COL3A1 and SNAP91: novel glioblastoma markers with diagnostic and prognostic value

RNF185 Control of COL3A1 Expression Limits Prostate Cancer Migration and Metastatic Potential

RNF185 is a RING finger domain-containing ubiquitin ligase implicated in ER-associated degradation. Prostate tumor patient data analysis revealed a negative correlation between RNF185 expression and prostate cancer progression and metastasis. Likewise, several prostate cancer cell lines exhibited greater migration and invasion capabilities in culture upon RNF185 depletion. Subcutaneous inoculation of mouse prostate cancer MPC3 cells stably expressing short hairpin RNA against RNF185 into mice resulted in larger tumors and more frequent lung metastases. RNA-sequencing and Ingenuity Pathway Analysis identified wound-healing and cellular movement among the most significant pathways upregulated in RNF185-depleted lines, compared with control prostate cancer cells. Gene Set Enrichment Analyses performed in samples from patients harboring low RNF185 expression and in RNF185-depleted lines confirmed the deregulation of genes implicated in epithelial-to-mesenchymal transition. Among those, COL3A1 was identified as the primary mediator of RNF185's ability to impact migration phenotypes. Correspondingly, enhanced migration and metastasis of RNF185 knockdown (KD) prostate cancer cells were attenuated upon co-inhibition of COL3A1. Our results identify RNF185 as a gatekeeper of prostate cancer metastasis, partly via its control of COL3A1 availability.

IMPLICATIONS

RNF185 is identified as an important regulator of prostate cancer migration and metastasis, in part due to its regulation of COL3A1. Both RNF185 and COL3A1 may serve as novel markers for prostate tumors.

Identification of LOX as a candidate prognostic biomarker in Glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most malignant type of glioma. GBM tumors grow rapidly, have a high degree of malignancy, and are characterized by a fast disease progression. Unfortunately, there is a lack of effective treatments. An effective strategy for the treatment of GBM would be to identify key biomarkers correlating with the occurrence and progression of GBM and developing these biomarkers into therapeutic targets.

METHOD AND RESULTS

In this study, using integrated bioinformatics analysis, we identified differentially expressed genes (DEGs), including 130 genes that were upregulated in GBM compared to normal brain tissue, and 128 genes that were downregulated in GBM. Based on Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis, these genes were associated with regulation of tumor cell adhesion, differentiation, morphology in GBM and were mainly enriched in Complement and coagulation cascades pathway. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to construct a Protein-Protein Interaction network. Ten hub genes were identified, including FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2, all of which were significantly upregulated in GBM, these results were confirmed by oncomine database exploration. Alteration analysis of hub genes found that patients with alteration in at least one of the hub genes showed shorter median survival times (p = 0.013) and shorter median disease-free survival times (p = 2.488E-3) than patients without alterations in any of the hub genes. Multiple tests for survival analysis showed that among individual hub genes only expression of LOX was correlated with patient survival (P < 0.05).GDS4467 data set was used to analyze the expression of LOX in gliomas with different degrees of malignancy, and it was found that the expression level of LOX was positively correlated with the malignant degree of gliomas.By analyzing GDS 4535 data set showed that the expression level of LOX was positively correlated with the differentiation degree of GBM cells CONCLUSION: This research suggests that FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2 are key genes in GBM. However, only LOX is correlated with patient survival and promotes glioblastoma cell differentiation and tumor recurrence. LOX may be a candidate prognostic biomarker and potential therapeutic target for GBM.

RNF185 control of COL3A1 expression limits prostate cancer migration and metastatic potential

RNF185 is a RING finger domain-containing ubiquitin ligase implicated in ER-associated degradation. Prostate tumor patient data analysis revealed a negative correlation between RNF185 expression and prostate cancer progression and metastasis. Likewise, several prostate cancer cell lines exhibited greater migration and invasion capabilities in culture upon RNF185 depletion. Subcutaneous inoculation of mouse prostate cancer MPC3 cells stably expressing shRNA against RNF185 into mice resulted in larger tumors and more frequent lung metastases. RNA-sequencing and Ingenuity Pathway Analysis identified wound healing and cellular movement among the most significant pathways upregulated in RNF185-depleted, compared to control prostate cancer cells. Gene Set Enrichment Analyses performed in samples from patients harboring low RNF185 expression and in RNF185-depleted lines confirmed the deregulation of genes implicated in EMT. Among those, COL3A1 was identified as the primary mediator of RNF185's ability to impact migration phenotypes. Correspondingly, enhanced migration and metastasis of RNF185 KD prostate cancer cells were attenuated upon co-inhibition of COL3A1. Our results identify RNF185 as a gatekeeper of prostate cancer metastasis, partly via its control of COL3A1 availability.

A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data

The high dimensionality and sparsity of the microarray gene expression data make it challenging to analyze and screen the optimal subset of genes as predictors of breast cancer (BC). The authors in the present study propose a novel hybrid Feature Selection (FS) sequential framework involving minimum Redundancy-Maximum Relevance (mRMR), a two-tailed unpaired t-test, and meta-heuristics to screen the most optimal set of gene biomarkers as predictors for BC. The proposed framework identified a set of three most optimal gene biomarkers, namely, MAPK 1, APOBEC3B, and ENAH. In addition, the state-of-the-art supervised Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Neural Net (NN), Naïve Bayes (NB), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR) were used to test the predictive capability of the selected gene biomarkers and select the most effective breast cancer diagnostic model with higher values of performance matrices. Our study found that the XGBoost-based model was the superior performer with an accuracy of 0.976 ± 0.027, an F1-Score of 0.974 ± 0.030, and an AUC value of 0.961 ± 0.035 when tested on an independent test dataset. The screened gene biomarkers-based classification system efficiently detects primary breast tumors from normal breast samples.

Perfluorooctanoic acid-induced developmental cardiotoxicity in chicken embryo: Roles of miR-490-5p

Perfluorooctanoic acid (PFOA) could induce developmental toxicities, affecting various organs, including the heart. Although peroxisome-proliferation activated receptor alpha (PPARα) had been identified as a major target of PFOA, PPARα-independent effects are frequently reported. To further elucidate the mechanism of toxicity in PFOA-induced developmental cardiotoxicity, RNA-seq analysis was performed in hatchling chicken hearts developmentally exposed to vehicle or 2 mg/kg (egg weight) PFOA. RT-PCR and western blotting were then performed to confirm the identified potential targets. Furthermore, lentivirus was designed to overexpress and silence identified target miRNA in developing chicken embryo, and the resulting phenotypes were investigated. 21 miRNAs and 1142 mRNAs were identified to be affected by developmental exposure to PFOA in chicken embryo hearts. Among the identified differentially expressed miRNAs, miR-490-5p was confirmed to be significantly affected by PFOA exposure, along with its downstream targets, Synaptosome associated protein 91 (SNAP91) and LY6/PLAUR domain containing 6 (LYPD6), as indicated by RT-PCR and western blotting results. Lentivirus overexpressing miR-490-5p mimicked the phenotype induced by PFOA exposure, while lentivirus silencing miR-490-5p alleviated PFOA-induced changes. Similar patterns were also observed in the expression of downstream target genes, SNAP91 and LYPD6. In summary, miR-490-5p and its downstream genes, SNAP91 and LYPD6 are associated with PFOA-induced developmental cardiotoxicity in chicken embryo, which might help to further elucidate the mechanism of PFOA-induced developmental cardiotoxicity.

Identification of Prognostic Signature of Necroptosis-Related lncRNAs and Molecular Subtypes in Glioma

Background

In tumor progression and epigenetic regulation, long non-coding RNA (lncRNA) and necroptosis are crucial regulators. However, in glioma microenvironment, the role of necroptosis-related lncRNAs (NRLs) remains unknown.

