Identification of hub genes, key miRNAs and potential molecular mechanisms of colorectal cancer

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis

PURPOSE

To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

METHODS

Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

RESULTS

There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

CONCLUSIONS

The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

CircABCB10 Promotes the Apoptosis and Inflammatory Response of 16HBE Cells by Cigarette Smoke Extract by Targeting miR-130a/PTEN Axis

Background

Chronic obstructive pulmonary disease (COPD) has become a global public health problem due to its high mortality. So there is an urgent need to find an effective treatment.

Methods

The targeting relationship among circABCB10, miR-130a and PTEN was predicted by the targetscan database (TargetScanHuman 8.0, https://www.targetscan.org/vert_80/). A total of 60 patients which were from the second affiliated hospital of Qiqihar Medical University from 2022 to 2023 were enrolled. The lung condition was detected by CT (Computed Tomography). The expression levels of circABCB10, miR-130a and PTEN in lung tissues were determined by qRT-PCR. The COPD model was established by stimulating normal and silenced 16HBE cells in circABCB10 genes with cigarette smoke extract (CSE) at different concentrations. qRT-PCR was conducted for the expression levels of circABCB10, miR-130a and PTEN, WB for the expression levels of apoptotic proteins, ELISA for the content of inflammatory factors, and CCK8 for the effect of CSE on the proliferation of cells.

Results

CircABCB10 expression increased in lung tissues from patients with COPD and in 16HBE cells treated with CSE. The stimulation on cells with CSE increased the expression of inflammatory factors, while knocking down circABCB10 could reverse this response. The inflammatory response to the knockdown of circABCB10 was reversed by miR-130a inhibitor, which increased the expression of c-caspase 3. The targetscan database predicted the target factor downstream miR-130a was PTEN. Transfecting OE-PTEN reversed the inflammation of knocking down circABCB10, and increased the apoptosis and inflammation.

Conclusion

CircABCB10 can cause the inflammatory response by targeting miR-130a/PTEN axis, which is a mechanism that may lead to the occurrence and development of COPD.

DNMT1-mediated NR3C1 DNA methylation enables transcription activation of connexin40 and augments angiogenesis during colorectal cancer progression

Colorectal cancer (CRC) continues to be a major contributor to cancer-related mortality. Connexin 40 (CX40) is one of the major gap junction proteins with the capacity in regulating cell-to-cell communication and angiogenesis. This study investigates its role in angiogenesis in CRC and explores the regulatory mechanism. Aberrant high CX40 expression was detected in tumor tissues, which was associated with a poor prognosis in CRC patients. Elevated CX40 expression was detected in CRC cell lines as well. Conditioned medium of SW620 and HT29 cell lines was used to induce angiogenesis of human umbilical vein endothelial cells (HUVECs). CX40 knockdown in CRC cells reduced angiogenesis and mobility of HUVECs and blocked CRC cell proliferation, mobility, and survival. Following bioinformatics predictions, we validated by chromatin immunoprecipitation and luciferase assays that nuclear receptor subfamily 3 group C member 1 (NR3C1), which was poorly expressed in CRC samples, suppressed CX40 transcription. The poor NR3C1 expression was attributive to DNA hypermethylation induced by DNA methyltransferase 1 (DNMT1). Restoration of NR3C1 suppressed the pro-angiogenic effect, proliferation and survival, and tumorigenic activity of CRC cells, which were, however, rescued by CX40 upregulation. Collectively, this study demonstrates that transcription activation of CX40 upon DNMT1-mediated NR3C1 DNA methylation potentiates angiogenesis in CRC.

The impact of SLC10A3 on prognosis and immune microenvironment in colorectal adenocarcinoma

BACKGROUND

SLC10A3, a gene upregulated in pan-cancer, lacks full understanding regarding its prognostic implications and association with immune infiltration in colorectal cancer (CRC). This study comprehensively analyzed SLC10A3 in CRC, evaluating its prognostic significance and influence on the tumor's immune microenvironment.

METHODS

Transcriptomic data from TCGA were obtained to compare SLC10A3 expression in both colorectal cancer (CRC) and normal tissues. Prognostic value was assessed for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). DNA methylation patterns of SLC10A3 and correlation with DNA mismatch repair (MMR) were explored. Genetic alterations in SLC10A3 were scrutinized. The study also delved into the influence of SLC10A3 on the immune microenvironment of CRC, including immune cell infiltration and chemokines. Involvement of cancer-associated fibroblasts (CAFs) was explored. Methylation status of specific CpG islands in the SLC10A3 gene correlated with CRC patient prognosis. CRC tissue microarray was performed to verify the expression of SLC10A3 and its relationship with prognosis.

RESULTS

The research revealed that SLC10A3 is significantly upregulated in CRC and holds promise as a potential diagnostic marker. Elevated SLC10A3 expression was linked to poorer OS, DSS, and PFI. Methylation patterns of SLC10A3 displayed prognostic relevance, and genetic alterations in the gene were identified. SLC10A3 was shown to impact the immune microenvironment, with significant correlations observed between its expression and various immune cell types, chemokines, and markers associated with CAFs. Furthermore, an inverse relationship between SLC10A3 and MMR molecules was established. Methylation status of specific CpG islands within the SLC10A3 gene was associated with CRC patient prognosis. Tissue microarray showed that SLC10A3 was highly expressed in CRC and significantly correlated with poor prognosis.

