Bioinformatics identification of lncRNA biomarkers associated with the progression of esophageal squamous cell carcinoma. Mol Med Rep. 2019;19:5309-5320. [PMID: 31059058 PMCID: PMC6522958 DOI: 10.3892/mmr.2019.10213]

Novel milestones for early esophageal carcinoma: From bench to bed

Esophageal cancer (EC) is the seventh most common cancer worldwide, and esophageal squamous cell carcinoma (ESCC) accounts for the majority of cases of EC. To effectively diagnose and treat ESCC and improve patient prognosis, timely diagnosis in the initial phase of the illness is necessary. This article offers a detailed summary of the latest advancements and emerging technologies in the timely identification of ECs. Molecular biology and epigenetics approaches involve the use of molecular mechanisms combined with fluorescence quantitative polymerase chain reaction (qPCR), high-throughput sequencing technology (next-generation sequencing), and digital PCR technology to study endogenous or exogenous biomolecular changes in the human body and provide a decision-making basis for the diagnosis, treatment, and prognosis of diseases. The investigation of the microbiome is a swiftly progressing area in human cancer research, and microorganisms with complex functions are potential components of the tumor microenvironment. The intratumoral microbiota was also found to be connected to tumor progression. The application of endoscopy as a crucial technique for the early identification of ESCC has been essential, and with ongoing advancements in technology, endoscopy has continuously improved. With the advancement of artificial intelligence (AI) technology, the utilization of AI in the detection of gastrointestinal tumors has become increasingly prevalent. The implementation of AI can effectively resolve the discrepancies among observers, improve the detection rate, assist in predicting the depth of invasion and differentiation status, guide the pericancerous margins, and aid in a more accurate diagnosis of ESCC.

Potential effective diagnostic biomarker in patients with primary and metastatic small intestinal neuroendocrine tumors

Background: Small intestinal neuroendocrine tumors (SI-NETs) are the most common malignant tumors of the small intestine, with many patients presenting with metastases and their incidence increasing. We aimed to find effective diagnostic biomarkers for patients with primary and metastatic SI-NETs that could be applied for clinical diagnosis. Methods: We downloaded GSE65286 (training set) and GSE98894 (test set) from the GEO database and performed differential gene expression analysis to obtain differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs). The functions and pathways involved in these genes were further explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a global regulatory network involving dysregulated genes in SI-NETs was constructed based on RNAInter and TRRUST v2 databases, and the diagnostic power of hub genes was identified by receiver operating characteristic curve (ROC). Results: A total of 2,969 DEGs and DElncRNAs were obtained in the training set. Enrichment analysis revealed that biological processes (BPs) and KEGG pathways were mainly associated with cancer. Based on gene set enrichment analysis (GSEA), we obtained five BPs (cytokinesis, iron ion homeostasis, mucopolysaccharide metabolic process, platelet degranulation and triglyceride metabolic process) and one KEGG pathway (ppar signaling pathway). In addition, the core set of dysregulated genes obtained included MYL9, ITGV8, FGF2, FZD7, and FLNC. The hub genes were upregulated in patients with primary SI-NETs compared to patients with metastatic SI-NETs, which is consistent with the training set. Significantly, the results of ROC analysis showed that the diagnostic power of the hub genes was strong in both the training and test sets. Conclusion: In summary, we constructed a global regulatory network in SI-NETs. In addition, we obtained the hub genes including MYL9, ITGV8, FGF2, FZD7, and FLNC, which may be useful for the diagnosis of patients with primary and metastatic SI-NETs.

Advanced Platelet-Rich Fibrin Extract Treatment Promotes the Proliferation and Differentiation of Human Adipose-Derived Mesenchymal Stem Cells through Activation of Tryptophan Metabolism

BACKGROUND

Advanced platelet-rich fibrin extract (APRFE) contains a high concentration of various cytokines that are helpful for improving stem cells repair function.

