Aberrantly methylated-differentially expressed genes and pathways in colorectal cancer

Genetic variants reduced POPs-related colorectal cancer risk via altering miRNA binding affinity and m6A modification

Exposure to persistent organic pollutants (POPs) may contribute to colorectal cancer risk, but the underlying mechanisms of crucial POPs exposure remain unclear. Hence, we systematically investigated the associations among POPs exposure, genetics and epigenetics and their effects on colorectal cancer. A case-control study was conducted in the Chinese population for detecting POPs levels. We measured the concentrations of 24 POPs in the plasma using gas chromatography-tandem mass spectrometry (GC-MS/MS) and evaluated the clinical significance of POPs by calculating the area under the receiver operating characteristic curve (AUC). To assess the associations between candidate genetic variants and colorectal cancer risk, unconditional logistic regression was used. Compared with healthy control individuals, individuals with colorectal cancer exhibited higher concentrations of the majority of POPs. Exposure to PCB153 was positively associated with colorectal cancer risk, and PCB153 demonstrated superior accuracy (AUC=0.72) for predicting colorectal cancer compared to other analytes. On PCB153-related genes, the rs67734009 C allele was significantly associated with reduced colorectal cancer risk and lower plasma levels of PCB153. Moreover, rs67734009 exhibited an expression quantitative trait locus (eQTL) effect on ESR1, of which the expression level was negatively related to PCB153 concentration. Mechanistically, the risk allele of rs67734009 increased ESR1 expression via miR-3492 binding and m6A modification. Collectively, this study sheds light on potential genetic and epigenetic mechanisms linking PCB153 exposure and colorectal cancer risk, thereby providing insight into the accurate protection against POPs exposure.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Association analysis of hepatocellular carcinoma-related hub proteins and hub genes

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

EXPERIMENTAL DESIGN

Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

RESULTS

This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

CONCLUSIONS AND CLINICAL RELEVANCE

The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

Microbiota composition and its impact on DNA methylation in colorectal cancer

Colorectal cancer is a complex disease resulting from the interaction of genetics, epigenetics, and environmental factors. DNA methylation is frequently found in tumor suppressor genes to promote cancer development. Several factors are associated with changes in the DNA methylation pattern, and recently, the gastrointestinal microbiota could be associated with this epigenetic change. The predominant phyla in gut microbiota are Firmicutes and Bacteroidetes; however, an enrichment of Bacteroides fragilis, Fusobacterium nucleatum, and Streptococcus bovis, among others, has been reported in colorectal cancer, although the composition could be influenced by several factors, including diet, age, sex, and cancer stage. Fusobacterium nucleatum, a gram-negative anaerobic bacillus, is mainly associated with colorectal cancer patients positive for the CpG island methylator phenotype, although hypermethylation in genes such as MLH1, CDKN2A, MTSS1, RBM38, PKD1, PTPRT, and EYA4 has also been described. Moreover, Hungatella hathewayi, a gram-positive, rod-shaped bacterium, is related to hypermethylation in SOX11, THBD, SFRP2, GATA5, ESR1, EYA4, CDX2, and APC genes. The underlying epigenetic mechanism is unclear, although it could be implicated in the regulation of DNA methyltransferases, enzymes that catalyze the transfer of a methyl group on cytosine of CpG sites. Since DNA methylation is a reversible event, changes in gut microbiota could modulate the gene expression through DNA methylation and improve the colorectal cancer prognosis.

Identification of potential differentially methylated gene-related biomarkers in endometriosis

Aim: To identify epigenetic alterations of differentially expressed genes and screen out targeted therapeutic drugs in endometriosis. Methods: Based on the Gene Expression Omnibus database and a series of biological information analysis tools, supplemented by validation of clinical samples, aberrant DNA methylation-driven genes and their functions were explored, as well as possible targeted drugs. Results: This study screened out a range of DNA methylation-driven genes that were associated with powerful properties and corresponding pathways. Among them, BDNF and CCL2 were key genes in the development of endometriosis. Four chemical agents have been flagged as potential treatments for endometriosis. Conclusion: These candidate genes and small-molecule agents may be further explored as potential targets and drugs for endometriosis diagnosis and therapy, respectively.

Integrin α6 Indicates a Poor Prognosis of Craniopharyngioma through Bioinformatic Analysis and Experimental Validation

Background. Craniopharyngioma (CP) is a benign slow-growing tumor. It tends to affect children, and the number of patients is on rise. Considering the high morbidity and mortality of CP, it is urgent and pivotal to identify new biomarkers to uncover the etiology and pathogenesis of CP. Methods. The “limma” package was utilized to calculate the data from the Gene Expression Omnibus (GEO) database. Based on differentially expressed genes (DEGs), gene ontology and pathway analysis were deduced from the DAVID web tool. Further, we constructed a protein-protein interaction (PPI) network. Weighted correlation network analysis (WGCNA) was utilized to build a coexpression network. Finally, Western blotting and survival analysis were performed to examine the expression level of important metabolism-related genes. Results. Three hundred and eighty-four DEGs were identified between normal tissues and CPs from the GSE94349 and GSE26966 datasets. The Venn diagram for DEGs and hub genes in the ‘turquoise’ module revealed four key genes. Finally, the outcome of the survival analysis suggested that Integrin α6 (ITGA6) significantly affected the overall survival time of the patients with CP. Conclusion. IGTA6, as a metabolism-related molecule, was found to be substantially related to the overall survival of patients with CP.

Identifying potential pharmacological targets and mechanisms of vitamin D for hepatocellular carcinoma and COVID-19

Coronavirus disease 2019 (COVID‐19) is a severe pandemic that has posed an unprecedented challenge to public health worldwide. Hepatocellular carcinoma (HCC) is a common digestive system malignancy, with high aggressiveness and poor prognosis. HCC patients may be vulnerable to COVID-19. Since the anti-inflammatory, immunomodulatory and antiviral effects of vitamin D, we aimed to investigate the possible therapeutic effects and underlying action mechanisms of vitamin D in COVID-19 and HCC in this study. By using a range of bioinformatics and network pharmacology analyses, we identified many COVID-19/HCC target genes and analyzed their prognostic significance in HCC patients. Further, a risk score model with good predictive performance was developed to evaluate the prognosis of HCC patients with COVID-19 based on these target genes. Moreover, we identified seven possible pharmacological targets of vitamin D against COVID-19/HCC, including HMOX1, MB, TLR4, ALB, TTR, ACTA1 and RBP4. And we revealed the biological functions, signaling pathways and TF-miRNA coregulatory network of vitamin D in COVID-19/HCC. The enrichment analysis revealed that vitamin D could help in treating COVID-19/HCC effects through regulation of immune response, epithelial structure maintenance, regulation of chemokine and cytokine production involved in immune response and anti-inflammatory action. Finally, the molecular docking analyses were performed and showed that vitamin D possessed effective binding activity in COVID-19. Overall, we revealed the possible molecular mechanisms and pharmacological targets of vitamin D for treating COVID-19/HCC for the first time. But these findings need to be further validated in actual HCC patients with COVID-19 and need further investigation to confirm.

Aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma

This study aimed to explore aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma (CCA).The mRNA expression data (GSE26566) and methylation profiling data (GSE44965) were collected from the Gene Expression Omnibus (GEO) Datasets. Differentially expressed genes and differentially methylated genes were identified using GEO2R. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using clusterprofiler in R. MCODE clustering tool was used to screen modules of the protein-protein interaction network in Cytoscape. Related pathways of hub gene by using gene set enrichment analysis.Eighty-one hypermethylated, lowly expressed genes (Hyper-LGs) and 76 hypomethylated, highly expressed genes (Hypo-HGs) were identified in this study. Hyper-LGs were enriched in ion channel binding and transcription factor activity, which was associated with Mineral absorption and Cell adhesion molecules. Hypo-HGs were enriched in cysteine-type endopeptidase activity, which was associated with Sphingolipid signaling pathway and T cell receptor signaling pathway. Based on protein-protein interaction networks, MYC and VWF were identified as hub genes for Hyper-LGs, and no hub genes for Hypo-HGs.This study found methylated-differentially expressed genes and signaling pathways that are connected with the CCA by using a series of bioinformatics databases and tools. MYC and VWF act as hub genes of CCA, which can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of CCA.