CONCLUSION

The study underscores the importance of elevated SLC10A3 in CRC, associating it with decreased survival and immune infiltration, proposing it as a diagnostic biomarker and appealing immunotherapy target, given its significant overexpression and influence on the immune microenvironment and prognosis through methylation patterns.

Identification of candidate biomarkers and prognostic analysis of recurrence in colorectal cancer

Colorectal cancer (CRC) is one of the most common digestive tract malignant tumors, which has a high mortality rate especially for patients with CRC recurrence. However, the pathological mechanism of recurrence of CRC is unclear. In this study, we integrated multiple cohort datasets and databases to clarify and verify potential key candidate biomarkers and signal transduction pathways in recurrence of CRC. As results, 628 DEGs were identified from GSE33113 and GSE2630 datasets and their function and pathway were analyzed. 14 hub genes related to CRC recurrence were screened from and their influence on survival were analyzed. Two key genes (IL1B and DDAH1) regarded as prognostic factors were further screened. Relapse-free survival results indicated the interaction between IL1B and DDAH1 genes and B cells was the most obvious and correlated with survival, with statistical significance (P< 0.05). Specially, cox regression analysis suggested that patients with T1 and N0 stages had a higher risk of recurrence than patients with T2 and N1. This work would provide potential value for prognosis, and would promote molecular targeting therapy for CRC recurrence.

Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor

Wilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein-protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.

Kinase Inhibitors in Genetic Diseases

Over the years, several studies have shown that kinase-regulated signaling pathways are involved in the development of rare genetic diseases. The study of the mechanisms underlying the onset of these diseases has opened a possible way for the development of targeted therapies using particular kinase inhibitors. Some of these are currently used to treat other diseases, such as cancer. This review aims to describe the possibilities of using kinase inhibitors in genetic pathologies such as tuberous sclerosis, RASopathies, and ciliopathies, describing the various pathways involved and the possible targets already identified or currently under study.

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.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

MiR-552-3p facilitated cell proliferation, migration and invasion by sponging Fibulin 5 in non-small cell lung cancer via activation of ERK/GSK3β/β-catenin signaling pathway

Apart from the fact that miR-552-3p is known to promote cell progression among various cancers, its function on non-small cell lung cancer (NSCLC) is unknown which therefore emerges as the purpose of this research. TargetScan, Starbase, miRWalk, miRDB and the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) were utilized to analyze the target genes of miR-552-3p. NSCLC cells were transfected with miR-552-3p mimic, miR-552-3p inhibitor, Fibulin 5 (FBLN5) overexpression plasmid, and small interfering FBLN5 (siFBLN5) and treated with extracellular regulated protein kinases (ERK) pathway inhibitor PD98059. MiR-552-3p, FBLN5, p-ERK, ERK, p-glycogen synthase kinase 3β (GSK3β) and β-catenin levels were detected through quantitative reverse transcription-polymerase chain reaction and western blot. The binding sites between miR-552-3p and FBLN5 were predicted by TargetScan, which was tested through dual luciferase reporter analysis. Cell viability, migration and invasion were determined by cell counting kit-8 (CCK-8) assay, wound healing assay and transwell assay, respectively. MiR-552-3p expression was upregulated in NSCLC and FBLN5 functioned as its target. MiR-552-3p mimic promoted proliferation, migration, invasion, p-ERK, p-GSK3β and β-catenin expressions in NSCLC cells while miR-552-3p inhibitor did the opposite. Overexpressed FBLN5 suppressed proliferation, migration, invasion, p-ERK, p-GSK3β and β-catenin expressions in NSCLC cells whereas siFBLN5 exerted the effects opposite to overexpressed FBLN5. PD98059 enhanced the effect of overexpressed FBLN5 on NSCLC cell migration and invasion while reversing the effect of siFBLN5. MiR-552-3p facilitated cell proliferation, migration and invasion in NSCLC through sponging FBLN5 via activation of ERK/GSK3β/β-catenin pathway.

Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Biomarker discovery is critical to improve CRC diagnosis, however, machine learning offers a new platform to study the etiology of CRC for this purpose. Therefore, the current study aimed to perform an integrated bioinformatics and machine learning analyses to explore novel biomarkers for CRC prognosis. In this study, we acquired gene expression microarray data from Gene Expression Omnibus (GEO) database. The microarray expressions GSE103512 dataset was downloaded and integrated. Subsequently, differentially expressed genes (DEGs) were identified and functionally analyzed via Gene Ontology (GO) and Kyoto Enrichment of Genes and Genomes (KEGG). Furthermore, protein protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software to identify hub genes; however, the hub genes were subjected to Support Vector Machine (SVM), Receiver operating characteristic curve (ROC) and survival analyses to explore their diagnostic values. Meanwhile, TCGA transcriptomics data in Gene Expression Profiling Interactive Analysis (GEPIA) database and the pathology data presented by in the human protein atlas (HPA) database were used to verify our transcriptomic analyses. A total of 105 DEGs were identified in this study. Functional enrichment analysis showed that these genes were significantly enriched in biological processes related to cancer progression. Thereafter, PPI network explored a total of 10 significant hub genes. The ROC curve was used to predict the potential application of biomarkers in CRC diagnosis, with an area under ROC curve (AUC) of these genes exceeding 0.92 suggesting that this risk classifier can discriminate between CRC patients and normal controls. Moreover, the prognostic values of these hub genes were confirmed by survival analyses using different CRC patient cohorts. Our results demonstrated that these 10 differentially expressed hub genes could be used as potential biomarkers for CRC diagnosis.