Method

In this study, the RNA-seq and clinical annotation of glioma patients were analyzed using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To investigate prognosis and tumor microenvironment of NRLs in gliomas, we conducted a prediction model based on the training cohort. The accuracy of the model was verified in the verification cohort.

Results

A signature composed of 13 NRLs was identified, and all glioma patients were divided into two groups. We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status. The necroptosis-related lncRNA signature (NRLS) model was found to be an independent risk factor in multivariate Cox analysis. Immunosuppressive microenvironment was positively correlated with the high-risk group. Due to significantly different IC50 between risk groups, NRLS could be used as a guide for chemotherapeutic treatment. Further, the entire cohort was divided into two clusters depending on NRLs. Consensus clustering method and the risk scoring system were basically similar. Survival probability was higher in Cluster 2, while Cluster 1 has stronger immunologic infiltration.

Conclusion

The predictive signature could be a prognostic factor independently and serve to detect the role of NRLs in glioma immunotherapy response.

Comprehensive analysis of pyroptosis regulation patterns and their influence on tumor immune microenvironment and patient prognosis in glioma

BACKGROUND

Glioma is the most common intracranial malignancy with a poor prognosis. Although remarkable advances have been made in the study of diagnostic and prognostic biomarkers, the efficacy of current treatment strategies is still unsatisfactory. Therefore, developing novel and reliable targets is desperately needed for glioma patients. Pyroptosis reshapes tumor immune microenvironment (TME) and promotes the destruction of the tumor by the immune system. Moreover, pyroptosis levels correlate with prognosis and immunotherapy response in many cancer patients. This study performed a comprehensive analysis of pyroptosis in the glioma, unveiling its potential value in glioma prognosis prediction and therapy efficacy.

METHODS

Firstly, the pyroptosis regulation patterns were comprehensively evaluated on 33 pyroptosis-related genes in 1716 glioma samples. The correlations were analyzed between pyroptosis regulation patterns and TME immune cell infiltration properties. Next, pyroptosis regulation patterns were measured by the PSscore model based on principal component analysis algorithms. The correlations were analyzed between PSscore and tumor mutational burden (TMB), immune checkpoint blockade (ICB) therapeutic advantages. Last, the findings were validated in an independently collected external clinical cohort.

RESULTS

We determined two distinct pyroptosis regulation patterns. The cluster-A was high immune cell infiltration with a poor prognosis (p < 0.001), whereas the cluster-B was low immune cell infiltration with a better prognosis (p < 0.001). We developed the PSscore as a measure for pyroptosis regulation patterns. The high PSscore with an inflamed TME phenotype, a high TMB (p < 0.0001), increased innate immune response, and a poor prognosis (p < 0.001). It was in stark contrast to the low PSscore (p < 0.001). Analysis of PSscore with checkpoint therapy indicated high PSscore were correlated with enhanced response to anti-PD-1 immunotherapy (p = 0.0046). For validation, we utilized in vitro experiments on an external clinical cohort. The results demonstrated that GSDMD expression level in the high PSscore group was significantly upregulated compared to the low PSscore group (p < 0.001); the CD3+ T cells and the CD3+PD-1+ cells significantly increased in the high PSscore group compared to the low PSscore group (p < 0.01).

CONCLUSIONS

The PSscore of pyroptosis regulation pattern is a reliable biomarker, and it is valuable to predict prognosis, TME, and ICB therapeutic efficiency in glioma patients.

Identification of Prognostic Biomarkers for Glioblastoma Based on Transcriptome and Proteome Association Analysis

Objective:

Glioblastoma multiforme (GBM) is the most malignant primary brain tumor in adults. This study aimed to identify significant prognostic biomarkers related to GBM.

Methods:

We collected 3 GBM and 3 healthy human brain samples for transcriptome and proteomic sequencing analysis. Differentially expressed genes (DEGs) between GBM and control samples were identified using the edge R package in R. Functional enrichment analyses, prediction of long noncoding RNA target genes, and protein-protein interaction network analyses were performed. Subsequently, transcriptomic and proteomic association analyses, validation using The Cancer Genome Atlas (TCGA) database, and survival and prognostic analyses were conducted. Then the hub genes directly related to GBM were screened. Finally, the expression of key genes was verified by quantitative polymerase chain reaction (qPCR).

Results:

Totally, 1140 transcripts and 503 proteins were significantly up- or down-regulated. A total of 25 genes were upregulated and 62 were downregulated at both the transcriptome and proteome levels. Results from TCGA database showed that 84 of these 87 genes matched with transcriptome sequencing results. A Cox regression analysis suggested that Fibronectin 1(FN1) was a prognostic risk factor. The qPCR results showed that FN1 was significantly upregulated in GBM samples.

Conclusions:

FN1 may play a role in GBM progression through ECM-receptor interaction and PI3K-Akt signaling pathways. FN1 may be considered as a prognostic biomarkers related to GBM.

Bioinformatics Analysis of Hub Genes and Potential Therapeutic Agents Associated with Gastric Cancer

Purpose

The current treatment methods available for advanced gastric cancer are not very promising. Hence, it is important to explore novel biomarkers and potential therapeutic agents to treat gastric cancer (GC). This study aimed to identify hub genes associated with GC prognosis and explore potential drugs for its treatment.

Materials and Methods

Three gene expression data of GC and normal tissues were downloaded from the Gene Expression Omnibus (GEO) and processed to identify the differentially expressed genes (DEGs). We conducted a comprehensive analysis of DEGs, including functional enrichment analysis, construction of protein-protein interaction (PPI) network, identification of hub genes, survival analysis and expression verification of hub genes. Finally, we constructed the network of miRNA-mRNA, and predicted the drugs that might be effective for GC treatment.

Results

A total of 340 DEGs, including 94 up-regulated and 246 down-regulated genes, were identified. Among the up-regulated DEGs, the enrichment terms were primarily related to tumorigenesis and tumor progression, extracellular matrix organization, and collagen catabolic process. Additionally, 10 hub genes (FN1, COL3A1, COL1A2, BGN, THBS2, COL5A2, THBS1, COL5A1, SPARC, and COL4A1) were identified, out of which 7 genes were significantly associated with poor overall survival (OS) in GC. The expression levels of these 7 hub genes were verified using real-time PCR, immunohistochemistry, and the GEPIA2 (Gene Expression Profiling Interactive Analysis) server. A regulatory network of miRNA-mRNA was also constructed, and the top 4 interactive miRNAs (hsa-miR-29b-3p, hsa-miR-140-3p, hsa-miR-29a-3p, and hsa-miR-29c-3p) that targeted the most hub genes were identified. Finally, fourteen small molecules were predicted to be effective in treating GC.

Conclusion

The identification of the hub genes, miRNA-mRNA network, and potential candidate drugs associated with GC provides new insights into the molecular mechanisms and treatment of GC.

A novel pyroptosis-related gene signature predicts the prognosis of glioma through immune infiltration

BACKGROUND

Glioma is the most common primary intracranial tumour and has a very poor prognosis. Pyroptosis, also known as inflammatory necrosis, is a type of programmed cell death that was discovered in recent years. The expression and role of pyroptosis-related genes in gliomas are still unclear.

METHODS

In this study, we analysed the RNA-seq and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) database and Chinese Glioma Genome Atlas (CGGA) database. To investigate the prognosis and immune microenvironment of pyroptosis-related genes in gliomas, we constructed a risk model based on the TCGA cohort. The patients in the CGGA cohort were used as the validation cohort.