Immune-Related Biomarkers Associated with Lung Metastasis from the Colorectal Cancer Microenvironment

Immune-associated biomarkers can predict lung metastases from colorectal cancer. Differentially expressed genes (DEGs) were screened from sample data extracted from gene expression omnibus (GEO) database. The DEGs were screened from the lung metastasis (LM) and primary cancer (PC) groups of the Moffitt Cancer Center cohort dataset. Then, the tumor immune microenvironment and abundance of immune cell infiltration analyses were performed, and the immune-related DEGs were retrieved. In addition, the transcription factor (TF)-miRNA-mRNA network was constructed and enrichment analyses of the immune-related DEGs and upregulated and downregulated DEGs were carried out. Then, the protein-protein interaction (PPI) network was conducted and the drug-gene interaction was predicted. A total of 268 DEGs were screened. The Immune_Score of samples in the LM group was significantly higher compared with the PC group. The infiltration ratio of M0 macrophages and M2 macrophages of samples was higher than others. A total of 54 immune-related DEGs in M0 macrophages were screened. Moreover, the TF-miRNA-mRNA network was constructed among 8 miRNA-mRNA and 50 TF-mRNA, and the secreted phosphoprotein 1 was regulated by 12 TFs, and the oxidized low-density lipoprotein receptor 1 was regulated by 3 miRNAs and 3 TFs. The TF SAM pointed domain containing ETS TF was also a downregulated DEG. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the DEGs in the TF-miRNA-mRNA network were mainly involved in the interleukin-7 signaling pathway and cell adhesion molecules. In total, 23 protein interactions in this PPI network of M0 macrophage cells were involved in 27 mRNAs. There were 38 drug-gene interactions of immune-related DEGs of M0 macrophage cells predicted to contain 34 small molecule drugs and 8 mRNAs. Finally, the CON cohort dataset verified that the infiltration ratio of M0 and M2 macrophages of the samples was higher.

Integrative analysis of transcriptomics and metabolomics to reveal the melanogenesis pathway of muscle and related meat characters in Wuliangshan black-boned chickens

Background

Melanin is an important antioxidant in food and has been used in medicine and cosmetology. Chicken meat with high melanin content from black-boned chickens have been considered a high nutritious food with potential medicinal properties. The molecular mechanism of melanogenesis of skeletal muscle in black-boned chickens remain poorly understood. This study investigated the biological gene-metabolite associations regulating the muscle melanogenesis pathways in Wuliangshan black-boned chickens with two normal boned chicken breeds as control.

Results

We identified 25 differentially expressed genes and 11 transcription factors in the melanogenesis pathways. High levels of the meat flavor compounds inosine monophosphate, hypoxanthine, lysophospholipid, hydroxyoctadecadienoic acid, and nicotinamide mononucleotide were found in Wuliangshan black-boned chickens.

Conclusion

Integrative analysis of transcriptomics and metabolomics revealed the dual physiological functions of the PDZK1 gene, involved in pigmentation and/or melanogenesis and regulating the phospholipid signaling processes in muscle of black boned chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08388-w.

Differential DNA methylation analysis of SUMF2, ADAMTS5, and PXDN provides novel insights into colorectal cancer prognosis prediction in Taiwan

BACKGROUND

Patients with colorectal cancer (CRC) undergo surgery, as well as perioperative chemoradiation or adjuvant chemotherapy primarily based on the tumor–node– metastasis (TNM) cancer staging system. However, treatment responses and prognostic outcomes of patients within the same stage vary markedly. The potential use of novel biomarkers can improve prognostication and shared decision making before implementation into certain therapies.

AIM

To investigate whether SUMF2, ADAMTS5, and PXDN methylation status could be associated with CRC prognosis.

METHODS

We conducted a Taiwan region cohort study involving 208 patients with CRC recruited from Tri-Service General Hospital and applied the candidate gene approach to identify three genes involved in oncogenesis pathways. A methylation-specific polymerase chain reaction (MS-PCR) and EpiTYPER DNA methylation analysis were employed to detect methylation status and to quantify the methylation level of candidate genes in tumor tissue and adjacent normal tissue from participants. We evaluated SUMF2, ADAMTS5, and PXDN methylation as predictors of prognosis, including recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS), using a Cox regression model and Kaplan–Meier analysis.

RESULTS

We revealed various outcomes related to methylation and prognosis. Significantly shorter PFS and OS were associated with the CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue compared with CpG_3+CpG_7 hypomethylation [hazard ratio (HR) = 2.24, 95% confidence interval (CI) = 1.03-4.85 for PFS, HR = 2.56 and 95%CI = 1.08-6.04 for OS]. By contrast, a significantly longer RFS was associated with CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue compared with CpG_2 and CpG_13 hypomethylation [HR (95%CI) = 0.15 (0.03-0.71) for CpG_2 and 0.20 (0.04-0.97) for CpG_13]. The relationship between the methylation status of PXDN and the prognosis of CRC did not reach statistical significance.

CONCLUSION

Our study found that CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue was associated with significantly shorter PFS and OS compared with CpG_3+CpG_7 hypomethylation. CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue was associated with a significantly longer RFS compared with CpG_2 and CpG_13 hypomethylation. These methylation-related biomarkers which have implications for CRC prognosis prediction may aid physicians in clinical decision-making.

Site-Specific Hypermethylation of SST 1stExon as a Biomarker for Predicting the Risk of Gastrointestinal Tract Cancers

Background

DNA methylation is an important epigenetic modification in tumorigenesis, and similar epigenetic regulation mechanisms have been found in the gastrointestinal tract (GIT) cancers. Somatostatin (SST) has been confirmed to be expressed throughout the GIT. This study aimed to simultaneously explore the relationships between the SST methylation and the risks of three GIT cancers (esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)) and to evaluate its diagnostic value.

Methods

Differentially methylated regions (DMRs) of the SST gene, including TSS200, 1stExon, and the gene body, were identified in GIT cancers by The Cancer Genome Atlas (TCGA) database analysis. Further analyses were conducted in tissue samples of EC (n = 50), GC (n = 99), and CRC (n = 80). The SST methylation was detected by bisulfite-sequencing PCR (BSP), and the SST expression was detected by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR).

Results

In GIT cancers, DMR-related CpG islands were mainly located in the 1stExon. The methylation status of the SST 1stExon in the tumor tissues was significantly higher than that in the adjacent noncancerous tissues, and the methylation rates of the specific CpG sites were correlated with clinical phenotypes. The average methylation rate (AMR) of the SST 1stExon was negatively correlated with the SST gene expression in GC and CRC (both P < 0.001). For the diagnosis of GIT cancers, the combined detection of methylation at CpG sites +18 and +129 showed the highest area under the curve (AUC 0.698), with a sensitivity of 59.3% and a specificity of 72.8%.

Conclusions

The site-specific hypermethylation of the SST 1stExon increases the risk of GIT cancers and might be a potential predictive marker for pan-GIT cancers.

Interleukin 20 receptor A expression in colorectal cancer and its clinical significance

Background

Interleukin 20 receptor A (IL20RA) has been shown to play a role in the establishment and progression of multiple tumors. However, the expression of this protein in colorectal cancer (CRC) and its correlation with the clinicopathological parameters of CRC have remained unclear.

Methods

A total of 323 paraffin sections including CRC tissues and adjacent normal tissues after surgery were collected. IL20RA protein expression was detected by immunohistochemical staining. The difference expression of IL20RA mRNA between CRC and normal tissues was also explored in the Oncomine and GEO databases. In addition, the IL20RA-related differentially expressed genes were analyzed in TCGA database and enrichment analysis was conducted to explore the cell functions and pathways related to IL20RA expression.

Results

There was increased IL20RA expression in CRC compared with that in normal tissues. High IL20RA expression was associated with greater tumor diameter, lymph node metastasis, and poor TNM stage in CRC, while also being suggestive of poor prognosis. The main pathways of IL20RA-related differentially expressed genes in TCGA were protein heterodimerization activity, oxygen binding, oxygen transporter activity, hormone activity, and lipid transporter activity. Meanwhile, IL20RA-related differentially expressed genes were mainly enriched in peroxidase, nucleotide stimulant repair, fatty acid metabolism, basal transcription factor, and RNA degradation.

Conclusions

IL20RA might have a role as a biomarker for CRC. Its upregulation might contribute to an aggressive phenotype in CRC. IL20RA’s involvement in the development and progression of CRC might occur through it affecting fatty acid metabolism, oxygen binding, oxygen transport, and hormone activity.

Identification of key genes in cutaneous squamous cell carcinoma: a transcriptome sequencing and bioinformatics profiling study

Background

Long-term exposure to ultraviolet (UV) radiation can cause cutaneous squamous cell carcinoma (cSCC), which is one of the most common malignant cancers worldwide. Actinic keratosis (AK) is generally considered a precancerous lesion of cSCC. However, the pathogenesis and oncogenic processes of AK and cSCC remain elusive, especially in the context of photodamage.

Methods

In this study, transcriptome sequencing was performed on AK, cSCC, normal sun-exposed skin (NES) tissues, and normal non-sun-exposed skin (NNS) from 24 individuals. Bioinformatics analysis to identify the differentially expressed genes (DEGs) of 4 groups, and potential key genes of cSCC were validated by real-time quantitative reverse transcription PCR (qRT-PCR).