Investigating the Mechanism of Scutellariae barbata Herba in the Treatment of Colorectal Cancer by Network Pharmacology and Molecular Docking

Background

Colorectal cancer (CRC) is one of the most common gastrointestinal tumors, which accounts for approximately 10% of all diagnosed cancers and cancer deaths worldwide per year. Scutellariae barbatae Herba (SBH) is one of the most frequently used traditional Chinese medicine (TCM) in the treatment of CRC. Although many experiments have been carried out to explain the mechanisms of SBH, the mechanisms of SBH have not been illuminated fully. Thus, we constructed a network pharmacology and molecular docking to investigate the mechanisms of SBH.

Methods

We adopted active constituent prescreening, target predicting, protein-protein interaction (PPI) analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, differentially expressed gene analysis, and molecular docking to establish a system pharmacology database of SBH against CRC.

Results

A total of 64 active constituents of SBH were obtained and 377 targets were predicted, and the result indicated that quercetin, luteolin, wogonin, and apigenin were the main active constituents of SBH. Glucocorticoid receptor (NR3C1), pPhosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA), cellular tumor antigen p53 (TP53), transcription factor AP-1 (JUN), mitogen-activated protein kinase 1 (MAPK1), Myc protooncogene protein (MYC), cyclin-dependent kinase 1 (CDK1), and broad substrate specificity ATP-binding cassette transporter ABCG2 (ABCG2) were the major targets of SBH in the treatment of CRC. GO analysis illustrated that the core biological process regulated by SBH was the regulation of the cell cycle. Thirty pathways were presented and 8 pathways related to CRC were involved. Molecular docking presented the binding details of 3 key targets with 6 active constituents.

Conclusions

The mechanisms of SBH against CRC depend on the synergistic effect of multiple active constituents, multiple targets, and multiple pathways.

SGK1 in Human Cancer: Emerging Roles and Mechanisms

Serum and glucocorticoid-induced protein kinase 1 (SGK1) is a member of the "AGC" subfamily of protein kinases, which shares structural and functional similarities with the AKT family of kinases and displays serine/threonine kinase activity. Aberrant expression of SGK1 has profound cellular consequences and is closely correlated with human cancer. SGK1 is considered a canonical factor affecting the expression and signal transduction of multiple genes involved in the genesis and development of many human cancers. Abnormal expression of SGK1 has been found in tissue and may hopefully become a useful indicator of cancer progression. In addition, SGK1 acts as a prognostic factor for cancer patient survival. This review systematically summarizes and discusses the role of SGK1 as a diagnostic and prognostic biomarker of diverse cancer types; focuses on its essential roles and functions in tumorigenesis, cancer cell proliferation, apoptosis, invasion, metastasis, autophagy, metabolism, and therapy resistance and in the tumor microenvironment; and finally summarizes the current understanding of the regulatory mechanisms of SGK1 at the molecular level. Taken together, this evidence highlights the crucial role of SGK1 in tumorigenesis and cancer progression, revealing why it has emerged as a potential target for cancer therapy.

Prognostic Model of Colorectal Cancer Constructed by Eight Immune-Related Genes

Background

Colorectal cancer (CRC) is a common malignant tumor of the digestive tract with a high mortality rate. Growing evidence demonstrates that immune-related genes play a prominent role in the occurrence and development of CRC. The aim of this study was to investigate the prognostic value of immune-related genes in CRC.

Methods

Gene expression profiles and clinical data of 568 CRC and 44 non-tumorous tissues were obtained from The Cancer Genome Atlas (TCGA) database. First, we performed a differentially expressed gene (DEG) analysis and univariate Cox regression analysis to determine the DEGs associated with overall survival. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently performed for prognostic immune-related genes. Then, a multivariate Cox regression analysis was performed to establish the immune prognostic model and identify the independent prognostic factors of CRC. Next, in vitro experiments were done to further validate the model. Finally, we analyzed the correlation among immune-related genes, clinical traits, and immune cell infiltration.

Results

In total, 3,702 DEGs were obtained, and 338 prognostic immune-related genes were identified. Among them, 45 genes were significantly correlated with the prognosis of CRC patients. A TF-mediated network was set up to explore its internal mechanism. GO and KEGG analyses further illustrated that these genes were enriched in immune-and inflammatory-related pathways. Then, a prognostic prediction model composed of eight immune-related genes (SLC10A2, UTS2, FGF2, UCN, IL1RL2, ESM1, ADIPOQ, and VIP) was constructed. The AUC of the ROC curve for 1, 3, 5, and 10 years overall survival (OS) was 0.751, 0.707, 0.680, and 0.729, respectively. The survival analysis suggested that the OS of the high-risk group was significantly poorer than that of the low-risk group. Meanwhile, in vitro assays revealed that ESM1 and SLC10A2 exert opposing roles in colon cancer cell proliferation, validating the accuracy of the model. The correlation analysis indicated that immune cell infiltration was positively related to the model.

Conclusion

This study screened prognosis-related immune genes and developed a prognostic prediction model of CRC. These findings may help provide potential novel prognostic biomarkers and therapeutic targets for CRC. At the same time, the understanding of the CRC immune microenvironment status was deepened.