RESULTS

In this study, we identified 34 pyroptosis-related differentially expressed genes (DEGs) in glioma. By clustering these DEGs, all glioma cases can be divided into two clusters. Survival analysis showed that the overall survival time of Cluster 1 was significantly higher than that of Cluster 2. Using the TCGA cohort as the training set, a 10-gene risk model was constructed through univariate Cox regression analysis and LASSO Cox regression analysis. According to the risk score, gliomas were divided into high-risk and low-risk groups. Survival analysis showed that the low-risk group had a longer survival time than the high-risk group. The above results were verified in the CGGA validation cohort. To verify that the risk model was independent of other clinical features, the distribution and the Kaplan-Meier survival curves associated with risk scores were performed. Combined with the characteristics of the clinical cases, the risk score was found to be an independent factor predicting the overall survival of patients with glioma. The analysis of single sample Gene Set Enrichment Analysis (ssGSEA) showed that compared with the low-risk group, the high-risk group had immune cell and immune pathway activities that were significantly upregulated.

CONCLUSION

We established 10 pyroptosis-related gene markers that can be used as independent clinical predictors and provide a potential mechanism for the treatment of glioma.

PLEK2, RRM2, GCSH: A Novel WWOX-Dependent Biomarker Triad of Glioblastoma at the Crossroads of Cytoskeleton Reorganization and Metabolism Alterations

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of gliomas. Although the role of WWOX in the cytoskeleton rearrangement has been found in neural progenitor cells, its function as a modulator of cytoskeleton in gliomas was not investigated. Therefore, this study aimed to investigate the role of WWOX and its collaborators in cytoskeleton dynamics of glioblastoma. Methodology on RNA-seq data integrated the use of databases, bioinformatics tools, web-based platforms, and machine learning algorithm, and the obtained results were validated through microarray data. PLEK2, RRM2, and GCSH were the most relevant WWOX-dependent genes that could serve as novel biomarkers. Other genes important in the context of cytoskeleton (BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1, and WT1), metabolism (MTHFD2), or correlation with WWOX (COL3A1, KIF20A, RNF141, and RXRG) were also discovered. For the first time, we propose that changes in WWOX expression dictate a myriad of alterations that affect both glioblastoma cytoskeleton and metabolism, rendering new therapeutic possibilities.

Identification of a Seven-lncRNA-mRNA Signature for Recurrence and Prognostic Prediction in Relapsed Acute Lymphoblastic Leukemia Based on WGCNA and LASSO Analyses

Abnormal expressions of long noncoding RNAs (lncRNAs) and protein-encoding messenger RNAs (mRNAs) are important for the development of childhood acute lymphoblastic leukemia (ALL). This study developed an lncRNA-mRNA integrated classifier for the prediction of recurrence and prognosis in relapsed childhood ALL by using several transcriptome data. Weighted gene coexpression network analysis revealed that green, turquoise, yellow, and brown modules were preserved across the TARGET, GSE60926, GSE28460, and GSE17703 datasets, and they were associated with clinical relapse and death status. A total of 184 genes in these four modules were differentially expressed between recurrence and nonrecurrence samples. Least absolute shrinkage and selection operator analysis showed that seven genes constructed a prognostic signature (including one lncRNA: LINC00652 and six mRNAs: INSL3, NIPAL2, REN, RIMS2, RPRM, and SNAP91). Kaplan-Meier curve analysis observed that patients in the high-risk group had a significantly shorter overall survival than those of the low-risk group. Receiver operating characteristic curve analysis demonstrated that this signature had high accuracy in predicting the 5-year overall survival and recurrence outcomes, respectively. LINC00652 may function by coexpressing with the above prognostic genes (INSL3, SNAP91, and REN) and lipid metabolism-related genes (MIA2, APOA1). Accordingly, this lncRNA-mRNA-based classifier may be clinically useful to predict the recurrence and prognosis for childhood ALL. These genes represent new targets to explain the mechanisms for ALL.

Identification of collagen genes related to immune infiltration and epithelial-mesenchymal transition in glioma

Background

Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression.

Methods

We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers.

Results

We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells.

Conclusions

In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01982-0.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

P-selectin axis plays a key role in microglia immunophenotype and glioblastoma progression

Glioblastoma (GB) is a highly invasive type of brain cancer exhibiting poor prognosis. As such, its microenvironment plays a crucial role in its progression. Among the brain stromal cells, the microglia were shown to facilitate GB invasion and immunosuppression. However, the reciprocal mechanisms by which GB cells alter microglia/macrophages behavior are not fully understood. We propose that these mechanisms involve adhesion molecules such as the Selectins family. These proteins are involved in immune modulation and cancer immunity. We show that P-selectin mediates microglia-enhanced GB proliferation and invasion by altering microglia/macrophages activation state. We demonstrate these findings by pharmacological and molecular inhibition of P-selectin which leads to reduced tumor growth and increased survival in GB mouse models. Our work sheds light on tumor-associated microglia/macrophage function and the mechanisms by which GB cells suppress the immune system and invade the brain, paving the way to exploit P-selectin as a target for GB therapy.

miR-193a-3p Promotes the Invasion, Migration, and Mesenchymal Transition in Glioma through Regulating BTRC

BACKGROUND

The present study is aimed at exploring the specific expression of miR-193a-3p and the mechanism underlying miR-193a-3p-mediated mesenchymal transition (MT), invasion, and migration in glioma.

METHODS

The gene expression profile datasets of GSE39486 and GSE25676 were downloaded from the National Center for Biotechnology (NCBI). Data regarding the expression of miR-193a-3p and survival curves were derived from Chinese Glioma Genome Atlas (CGGA). Online websites including miRWalk, DIANA, and starbase were employed to predict the target genes for miR-193a-3p. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the Omicsbean online software. Module analysis of the protein-protein interaction (PPI) networks was performed by the plug-in Molecular Complex Detection (MCODE), and the degrees of genes were calculated by CytoHubba plug-in of Cytoscape. Survival curves were based on the Gene Expression Profile Interaction Analysis (GEPIA). Transwell, wound healing, and Western blot experiments were performed to investigate the effects of miR-193a-3p and beta-transducin repeat containing E3 ubiquitin protein ligase (BTRC) on the invasion, migration, and MT of glioma.

RESULTS

miR-193a-3p was highly expressed in glioma tissues and significantly correlated with poor survival in patients with glioma. The target genes for miR-193a-3p were involved in many cancer-related signaling pathways. The PPI showed 11 genes with both high degrees and MCODE scores in the network. Survival analysis demonstrated that the expression of BTRC was significantly correlated with the prognosis of patients with glioma. The results from the transwell, wound healing, and Western blot analyses suggested that miR-193a-3p promoted the invasion, migration, and MT of glioma cells, which could be reversed by BTRC.

CONCLUSIONS

miR-193a-3p was upregulated in patients with glioma and could affect the invasion, migration, and MT of glioma by regulating BTRC.

Clinical significance and potential molecular mechanism of miRNA-222-3p in metastatic prostate cancer

The clinical significance and underlying molecular mechanism of miRNA-222-3p in metastatic prostate cancer (MPCa) remain unclear. The present study used a large number of cases (n = 1,502) based on miRNA chip and miRNA sequencing datasets to evaluate the expression and diagnostic potential of miRNA-222-3p in MPCa. We applied a variety of meta-analytic methods, including forest maps, sensitivity analysis, subgroup analysis and summary receiver operating characteristic curves, to prove the final results. MiRNA-222-3p was reduced in MPCa and had a moderate diagnostic potential in MPCa. We screened 118 miRNA-222-3p targets using three different methods including miRNA-222-3p transfected MPCa cell lines, online prediction databases and differently upregulated genes in MPCa. Moreover, functional enrichment analysis performed to explore the potential molecular mechanism of miRNA-222-3p showed that the potential target genes of miRNA-222-3p were significantly enriched in the p53 signal pathway. In the protein–protein interaction network analysis, SNAP91 was identified as a hub gene that may be closely related to MPCa. Gene chip and RNA sequencing datasets containing 1,237 samples were used to determine the expression level and diagnostic potential of SNAP91 in MPCa. SNAP91 was found to be overexpressed in MPCa and had a moderate diagnostic potential in MPCa. In addition, miRNA-222-3p expression was negatively correlated with SNAP91 expression in MPCa (r = −0.636, P = 0.006). These results demonstrated that miRNA-222-3p might play an important role in MPCa by negatively regulating SNAP91 expression. Thus, miRNA-222-3p might be a potential biomarker and therapeutic target of MPCa.