Results

A total of 46,930 genes were differentially expressed in the 4 groups, including 127 genes that were differentially expressed between NES and NNS, 420 DEGs in AK compared to NES, 1,658 DEGs in cSCC compared to NES, and 1,389 DEGs in cSCC compared to AK. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that the DEGs are involved in multiple pathways, including extracellular matrix (ECM)-receptor interaction, immune, inflammatory, microbial infection, and other related pathways. Finally, 5 new genes (HEPHL1, FBN2, SULF1, SULF2, and TCN1) were confirmed significantly upregulated in cSCC.

Conclusions

Using transcriptome sequencing and integrated bioinformatical analysis, we have identified key DEGs and pathways in cSCC, which could improve our understanding of the cause and underlying molecular events of AK and cSCC. HEPHL1, FBN2, SULF1, SULF2, and TCN1 may be novel potential biomarkers and therapeutic targets of cSCC.

Somatostatin and Its Receptor System in Colorectal Cancer

Somatostatin (SST)/somatotropin release-inhibiting factor (SRIF) is a well-known neuropeptide, widely distributed in the central and peripheral nervous systems, that regulates the endocrine system and affects neurotransmission via interaction with five SST receptors (SST1-5). In the gastrointestinal tract, the main SST-producing cells include intestinal enteroendocrine cells (EECs) restricted to the mucosa, and neurons of the submucosal and myenteric plexuses. The action of the SRIF system is based on the inhibition of endocrine and exocrine secretion, as well as the proliferative responses of target cells. The SST1–5 share common signaling pathways, and are not only widely expressed on normal tissues, but also frequently overexpressed by several tumors, particularly neuroendocrine neoplasms (NENs). Furthermore, the SRIF system represents the only peptide/G protein-coupled receptor (GPCR) system with multiple approved clinical applications for the diagnosis and treatment of several NENs. The role of the SRIF system in the histogenesis of colorectal cancer (CRC) subtypes (e.g., adenocarcinoma and signet ring-cell carcinoma), as well as diagnosis and prognosis of mixed adenoneuroendocrine carcinoma (MANEC) and pure adenocarcinoma, is poorly understood. Moreover, the impact of the SRIF system signaling on CRC cell proliferation and its potential role in the progression of this cancer remains unknown. Therefore, this review summarizes the recent collective knowledge and understanding of the clinical significance of the SRIF system signaling in CRC, aiming to evaluate the potential role of its components in CRC histogenesis, diagnosis, and potential therapy.

Integrated analyses of long noncoding RNAs and mRNAs in the progression of breast cancer

Objective

The objective was to explore the expression and potential functions of long noncoding RNA (lncRNA) and mRNAs in human breast cancer (BC).

Methods

Differentially expressed lncRNAs and mRNAs were identified and annotated in BC tissues by using the Agilent human lncRNA assay (Agilent Technologies, Santa Clara, CA, USA) and RNA sequencing. After identification of lncRNAs and mRNAs through quantitative reverse transcription polymerase chain reaction, we conducted a series of functional experiments to confirm the effects of knockdown of one lncRNA, TCONS_00029809, on the progression of BC.

Results

We discovered 238 lncRNAs and 200 mRNAs that were differentially expressed in BC tissues and para-carcinoma tissue. We showed that differentially expressed mRNAs were related to biological adhesion and biological regulation and mainly enriched in cytokine-cytokine receptor interaction, metabolic pathways, and PI3K-Akt signaling pathway. We created a protein–protein interaction network to analyze the proteins enriched in these pathways. We demonstrated that silencing of TCONS_00029809 remarkably inhibited proliferation, invasion, and migration of BC cells, and accelerated their apoptosis.

Conclusions

We identified a large number of differentially expressed lncRNAs and mRNAs, which provide data useful in understanding BC carcinogenesis. The lncRNA TCONS_00029809 may be involved in the development of BC.

Hypermethylation and Downregulation of UTP6 Are Associated With Stemness Properties, Chemoradiotherapy Resistance, and Prognosis in Rectal Cancer: A Co-expression Network Analysis

Background

To identify the hub genes associated with chemoradiotherapy resistance in rectal cancer and explore the potential mechanism.

Methods

Weighted gene co-expression network analysis (WGCNA) was performed to identify the gene modules correlated with the chemoradiotherapy resistance of rectal cancer.

Results

The mRNA expression of 31 rectal cancer patients receiving preoperative chemoradiotherapy was described in our previous study. Through WGCNA, we demonstrated that the chemoradiotherapy resistance modules were enriched for translation, DNA replication, and the androgen receptor signaling pathway. Additionally, we identified and validated UTP6 as a new effective predictor for chemoradiotherapy sensitivity and a prognostic factor for the survival of colorectal cancer patients using our data and the GSE35452 dataset. Low UTP6 expression was correlated with significantly worse disease-free survival (DFS), overall survival (OS), and event- and relapse-free survival both in our data and the R2 Platform. Moreover, we verified the UTP6 expression in 125 locally advanced rectal cancer (LARC) patients samples by immunohistochemical analysis. The results demonstrated that low UTP6 expression was associated with worse DFS and OS by Kaplan-Meier and COX regression model analyses. Gene set enrichment and co-expression analyses showed that the mechanism of the UTP6-mediated chemoradiotherapy resistance may involve the regulation of FOXK2 expression by transcription factor pathways.

Conclusion

Low expression of the UTP6 was found to be associated with chemoradiotherapy resistance and the prognosis of colorectal cancer possibly via regulating FOXK2 expression by transcription factor pathways.

Epigenetic regulation of somatostatin and somatostatin receptors in neuroendocrine tumors and other types of cancer

Both somatostatin (SST) and somatostatin receptors (SSTRs) are proteins with important functions in both physiological tissue and in tumors, particularly in neuroendocrine tumors (NETs). NETs are frequently characterized by high SSTRs expression levels. SST analogues (SSAs) that bind and activate SSTR have anti-proliferative and anti-secretory activity, thereby reducing both the growth as well as the hormonal symptoms of NETs. Moreover, the high expression levels of SSTR type-2 (SSTR2) in NETs is a powerful target for therapy with radiolabeled SSAs. Due to the important role of both SST and SSTRs, it is of great importance to elucidate the mechanisms involved in regulating their expression in NETs, as well as in other types of tumors. The field of epigenetics recently gained interest in NET research, highlighting the importance of this process in regulating the expression of gene and protein expression. In this review we will discuss the role of the epigenetic machinery in controlling the expression of both SSTRs and the neuropeptide SST. Particular attention will be given to the epigenetic regulation of these proteins in NETs, whereas the involvement of the epigenetic machinery in other types of cancer will be discussed as well. In addition, we will discuss the possibility to target enzymes involved in the epigenetic machinery to modify the expression of the SST-system, thereby possibly improving therapeutic options.

Prognostic Impact of MITD1 and Associates With Immune Infiltration in Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most malignant diseases with poor survival rate over the world. The tumor microenvironment (TME) is highly related to the oncogenesis, development, and prognosis of KIRC. Thus, making the identification of KIRC biomarkers and immune infiltrates critically important. Microtubule Interacting and Trafficking Domain containing 1(MITD1) was reported to participate in cytokinesis of cell division. In the present study, multiple bioinformatics tools and databases were applied to investigate the expression level and clinical value of MITD1 in KIRC. We found that the expression of MITD1 was significantly increased in KIRC tissues. Further, the KIRC patients with high MITD1 levels showed a worse overall survival (OS) rate and disease free survival (DFS) rate. Otherwise, we found a significant correlation MITD1 expression and the abundance of CD8+ T cells. Functional enrichment analyses revealed that immune response and cytokine-cytokine receptor are very critical signaling pathways which associated with MITD1 in KIRC. In conclusion, our findings indicated that MITD1 may be a potential biomarker and associated with immune infiltration in KIRC.

An aberrant DNA methylation signature for predicting the prognosis of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy worldwide with a poor prognosis. DNA methylation is an epigenetic modification that plays a critical role in the etiology and pathogenesis of HNSCC. The current study aimed to develop a predictive methylation signature based on bioinformatics analysis to improve the prognosis and optimize therapeutic outcome in HNSCC. Clinical information and methylation sequencing data of patients with HNSCC were downloaded from The Cancer Genome Atlas database. The R package was used to identify differentially methylated genes (DMGs) between HNSCC and adjacent normal tissues. We identified 22 DMGs associated with 246 differentially methylated sites. Patients with HNSCC were classified into training and test groups. Cox regression analysis was used to build a risk score formula based on the five methylation sites (cg26428455, cg13754259, cg17421709, cg19229344, and cg11668749) in the training group. The Kaplan–Meier survival curves showed that the overall survival (OS) rates were significantly different between the high‐ and low‐risk groups sorted by the signature in the training group (median: 1.38 vs. 1.57 years, log‐rank test, p < 0.001). The predictive power was then validated in the test group (median: 1.34 vs. 1.75 years, log‐rank test, p < 0.001). The area under the receiver operating characteristic curve (area under the curve) based on the signature for predicting the 5‐year survival rates, was 0.7 in the training and 0.73 in test groups, respectively. The results of multivariate Cox regression analysis showed that the riskscore (RS) signature based on the five methylation sites was an independent prognostic tool for OS prediction in patients. In addition, a predictive nomogram model that incorporated the RS signature and patient clinical information was developed. The innovative methylation signature‐based model developed in our study represents a robust prognostic tool for guiding clinical therapy and predicting the OS in patients with HNSCC.