OBJECTIVE

However, the underlying mechanism of APRFE improving stem cell repairing is not clear.

METHODS

We produced APRFE by centrifuging fresh peripheral blood samples and isolated and identified human adipose-derived mesenchymal stem cells (ADMSCs). The abundance of cytokines contained in APRFE was detected by the Enzyme-linked immunosorbent assay (ELISA). The ADMSCs treated with or without APRFE were collected for transcriptome sequencing.

RESULTS

Based on the sequencing data, the expression profiles were contracted. The differentially expressed genes and lncRNA (DEGs and DElncRNAs) were obtained using for the differential expression analysis. The lncRNA-miRNA-mRNA network was constructed based on the miRNet database. The further enrichment analysis results showed that the biological functions were mainly related to proliferation, differentiation, and cell-cell function. To explore the role of APRFE, the protein-protein interaction network was constructed among the cytokines included in APRFE and DEGs. Furthermore, we constructed the global regulatory network based on the RNAInter and TRRUST database. The pathways in the global regulatory network were considered as the core pathways. We found that the DEGs in the core pathways were associated with stemness scores.

CONCLUSION

In summary, we predicted that APRFE activated three pathways (tryptophan metabolism, mTOR signaling pathway, and adipocytokine signaling) to promote the proliferation and differentiation of ADMSCs. The finding may be helpful for guiding the application of ADMSCs in the clinic.

Intestinal flora induces depression by mediating the dysregulation of cerebral cortex gene expression and regulating the metabolism of stroke patients

Post-stroke depression (PSD) is a common cerebrovascular complication characterized by complex pathogenesis and poor treatment effects. Here, we tested the influence of differentially expressed genes (DEGs), non-targeted metabolites, and intestinal microbes on the occurrence and development of PSD. We acquired gene expression profiles for stroke patients, depression patients, and healthy controls from the Gene Expression Omnibus database. After screening for DEGs using differential expression analysis, we identified common DEGs in stroke and depression patients that were considered to form the molecular basis of PSD. Functional enrichment analysis of DEGs also revealed that the majority of biological functions were closely related to metabolism, immunity, the nervous system, and microorganisms, and we also collected blood and stool samples from healthy controls, stroke patients, and PSD patients and performed 16S rDNA sequencing and untargeted metabolomics. After evaluating the quality of the sequencing data, we compared the diversity of the metabolites and intestinal flora within and between groups. Metabolic pathway enrichment analysis was used to identify metabolic pathways that were significantly involved in stroke and PSD, and a global metabolic network was constructed to explore the pathogenesis of PSD. Additionally, we constructed a global regulatory network based on 16S rDNA sequencing, non-targeted metabolomics, and transcriptomics to explore the pathogenesis of PSD through correlation analysis. Our results suggest that intestinal flora associates the dysregulation of cerebral cortex gene expression and could potentially promote the occurrence of depression by affecting the metabolism of stroke patients. Our findings may be helpful in identifying new targets for the prevention and treatment of PSD.

An efficient five-lncRNA signature for lung adenocarcinoma prognosis, with AL606489.1 showing sexual dimorphism

Background: Lung adenocarcinoma (LUAD) is a sex-biased and easily metastatic malignant disease. A signature based on 5 long non-coding RNAs (lncRNAs) has been established to promote the overall survival (OS) prediction effect on LUAD.

Methods: The RNA expression profiles of LUAD patients were obtained from The Cancer Genome Atlas. OS-associated lncRNAs were identified based on the differential expression analysis between LUAD and normal samples followed by survival analysis, univariate and multivariate Cox proportional hazards regression analyses. OS-associated lncRNA with sex dimorphism was determined based on the analysis of expression between males and females. Functional enrichment analysis of the Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed to explore the possible mechanisms of 5-lncRNA signatures.