Construction and validation of an immunity-related prognostic signature for breast cancer

Breast cancer is one of the most lethal malignancies among women, and understanding the effects of host immunity on disease progression offers the potential to improve immunotherapies against it. Here, we constructed an immunity-related gene (IRG)-based prognostic signature to stratify breast cancer patients and predict their survival. We identified differentially-expressed genes by analyzing the breast cancer transcriptome data from The Cancer Genome Atlas. Univariate Cox regression revealed 179 survival-correlated IRGs, 12 of which we used to construct an immunity-based prognostic signature that stratified breast cancer patients into high- and low-risk groups. The signature was an independent predictor for survival and was validated in an independent dataset. We also investigated the correlations between our prognostic signature and immune infiltrates and found that signature-derived risk scores correlated negatively with infiltration of B cells, CD4+ T cells, CD8+ T cells, neutrophils and dendritic cells. Our results show that the proposed prognostic signature reflects the tumor immune microenvironment, which makes it a potential indicator for survival that warrants further research to assess its clinical utility.

The Dynamic Proteome of Oligodendrocyte Lineage Differentiation Features Planar Cell Polarity and Macroautophagy Pathways

Background

Generation of oligodendrocytes is a sophisticated multistep process, the mechanistic underpinnings of which are not fully understood and demand further investigation. To systematically profile proteome dynamics during human embryonic stem cell differentiation into oligodendrocytes, we applied in-depth quantitative proteomics at different developmental stages and monitored changes in protein abundance using a multiplexed tandem mass tag-based proteomics approach.

Findings

Our proteome data provided a comprehensive protein expression profile that highlighted specific expression clusters based on the protein abundances over the course of human oligodendrocyte lineage differentiation. We identified the eminence of the planar cell polarity signalling and autophagy (particularly macroautophagy) in the progression of oligodendrocyte lineage differentiation—the cooperation of which is assisted by 106 and 77 proteins, respectively, that showed significant expression changes in this differentiation process. Furthermore, differentially expressed protein analysis of the proteome profile of oligodendrocyte lineage cells revealed 378 proteins that were specifically upregulated only in 1 differentiation stage. In addition, comparative pairwise analysis of differentiation stages demonstrated that abundances of 352 proteins differentially changed between consecutive differentiation time points.

Conclusions

Our study provides a comprehensive systematic proteomics profile of oligodendrocyte lineage cells that can serve as a resource for identifying novel biomarkers from these cells and for indicating numerous proteins that may contribute to regulating the development of myelinating oligodendrocytes and other cells of oligodendrocyte lineage. We showed the importance of planar cell polarity signalling in oligodendrocyte lineage differentiation and revealed the autophagy-related proteins that participate in oligodendrocyte lineage differentiation.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.

Collagen Type III Alpha 1 chain regulated by GATA-Binding Protein 6 affects Type II IFN response and propanoate metabolism in the recurrence of lower grade glioma

Some studies suggested the prognosis value of immune gene in lower grade glioma (LGG). Recurrence in LGG is a tough clinical problem for many LGG patients. Therefore, prognosis biomarker is required. Multivariate prognosis Cox model was constructed and then calculated the risk score. And differential expressed transcription factors (TFs) and differential expressed immune genes (DEIGs) were co‐analysed. Besides, significant immune cells/pathways were identified by single sample gene set enrichment analysis (ssGSEA). Moreover, gene set variation analysis (GSVA) and univariate Cox regression were applied to filter prognostic signalling pathways. Additionally, significant DEIG and immune cells/pathways, and significant DEIG and pathways were co‐analysed. Further, differential enriched pathways were identified by GSEA. In sum, a scientific hypothesis for recurrence LGG including TF, immune gene and immune cell/pathway was established. In our study, a total of 536 primary LGG samples, 2,498 immune genes and 318 TFs were acquired. Based on edgeR method, 2,164 DEGs, 2,498 DEIGs and 31 differentials expressed TFs were identified. A total of 106 DEIGs were integrated into multivariate prognostic model. Additionally, the AUC of the ROC curve was 0.860, and P value of Kaplan‐Meier curve < 0.001. GATA6 (TF) and COL3A1 (DEIG) were selected (R = 0.900, P < 0.001, positive) as significant TF‐immune gene links. Type II IFN response (P < 0.001) was the significant immune pathway. Propanoate metabolism (P < 0.001) was the significant KEGG pathway. We proposed that COL3A1 was positively regulated by GATA6, and by effecting type II IFN response and propanoate metabolism, COL3A1 involved in LGG recurrence.

Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications

Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas-33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)-based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II-III grade diagnosed, which have different prognosis and treatment strategies. Microarrays based GEP was analyzed on 155 diffuse astrocytic gliomas (discovery cohort) and validated in another 113 tumors (validation set) via sequential univariate analysis (pairwise comparison) for discriminatory gene selection, followed by nonnegative matrix factorization and canonical biplot for identification of discriminatory GEP among the distinct histological tumor subtypes. GEP data analysis identified a set of 27 genes capable of differentiating among distinct subtypes of gliomas that might support current histological classification. DA + AA showed similar molecular profiles with only a few discriminatory genes overexpressed (FSTL5 and SFRP2) and underexpressed (XIST, TOP2A and SHOX2) in DA vs AA and GBM. Compared to DA + AA, GBM displayed underexpression of ETNPPL, SH3GL2, GABRG2, SPX, DPP10, GABRB2 and CNTN3 and overexpression of CHI3L1, IGFBP3, COL1A1 and VEGFA, among other differentially expressed genes.

STAT1 is a modulator of the expression of frequently rearranged in advanced T-cell lymphomas 1 expression in U251 cells

Aberrant expression of frequently rearranged in advanced T-cell lymphomas 1 (FRAT1) contributes to poor prognosis in a number of carcinomas. However, its role in glioma remains controversial. In the present study, gene expression profiling was performed using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) functional enrichment and ingenuity pathway analysis (IPA) to evaluate the differential expression of genes and proteins in FRAT1 knockdown U251 glioma cells in comparison with the control. Western blot analysis was conducted to assess the expression levels of FRAT1 and STAT1. A total of 895 downregulated genes were identified in FRAT1-silenced U251 cells. The most enriched processes determined by GO and KEGG analysis of the 895 differentially expressed genes were associated with proliferation, migration and invasion. According to IPA, significant canonical pathways, including the interferon, hepatic fibrosis and Wnt/β-catenin signaling pathways, were identified to be the major enriched pathways. The elevated expression of STAT1 in U251 cells was validated. These results highlighted the regulatory role of FRAT1 in glioma cells with upregulated STAT1 expression.

Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

Background

Gastric cancer is one of the most common malignant cancers worldwide. Despite substantial developments in therapeutic strategies, the five-year survival rate remains low. Therefore, novel biomarkers and therapeutic targets involved in the progression of gastric tumors need to be identified.

Methods

We obtained the mRNA microarray datasets GSE65801, GSE54129 and GSE79973 from the Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to analyze DEG pathways and functions, and the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape to obtain the protein-protein interaction (PPI) network. Next, we validated the hub gene expression levels using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA), and conducted stage expression and survival analysis.

Results

From the three microarray datasets, we identified nine major hub genes: COL1A1, COL1A2, COL3A1, COL5A2, COL4A1, FN1, COL5A1, COL4A2, and COL6A3.