Prediction of Disease Genes Based on Stage-Specific Gene Regulatory Networks in Breast Cancer

Breast cancer is one of the most common malignant tumors in women, which seriously endangers women’s health. Great advances have been made over the last decades, however, most studies predict driver genes of breast cancer using biological experiments and/or computational methods, regardless of stage information. In this study, we propose a computational framework to predict the disease genes of breast cancer based on stage-specific gene regulatory networks. Firstly, we screen out differentially expressed genes and hypomethylated/hypermethylated genes by comparing tumor samples with corresponding normal samples. Secondly, we construct three stage-specific gene regulatory networks by integrating RNA-seq profiles and TF-target pairs, and apply WGCNA to detect modules from these networks. Subsequently, we perform network topological analysis and gene set enrichment analysis. Finally, the key genes of specific modules for each stage are screened as candidate disease genes. We obtain seven stage-specific modules, and identify 20, 12, and 22 key genes for three stages, respectively. Furthermore, 55%, 83%, and 64% of the genes are associated with breast cancer, for example E2F2, E2F8, TPX2, BUB1, and CKAP2L. So it may be of great importance for further verification by cancer experts.

DNA Methylation-based Diagnostic and Prognostic Biomarkers for Glioblastoma

Glioblastomas are the most common primary central nervous system malignancy tumor in adults. Glioblastoma patients have poor prognosis, with an average survival period of approximately 14 mo after diagnosis. To date, there are a limited number of effective treatment methods for glioblastoma, and its molecular mechanisms remain elusive. In this article, we analyzed the key biomarkers and pathways in glioblastoma patients based on gene expression and DNA methylation datasets. The 60 hypomethylated/upregulated genes and 110 hypermethylated/downregulated genes were identified in GSE50923, GSE50161, and GSE116520 microarrays. Functional enrichment analyses indicated that these methylated-differentially expressed genes were primarily involved in collagen fibril organization, chemical synaptic transmission, extracellular matrix-receptor interaction, and GABAergic synapse. The hub genes were screened from a protein–protein interaction network; in selected genes, increased NMB mRNA level was associated with favorable overall survival, while elevated CHI3L1, POSTN, S100A4, LOX, S100A11, IGFBP2, SLC12A5, VSNL1, and RGS4 mRNA levels were associated with poor overall survival in glioblastoma patients. Additionally, CHI3L1, S100A4, LOX, and S100A11 expressions were negatively correlated with their corresponding methylation status. Furthermore, the receiver-operator characteristic curve analysis indicated that CHI3L1, S100A4, LOX, and S100A11 can also serve as highly specific and sensitive diagnostic biomarkers for glioblastoma patients. Collectively, our study revealed the possible methylated-differentially expressed genes and associated pathways in glioblastoma and identified four DNA methylation-based biomarkers of glioblastoma. These results may provide insight on diagnostic and prognostic biomarkers, and therapeutic targets in glioblastoma.

The remodelling of actin composition as a hallmark of cancer

Actin is a key structural protein that makes up the cytoskeleton of cells, and plays a role in functions such as division, migration, and vesicle trafficking. It comprises six different cell-type specific isoforms: ACTA1, ACTA2, ACTB, ACTC1, ACTG1, and ACTG2. Abnormal actin isoform expression has been reported in many cancers, which led us to hypothesize that it may serve as an early biomarker of cancer. We show an overview of the different actin isoforms and highlight mechanisms by which they may contribute to tumorigenicity. Furthermore, we suggest how the aberrant expression of actin subunits can confer cells with greater proliferation ability, increased migratory capability, and chemoresistance through incorporation into the normal cellular F-actin network and altered actin binding protein interaction. Studying this fundamental change that takes place within cancer cells can further our understanding of neoplastic transformation in multiple tissue types, which can ultimately aid in the early-detection, diagnosis and treatment of cancer.

DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer

Simple Summary

The role of DNA methylation in the carcinogenesis of colorectal cancer (CRC) diagnosed <50 years of age (early-onset CRC or EOCRC) is currently unknown. In this study, we investigated the genome-wide DNA methylation of 97 tumour and 54 normal colonic mucosa samples from people with EOCRC with the aim of identifying unique DNA methylation signatures and determining the role of ageing-related DNA methylation drift and age-acceleration in EOCRC aetiology. We found extensive DNA methylation alterations associated with EOCRC carcinogenesis, including a unique signature comprising 234 loci compared with CRCs from people >50 years of age. CpGs that undergo ageing-related methylation drift were significantly altered in EOCRC, and accelerated ageing was also evident in normal mucosa from people with EOCRC. Our study is the first study to identify unique DNA methylation changes in EOCRC, contributing novel information that may aid future efforts towards EOCRC prevention.

Abstract

We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50–70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10⁻¹⁶) and young people without CRC (p = 5.8 × 10⁻⁶). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.

6-lncRNA Assessment Model for Monitoring and Prognosis of HER2-Positive Breast Cancer: Based on Transcriptome Data

Background: In view of the high malignancy and poor prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer, we analyzed the RNA expression profiles of HER2-positive breast cancer samples to identify the new prognostic biomarkers. Methods: The linear fitting method was used to identify the differentially expressed RNAs from the HER2-positive breast cancer RNA expression profiles in the Cancer Genome Atlas (TCGA). Then, a series of methods including univariate Cox, Kaplan-Meier, and random forests, were used to identify the core long non-coding RNAs (lncRNAs) with stable prognostic value for HER2-positive breast cancer. A clinical feature analysis was performed, and a competing endogenous RNA network was constructed to explore the role of these core lncRNAs in HER2-positive breast cancer. In addition, a functional analysis of differentially expressed messenger RNAs in HER-2 positive breast cancer also provided us with some enlightening insights. Results: The high expression of four core lncRNAs (AC010595.1, AC046168.1, AC069277.1, and AP000904.1) was associated with worse overall survival, while the low expression of LINC00528 and MIR762HG was associated with worse overall survival. The 6-lncRNA model has an especially good predictive power for overall survival (p < 0.0001) and 3-year survival (the area under the curve = 0.980) in HER2-positive breast cancer patients. Conclusion: This study provides a new efficient prognostic model and biomarkers of HER2-positive breast cancer. Meanwhile, it also provides a new perspective for elucidating the molecular mechanisms underlying HER2-positive breast cancer.

A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma

Background

Currently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.

Methods

Four hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set. The prognostic gene biomarker was developed and validated based on the above three sets. The developed gene biomarker combined with clinical characteristics was used as variables to develop and validate a nomogram predictive model based on 379 patients with complete clinical data from TCGA (Among 470 cases, 91 cases with missing clinical data were excluded from the study), which were randomly divided into the training set II (n = 189) and validation set II (n = 190). Area under the curve (AUC), concordance index (C-index), calibration curve, and Kaplan-Meier estimate were used to assess predictive performance of the nomogram model.

Results

Four genes, i.e., CLEC7A, CLEC10A, HAPLN3, and HCP5 comprise an immune-related prognostic biomarker. The predictive performance of the biomarker was validated using tROC and log-rank test in the training set I (n = 224, 5-year AUC of 0.683), validation set I (n = 225, 5-year AUC of 0.644), and test set I (n = 210, 5-year AUC of 0.645). The biomarker was also significantly associated with improved survival in the training set (P < 0.01), validation set (P < 0.05), and test set (P < 0.001), respectively. In addition, a nomogram combing the four-gene biomarker and six clinical factors for predicting survival in melanoma was developed in the training set II (n = 189), and validated in the validation set II (n = 190), with a concordance index of 0.736 ± 0.041 and an AUC of 0.832 ± 0.071.

Conclusion

We developed and validated a nomogram predictive model combining a four-gene biomarker and six clinical factors for melanoma patients, which could facilitate risk stratification and treatment planning.

Prognostic value of aberrantly expressed methylation genes in human hepatocellular carcinoma

Objectives: To identify the prognostic value of aberrantly methylated differentially expressed genes (DEGs) in hepatocellular carcinoma (HCC) and to explore the underlying mechanisms of tumorigenesis.