Results: A 5-lncRNA signature (composed of AC068228.1, SATB2-AS1, LINC01843, AC026355.1, and AL606489.1) was found to be effective in predicting high-risk LUAD patients as well as applicable to female and male subgroups and <65-year and ≥65-year age subgroups. The forecasted effect of the 5-lncRNA signature was more efficient and stable than the TNM stage and other clinical risk factors (such as sex and age). Functional enrichment analysis revealed that the mRNA co-expressed with these five OS-related lncRNAs was associated with RNA regulation within the nucleus. AL606489.1 demonstrated a sexual dimorphism that may be associated with microtubule activity.

Conclusion: Our 5-lncRNA signature could efficaciously predict the OS of LUAD patients. AL606489.1 demonstrated gender dimorphism, which provides a new direction for mechanistic studies on sexual dimorphism.

Cuproptosis-Associated lncRNA Establishes New Prognostic Profile and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) accounts for 80% of all kidney cancers and has a poor prognosis. Recent studies have shown that copper-dependent, regulated cell death differs from previously known death mechanisms (apoptosis, ferroptosis, and necroptosis) and is dependent on mitochondrial respiration (Tsvetkov et al., Science, 2022, 375 (6586), 1254–1261). Studies also suggested that targeting cuproptosis may be a novel therapeutic strategy for cancer therapy. In ccRCC, both cuproptosis and lncRNA were critical, but the mechanisms were not fully understood. The aim of our study was to construct a prognostic profile based on cuproptosis-associated lncRNAs to predict the prognosis of ccRCC and to study the immune profile of clear cell renal cell carcinoma (ccRCC).

Methods: We downloaded the transcriptional profile and clinical information of ccRCC from The Cancer Genome Atlas (TCGA). Co-expression network analysis, Cox regression method, and least absolute shrinkage and selection operator (LASSO) method were used to identify cuproptosis-associated lncRNAs and to construct a risk prognostic model. In addition, the predictive performance of the model was validated and recognized by an integrated approach. We then also constructed a nomogram to predict the prognosis of ccRCC patients. Differences in biological function were investigated by GO, KEGG, and immunoassay. Immunotherapy response was measured using tumor mutational burden (TMB) and tumor immune dysfunction and rejection (TIDE) scores.

Results: We constructed a panel of 10 cuproptosis-associated lncRNAs (HHLA3, H1-10-AS1, PICSAR, LINC02027, SNHG15, SNHG8, LINC00471, EIF1B-AS1, LINC02154, and MINCR) to construct a prognostic prediction model. The Kaplan–Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. The cuproptosis-associated lncRNA model had higher diagnostic efficiency compared to other clinical features. The analysis of Immune cell infiltration and ssGSEA further confirmed that predictive features were significantly associated with the immune status of ccRCC patients. Notably, the superimposed effect of patients in the high-risk group and high TMB resulted in shorter survival. In addition, the higher TIDE scores in the high-risk group suggested a poorer outcome for immune checkpoint blockade response in these patients.

Conclusion: The ten cuproptosis-related risk profiles for lncRNA may help assess the prognosis and molecular profile of ccRCC patients and improve treatment options, which can be further applied in the clinic.

Relationship of expression of heat shock transcription factor 1 with sensitivity to radiotherapy and chemotherapy in esophageal squamous cell carcinoma

BACKGROUND

The morbidity and mortality of esophageal cancer are extremely high all over the world, and the treatment effect is not good. As the pathogenesis of esophageal cancer is not yet fully understood, this is not conducive to the study of specific therapeutic drugs for esophageal cancer. Heat shock transcription fact 1 (HSF1) is closely related to the occurrence and development of a variety of malignant tumors. Is HSF1 also closely related to the occurrence and development of esophageal squamous cell carcinoma (ESCC)? Will HSF1 become a biological target for the treatment of ESCC? Different patients with advanced ESCC have different sensitivity to radiotherapy and chemotherapy. Studies have shown that in hepatocellular carcinoma, HSF1 can weaken the toxic effect of radiotherapy and chemotherapy on tumors and reduce the curative effect. Does HSF1 affect the sensitivity of ESCC to radiotherapy and chemotherapy?