Desmoglein 3 and Keratin 14 for Distinguishing Between Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Background

Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the leading major histological phenotypes of all non-small cell lung cancer (NSCLC). In this study, the candidate genes and the potential tumorigenesis distinguishing between LUAD and LUSC were analyzed.

Methods

The present study investigated two microarray datasets (GSE28571 and GSE10245) downloaded from the Gene Expression Omnibus (GEO) database. A protein–protein interaction (PPI) network was applied to screen out the candidate genes. In addition, differently expressed genes (DEGs) between lung adenocarcinoma and lung squamous cell carcinoma of the two datasets were functionally analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. R 4.0.2 was used to perform Kaplan–Meier analysis of DSG3 (desmoglein 3) and KRT14 (keratin 14) by analyzing the expression and clinical data from The Cancer Genome Atlas (TCGA) database.

Results

The results revealed that 47 DEGs of the two datasets were ascertained in our study. It was found that the DEGs were mainly involved in pathways related to p63 transcription factor network and validated transcriptional factor targeting TAp63, etc. Based on the analysis, we finally identified DSG3 and KRT14 as potential biomarkers for distinguishing between LUAD and LUSC. These results suggested that DSG3 and KRT14 could have the potential to play an important role in NSCLC patients, as diagnostic markers. At the same time, DSG3 or KRT14 indicated a worse prognosis in LUSC patients, which were associated with pathways relevant to the TRAIL signaling pathway and TNF receptor signaling pathway according to bioinformatic analysis.

Conclusion

The DSG3 and KRT14 have the potential to be used as diagnostic markers, which presented here may facilitate improvements in distinguishing between LUAD and LUSC in advanced NSCLC patients.

The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer

Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients.

MALAT1/miR-15b-5p/MAPK1 mediates endothelial progenitor cells autophagy and affects coronary atherosclerotic heart disease via mTOR signaling pathway

Objective: Present study focused on the influence of lncRNA MALAT1 on coronary atherosclerotic heart disease (CAD) by regulating miR-15b-5p/MAPK1 and mTOR signaling pathway.

Method: Differentially expressed genes and activated pathway were investigated through bioinformatics analysis. QRT-PCR was conducted to verify expression of MALAT1, miR-15b-5p and MAPK1 in CAD blood samples and endothelial progenitor cells (EPCs). In addition, the interactions among MALAT1, miR-15b-5p and MAPK1 were revealed by Luciferase reporter assay. Cell autophagy of EPCs was examined by Cyto-ID Autophagy Detection Kit and transmission electron microscope. MTT assay and flow cytometry were carried out to assess cell viability and apoptosis in different interference conditions. Western blot was performed to testify the expression of pERK1/2 (MAPK1), phosphorylated mTOR, ATG1 and LC3-II. Vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) were detected by qRT-PCR. Finally, the effect of lncRNA MALAT1 on cell autophagy and atherogenesis was tested in vivo.

Results: MALAT1 was overexpressed in CAD blood samples and EPCs. Knockdown of MALAT1 and MAPK1 promoted cell viability, autophagy and further suppressed the development of CAD. AntagoMALAT1 protects mice against atherosclerosis.

Conclusion: LncRNA MALAT1 inhibited EPCs autophagy and increased cell viability while repressed apoptosis of CAD via activating mTOR signaling pathway.

Integrated analysis of key microRNAs /TFs /mRNAs/ in HPV-positive cervical cancer based on microRNA sequencing and bioinformatics analysis

BACKGROUND

Cervical squamous cell carcinoma (CESC) is one of the most common malignancies associated with mortality in females. Its onset and prognosis are primarily concerned with persistent infection with high-risk types of human papillomavirus (HPV). However, the molecular mechanisms of HPV-positive CESC remain unclear.

METHODS

In this study, we conducted a high-throughput sequencing to identify differentially expressed miRNAs (DEMs). Besides, three series were selected from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Then the miRNA-TF-gene regulatory network was constructed using bioinformatic methods. Genes in the network were performed functional enrichment analysis and protein-protein interaction (PPI) network analysis. Ultimately, the expression levels of six key miRNAs, TFs, and mRNAs were validated by 20 HPV-positive CESC tissues and 15 normal cervical samples.

RESULTS

A total of 52 DEMs and 300 DEGs differed between the HPV-positive CESC and normal cervical samples. Then the miRNA-TF-gene regulatory network was constructed consisting of 22 miRNAs, 6 TFs, and 76 corresponding genes, among which miR-149-5p, miRNA-1248 and E2F4 acted as key regulators. PPI network analysis showed that ten genes including TOP2A, AURKA, CHEK1, KIF11, MCM4, MKI67, DTL, FOXM1, SMC4, and FBXO5 were recognized as hub genes with the highest connectivity degrees. Besides, five key molecules miRNA-149-5p, E2F4, KIF11, DTL, and SMC4 were suggested to play crucial roles in the development of HPV-positive CESC.

CONCLUSION

These results present a unique insight into the pathological mechanisms of HPV-positive CESC and possibly provides potential therapeutic targets.