Methods: Gene expression profiles (GSE65372 and GSE37988) were analyzed using GEO2R to obtain aberrantly methylated DEGs. Functional enrichment analysis of screened genes was performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Cytoscape software was used to analyze the PPI network and to select hub genes. Transcriptional and proteinic expression data of hub genes were obtained through UALCAN and the Human Protein Reference Database. Finally, we analyzed the prognostic value of hub genes with the Kaplan–Meier Plotter and MethSurv database.

Results: In total, 24 up-hypomethylated oncogenes and 37 down-hypermethylated tumor suppressor genes (TSGs) were identified, and 8 hub genes, including 4 up-hypomethylated oncogenes (CDC5L, MERTK, RHOA and YBX1) and 4 down-hypermethylated TSGs (BCR, DFFA, SCUBE2 and TP63), were selected by PPI. Higher expression of methylated CDC5L-cg05671347, MERTK-cg08279316, RHOA-cg05657651 and YBX1-cg16306148, and lower expression of methylated BCR-cg25410636, DFFA-cg20696875, SCUBE2-cg19000089 and TP63-cg06520450, were associated with better overall survival (OS) in HCC patients. Multivariate analysis also showed they were independent prognostic factors for OS of HCC patients.

Conclusions: In summary, different expression of methylated genes above mentioned were associated with better prognosis in HCC patients. Altering the methylation status of these genes may be a therapeutic target for HCC, but it should be further evaluated in clinical studies.

Integrated analysis of DNA methylation and mRNA expression profiles to identify key genes in head and neck squamous cell carcinoma

DNA methylation has been demonstrated to play significant roles in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). In the present study, methylation microarray dataset (GSE87053) and gene expression microarray dataset (GSE23558) were downloaded from GEO database and analyzed through R language. A total of 255 hypermethylated-downregulated genes and 114 hypomethylated-upregulated genes were finally identified. Functional enrichment analyses were performed and a comprehensive protein–protein interaction (PPI) network was constructed. Subsequently, the top ten hub genes selected by Cytoscape software were subjected to further analyses. It was illustrated that the expression level of CSF2, CTLA4, ETS1, PIK3CD, and CFTR was intimately associated with HNSCC. Survival analysis suggested that CTLA4 and FGFR2 could serve as effective independent prognostic biomarkers for HNSCC patients. Overall, our study lay a groundwork for further investigation into the underlying molecular mechanisms in HNSCC carcinogenesis, providing potential biomarkers and therapeutic targets for HNSCC.

Association between circulating follistatin-like-1 and metabolic syndrome in middle-aged and old population: A cross-sectional study

AIM

Follistatin-like-1 (FSTL-1) is considered to be a novel cytokine, and it is associated with metabolic diseases. However, it is necessary to investigate further the association of FSTL-1 with metabolic syndrome (MetS) and insulin resistance (IR). We performed a cross-sectional study to investigate the associated of circulating FSTL-1 with the MetS.

MATERIALS AND METHODS

A cross-sectional study was performed in 487 Chinese people, including 231 control subjects and 256 patients with MetS. Bioinformatics analysis was used to determine the protein and pathways associated with FSTL-1. The protein and protein interaction (PPI) network was constructed and analysed. Serum FSTL-1 concentrations were determined by an ELISA assay. The association of FSTL-1 with MetS components and IR was assessed.

RESULTS

Serum FSTL-1 levels were markedly higher in patients with newly diagnosed MetS than in controls (7.5 [5.6-9.2] vs 5.8 [5.0-7.7] μg/L, P < .01). According to bioinformatics analysis, the top high-degree genes were identified as the core genes, including SPARCL1, CYR61, LTBP1, IL-6, BMP2, BMP4, FBN1, FN1 CHRDL1 and FSTL-3. These genes are mainly enriched in pathways including TGF-ß, AGE-RAGE signalling pathway in diabetic complications, and Hippo signalling pathways; in basal cell carcinoma, cytokine-cytokine receptor interaction and in amoebic and Yersinia infections. Furthermore, serum FSTL-1 levels were positively associated with fasting plasma glucose (FPG), waist circumference (WC), blood pressure, triglyceride levels and visceral adiposity index (VAI). We found that serum FSTL-1 levels were markedly associated with MetS and IR by binary logistic regression analysis.

CONCLUSIONS

We conclude that FSTL-1 may be a novel cytokine related to MetS and IR.

Investigation of circRNA-miRNA-mRNA network in colorectal cancer using an integrative bioinformatics approach

AIM

The aim of this study was to integrate both coding and non-coding available microarray data in the development of colorectal cancer (CRC) with bioinformatics analyses to attain a more inclusive pathobiologic map of their molecular interactions and functions.

BACKGROUND

Identification of competing endogenous RNAs (ceRNAs), especially circRNAs, has become a new hotspot in cancer research, although their roles and underlying mechanisms in CRC development remain mostly unknown.

METHODS

Microarray data was retrieved from the Gene Expression Omnibus (GEO) database and analyzed. Several bioinformatics tools and databases were applied for further elucidation. Principal component analysis (PCA) was run separately for four datasets. The dysregulated circRNA-miRNA-mRNA, co-expression, and protein-protein interaction (PPI) networks were established.

RESULTS

PCA discloses colorectal tumors; normal tissue can be distinguished not only by mRNAs expression profile, but also by both circRNA and miRNA expression profiles. In this study, 14 DE mRNAs, 85 DE miRNAs, and 36 DE circRNAs were identified in CRC tissue and compared with normal tissue. Taking their potential interactions into account, a circRNA-miRNA-mRNA network was constructed. The results disclosed some DE circRNAs with potential oncogenic (circ_0014879) or tumor suppressive (circ_0001666 and circ_0000977) effects. Finally, the PPI network suggests pivotal roles for DOCK2 and PTPRC dysregulation in the progression of CRC, possibly by facilitating tumor escape from immune surveillance.

CONCLUSION

The current study proposes a novel regulatory network consisting of DE circRNAs, miRNAs, and mRNAs in CRC development that highlights the roles of DE circRNAs at the upstream of oncotranscriptomic cascade in CRC development, suggesting their potential to be utilized as both prognostic and therapeutic biomarkers.

Circulating CTRP7 Is a Potential Predictor for Metabolic Syndrome

BACKGROUND

Previous animal studies have revealed that CTRP7 is related to energy metabolism. However, little is known regarding the relationship between CTRP7 and metabolic diseases in humans. Hence, this study was designed to explore the association between CTRP7 and MetS through a cross-sectional study and multiple intervention studies.

METHODS

A total of 624 individuals were enrolled in this study. The levels of CTRP7 and APN were determined by ELISA kit. HEC, OGTT and lipid infusion were performed in heathy individuals to investigate the association of CTRP7 and glucose, insulin and FFA. Bioinformatics analysis was then undertaken to identify genes and signaling pathways associated with CTRP7. The relationship between CTRP7 with MetS components was also evaluated.

RESULTS

In MetS patients, serum CTRP7 concentrations were significantly higher than in healthy controls, and was positively correlated with WC, BP, FBG, 2h-BG and TG, but negatively correlated with HDL-C and APN. Multivariate logistic regression analysis uncovered that CTRP7 was strongly correlated with the occurrence of MetS. In addition, circulating levels of CTRP7 in patients with two or more MetS components were higher than those with one MetS component. In the intervention studies, OGTTs resulted in a significant reduction in serum CTRP7 concentration. However, the increase in insulin levels caused by EHC and the increase of FFA caused by lipid-infusion led to the significant increase of serum CTRP7 concentration. Meanwhile, bioinformatics analysis revealed that CTRP7 was strongly associated with metabolism-related genes and signal pathways, which further illustrate the association of CTRP7 with whole-body metabolism.

CONCLUSIONS

Serum CTRP7 is increased in MetS patients, which may be a biomarker related to metabolic diseases.

CLINICAL TRIAL REGISTRATION NUMBER

ChiCTR2000032878.

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.