AIM

To investigate the expression of HSF1 in ESCC and its effect on the sensitivity of ESCC to radiotherapy and chemotherapy.

METHODS

Ninety-two patients were divided into four groups: 20 stage Ⅰ/Ⅱ ESCC patients undergoing surgical resection, 18 stage Ⅲ/Ⅱ ESCC patients undergoing surgical resection, and 44 stage Ⅲ/Ⅱ ESCC patients undergoing radiotherapy and chemotherapy. Among the 44 stage Ⅲ/Ⅱ ESCC patients undergoing radiotherapy and chemotherapy, 16 had low HSF1 expression and 28 had high expression. Ten cases of esophageal dysplasia. Ten esophagitis tissues were used as a control group. The expression of HSF1 in each group was detected by immunohistochemistry. The changes of non-tumorous lesion size, tumor diameter, and CEA value were compared between the HSF1 low expression group and high expression group before and after radiotherapy and chemotherapy to assess the sensitivity of patients to radiotherapy and chemotherapy. Factors that might affect the 3-year survival of ESCC patients were identified, and the 3-year overall survival rate of ESCC patients was calculated.

RESULTS

HSF1 was highly expressed in each ESCC group, but lowly expressed in esophagitis group and esophageal dysplasia group, and there was a significant difference in the expression of HSF1 between each ESCC group and esophagitis group and esophageal dysplasia group (P = 0.001). HSF1 expression was not significantly associated with age, gender, tumor location , tumor size, degree of differentiation, T stage, N stage, or M stage (P > 0.05). In the HSF1 low expression group, the non-tumor lesion was more significantly relieved, the tumor diameter was more significantly reduced, and the CEA value was more significantly decreased after radiotherapy and chemotherapy compared with those in the HSF1 high expression group (P < 0.05). In the ESCC surgical resection group, the 3-year survival period was significantly related to age (P = 0.019), HSF1 expression (P = 0.028), T stage (P = 0.007), and N stage (P = 0.016), but not related to gender, tumor location, tumor diameter, or degree of differentiation (P > 0.05). In stage Ⅲ/Ⅱ ESCC patients undergoing radiotherapy and chemotherapy, the HSF1 low expression group had a significantly higher 3-year overall survival rate than the HSF1 high expression group (P = 0.016). The 1-, 2-, and 3-year survival rates of the HSF1 low expression group were significantly higher than those of the HSF1 high expression group (P < 0.05). The HSF1 low expression group had a significantly higher 3-year overall survival rate than the HSF1 high expression group (P = 0.03).

CONCLUSION

HSF1 is highly expressed in ESCC and the higher the HSF1 expression, the worse the prognosis of patients. HSF1 expression is not related to patients' clinical characteristics. In stage Ⅲ/Ⅳ ESCC patients receiving radiotherapy and chemotherapy, the higher the expression of HSF1, the worse the sensitivity of patients to radiotherapy and chemotherapy. In ESCC patients undergoing surgical resection and stage Ⅲ/Ⅳ ESCC patients receiving radiotherapy and chemotherapy, the 3-year overall survival rate is higher in the HSF1 low expression group than in the HSF1 high expression group.

Identification of Potential Key Genes Involved in the Carotid Atherosclerosis

Purpose

Carotid atherosclerosis is a kind of systemic atherosclerosis in the carotid arteries. However, the efficiency of treatment is insufficient. Therefore, it is urgent to find therapeutic targets and deepen the understanding of carotid atherosclerosis.

Materials and Methods

In this study, we analyzed differentially expressed genes (DEGs) between atheroma plaque and macroscopically intact tissue (control samples). Furthermore, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analysis based on the DEGs. Four methods were used to identify the hub genes in the protein–protein interaction networks of the DEGs. Furthermore, we also performed network module analysis to reveal carotid atherosclerosis-related gene modules and biological functions.