Comprehensive transcriptome profiling of Taiwanese colorectal cancer implicates an ethnic basis for pathogenesis

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. While both genetic and environmental factors have been linked to the incidence and mortality associated with CRC, an ethnic aspect of its etiology has also emerged. Since previous large-scale cancer genomics studies are mostly based on samples of European ancestry, the patterns of clinical events and associated mechanisms in other minority ethnic patients suffering from CRC are largely unexplored. We collected 104 paired and adjacent normal tissue and CRC tumor samples from Taiwanese patients and employed an integrated approach - paired expression profiles of mRNAs and microRNAs (miRNAs) combined with transcriptome-wide network analyses - to catalog the molecular signatures of this regional cohort. On the basis of this dataset, which is the largest ever reported for this type of systems analysis, we made the following key discoveries: (1) In comparison to the The Cancer Genome Atlas (TCGA) data, the Taiwanese CRC tumors show similar perturbations in expressed genes but a distinct enrichment in metastasis-associated pathways. (2) Recurrent as well as novel CRC-associated gene fusions were identified based on the sequencing data. (3) Cancer subtype classification using existing tools reveals a comparable distribution of tumor subtypes between Taiwanese cohort and TCGA datasets; however, this similarity in molecular attributes did not translate into the predicted subtype-related clinical outcomes (i.e., death event). (4) To further elucidate the molecular basis of CRC prognosis, we developed a new stratification strategy based on miRNA-mRNA-associated subtyping (MMAS) and consequently showed that repressed WNT signaling activity is associated with poor prognosis in Taiwanese CRC. In summary, our findings of distinct, hitherto unreported biosignatures underscore the heterogeneity of CRC tumorigenesis, support our hypothesis of an ethnic basis of disease, and provide prospects for translational medicine.

Application of cAMP-dependent catalytic subunit β (PRKACB) Low Expression in Predicting Worse Overall Survival: A Potential Therapeutic Target for Colorectal Carcinoma

Low expressions of PRKACB are related to the occurrence of various human malignancies. However, the prognostic value of PRKACB expression in colorectal cancer (CRC) patients remains controversial. In this analysis, PRKACB expression in CRC tumors was evaluated across the GEO, TCGA, and Oncomine databases, and a PRKACB survival analysis was performed based on the TCGA profile. We detected PRKACB in 7 GEO series (GSE110225, GSE32323, GSE44076, GSE9348, GSE41328, GSE21510, GSE68468) and TCGA spectra (all P <0.05). A meta-analysis performed in the Oncomine database revealed that PRKACB was significantly up-regulated in neoplastic tissues compared to normal tissues (all P <0.05). A Kaplan-Meier analysis demonstrated that lower PRKACB expression in tumors was significantly associated with poorer overall survival (OS) in patients with CRC (P <0.05). A subgroup analysis showed that low expression of PRKACB correlated with poor 1-, 3-, and 5-year OS (all P <0.05). Furthermore, in males (P = 0.0083), whites (P = 0.0463), and non-mucinous adenocarcinoma patients (P = 0.0108), the down-regulation of PRKACB expression was more significant for the OS prognostic value. Conclusion: PRKACB is down-regulated in tumors and associated with worsening OS in CRC patients.

Screening of potential biomarkers and their predictive value in early stage non-small cell lung cancer: a bioinformatics analysis

BACKGROUND

Non-small cell lung cancer (NSCLC) remains the first leading cause of death in malignancies worldwide. Despite the early screening of NSCLC by low-dose spiral computed tomography (CT) in high-risk individuals caused a 20% reduction in the mortality, there still exists imperative needs for the identification of novel biomarkers for the diagnosis and treatment of lung cancer.

METHODS

mRNA microarray datasets GSE19188, GSE33532, and GSE44077 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. Functional and pathway enrichment analyses were performed for the DEGs using DAVID database. Protein-protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was done through MCODE. The overall survival (OS) analysis of genes from MCODE was performed with the Kaplan Meier-plotter.

RESULTS

A total of 221 DEGs were obtained, which were mainly enriched in the terms related to cell division, cell proliferation, and signal transduction. A PPI network was constructed, consisting of 221 nodes and 739 edges. A significant module including 27 genes was identified in the PPI network. Elevated expression of these genes was associated with poor OS of NSCLC patients, including UBE2T, UNF2, CDKN3, ANLN, CCNB2, and CKAP2L. The enriched functions and pathways included protein binding, ATP binding, cell cycle, and p53 signaling pathway.

CONCLUSIONS

The DEGs in NSCLC have the potential to become useful targets for the diagnosis and treatment of NSCLC.

Study on miRNAs in Pan-Cancer of the Digestive Tract Based on the Illumina HiSeq System Data Sequencing

Objective

miRNA has gained attention as a therapeutic target in various malignancies. The proposal of this study was to investigate the biological functions of key miRNAs and target genes in cancers of the digestive tract which include esophageal carcinoma (ESCA), gastric adenocarcinoma (GAC), colon adenocarcinoma (COAD), and rectal adenocarcinoma (READ).

Materials and Methods

After screening differentially expressed miRNAs (DEMIs) and differentially expressed mRNAs (DEMs) in four digestive cancers from The Cancer Genome Atlas (TCGA) database, the diagnostic value of above DEMIs was evaluated by receiver-operating characteristic (ROC) curve analysis. Then, corresponding DEMIs' target genes were predicted by miRWalk 2.0. Intersection of predicted target genes and DEMs was taken as the target genes of DEMIs, and miRNA-mRNA regulatory networks between DEMIs and target genes were constructed. Meanwhile, the univariate Cox risk regression model was used to screen miRNAs with distinct prognostic value, and Kaplan-Meier analysis was used to determine their significance of prognosis. Furthermore, we performed bioinformatics methods including protein-protein interaction (PPI) networks, gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene group RIDA analysis by Gene-Cloud of Biotechnology Information (GCBI) to explore the function and molecular mechanisms of DEMIs and predicted target genes in tumor development.