Differential Expression and Bioinformatics Analysis of circRNA in Non-small Cell Lung Cancer

Circular RNA (CircRNA) plays an important role in tumorigenesis and progression of non-small cell lung cancer (NSCLC), but the pathogenesis of NSCLC caused by circRNA has not been fully elucidated. This study aimed to investigate differentially expressed circRNAs and identify the underlying pathogenesis hub genes of NSCLC by comprehensive bioinformatics analysis. Data of gene expression microarrays (GSE101586, GSE101684, and GSE112214) were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DECs) were obtained by the “limma” package of R programs and the overlapping operation was implemented of DECs. CircBase database and Cancer-Specific CircRNA database (CSCD) were used to find miRNAs binding to DECs. Target genes of the found miRNAs were identified utilizing Perl programs based on miRDB, miRTarBase, and TargetScan databases. Functional and enrichment analyses of selected target genes were performing using the “cluster profiler” package. Protein-protein interaction (PPI) network was constructed by the Search Tool for the STRING database and module analysis of selected hub genes was performed by Cytoscape 3.7.1. Survival analysis of hub genes were performed by Gene Expression Profiling Interactive Analysis (GEPIA). Respectively, 1 DEC, 249 DECs, and 101 DECs were identified in GSE101586, GSE101684, and GSE112214. A total of eight overlapped circRNAs, 43 miRNAs and 427 target genes were identified. Gene Ontology (GO) enrichment analysis showed these target genes were enriched in biological processes of regulation of histone methylation, Ras protein signal transduction and covalent chromatin modification etc. Pathway enrichment analysis showed these target genes are mainly involved in AMPK signaling pathway, signaling pathways regulating pluripotency of stem cells and insulin signaling pathway etc. A PPI network was constructed based on 427 target genes of the 43 miRNAs. Ten hub genes were found, of which the expression of MYLIP, GAN, and CDC27 were significantly related to NSCLC patient prognosis. Our study provide a deeper understanding the circRNAs-miRNAs-target genes by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of NSCLC. MYLIP, GAN, and CDC27 genes might serve as novel biomarker for precise treatment and prognosis of NSCLC in the future.

Systems-level differential gene expression analysis reveals new genetic variants of oral cancer

Oral cancer (OC) ranked as eleventh malignancy worldwide, with the increasing incidence among young patients. Limited understanding of complications in cancer progression, its development system, and their interactions are major restrictions towards the progress of optimal and effective treatment strategies. The system-level approach has been designed to explore genetic complexity of the disease and to identify novel oral cancer related genes to detect genomic alterations at molecular level, through cDNA differential analysis. We analyzed 21 oral cancer-related cDNA datasets and listed 30 differentially expressed genes (DEGs). Among 30, we found 6 significant DEGs including CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13 and studied their functional role in OC. Our genomic and interactive analysis showed significant enrichment of xenobiotics metabolism, p53 signaling pathway and microRNA pathways, towards OC progression and development. We used human proteomic data for post-translational modifications to interpret disease mutations and inter-individual genetic variations. The mutational analysis revealed the sequence predicted disordered region of 14%, 12.5%, 10.5% for ADCY2, CYP1B1, and C7 respectively. The MiRNA target prediction showed functional molecular annotation including specific miRNA-targets hsa-miR-4282, hsa-miR-2052, hsa-miR-216a-3p, for CYP1B1, C7, and ADCY2 respectively associated with oral cancer. We constructed the system level network and found important gene signatures. The drug-gene interaction of OC source genes with seven FDA approved OC drugs help to design or identify new drug target or establishing novel biomedical linkages regarding disease pathophysiology. This investigation demonstrates the importance of system genetics for identifying 6 OC genes (CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13) as potential drugs targets. Our integrative network-based system-level approach would help to find the genetic variants of OC that can accelerate drug discovery outcomes to develop a better understanding regarding treatment strategies for many cancer types.

Identifying the hub gene and immune infiltration of osteoarthritis by bioinformatical methods

BACKGROUND

Nowadays, there are more and more people who have been diagnosed osteoarthritis (OA). However, due to the complex changes of OA, the treatment outcome is not very well. In order to improve this situation, I decided to aggregate a series of data and use complex bioinformatical methods to analyze them, hoping to explore new therapeutic targets.

METHODS

After downloading and processing the data from Gene Expression Omnibus (GEO) database, I analyzed the relationship between genes and OA formation by the weighted correlation network analysis (WGCNA)and selected the turquoise module which owned the closest relationship with clinical traits. Then, via online database and CIBERSORT algorithm method, I analyzed the function of this key module and the situation of immune infiltration in OA tissues.

RESULTS

With the help of WGCNA and functional enrichment analysis, I found out that most of genes in the turquoise module took part in the inflammation development, immune responses, and cell proliferation, especially the hub gene PRKACB. At the same time, my results of immune infiltration and expression level analysis also showed that PRKACB has a close relationship with immune cells, especially M2 macrophage.

CONCLUSION

In a word, my results suggested that PRKACB played an essential role in osteoarthritis development. Key Points • Used the "sva" R package to combine the data of 59 samples from four studies to do the bioinformatical analysis. • Identifying the hub gene PRKACB as potential marker for OA and using validation sets to confirm it. • Detecting the situation of immune infiltration in synovium by CIBERSORT algorithm method.

Study of Osteoarthritis-Related Hub Genes Based on Bioinformatics Analysis

Osteoarthritis (OA) is a common cause of morbidity and disability worldwide. However, the pathogenesis of OA is unclear. Therefore, this study was conducted to characterize the pathogenesis and implicated genes of OA. The gene expression profiles of GSE82107 and GSE55235 were downloaded from the Gene Expression Omnibus database. Altogether, 173 differentially expressed genes including 68 upregulated genes and 105 downregulated genes in patients with OA were selected based on the criteria of ∣log fold-change | >1 and an adjusted p value < 0.05. Protein-protein interaction network analysis showed that FN1, COL1A1, IGF1, SPP1, TIMP1, BGN, COL5A1, MMP13, CLU, and SDC1 are the top ten genes most closely related to OA. Quantitative reverse transcription-polymerase chain reaction showed that the expression levels of COL1A1, COL5A1, TIMP1, MMP13, and SDC1 were significantly increased in OA. This study provides clues for the molecular mechanism and specific biomarkers of OA.

Clinicopathological Analysis and Prognostic Assessment of Transcobalamin I (TCN1) in Patients with Colorectal Tumors

BACKGROUND Colorectal cancer (CRC) is one of the most common malignancies worldwide. Overall survival (OS) of patients is largely dependent on disease stage at diagnosis and/or surgical resection. TCN1 mainly encodes the vitamin B12 transporter, transcobalamin. Early studies show that TCN1 is a marker of CRC progression, but the impact of TCN1 on survival is unclear. MATERIAL AND METHODS We reviewed and analyzed colorectal tumor records, summarized the clinicopathological data, performed immunohistochemical detection of TCN1 again, and semi-quantitatively analyzed protein expression in tumor tissue, non-tumor tissue, and lymph nodes. We followed up patients for 5-year survival. RESULTS Of 123 patients, 60 (48.7%) had a strong TCN1 immunohistochemical reaction, 36 (29.3%) had a moderate immune response, and 27 (22.0%) had weak expression. The level of immunohistochemical reactivity of TCN1 was correlated with the degree of histological differentiation (H (2.92)=4.976; P=0.083). Survival analysis showed that OS in patients with low TCN1 expression was significantly longer than that in the medium and high TCN1 expression groups (P=0.045). Five-year OS in patients with low, medium, and high TCN1 expression was 88.9%, 50.0%, and 40.0%, respectively. In univariate analysis, TCN1 immune expression was significantly correlated with the 5-year survival rate. CONCLUSIONS Although independent risk factors affecting survival of patients with CRC are age, serum CA125, CA19-9, lymph node metastasis, and nerve invasion, negative factors affecting overall 5-year survival in TCN1 should not be ignored, because its high expression suggests a worse clinical prognosis.

Identification of methylated-differentially expressed genes and pathways in esophageal squamous cell carcinoma

Methylation, as an epigenetic modification, can affect gene expression and play a role in the occurrence and development of cancer. This research is devoted to discover methylated-differentially expressed genes (MDEGs) in esophageal squamous cell carcinoma (ESCC) and explore special associated pathways. We downloaded GSE51287 methylation profiles and GSE26886 expression profiles from GEO DataSets, and performed a comprehensive bioinformatics analysis. Totally, 19 hypermethylated, lowly expressed genes (Hyper-LGs) were identified, and involved in regulation of cell proliferation, phosphorus metabolic process and protein kinase activity. Meanwhile, 17 hypomethylated, highly expressed genes (Hypo-HGs) were participated in collagen catabolic process, metallopeptidase and cytokine activity. Pathway analysis determined that Hyper-LGs were enriched in arachidonic acid metabolism pathway, while Hypo-HGs were primarily associated with the cytokine-cytokine receptor interaction pathway. IL 6, MMP3, MMP9, SPP1 were identified as hub genes based on the PPI network that combined 7 ranked methods included in cytoHubba, and verification was performed in human tissues. Our integrated analysis identified many novel genetic lesions in ESCC and provides a crucial molecular foundation to improve our understanding of ESCC. Hub genes, including IL 6, MMP3, MMP9 and SPP1, could be considered for use as aberrant methylation-based biomarkers to facilitate the accurate diagnosis and therapy of ESCC.