Results

The enrichment results showed that the biological functions were related to inflammation, immunity, chemokine and cell adhesion molecule, such as PIK-Akt signaling pathway, Rap1 signaling pathway, MAPK signaling pathway, NOD-like receptor signaling pathway and B cell receptor signaling pathway. In addition, we screened the hub genes. A total of 16 up-regulated genes (C3AR1, CCR1, CCR2, CD33, CD53, CXCL10, CXCL8, CXCR4, CYBB, FCER1G, FPR2, ITGAL, ITGAM, ITGAX, ITGB2, and LILRB2) were identified as hub genes. A total of 5 gene modules were obtained. We found that biological functions obtained for each cluster were mostly related to immunity, chemokines and cell adhesion molecules.

Conclusion

The present study identified key DEGs in atheroma plaque compared with control samples. The key genes involved in the development of carotid atherosclerosis may provide valuable therapeutic targets for carotid atherosclerosis.

Artificial intelligence technique in detection of early esophageal cancer

Due to the rapid progression and poor prognosis of esophageal cancer (EC), the early detection and diagnosis of early EC are of great value for the prognosis improvement of patients. However, the endoscopic detection of early EC, especially Barrett's dysplasia or squamous epithelial dysplasia, is difficult. Therefore, the requirement for more efficient methods of detection and characterization of early EC has led to intensive research in the field of artificial intelligence (AI). Deep learning (DL) has brought about breakthroughs in processing images, videos, and other aspects, whereas convolutional neural networks (CNNs) have shone lights on detection of endoscopic images and videos. Many studies on CNNs in endoscopic analysis of early EC demonstrate excellent performance including sensitivity and specificity and progress gradually from in vitro image analysis for classification to real-time detection of early esophageal neoplasia. When AI technique comes to the pathological diagnosis, borderline lesions that are difficult to determine may become easier than before. In gene diagnosis, due to the lack of tissue specificity of gene diagnostic markers, they can only be used as supplementary measures at present. In predicting the risk of cancer, there is still a lack of prospective clinical research to confirm the accuracy of the risk stratification model.

Genome-wide identification and analysis of long noncoding RNAs in longissimus muscle tissue from Kazakh cattle and Xinjiang brown cattle

Objective

In recent years, lncRNAs have been identified in many species, and some of them have been shown to play important roles in muscle development and myogenesis. However, the differences in lncRNAs between Kazakh cattle and Xinjiang brown cattle remain undefined; therefore, we aimed to confirm whether lncRNAs are differentially expressed in the longissimus dorsi between these two types of cattle and whether differentially expressed lncRNAs regulate muscle differentiation.

Methods

We used RNA-seq technology to identify lncRNAs in longissimus muscles from these cattle. The expression of lncRNAs were analyzed using StringTie (1.3.1) in terms of the FPKM values of the encoding genes. The differential expression of the transcripts in the two samples were analyzed using the DESeq R software package. The resulting FDR was controlled by the Benjamini and Hochberg's approach. KOBAS software was utilized to measure the expression of different genes in KEGG pathways. We randomly selected eight lncRNA genes and validated them by RT-qPCR.

Results

We found that 182 lncRNA transcripts, including 102 upregulated and 80 downregulated transcripts, were differentially expressed between Kazakh cattle and Xinjiang brown cattle. The results of RT-qPCR were consistent with the sequencing results. Enrichment analysis and functional annotation of the target genes revealed that the differentially expressed lncRNAs were associated with the MAPK, Ras and PI3k/Akt signaling pathways. We also constructed a lncRNA/mRNA coexpression network for the PI3k/Akt signaling pathway.

Conclusion

Our study provides insights into cattle muscle-associated lncRNAs and will contribute to a more thorough understanding of the molecular mechanism underlying muscle growth and development in cattle.