Conclusion

Our study identified COL1A1 and COL1A2 as potential gastric cancer prognostic biomarkers.

Key Genes Associated with Prognosis and Tumor Infiltrating Immune Cells in Gastric Cancer Patients Identified by Cross-Database Analysis

Background: The molecular mechanisms underlying gastric cancer (GC) progression are unclear. The authors examined key genes associated with the prognosis and tumor-infiltrating immune cells in patients with GC. Materials and Methods: Gene expression omnibus (GEO) was used to filter and obtain GC-related differentially expressed genes (DEGs). The molecular functions, biological processes, and cellular components of the DEGs were subjected to enrichment analysis. Protein-protein interaction networks of proteins encoded by the DEGs were analyzed using STRING. The authors also identified hub genes of GC, as well as their expression levels in GC and their relationship with patient prognosis. The relationship between hub genes and tumor-infiltrating immune cells was analyzed by Tumor IMmune Estimation Resource. Results: Six GEO datasets were included in this study, and 265 DEGs were identified. These DEGs were enriched in different signaling pathways and had different biological functions. Six hub genes were potentially significantly related to the molecular mechanisms of GC (TOP2A, FN1, SPARC, COL3A1, COL1A1, and TIMP1). These genes are potential markers of prognosis. Five hub genes were significantly positively correlated with the number of macrophages, neutrophils, and dendritic cells. Conclusions: The authors provide a theoretical basis for exploring the molecular regulation mechanism underlying GC and identifying therapeutic targets.

MicroRNA-301b and its target gene synaptosome-associated protein 91 as important modulators in esophageal cancer: functional experiments

The aim of this study was to probe the influence of microRNA-301b (miR-301b) in esophageal cancer pathogenesis. Based on the data acquired from The Cancer Genome Atlas database, we found that miR-301b was highly expressed in esophageal cancer tissues and high expression of miR-301b was related to worse prognosis in patients with esophageal cancer. Quantitative real-time PCR revealed that the expression of miR-301b was higher in all examined esophageal cancer cell lines (ECA109, KY-SE150, TE-1, and NEC) than that in a human esophageal epithelial cell line (HEEC). Upregulation/downregulation of miR-301b facilitated/suppressed the growth, migration, and invasion of ECA109/KY-SE150 cells. Synaptosome-associated protein 91 (SNAP91) was proved to be one of the target genes of miR-301b and was negatively modulated by miR-301b. Besides, SNAP91 was lowly expressed in human esophageal cancer tissues and cell lines. Meanwhile, low expression of SNAP91 was concerned with poor prognosis in patients with esophageal cancer. Furthermore, we discovered that overexpression/depletion of SNAP91 suppressed/facilitated the proliferation of KY-SE150/ECA109 cells. MiR-301b and SNAP91 had little impact on HEEC cell proliferation and this degree of influence was negligible compared with their impacts on esophageal cancer cell proliferation. By rescue assay, we showed that overexpression of SNAP91 restrained the growth, migration, and invasion of ECA109 cells with overexpressed miR-301b while knockdown of SNAP91 showed the contrary effects on KY-SE150 cells with downregulated miR-301b. These consequences indicated that miR-301b played an important effect on esophageal cancer cells through regulating SNAP91, insinuating that miR-301b/SNAP91 might be novel potential targets for esophageal cancer therapy and prognosis.

LncRNA FOXD1-AS1 acts as a potential oncogenic biomarker in glioma

AIMS

Altered activities of long noncoding RNAs (lncRNAs) have been associated with cancer development, and lncRNA FOXD1-AS1 (FOXD1-AS1) is the antisense transcript of the gene encoding for FOXD1, known for its role as an oncogene in several tumor types including glioma. However, the role of FOXD1-AS1 in the differentiation and progression of glioma is not well known.

METHODS

Expression profile chip and qPCR were used to screen and identify FOXD1-AS1. Glioma cells were transfected with siRNA or eukaryotic expression vector to observe FOXD1-AS1 function in vitro and in vivo. Dual luciferase reporter gene analysis, Western blot, and ChIRP-MS were used to detect microRNAs and protein that combine with FOXD1-AS1.

RESULTS

FOXD1-AS1 was upregulated and directly correlated with the glioma grade, and it was localized in both the nucleus and the cytoplasm of the glioma cell. FOXD1-AS1 silencing caused tumor suppressive effects via inhibiting cell proliferation, migration, and apoptosis, while FOXD1-AS1 overexpression resulted in opposite effects. Additionally, in vivo experiments showed that FOXD1-AS1 knockdown reduced tumor volume and weight. More importantly, mechanical studies revealed that FOXD1-AS1 targeted both miR339-5p and miR342-3p (miR339/342). Furthermore, protein eukaryotic translation initiation factor 5 subunit A (eIF5a) resulted a direct target of FOXD1-AS1.

CONCLUSIONS

These data indicated that FOXD1-AS1, a miR339/342 target, affected biological processes via protein eIF5a; thus, it might be considered as a new therapeutic target for glioblastoma.

Potential Prognostic and Diagnostic Values of CDC6, CDC45, ORC6 and SNHG7 in Colorectal Cancer

Background

Colorectal cancer (CRC) is a common human malignancy. The aims of this study are to investigate the gene expression profile of CRC and to explore potential strategy for CRC diagnosis, therapy and prognosis.

Methods

We use affy and Limma package of Bioconductor R to do differential expression genes (DEGs) and differential expression lncRNAs (DELs) analysis from the gene datasets (GSE8671, GSE21510, GSE32323, GSE39582 and TCGA) respectively. Then, DEGs were analyzed by GO and KEGG pathway and Kaplan-Meier survival curve and Cox regression analyses were used to find aberrantly expressed genes associated with survival outcome of CRC patients. Real-time PCR assay was used to verify the aberrantly expressed genes expression in CRC samples.

Results

306 up-regulation and 213 down-regulation common DEGs were found. A total of 485 DELs were identified, of which 241 up-regulated and 244 down-regulated. Then, GO and KEGG pathway analyses showed that DEGs were involved in cell cycle, mineral absorption, DNA replication, and Nitrogen metabolism. Among them, Kaplan-Meier survival curve and Cox regression analyses revealed that CDC6, CDC45, ORC6 and SNHG7 levels were significantly associated with survival outcome of CRC patients. Finally, real-time PCR assay was used to verify that the CDC6, CDC45, ORC6 and SNHG7 expression were up-regulated in 198 CRC samples compared with the expression levels in individual-matched adjacent mucosa samples.

Conclusion

CDC6, CDC45, ORC6 and SNHG7 are implicated in CRC initiation and progression and could be explored as potential diagnosis, therapy and prognosis targets for CRC.

Histone 2A Family Member J Drives Mesenchymal Transition and Temozolomide Resistance in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most aggressive brain tumor and has a poor prognosis and is poorly sensitive to radiotherapy or temozolomide (TMZ) chemotherapy. Therefore, identifying new biomarkers to predict therapeutic responses of GBM is urgently needed. By using The Cancer Genome Atlas (TCGA) database, we found that the upregulation of histone 2A family member J (H2AFJ), but not other H2AFs, is extensively detected in the therapeutic-insensitive mesenchymal, IDH wildtype, MGMT unmethylated, or non-G-CIMP GBM and is associated with poor TMZ responsiveness independent of radiation. Similar views were also found in GBM cell lines. Whereas H2AFJ knockdown diminished TMZ resistance, H2AFJ overexpression promoted TMZ resistance in a panel of GBM cell lines. Gene set enrichment analysis (GSEA) revealed that H2AFJ upregulation accompanied by the activation of TNF-α/NF-κB and IL-6/STAT3-related pathways is highly predicted. Luciferase-based promoter activity assay further validated that the activities of NF-κB and STAT3 are causally affected by H2AFJ expression in GBM cells. Moreover, we found that therapeutic targeting HADC3 by tacedinaline or NF-κB by ML029 is likely able to overcome the TMZ resistance in GBM cells with H2AFJ upregulation. Significantly, the GBM cohorts harboring a high-level H2AFJ transcript combined with high-level expression of TNF-α/NF-κB geneset, IL-6/STAT3 geneset or HADC3 were associated with a shorter time to tumor repopulation after initial treatment with TMZ. These findings not only provide H2AFJ as a biomarker to predict TMZ therapeutic effectiveness but also suggest a new strategy to combat TMZ-insensitive GBM by targeting the interaction network constructed by TNF-α/NF-κB, IL-6/STAT3, HDAC3, and H2AFJ.

