while the downregulated DEGs were most markedly enriched in 'cell migration', 'cell-cell signaling', 'extracellular matrix organization' and 'blood vessel development', including prostaglandin-endoperoxide synthase 2, transforming growth factor β-induced, 68 kDa endothelin receptor type A, brain-derived neurotrophic factor, TIMP metallopeptidase inhibitor 1, and serpin family E member 1, which were the top 6 hub nodes in the PPI network. Furthermore, 2 protein domains were significantly enriched by PPI modules, including: The collagen triple helix repeat (CTHR) family members collagen type (COL) 5A2, COL9A3, COL6A3, COL21A1, COL5A3, COL11A1, COL7A1 and CTHR-containing-1; and the olfactory receptor family (OR) members OR7E24, OR7A17, OR6A2, OR1F1, OR10H3 and OR7A10. A total of 7 upregulated DEGs were characterized as tumor suppressor genes, and 8 downregulated DEGs were characterized as oncogenes. The biological processes or protein domains enriched by upregulated or downregulated DEGs may improve the understanding of molecular characteristics in response to radiotherapy.