Role of non-coding RNAs in esophageal carcinoma

In recent years, the research on the role of non-coding RNAs (ncRNAs) in tumors has received more and more attention. Although research on the role of ncRNAs in the early diagnosis, disease monitoring, treatment guidance, and prognosis prediction of esophageal carcinoma has been gradually carried out, there are still many problems that need to be addressed. In the current paper, I review the progress in the research of ncRNAs in esophageal carcinoma, with an aim to help provide new strategies for the prevention and treatment of esophageal carcinoma.

Functional roles of lncRNAs in the pathogenesis and progression of cancer

Long noncoding RNAs (lncRNAs) act as regulators of gene expression and pivotal transcriptional regulators in cancer cells via diverse mechanisms. lncRNAs involves a variety of pathological and biological activities, such as apoptosis, cell proliferation, metastasis, and invasion. By using microarray and RNA sequencing, it was identified that dysregulation of lncRNAs affects the tumorigenesis process. Taken together, these lncRNAs are putative biomarker and therapeutic target in human malignancies. In this review, I discuss the latest finding regarding the dysregulation of some important lncRNAs and their diverse mechanisms of these lncRNAs in the pathogenesis and progression of certain cancers; also, I summarize the possible roles of lncRNAs in clinical application for diagnosis and prognosis of cancer.

The multifaceted roles of long noncoding RNAs in pancreatic cancer: an update on what we know

Pancreatic cancer (PC) is one of the leading causes of cancer-related deaths worldwide. Due to the shortage of effective biomarkers for predicting survival and diagnosing PC, the underlying mechanism is still intensively investigated but poorly understood. Long noncoding RNAs (lncRNAs) provide biological functional diversity and complexity in protein regulatory networks. Scientific studies have revealed the emerging functions and regulatory roles of lncRNAs in PC behaviors. It is worth noting that some in-depth studies have revealed that lncRNAs are significantly associated with the initiation and progression of PC. As lncRNAs have good properties for both diagnostic and prognostic prediction due to their translation potential, we herein address the current understanding of the multifaceted roles of lncRNAs as regulators in the molecular mechanism of PC. We also discuss the possibility of using lncRNAs as survival biomarkers and their contributions to the development of targeted therapies based on the literature. The present review, based on what we know about current research findings, may help us better understand the roles of lncRNAs in PC.

Identification of a nomogram based on long non-coding RNA to improve prognosis prediction of esophageal squamous cell carcinoma

PURPOSE

Esophageal squamous cell carcinoma (ESCC) remains a common aggressive malignancy in the world. Several long non-coding RNAs (lncRNAs) are reported to predict the prognosis of ESCC. Therefore, an in-depth research is urgently needed to further investigate the prognostic value of lncRNAs in ESCC.

RESULTS

From the training set, we identified a eight-lncRNA signature (including AP000487, AC011997, LINC01592, LINC01497, LINC01711, FENDRR, AC087045, AC137770) which separated the patients into two groups with significantly different overall survival (hazard ratio, HR = 3.79, 95% confidence interval, 95% CI [2.56-5.62]; P < 0.001). The signature was applied to the validation set (HR = 2.73, 95%CI [1.65-4.53]; P < 0.001) and showed similar prognostic values. Stratified, univariate and multivariate Cox regression analysis indicated that the signature was an independent prognostic factor for patients with ESCC. A nomogram based on the lncRNAs signature, age, grade and stage was developed and showed good accuracy for predicting 1-, 3- and 5-year survival probability of ESCC patients. We found a strong correlation between the gene significance for the survival time and T stage. Eight modules were constructed, among which the key module most closely associated with clinical information was identified.

CONCLUSIONS

Our eight-lincRNA signature and nomogram could be practical and reliable prognostic tools for esophageal squamous cell carcinoma.