Long non-coding RNA, HOTAIRM1, promotes glioma malignancy by forming a ceRNA network

Long non-coding RNAs play critical roles in tumorigenesis and the immune process. In this study, RNA sequencing data for 946 glioma samples from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas databases were analyzed to evaluate the prognostic value and function of homeobox A transcript antisense RNA myeloid-specific (HOTAIRM)1. HOTAIRM1 expression was associated with clinical and molecular features of glioma: patients with high HOTAIRM1 expression were more likely to be classified as malignant cases, and elevated HOTAIRM1 level was associated with shorter survival time in subgroups stratified by clinical and molecular features. A multivariate Cox regression analysis showed that HOTAIRM1 was an independent prognostic factor for patient outcome. In vitro experiments revealed that HOTAIRM1 knockdown suppressed the malignant behavior of glioma and increased tumor sensitivity to temozolomide. The results of an in silico analysis indicated that HOTAIRM1 promotes the malignancy of glioma by acting as a sponge for microRNA (miR)-129-5p and miR-495-3p. HOTAIRM1 overexpression was also associated with immune activation characterized by enhanced T cell-mediated immune and inflammatory responses. These results suggest that HOTAIRM1 is a prognostic biomarker and potential therapeutic target in glioma.

Common Molecular Alterations in Canine Oligodendroglioma and Human Malignant Gliomas and Potential Novel Therapeutic Targets

Spontaneous canine (Canis lupus) oligodendroglioma (ODG) holds tremendous potential as an immunocompetent large animal model of human malignant gliomas (MG). However, the feasibility of utilizing this model in pre-clinical studies depends on a thorough understanding of the similarities and differences of the molecular pathways associated with gliomas between the two species. We have previously shown that canine ODG has an immune landscape and expression pattern of commonly described oncogenes similar to that of human MG. In the current study, we performed a comprehensive analysis of canine ODG RNAseq data from 4 dogs with ODG and 2 normal controls to identify highly dysregulated genes in canine tumors. We then evaluated the expression of these genes in human MG using Xena Browser, a publicly available database. STRING-database inquiry was used in order to determine the suggested protein associations of these differentially expressed genes as well as the dysregulated pathways commonly enriched by the protein products of these genes in both canine ODG and human MG. Our results revealed that 3,712 (23%) of the 15,895 differentially expressed genes demonstrated significant up- or downregulation (log2-fold change > 2.0). Of the 3,712 altered genes, ~50% were upregulated (n = 1858) and ~50% were downregulated (n = 1854). Most of these genes were also found to have altered expression in human MG. Protein association and pathway analysis revealed common pathways enriched by members of the up- and downregulated gene categories in both species. In summary, we demonstrate that a similar pattern of gene dysregulation characterizes both human MG and canine ODG and provide additional support for the use of the canine model in order to therapeutically target these common genes. The results of such therapeutic targeting in the canine model can serve to more accurately predict the efficacy of anti-glioma therapies in human patients.

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets.

Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan–Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD).

Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer.

Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.

Joint bioinformatics analysis of underlying potential functions of hsa-let-7b-5p and core genes in human glioma

BACKGROUND

Glioma accounts for a large proportion of cancer, and an effective treatment for this disease is still lacking because of the absence of specific driver molecules. Current challenges in the treatment of glioma are the accurate and timely diagnosis of brain glioma and targeted treatment plans. To investigate the diagnostic biomarkers and prospective role of miRNAs in the tumorigenesis and progression of glioma, we analyzed the expression of miRNAs and key genes in glioma based on The Cancer Genome Atlas database.

METHODS

Of the 701 cases that were downloaded, five were normal and 696 were glioma. Then, 1626 differentially expressed genes were identified, and 173 aberrantly expressed miRNAs were calculated by edgeR. GO and KEGG pathway enrichment analyses were performed using Cytoscape software. A coexpression network was built by weighted correlation network analysis (WGCNA). A cell scratch test and transwell, cell apoptosis and cell cycle assays were performed to validate the function of hsa-let-7b-5p.

RESULTS

Based on crosstalk genes in the KEGG, PPI network, and WGCNA analyses, PLK1, CCNA2, cyclin B2 (CCNB2), and AURKA were screened as candidate diagnostic marker genes. The survival analysis revealed that high mRNA expression of PLK1, CCNA2, and AURKA was significantly associated with poor overall survival. Furthermore, hsa-let-7b-5p was identified as a core miRNA in the regulation of candidate genes involved in glioma development. We confirmed that hsa-let-7b-5p could inhibit the migration, invasion, and cell cycle of glioma cells.

CONCLUSIONS

This study provides four potential biomarkers for the diagnosis of glioma, offers a potential explanation of its pathogenesis, and proposes hsa-let-7b-5p as a therapeutic target.

Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer

Background

Gastric cancer (GC) is one of the most common types of malignancy and is associated with high morbidity and mortality rates around the world. With poor clinical outcomes, potential biomarkers for diagnosis and prognosis are important to investigate.

Objective

The aim of this study is to investigate the gene expression module of GC and to identify potential diagnostic and prognostic biomarkers.

Method

Microarray data (GSE13911, GSE29272, GSE54129, and GSE79973), including 293 stomach tumor tissues and 196 normal tissues, were analyzed to identify differentially expressed genes (DEGs). DEGs were identified in four profiles by intersecting four overlapping subsets, including 90 downregulated and 45 upregulated DEGs in common. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses have been showed that extracellular matrix was the most enriched signal pathway. Furthermore, hub genes were analyzed by protein-protein interaction network and clinical outcomes were assessed by Kaplan-Meier survival analysis. Two independent datasets were used to validate the differential expression of two hub genes: Serpin Family E Member 1 (SERPINE1) and Secreted Protein Acidic and Cysteine Rich (SPARC).

Results

Validation of independent datasets indicated that SERPINE1 and SPARC expression were drastically increased in gastric tumor tissues and associated with poor outcomes in GC patients. The expression of SERPINE1 was related to race (Asian and White) (P< 0.05).

Conclusion

SERPINE1 and SPARC were significantly upregulated in gastric tissues and associated with poor outcomes. The investigations of SERPINE1 and SPARC may promote their predictive and prognostic value in GC.

Genome-wide expression profiling of glioblastoma using a large combined cohort

Glioblastomas (GBMs), are the most common intrinsic brain tumors in adults and are almost universally fatal. Despite the progresses made in surgery, chemotherapy, and radiation over the past decades, the prognosis of patients with GBM remained poor and the average survival time of patients suffering from GBM was still short. Discovering robust gene signatures toward better understanding of the complex molecular mechanisms leading to GBM is an important prerequisite to the identification of novel and more effective therapeutic strategies. Herein, a comprehensive study of genome-scale mRNA expression data by combining GBM and normal tissue samples from 48 studies was performed. The 147 robust gene signatures were identified to be significantly differential expression between GBM and normal samples, among which 100 (68%) genes were reported to be closely associated with GBM in previous publications. Moreover, function annotation analysis based on these 147 robust DEGs showed certain deregulated gene expression programs (e.g., cell cycle, immune response and p53 signaling pathway) were associated with GBM development, and PPI network analysis revealed three novel hub genes (RFC4, ZWINT and TYMS) play important role in GBM development. Furthermore, survival analysis based on the TCGA GBM data demonstrated 38 robust DEGs significantly affect the prognosis of GBM in OS (p < 0.05). These findings provided new insights into molecular mechanisms underlying GBM and suggested the 38 robust DEGs could be potential targets for the diagnosis and treatment.