Hypomethylation of the cyclin D1 promoter in hepatitis B virus-associated hepatocellular carcinoma

The hypomethylation of the Cyclin D1 (CCND1) promoter induced by excess oxidative stress likely promotes the development of hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC). We aimed to evaluate methylation status of the CCND1 promoter as a new plasma marker for the detection of HBV-HCC.We consecutively recruited 191 participants, including 105 patients with HBV-HCC, 54 patients with chronic hepatitis B (CHB), and 32 healthy controls (HCs). Using methylation-specific polymerase chain reaction, we identified the methylation status of the CCND1 promoter in plasma samples. We analyzed the expression levels of the CCND1 mRNA in peripheral blood mononuclear cells by using quantitative real-time PCR. We assessed the plasma levels of superoxide dismutase, 8-hydroxydeoxyguanosine and malondialdehyde by using enzyme-linked immunosorbent assays.Patients with HBV-HCC (23.81%) presented a reduced methylation frequency compared with patients with CHB (64.81%) or HCs (78.13%) (P < .001). When receiver operating characteristic curves were plotted for patients with HBV-HCC versus CHB, the methylation status of the CCND1 promoter yielded diagnostic parameter values for the area under the curve of 0.705, sensitivity of 76.19%, and specificity of 64.81%, thus outperforming serum alpha-fetoprotein (AFP), which had an area under the curve of 0.531, sensitivity of 36.19%, and specificity of 90.74%. Methylation of the CCND1 promoter represents a prospective diagnostic marker for patients with AFP-negative HBV-HCC and AFP-positive CHB. The expression levels of CCND1 mRNA was increased in patients with HBV-HCC compared with patients with CHB (Z = -4.946, P < .001) and HCs (Z = -6.819, P < .001). Both the extent of oxidative injury and antioxidant capacity indicated by the superoxide dismutase, 8-hydroxydeoxyguanosine and malondialdehyde levels were increased in patients with HBV-HCC. Clinical follow up of patients with HBV-HCC revealed a worse overall survival (P = .012, log-rank test) and a decreased progression-free survival (HR = 0.109, 95%CI: 0.031-0.384) for the unmethylated CCND1 group than methylated CCND1 group.Our study confirms that oxidative stress appears to correlate with plasma levels of CCND1 promoter methylation, and the methylation status of the CCND1 promoter represents a prospective biomarker with better diagnostic performance than serum AFP levels.

The potential drug for treatment in pancreatic adenocarcinoma: a bioinformatical study based on distinct drug databases

Background

The prediction of drug-target interaction from chemical and biological data can advance our search for potential drug, contributing to a therapeutic strategy for pancreatic adenocarcinoma (PAAD). We aim to identify hub genes of PAAD and search for potential drugs from distinct databases. The docking simulation is adopted to validate our findings from computable perspective.

Methods

Differently expressed genes (DEGs) of PAAD were performed based on TCGA. With two Cytoscape plugins of CentiScaPe and MCODE, hub genes were analyzed and visualized by STRING analysis of Protein–protein Interaction (PPI). The hub genes were further selected with significant prognostic values. In addition, we examined the correlation between hub genes and immune infiltration in PAAD. Subsequently, we searched for the hub gene-targeted drugs in Connectivity map (Cmap) and cBioportal, which provided a large body of candidate drugs. The hub gene, which was covered in the above two databases, was estimated in Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Herbal Ingredients’ Targets (HIT) database, which collected natural herbs and related ingredients. After obtaining molecular structures, the potential ingredient from TCMSP was applied for a docking simulation. We finalized a network connectivity of ingredient and its targets.

Results

A total of 2616 DEGs of PAAD were identified, then we further determined and visualized 24 hub genes by a connectivity analysis of PPI. Based on prognostic value, we identified 5 hub genes including AURKA (p = 0.0059), CCNA2 (p = 0.0047), CXCL10 (p = 0.0044), ADAM10 (p = 0.00043), and BUB1 (p = 0.0033). We then estimated tumor immune correlation of these 5 hub genes, because the immune effector process was one major result of GO analysis. Subsequently, we continued to search for candidate drugs from Cmap and cBioportal database. BUB1, not covered in the above two databases, was estimated in TCMSP and HIT databases. Our results revealed that genistein was a potential drug of BUB1. Next, we generated two docking modes to validate drug-target interaction based on their 3D structures. We eventually constructed a network connectivity of BUB1 and its targets.

Conclusions

All 5 hub genes that predicted poor prognosis had their potential drugs, especially our findings showed that genistein was predicted to target BUB1 based on TCMSP and docking simulation. This study provided a reasonable approach to extensively retrieve and initially validate putative therapeutic agents for PAAD. In future, these drug-target results should be investigated with solid data from practical experiments.

FBXW4 Acts as a Protector of FOLFOX-Based Chemotherapy in Metastatic Colorectal Cancer Identified by Co-Expression Network Analysis

Background

FOLFOX chemotherapy is one of the most commonly used treatments for colorectal cancer (CRC) patients. However, the efficacy and tolerance of FOLFOX therapy varies between patients. The purpose of this study was to explore hub genes associated with primary chemotherapy-resistance and to explore the possible mechanisms involved from non-European patients.

Method

A weighted gene co-expression network was constructed to identify gene modules associated with chemotherapy resistance in mCRC from China.

Results

A Gene Array Chip was used to detect mRNA expression in 11 mCRC patients receiving preoperative FOLFOX chemotherapy. The immune response was associated with chemotherapy-resistance in microarray data. Through the use of WGCNA, we demonstrated that the crucial functions enriched in chemotherapy-resistance modules were cell proliferation, MAPK signaling pathways, and PI3K signaling pathways. Additionally, we identified and validated FBXW4 as a new effective predictor for chemotherapy sensitivity and a prognostic factor for survival of CRC patients by using our own data and GSE69657. Furthermore, a meta-analysis of 15 Gene Expression Omnibus–sourced datasets showed that FBXW4 messenger RNA levels were significantly lower in CRC tissues than in normal colon tissues. An analysis of the data from the R2: Genomics Analysis and Visualization Platform showed that low FBXW4 expression was correlated with a significantly worse event- and relapse-free survival. Gene set enrichment analysis showed that the mechanism of FBXW4-mediated chemotherapy resistance may involve the DNA replication signal pathway and the cell cycle.

Conclusion

FBXW4 is associated with chemotherapy resistance and prognosis of CRC probably by regulating DNA replication signaling pathways and the cell cycle.

Methylation of the ataxia telangiectasia mutated gene (ATM) promoter as a radiotherapy outcome biomarker in patients with hepatocellular carcinoma

The goal of this study was to evaluate the contribution of ataxia telangiectasia mutated (ATM) gene promoter methylation to hepatocellular carcinoma (HCC) and the predictive value of radiotherapy outcome. ATM promoter methylation status was detected using methylation-specific PCR in 118 HCC, 50 adjacent liver, and 20 normal liver samples. PCR products were verified by bisulfite sequencing PCR. ATM expression was detected by quantitative PCR (qPCR) and immunohistochemistry (IHC) in 50 paired HCC and adjacent normal tissues and 68 locally advanced HCC biopsy tissues. Furthermore, radiotherapy outcomes in 68 locally advanced HCC patients were determined using European Association for the Study of Liver criteria and survival analysis. The results revealed that the methylation frequency of the ATM promoter was significantly higher in HCC tissues than in normal liver tissues (χ = 16.830, P < .001). Quantitative PCR (qPCR) and IHC results showed a significant association between ATM promoter methylation and ATM expression in HCC (χ = 10.510, P < .001), and methylated ATM was correlated with lower ATM expression compared with unmethylated ATM (r = 0.356, P < .001). Furthermore, methylation of the ATM promoter was significantly associated with superior outcomes in patients with locally advanced HCC who initially received radiotherapy. Together, these results indicate that ATM promoter methylation might increase the risk of HCC by regulating ATM expression, and thus may function as a potential biomarker for predicting radiotherapy outcomes in HCC patients.

Prediction of crucial epigenetically‑associated, differentially expressed genes by integrated bioinformatics analysis and the identification of S100A9 as a novel biomarker in psoriasis

Psoriasis is one of the most common immune-mediated inflammatory diseases of the skin. The identification of the pivotal molecular mechanisms responsible for the disease pathogenesis may lead to the development of novel therapeutic options. The present study aimed to identify pivotal differentially expressed genes (DEGs) and methylated DEGs in psoriasis. The raw data from gene microarrays were obtained from the Gene Expression Omnibus database. The data were processed using packages in Bioconductor. In total, 352 upregulated and 137 downregulated DEGs were identified. The upregulated DEGs were primarily enriched in the 'innate immune defense' response and the 'cell cycle'. The down-regulated DEGs were primarily enriched in 'cell adhesion' and 'tight junction pathways'. A total of 95 methylated DEGs were identified, which were significantly enriched in the 'interleukin (IL)-17 signaling pathway' and the 'response to interferon'. Based on a comprehensive evaluation of all algorithms in cytoHubba, the key epigenetic-associated hub genes (S100A9, SELL, FCGR3B, MMP9, S100A7, IL7R, IRF7, CCR7, IFI44, CXCL1 and LCN2) were screened out. In order to further validate these genes, the present study constructed a model of imiquimod (IMQ)-induced psoriasiform dermatitis using mice. The levels of these hub genes were increased in the IMQ group. The knockdown of methylation-regulating enzyme ten-eleven translocation (TET) 2 expression in mice attenuated the expression levels of S100A9, SELL, IL7R, MMP9, CXCL1 and LCN2. Furthermore, the hydroxymethylated level of S100A9 was highly expressed in the IMQ group and was significantly decreased by TET2 deficiency in mice. On the whole, using an integrative system bioinformatics approach, the present study identified a series of characteristic enrichment pathways and key genes that may serve as potential biomarkers in psoriasis.