Results

Eventually, 3 DEMIs (miR-7-3, miR-328, and miR-323a) with significant prognostic value were obtained. In addition, 3 DEMIs (miR-490-3p, miR-133a-3p, and miR-552-3p) and 281 target genes were identified, and the 3 DEMIs showed high diagnostic value in READ and moderate diagnostic value in ESCA, GAC, and COAD. Also, the miRNA-mRNA regulatory network with 3 DEMIs and 281 overlapping genes was successfully established. Functional enrichment analysis showed that 281 overlapping genes were mainly related to regulation of cell proliferation, cell migration, and PI3K-Akt signaling pathway.

Conclusion

The diagnostic value and prognostic value of significant DEMIs in cancers of the digestive tract were identified, which may provide a novel direction for treatment and prognosis improvement of cancers of the digestive tract.

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.

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.

Bioinformatics analysis of molecular genetic targets and key pathways for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the second leading cause of death among cancers worldwide. In this study, we aimed to identify the molecular target genes and detect the key mechanisms of HCC. Three gene expression profiles (GSE84006, GSE14323, GSE14811) and two miRNA expression profiles (GSE40744, GSE36915) were analyzed to determine the molecular target genes, microRNAs (miRNAs) and the potential molecular mechanisms in HCC.

Methods

All profiles were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs) was analyzed by the GEO2R method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment analysis performed database for Integrated Discovery, Visualization and Annotation. The miRNA-gene network and protein–protein interaction (PPI) network were correlated by the Cytoscape software. The key target genes were identified by the CytoHubba plugin, Molecular Complex Detection (MCODE) plugin and miRNA-gene network. The identified hub genes were testified for survival curve using the Kaplan–Meier plotter database.

Results

Expression profiles had 592 overlapped DEGs. The majority of the DEGs were enriched in membrane-bounded organelles and intracellular membrane-bounded organelles. These DEGs were significantly enriched in metabolic, protein processing in the endoplasmic reticulum and thyroid cancer pathways. PPI network analysis showed these genes were mostly involved in the pathogenic Escherichia coli infection and the regulation of actin cytoskeleton pathways. Combining these results, we identified 10 key genes involving in the progression of HCC. Finally, PLK1, PRCC, PRPF4 and PSMA7 exhibited higher expression levels in HCC patients with poor prognosis than those for lower expression via Kaplan–Meier plotter database.

Conclusion

PLK1, PRCC, PRPF4 and PSMA7 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, protein processing in the endoplasmic reticulum and the thyroid cancer pathway may play vital roles in the progression of HCC.

MicroRNA-552 deficiency mediates 5-fluorouracil resistance by targeting SMAD2 signaling in DNA-mismatch-repair-deficient colorectal cancer

OBJECTIVE

Although DNA-mismatch-repair-deficient (dMMR) status and aberrant expression of miRNAs are both critically implicated in the pathogenesis of resistance to 5-fluorouracil (5-FU) in colorectal cancer (CRC), whether these two factors regulate tumor response to 5-FU in a coordinated manner remains unknown. This study is designed to elucidate whether changes in miR-552 expression levels correlate to 5-FU-based chemoresistance in CRC, and to further identify the putative targets of miR-552 using multiple approaches.

METHODS

miR-552 expression was assessed in 5-FU-resistant CRC tissues and cells using real-time PCR. Effects of miR-552 dysregulation on 5-FU resistance in CRC cells were determined by measuring cell viability, apoptosis and in vivo oncogenic capacity. Finally, we studied the posttranscriptional regulation of SMAD2 by miR-552 using multiple approaches including luciferase reporter assay, site-directed mutagenesis and transient/stable transfection, at molecular and functional levels.

RESULTS

Expression of miR-552 was significantly downregulated in 5-FU-resistant CRC tissues and cells, and this downregulation, regulated by dMMR, was associated with poor postchemotherapy prognosis. Functionally, forced expression of miR-552 exhibited a proapoptotic effect and attenuated 5-FU resistance, whereas inhibition of miR-552 expression potentiated 5-FU resistance in CRC cells. Mechanically, miR-552 directly targeted the 3'-UTR of SMAD2, and stable ablation of SMAD2 neutralized the promoting effects of miR-552 deficiency-induced 5-FU resistance.

CONCLUSIONS

Overall, our findings have revealed a critical role of miR-552/SMAD2 cascade in modulating cellular response to 5-FU chemotherapy. miR-552 may act as an efficient mechanistic link synchronizing dMMR and 5-FU resistance in CRC.