Knockdown of collagen α-1(III) inhibits glioma cell proliferation and migration and is regulated by miR128-3p

As a member of the collagen family, collagen α-1(III) (COL3A1) is an important protein in the development and progression of several tumors. However, the role of COL3A1 in glioma is not yet clear. The present study examined the expression and function of COL3A1 in glioma cell behavior and identified microRNA (miRNA) regulators. It was demonstrated that COL3A1 expression was upregulated in glioma and directly correlated with the tumor grade. Analysis of the GSE4290 and GSE7696 profiles acquired from the Gene Expression Omnibus database also revealed an increased COL3A1 expression in malignant gliomas compared with the lower grade gliomas and non-tumor brain tissue, which was directly correlated with glioma grade. To explore the functional role of COL3A1 in glioma cell growth, small interfering RNA interference was applied to inhibit COL3A1 expression in Hs683 and U251 cells. The relative COL3A1 mRNA and protein expression levels were significantly reduced in the knockdown cells as determined by western blot analysis. In addition, decreased COL3A1 expression in Hs683 and U251 glioma cells resulted in a delay in cell growth and colony disruption as determined by MTS and colony formation assays. Wound healing analysis indicated that cells with suppressed expression of COL3A1 had a reduced ability to migrate. COL3A1 mRNA levels were inversely correlated with the miR128-3p level in glioma, suggesting that miR128-3p expression is associated with COL3A1 inhibition as verified by reverse transcription-quantified polymerase chain reaction. These results suggest that COL3A1 may be a novel regulator of glioblastoma cell behavior and may represent a novel target for gene therapies against glioma.

Pharmacometabolomics Informs Quantitative Radiomics for Glioblastoma Diagnostic Innovation

Applications of omics systems biology technologies have enormous promise for radiology and diagnostics in surgical fields. In this context, the emerging fields of radiomics (a systems scale approach to radiology using a host of technologies, including omics) and pharmacometabolomics (use of metabolomics for patient and disease stratification and guiding precision medicine) offer much synergy for diagnostic innovation in surgery, particularly in neurosurgery. This synthesis of omics fields and applications is timely because diagnostic accuracy in central nervous system tumors still challenges decision-making. Considering the vast heterogeneity in brain tumors, disease phenotypes, and interindividual variability in surgical and chemotherapy outcomes, we believe that diagnostic accuracy can be markedly improved by quantitative radiomics coupled to pharmacometabolomics and related health information technologies while optimizing economic costs of traditional diagnostics. In this expert review, we present an innovation analysis on a systems-level multi-omics approach toward diagnostic accuracy in central nervous system tumors. For this, we suggest that glioblastomas serve as a useful application paradigm. We performed a literature search on PubMed for articles published in English between 2006 and 2016. We used the search terms "radiomics," "glioblastoma," "biomarkers," "pharmacogenomics," "pharmacometabolomics," "pharmacometabonomics/pharmacometabolomics," "collaborative informatics," and "precision medicine." A list of the top 4 insights we derived from this literature analysis is presented in this study. For example, we found that (i) tumor grading needs to be better refined, (ii) diagnostic precision should be improved, (iii) standardization in radiomics is lacking, and (iv) quantitative radiomics needs to prove clinical implementation. We conclude with an interdisciplinary call to the metabolomics, pharmacy/pharmacology, radiology, and surgery communities that pharmacometabolomics coupled to information technologies (chemoinformatics tools, databases, collaborative systems) can inform quantitative radiomics, thus translating Big Data and information growth to knowledge growth, rational drug development and diagnostics innovation for glioblastomas, and possibly in other brain tumors.

Identification of Common Genes Refers to Colorectal Carcinogenesis with Paired Cancer and Noncancer Samples

Colorectal cancer is a malignant tumor which harmed human beings' health. The aim of this study was to explore common biomarkers associated with colorectal carcinogenesis in paired cancer and noncancer samples. At first, fifty-nine pairs of colorectal cancer and noncancer samples from three gene expression datasets were collected and analyzed. Then, 181 upregulation and 282 downregulation common differential expression genes (DEGs) were found. Next, functional annotation was performed in the DAVID database with the DEGs. Finally, real-time polymerase chain reaction (PCR) assay was conducted to verify the analyses in sixteen colorectal cancer and individual-matched adjacent mucosa samples. Real-time PCR showed that MCM2, RNASEH2A, and TOP2A were upregulated in colorectal cancer compared with adjacent mucosa samples (MCM2, P < 0.001; RNASEH2A, P < 0.001; TOP2A, P = 0.001). These suggested that 463 DEGs might contribute to colorectal carcinogenesis.

Actin-capping protein CapG is associated with prognosis, proliferation and metastasis in human glioma

Glioma is the most aggressive and malignant primary brain tumor in adults. In the present study, we identified a vital oncoprotein, capping actin protein, gelsolin-like (CapG), and investigated its roles in the prognosis, proliferation and metastasis in glioma. The mRNA and protein levels of CapG were significantly increased in human glioma, and higher CapG expression was an independent prognostic factor for predicting unfavorable prognosis. The expression level of CapG was found to be associated with several common molecular features of glioblastoma (GBM; WHO grade IV glioma) in The Cancer Genome Atlas (TCGA) cohort. When analyzing the prognosis of GBM patients according to these molecular features, we observed that the prognostic value of CapG was affected by amplification of CDK6 or EGFR. However, overexpression of CapG markedly promoted cell growth in vitro, while depletion of CapG significantly inhibited cell proliferation by blocking the cell cycle in G1/S transition. Moreover, CapG manipulation in glioma cell lines U87 and U251 showed CapG-dependent cellular migration and invasiveness. These data suggest that CapG may serve as a prognostic biomarker with potentially important therapeutic implications for glioma.

T-lymphokine-activated killer cell-originated protein kinase (TOPK) as a prognostic factor and a potential therapeutic target in glioma

TOPK is overexpressed in various types of cancer and associated with poor outcomes in different types of cancer. In this study, we first found that the expression of T-lymphokine-activated killer cell-originated protein kinase (TOPK) was significantly higher in Grade III or Grade IV than that in Grade II in glioma (P = 0.007 and P < 0.001, respectively). Expression of TOPK was positively correlated with Ki67 (P < 0.001). Knockdown of TOPK significantly inhibited cell growth, colony formation and increased sensitivities to temozolomide (TMZ) in U-87 MG or U-251 cells, while TOPK overexpression promoted cell growth and colony formation in Hs 683 or A-172 cells. Glioma patients expressing high levels of TOPK have poor survival compared with those expressing low levels of TOPK in high-grade or low-grade gliomas (hazard ratio = 0.2995; 95% CI, 0.1262 to 0.7108; P = 0.0063 and hazard ratio = 0.1509; 95% CI, 0.05928 to 0.3842; P < 0.0001, respectively). The level of TOPK was low in TMZ-sensitive patients compared with TMZ-resistant patients (P = 0.0056). In TMZ-resistant population, patients expressing high TOPK have two months’ shorter survival time than those expressing low TOPK. Our findings demonstrated that TOPK might represent as a promising prognostic and predictive factor and potential therapeutic target for glioma.