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.

Identification of aberrantly methylated differentially expressed genes in glioblastoma multiforme and their association with patient survival

Glioblastoma multiforme (GBM) is the most malignant primary tumour type of the central nervous system with limited therapeutic options and poor prognosis, and its pathogenic mechanisms have remained to be fully elucidated. Aberrant DNA methylation is involved in multiple biological processes and may contribute to the occurrence and development of GBM by affecting the expression of certain genes. However, the specific molecular mechanisms remain to be fully elucidated. The present study focused on uncovering differentially expressed genes with altered methylation status in GBM and aimed to discover novel biomarkers for the diagnosis and treatment of GBM. These genes were identified by combined analysis of multiple gene expression and methylation datasets from gene expression omnibus (GSE16011, GSE50161 and GSE 50923) to increase the reliability. In addition, The Cancer Genome Atlas (TCGA) dataset for GBM was used to test the stability of the results. Overall, 251 hypomethylated upregulated genes (Hypo-UGs) and 199 hypermethylated downregulated genes (Hyper-DGs) were identified in the present study. Functional enrichment analysis revealed that the Hypo-UGs are involved in the regulation of immune- and infection-associated signalling, while the Hyper-DGs are involved in the regulation of synaptic transmission. The three hub genes for Hyper-DGs (somatostatin, neuropeptide Y and adenylate cyclase 2) and five hub genes for Hypo-UGs [interleukin-8, matrix metalloproteinase (MMP)9, cyclin-dependent kinase 1, 2′-5′-oligoadenylate synthetase 1, C-X-C motif chemokine ligand 10 and MMP2] were identified by protein-protein interaction network analysis. Among the Hypo-UGs and Hyper-DGs, overexpression of C-type lectin domain containing 5A, epithelial membrane protein 3, solute carrier family 43 member 3, STEAP3 metalloreductase, tumour necrosis factor α-induced protein 6 and apolipoprotein B mRNA editing enzyme catalytic subunit 3G was significantly associated with poor prognosis in the TCGA and GSE16011 datasets (P<0.001). In conclusion, the present study uncovered numerous novel aberrantly methylated genes and pathways associated with GBM. Methylation-based markers, including the hub genes and prognostic genes identified, may potentially serve as markers for the diagnosis of GBM and targets for its treatment.

DNA methylation and chromatin modifiers in colorectal cancer

Colorectal carcinogenesis is a multistep process involving the accumulation of genetic alterations over time that ultimately leads to disease progression and metastasis. Binding of transcription factors to gene promoter regions alone cannot explain the complex regulation pattern of gene expression during this process. It is the chromatin structure that allows for a high grade of regulatory flexibility for gene expression. Posttranslational modifications on histone proteins such as acetylation, methylation, or phosphorylation determine the accessibility of transcription factors to DNA. DNA methylation, a chemical modification of DNA that modulates chromatin structure and gene transcription acts in concert with these chromatin conformation alterations. Another epigenetic mechanism regulating gene expression is represented by small non-coding RNAs. Only very recently epigenetic alterations have been included in molecular subtype classification of colorectal cancer (CRC). In this chapter, we will provide examples of the different epigenetic players, focus on their role for epithelial-mesenchymal transition and metastatic processes and discuss their prognostic value in CRC.

Alteration of microRNA-4474/4717 expression and CREB-binding protein in human colorectal cancer tissues infected with Fusobacterium nucleatum

Colorectal cancer (CRC) is a common and highly lethal form of cancer. Although the etiologic role of Fusobacterium nucleatum (F. nucleatum) in the development of CRC has been elucidated, the specific tumor molecules involved in the progression of CRC induced by F. nucleatum have not been identified. This study investigated several miRNAs and genes involved in the progression of F. nucleatum-induced CRC by Affymetrix miRNA microarray technology and GeneChip Human Transcriptome Array 2.0. The results suggest that miR-4474 and miR-4717 are up-regulated in CRC tissues in response to F. nucleatum infection, compared with the control group (paracancerous tissues), while other genes associated with signaling pathways in cancer, including CREB-binding protein (CREBBP), STAT1, PRKACB, CAMK2B, JUN, TP53 and EWSR1, were dysregulated. Bioinformatic analysis identified CREBBP as the primary aberrantly expressed gene in F. nucleatum-induced CRC. Consistent with the microarray analysis results, real-time RT-PCR analysis demonstrated that the expression of miR-4474/4717 was upregulated while that of CREBBP mRNA was downregulated in CRC patients infected with F. nucleatum. Additionally, CREBBP was identified as a novel target of miR-4474/4717. The results of this study suggest that miR-4474 and miR-4717 are involved in the progression of F. nucleatum-induced CRC by posttranscriptionally regulating the target gene CREBBP.

Identification of SERPINE1, PLAU and ACTA1 as biomarkers of head and neck squamous cell carcinoma based on integrated bioinformatics analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the six leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains less than 65% due to lack of symptoms in the early stage. Hence, biomarkers which can improve detection of HNSCC should improve clinical outcome.

METHODS

Gene expression profiles (GSE6631, GSE58911) and the Cancer Genome Atlas (TCGA) HNSCC data were used for integrated bioinformatics analysis; the differentially expressed genes (DEGs) were then subjected to functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction. Subsequently, module analysis of the PPI network was performed and overall survival (OS) analysis of hub genes in subnetwork was studied. Finally, immunohistochemistry was used to verify the selected markers.

RESULTS

A total of 52 up-regulated and 80 down-regulated DEGs were identified, which were mainly associated with ECM-receptor interaction and focal adhesion signaling pathways. Importantly, a set of prognostic signatures including SERPINE1, PLAU and ACTA1 were screened from DEGs, which could predict OS in HNSCC patients from TCGA cohort. Experiment of clinical samples further successfully validated that these three signature genes were aberrantly expressed in the oral epithelial dysplasia and HNSCC, and correlated with aggressiveness of HNSCC patients.

CONCLUSIONS

SERPINE1, PLAU and ACTA1 played important roles in regulating the initiation and progression of HNSCC, and could be identified as key biomarkers for precise diagnosis and prognosis of HNSCC, which will provide potential targets for clinical therapies.

Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics

Background

Methylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis.

Methods

Expression profile (GSE29079) and methylation profile (GSE76938) datasets were obtained from the Gene Expression Omnibus (GEO). We used R 3.4.4 software to assess aberrantly methylated DEGs. The Cancer Genome Atlas (TCGA) RNA sequencing and Illumina HumanMethylation450 DNA methylation data were utilized to validate screened genes. Functional enrichment analysis of the screened genes was performed, and a protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Gens (STRING). The results were visualized in Cytoscape. After confirmation using TCGA, cBioPortal was used to examine alterations in genes of interest. Then, protein localization in PCa cells was observed using immunohistochemistry.

Results

Overall, 536 hypomethylated upregulated genes were identified that were enriched in biological processes such as negative regulation of transcription, osteoblast differentiation, intracellular signal transduction, and the Wnt signalling pathway. Pathway enrichment showed significant changes in factors involved in AMPK signalling, cancer, and adherens junction pathways. The hub oncogenes were AKT1, PRDM10, and FASN. Additionally, 322 hypermethylated downregulated genes were identified that demonstrated enrichment in biological processes including positive regulation of the MAPK cascade, muscle contraction, ageing, and signal transduction. Pathway analysis indicated enrichment in arrhythmogenic right ventricular cardiomyopathy (ARVC), focal adhesion, dilated cardiomyopathy, and PI3K-AKT signalling. The hub tumour suppressor gene was FLNA. Immunohistochemistry showed that AKT1, FASN, and FLNA were mainly expressed in PCa cell cytoplasm, while PRDM10 was mainly expressed in nuclei.

Conclusions

Our results identify numerous novel genetic and epigenetic regulatory networks and offer molecular evidence crucial to understanding the pathogenesis of PCa. Aberrantly methylated hub genes, including AKT1, PRDM10, FASN, and FLNA, can be used as biomarkers for accurate PCa diagnosis and treatment. In conclusion, our study suggests that AKT1, PRDM10, and FASN may be tumour promoters and that FLNA may be a tumour suppressor in PCa. We hope these findings will draw more attention to these hub genes in future cancer studies.