G Protein γ subunit 7 loss contributes to progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common urinary neoplasm, looking for useful candidates to establish scientific foundation for the therapy of ccRCC is urgent. We downloaded genomic profiles of GSE781, GSE6244, GSE53757, and GSE66271 from the Gene Expression Omnibus (GEO) database. GEO2R was used to analyze the derivative genes, while hub genes were screened by protein-protein interactions and cytoscape. Further, overall survival, gene methylation, gene mutation, and gene expression were all analyzed using bioinformatics tools. Colony formation and cell-cycle assay were used to detect the biological function of GNG7 in vitro. We found that GNG7 was downregulated in ccRCC tissues and negatively associated with overall survival in ccRCC patients. We also found that promoter methylation and frequent gene mutation were responsible for GNG7 gene suppression. GNG7 low expression was related to upregulation of enhancer of zeste homolog 2 and downregulation of disabled homolog 2-interacting protein. Further, Gene Set Enrichment Analysis results showed that mTOR1, E2F, G2M, and MYC pathways were all significantly altered in response to GNG7 low expression. In vitro, A498 and 786-O cells in which GNG7 expression was silenced, exhibited a lower G1 phase when compared to the negative control cells. Taken together, our findings suggest that GNG7 is a tumor suppressor gene in ccRCC progression and represents a novel candidate for ccRCC treatment.

miR-548c-5p inhibits colorectal cancer cell proliferation by targeting PGK1

Accumulating studies have implicated that microRNAs (miRNAs) are involved in the pathogenesis of colorectal cancer (CRC). However, the role of miR-548c-5p, a novel identified miRNA in malignancies, in colorectal carcinogenesis remains largely unknown. The present study is aimed to investigate the effect and molecular mechanism of miR-548c-5p in CRC by a sequence of cellular experiments. miR-548c-5p was significantly downregulated, whereas phosphoglycerate kinase 1 (PGK1), a key enzyme for glycolysis, was obviously upregulated in peripheral blood mononuclear cells and cancer tissues from patients with CRC. Besides, miR-548c-5p and PGK1 were negatively associated with each other. The luciferase reporter assay revealed that PGK1 was a targeted gene of miR-548c-5p. Moreover, the proliferation and generation of inflammatory cytokines (TNF-α and IL-6) were significantly inhibited in miR-548c-5p-overexpressed SW480 CRC cells stimulated by lipopolysaccharide (LPS). Accordingly, miR-548c-5p may serve as a cancer suppressor in CRC by targeting PGK1.

MicroRNA-552 promotes migration and invasion of osteosarcoma through targeting TIMP2

Aberrant miRNAs play important roles in tumor development and progression. Previous studies reported that miR-552 was dysregulated expressed in multiple cancers. However, its biological effects and underlying mechanism in osteosarcoma remains largely unknown. In present research, we demonstrated that miR-552 was significantly up-regulated in both osteosarcoma cell lines and tissues for the first time. Its high-expression was significantly associated with poor prognostic features and overall survival of osteosarcoma patients. Gain- and loss-of-function experiment confirmed that miR-552 promoted cell migration, invasion and MMPs expression. Moreover, TIMP2 was a direct downstream target of miR-552. miR-552 inversely correlated with TIMP2 in osteosarcoma tissues. TIMP2 restoration at least partially abolished the migration, invasion and MMPs expression of miR-552 on osteosarcoma cells. Above all, our data suggest that miR-552 promoted migration, invasion and MMPs expression of osteosarcoma by targeting TIMP2, and represent a novel potential therapeutic target for osteosarcoma.

Identification and Validation of Core Genes Involved in the Development of Papillary Thyroid Carcinoma via Bioinformatics Analysis

BACKGROUND

Papillary thyroid carcinoma (PTC) is a common endocrine malignant neoplasm, and its incidence increases continuously worldwide in the recent years. However, efficient clinical biomarkers were still deficient; the present research is aimed at exploring significant core genes of PTC.

METHODS

We integrated three cohorts to identify hub genes and pathways associated with PTC by comprehensive bioinformatics analysis. Expression profiles GSE33630, GSE35570, and GSE60542, including 114 PTC tissues and 126 normal tissues, were enrolled in this research. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to search for the crucial biological behaviors and pathways involved in PTC carcinogenesis. Protein-protein interaction (PPI) network was constructed, and significant modules were deeply studied.

RESULTS

A total of 831 differentially expressed genes (DEGs) were discovered, comprising 410 upregulated and 421 downregulated genes in PTC tissues compared to normal thyroid tissues. PPI network analysis demonstrated the interactions between those DEGs, and top 10 pivotal genes (TGFB1, CXCL8, LRRK2, CD44, CCND1, JUN, DCN, BCL2, ACACB, and CXCL12) with highest degree of connectivity were extracted from the network and verified by TCGA dataset and RT-PCR experiment of PTC samples. Four of the hub genes (CXCL8, DCN, BCL2, and ACACB) were linked to the prognosis of PTC patients and considered as clinically relevant core genes via survival analysis.

CONCLUSION

In conclusion, we propose a series of key genes associated with PTC development and these genes could serve as the diagnostic biomarkers or therapeutic targets in the future treatment for PTC.

MiR-552 promotes the proliferation, migration and EMT of hepatocellular carcinoma cells by inhibiting AJAP1 expression

Our goal was to explore the function of miR‐552 and its potential target AJAP1 in hepatocellular carcinoma (HCC) oncogenesis and progression. In this study, bioinformatics analysis was performed to detect abnormally expressed miRNAs. The relationship between miR‐552 and AJAP1 was validated using luciferase reporter assays. RT‐qPCR and Western blot assays were applied to explore the expression level of miR‐552, AJAP1 and epithelial‐mesenchymal transition (EMT) markers. HCC cell proliferation was examined using CCK8 assays, while migration and invasion were investigated using Transwell assays. Nude mouse tumourigenesis models were established to facilitate observation of HCC progression in vivo. Finally, prognostic analysis was performed to discover how the prognosis of HCC patients correlated with miR‐552 and AJAP1 expression. MiR‐552 overexpression in HCC cells promoted HCC cell migration, invasion and EMT by targeting/suppressing AJAP1. Poorer prognosis appeared in HCC patients with higher miR‐552 expression or lower AJAP1 levels. Our findings suggested that miR‐552 promotes HCC oncogenesis and progression by inhibiting AJAP1 expression.