Glioblastoma research: US and international networking achievements

Being the most aggressive type of brain tumor, glioblastoma is estimated to be diagnosed in about 12,400 new cases in 2017. The diagnosis is dramatic to patients and relatives and leaves open many unanswered questions for them. One is the big question why there is no cure as in other tumors. This review illustrates the US and global research efforts that have been made over the past century. It demonstrates the great magnitude of energy invested by US clinicians and scientists but undoubtedly, more research is needed and funding by NIH and other sources should be continued on the same level.

Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data

The aim of this study was to identify key genes associated with gliomas and glioblastoma and to explore the related signaling pathways. Gene expression profiles of three glioma stem cell line samples, three normal astrocyte samples, three astrocyte overexpressing 4 iPSC-inducing and oncogenic factors (myc(T58A), OCT-4, p53DD, and H-Ras(G12V)) samples, three astrocyte overexpressing 7 iPSC-inducing and oncogenic factors (OCT4, H-Ras(G12V), myc(T58A), p53DD, cyclin D1, CDK4(RC24) and hTERT) samples and three glioblastoma cell line samples were downloaded from the ArrayExpress database (accession: E-MTAB-4771). The differentially expressed genes (DEGs) in gliomas and glioblastoma were identified using FDR and t tests, and protein-protein interaction (PPI) networks for these DEGs were constructed using the protein interaction network analysis. The GeneTrail2 1.5 tool was used to identify potentially enriched biological processes among the DEGs using gene ontology (GO) terms and to identify the related pathways using the Kyoto Encyclopedia of Genes and Genomes, Reactome and WikiPathways pathway database. In addition, crucial modules of the constructed PPI networks were identified using the PEWCC1 plug-in, and their topological properties were analyzed using NetworkAnalyzer, both available from Cytoscape. We also constructed microRNA-target gene regulatory network and transcription factor-target gene regulatory network for these DEGs were constructed using the miRNet and binding and expression target analysis. We identified 200 genes that could potentially be involved in the gliomas and glioblastoma. Among them, bioinformatics analysis identified 137 up-regulated and 63 down-regulated DEGs in gliomas and glioblastoma. The significant enriched pathway (PI3K-Akt) for up-regulated genes such as COL4A1, COL4A2, EGFR, FGFR1, LAPR6, MYC, PDGFA, SPP1 were selected as well as significant GO term (ear development) for up-regulated genes such as CELSR1, CHRNA9, DDR1, FGFR1, GLI2, LGR5, SOX2, TSHR were selected, while the significant enriched pathway (amebiasis) for down-regulated gene such as COL3A1, COL5A2, LAMA2 were selected as well as significant GO term (RNA polymerase II core promoter proximal region sequence-specific binding (5) such as MEIS2, MEOX2, NR2E1, PITX2, TFAP2B, ZFPM2 were selected. Importantly, MYC and SOX2 were hub proteins in the up-regulated PPI network, while MET and CDKN2A were hub proteins in the down-regulated PPI network. After network module analysis, MYC, FGFR1 and HOXA10 were selected as the up-regulated coexpressed genes in the gliomas and glioblastoma, while SH3GL3 and SNRPN were selected as the down-regulated coexpressed genes in the gliomas and glioblastoma. MicroRNA hsa-mir-22-3p had a regulatory effect on the most up DEGs, including VSNL1, while hsa-mir-103a-3p had a regulatory effect on the most down DEGs, including DAPK1. Transcription factor EZH2 had a regulatory effect on the both up and down DEGs, including CD9, CHI3L1, MEIS2 and NR2E1. The DEGs, such as MYC, FGFR1, CDKN2A, HOXA10 and MET, may be used for targeted diagnosis and treatment of gliomas and glioblastoma.

Akt/FoxM1 signaling pathway-mediated upregulation of MYBL2 promotes progression of human glioma

Background

MYB-related protein B (B-MYB/MYBL2), a member of the myeloblastosis family of transcription factors, has been reported for its role in the genesis and progression of tumors. Forkhead box M1 (FoxM1), another transcriptional factor, is considered to be an independent predictor of poor survival in many solid cancers. The aim of the present study was to investigate the clinical significance of the correlation between MYBL2 and FoxM1 in glioma and the possible mechanism of FoxM1and MYBL2 expression.

Methods

MYBL2 and FoxM1expression in cancerous tissues and cell lines were determined by reverse transcription-PCR (RT-PCR), Western blotting and immunostaining. The co-expression of MYBL2 and FoxM1 was analyzed in low-grade glioma (LGG) and glioblastoma (HGG) cohorts of TCGA using cBioportal and UCSC Xena. And, the role of MYBL2 and FoxM1 in glioma cell progression and the underlying mechanisms were studied by using small interfering RNA (si-RNA) and pcDNA3.1 + HAvectors. Furthermore, the effects of MYBL2 and FoxM1 in cell proliferation, cell cycle progression, apoptosis, migration, invasion, and adhesion were determined by cell proliferation assays, flow cytometry analysis, transwell migration and cell adhesion assay.

Results

MYBL2 and FoxM1 expression are significantly associated with clinical stages and overall survival of glioma patients. In cohorts of TCGA, patients with high MYBL2 but without radio-chemotherapy had the highest hazard ratio (adjusted HR = 5.29, 95% CI = 1.475–18.969, P < 0.05). Meanwhile, MYBL2 closely related to the FoxM1 expression in 79 glioma tissues (r = 0.742, p < 0.05) and LGG (r = 0.83) and HGG (r = 0.74) cohorts of TCGA. Down regulation of FoxM1 and MYBL2 by siRNAs induced the cell cycle arrest, apoptosis and EMT of glioma cells. Furthermore, inactivations of Akt/FoxM1 signaling by Akt inhibitor and siRNA-FoxM1 reduce the expression of MYBL2 in glioma cells.

Conclusions

MYBL2 is a key downstream factor of Akt/FoxM1 signaling to promote progression of human glioma, and could be a new candidate gene for molecular targeting therapy and biomarker for radiotherapy of glioma.

Trial registration

CTXY-1300041-3-2. ChiCTR-COC-15006186. Registered date: 13 September 2013.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-017-0573-6) contains supplementary material, which is available to authorized users.

Genome-scale analysis identifies GJB2 and ERO1LB as prognosis markers in patients with pancreatic cancer

Pancreatic cancer is a complex and heterogeneous disease with the etiology largely unknown. The deadly nature of pancreatic cancer, with an extremely low 5-year survival rate, renders urgent a better understanding of the molecular events underlying it. The aim of this study is to investigate the gene expression module of pancreatic adenocarcinoma and to identify differentially expressed genes (DEGs) with prognostic potentials. Transcriptome microarray data of five GEO datasets (GSE15471, GSE16515, GSE18670, GSE32676, GSE71989), including 117 primary tumor samples and 73 normal pancreatic tissue samples, were utilized to identify DEGs. The five sets of DEGs had an overlapping subset consisting of 98 genes (90 up-regulated and 8 down-regulated), which were probably common to pancreatic cancer. Gene ontology (GO) analysis of the 98 DEGs showed that cell cycle and cell adhesion were the major enriched processes, and extracellular matrix (ECM)-receptor interaction and p53 signaling pathway were the most enriched pathways according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Elevated expression of gap junction protein beta 2 (GJB2) and reduced endoplasmic reticulum oxidoreductase 1-like beta (ERO1LB) expression were validated in an independent cohort. Kaplan-Meier survival analysis revealed that GJB2 and ERO1LB levels were significantly associated with the overall survival of pancreatic cancer patients. GJB2 and ERO1LB are implicated in pancreatic cancer progression and can be used to predict patient survival. Therapeutic strategies targeting GJB2 and facilitating ERO1LB expression may deserve evaluation to improve prognosis of pancreatic cancer patients.