METHODS

We downloaded the lncRNA expression profiles of ESCC patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets and separated to training and validation cohort. The univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to identify a lncRNA-based signature. The predictive value of the signature was assessed using the Kaplan-Meier method, receiver operating characteristic (ROC) curves and area under curve (AUC). Weighted gene co-expression network analysis (WGCNA) was applied to predict the intrinsic relationship between gene expressions. In addition, we further explored the combination of clinical information and module construction.

Single-nucleus chromatin accessibility reveals intratumoral epigenetic heterogeneity in IDH1 mutant gliomas

The presence of genome-wide DNA hypermethylation is a hallmark of lower grade gliomas (LGG) with isocitrate dehydrogenase (IDH) mutations. Further molecular classification of IDH mutant gliomas is defined by the presence (IDHmut-codel) or absence (IDHmut-noncodel) of hemizygous codeletion of chromosome arms 1p and 19q. Despite the DNA hypermethylation seen in bulk tumors, intra-tumoral heterogeneity at the epigenetic level has not been thoroughly analyzed. To address this question, we performed the first epigenetic profiling of single cells in a cohort of 5 gliomas with IDH1 mutation using single nucleus Assay for Transposase-Accessible Chromatin with high-throughput sequencing (snATAC-seq). Using the Fluidigm HT IFC microfluidics platform, we generated chromatin accessibility maps from 336 individual nuclei, and identified variable promoter accessibility of non-coding RNAs in LGGs. Interestingly, local chromatin structures of several non-coding RNAs are significant factors that contribute to heterogeneity, and show increased promoter accessibility in IDHmut-noncodel samples. As an example for clinical significance of this result, we identify CYTOR as a poor prognosis factor in gliomas with IDH mutation. Open chromatin assay points to differential accessibility of non-coding RNAs as an important source of epigenetic heterogeneity within individual tumors and between molecular subgroups. Rare populations of nuclei that resemble either IDH mutant molecular group co-exist within IDHmut-noncodel and IDHmut-codel groups, and along with non-coding RNAs may be an important issue to consider for future studies, as they may help guide predict treatment response and relapse.

A web-based explorer for the data is available at shiny.turcanlab.org.

Prognostic significance of contactin 3 expression and associated genes in glioblastoma multiforme

Contactin 3 (CNTN3) is a member of the contactin family that is primarily expressed in the nervous system. However, to the best of our knowledge, expression of contactin and its role in the development and progression of brain tumours has not been studied. Although glioblastoma multiforme (GBM) is the most common malignant brain tumour, advances in therapeutic options for patients with GBM have been modest due to an incomplete understanding of the molecular mechanisms underlying development and progression. The aim of the present study was to examine the correlation between CNTN3 and its associated genes and the clinical outcome in patients with GBM. CNTN3 and the expression levels of associated genes were analysed in GBM datasets obtained from the SAGE Anatomical viewer website, Gene Expression Omnibus, Oncomine and The Cancer Genome Atlas. CNTN3 was significantly downregulated in patients with GBM. Subsequently, the expression of CNTN3 was further validated using immunohistochemistry in a cohort of GBM specimens. The immunohistochemistry results were consistent with the in silico analyses. Kaplan-Meier analysis indicated that patients with lower expression levels of CNTN3 had a significantly shorter overall survival (OS) time compared with patients with higher levels of CNTN3 expression. Univariate and multivariate Cox regression analyses demonstrated that CNTN3 expression was an independent prognostic indicator in patients with GBM. Furthermore, gene set enrichment analysis revealed that CNTN3 was associated with the receptor tyrosine-protein kinase (ErbB) signalling pathway. In the ErbB signalling pathway, epidermal growth factor receptor (EGFR) was negatively correlated with CNTN3. Taken together, these data suggest that lower expression levels of CNTN3 may be an independent biomarker that predicts poor OS time in patients with GBM, and that EGFR expression in the ErbB pathway may be associated with CNTN3 expression.