Effect of HOXA6 on the proliferation, apoptosis, migration and invasion of colorectal cancer cells

Colorectal cancer (CRC) is one of the most common types of tumor worldwide. The morbidity and mortality rates of CRC have increased significantly in adults <50 years of age. In the present study, the effects of homeobox A6 (HOXA6) on the proliferation, apoptosis, migration and invasion of CRC cells were investigated. The results of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis demonstrated that the expression of HOXA6 in CRC tumor tissue was higher than that in adjacent normal tissue. Appropriate cell lines and plasmids were selected by RT-PCR and western blot analyses, and recombinant plasmids were transfected into Caco2 or HT-29 cells. The results of RT-qPCR and western blot analyses demonstrated that the expression of HOXA6 was effectively enhanced, or inhibited, following transfection. The rate of cell proliferation was measured with cell counting kit-8, colony formation assay and 5-ethynyl‑2'-deoxyuridine assay, apoptosis was detected using terminal deoxynucleotidyl transferase dUTP nick end labeling and flow cytometry assays, and migration and invasion were evaluated using Transwell and wound-healing assays. The results demonstrated that the upregulation of HOXA6 promoted cell proliferation, migration and invasion, but inhibited apoptosis, whereas the downregulated expression of HOXA6 produced the opposite effects. In addition, the expression levels of apoptosis- and epithelial-mesenchymal transition (EMT)-related proteins were examined. The results of the western blot analysis revealed that the upregulated expression of HOXA6 suppressed the expression of B-cell lymphoma-2 (Bcl-2)-associated X protein, caspase-3, poly(ADP-ribose) polymerase and E-cadherin, but promoted the expression of Bcl-2, N-cadherin and Vimentin, whereas the opposite effect was observed in cells with downregulated HOXA6. These results indicated that HOXA6 regulated apoptosis through the Bcl-2 signaling pathway, and regulated migration and invasion through the EMT process. In conclusion, the present study confirmed that HOXA6 was involved in the regulation of CRC, which may inform the development of strategies for the diagnosis and treatment of CRC.

Molecular differences between mature and immature dental pulp cells: Bioinformatics and preliminary results

Although previous studies have demonstrated that dental pulp stem cells (DPSCs) from mature and immature teeth exhibit potential for multi-directional differentiation, the molecular and biological difference between the DPSCs from mature and immature permanent teeth has not been fully investigated. In the present study, 500 differentially expressed genes from dental pulp cells (DPCs) in mature and immature permanent teeth were obtained from the Gene Expression Omnibus online database. Based on bioinformatics analysis using the Database for Annotation, Visualization and Integrated Discovery, these genes were divided into a number of subgroups associated with immunity, inflammation and cell signaling. The results of the present study suggest that immune features, response to infection and cell signaling may be different in DPCs from mature and immature permanent teeth; furthermore, DPCs from immature permanent teeth may be more suitable for use in tissue engineering or stem cell therapy. The Online Mendelian Inheritance in Man database stated that Sonic Hedgehog (SHH), a differentially expressed gene in DPCs from mature and immature permanent teeth, serves a crucial role in the development of craniofacial tissues, including teeth, which further confirmed that SHH may cause DPCs from mature and immature permanent teeth to exhibit different biological characteristics. The Search Tool for the Retrieval of Interacting Genes/Proteins database revealed that SHH has functional protein associations with a number of other proteins, including Glioma-associated oncogene (GLI)1, GLI2, growth arrest-specific protein 1, bone morphogenetic protein (BMP)2 and BMP4, in mice and humans. It was also demonstrated that SHH may interact with other genes to regulate the biological characteristics of DPCs. The results of the present study may provide a useful reference basis for selecting suitable DPSCs and molecules for the treatment of these cells to optimize features for tissue engineering or stem cell therapy. Quantitative polymerase chain reaction should be performed to confirm the differential expression of these genes prior to the beginning of a functional study.

Construction of a ceRNA network reveals potential lncRNA biomarkers in rectal adenocarcinoma

Competing endogenous RNAs (ceRNAs) render the functions of long non-coding RNAs (lncRNAs) more complicated during cancer processes. Potential lncRNA biomarkers and their roles as ceRNAs have not been clearly described for rectal adenocarcinoma (READ). In the present study, we extracted data from The Cancer Genome Atlas (TCGA) including data from 167 tumor samples and 10 adjacent non-tumor samples. A total of 202 lncRNAs, 190 microRNAs (miRNAs) and 1,530 mRNAs were identified as READ-specific RNAs [log₂(fold-change)>2, FDR<0.01]. The Gene Ontology (GO) biological processes and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways were analysed for 1,530 specific mRNAs. Among 202 READ-specific lncRNAs, 7 lncRNAs were identified as being associated with overall survival of READ patients. Then, a ceRNA network was constructed with 34 key lncRNAs, 25 miRNAs and 65 mRNAs. A total of 7 lncRNAs from the network were revealed to be linked to clinical features. The results of qRT-PCR ascertained that our analysis was credible. Overall, this research provides a novel perspective from which to study the lncRNA-related ceRNA network in READ and assists in the identification of new potential biomarkers to be used for diagnostic and prognostic purposes.