Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

Creation of signatures and identification of molecular subtypes based on disulfidptosis-related genes for glioblastoma patients' prognosis and immunological activity

BACKGROUND

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance of disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic.

METHODS

The GEO and TCGA databases provided transcriptional and clinically relevant data on tumor samples, while the GTEx database provided data on healthy tissues. Disulfidptosis-related genes (DisRGs) were procured from previous scholarly investigations. The expression profile of DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent to which their prognostic value was explored. Through consensus clustering, we constructed DisRGs-related clusters and gene subtypes. Our results established that the DisRG-related clusters had differentially expressed genes, resulting in a DisulfidptosisScore model, which had a positive prognostic value.

RESULTS

The differential expression profile of 24 DisRGs between GBM samples and healthy samples was acquired. Through consensus cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A and DisRGcluster B, were identified. Then, the DisulfidptosisScore model including 4 characteristic genes was constructed.Notably, patients with GBM assigned with lower score demonstrated a considerably longer overall survival (OS) compared to those with higher score.

CONCLUSION

We have effectively devised a prognostic model associated with disulfidptosis, presenting autonomous prognostic predictions for patients with GBM. These findings serve as a valuable addition to the current comprehension of disulfidptosis and offer fresh theoretical substantiation for the development of enhanced treatment strategies.

Profiling the molecular and clinical landscape of glioblastoma utilizing the Oncology Research Information Exchange Network brain cancer database

Background

Glioblastoma exhibits aggressive growth and poor outcomes despite treatment, and its marked variability renders therapeutic design and prognostication challenging. The Oncology Research Information Exchange Network (ORIEN) database contains complementary clinical, genomic, and transcriptomic profiling of 206 glioblastoma patients, providing opportunities to identify novel associations between molecular features and clinical outcomes.

Methods

Survival analyses were performed using the Logrank test, and clinical features were evaluated using Wilcoxon and chi-squared tests with q-values derived via Benjamini-Hochberg correction. Mutational analyses utilized sample-level enrichments from whole exome sequencing data, and statistical tests were performed using the one-sided Fisher Exact test with Benjamini-Hochberg correction. Transcriptomic analyses utilized a student's t-test with Benjamini-Hochberg correction. Expression fold changes were processed with Ingenuity Pathway Analysis to determine pathway-level alterations between groups.

Results

Key findings include an association of MUC17, SYNE1, and TENM1 mutations with prolonged overall survival (OS); decreased OS associated with higher epithelial growth factor receptor (EGFR) mRNA expression, but not with EGFR amplification or mutation; a 14-transcript signature associated with OS > 2 years; and 2 transcripts associated with OS < 1 year.

Conclusions

Herein, we report the first clinical, genomic, and transcriptomic analysis of ORIEN glioblastoma cases, incorporating sample reclassification under updated 2021 diagnostic criteria. These findings create multiple avenues for further investigation and reinforce the value of multi-institutional consortia such as ORIEN in deepening our knowledge of intractable diseases such as glioblastoma.

Identification of a novel five ferroptosis-related gene signature as a promising prognostic model for breast cancer

BACKGROUND

Breast cancer (BCa) is a major challenge for women's health worldwide. Ferroptosis is closely related to tumorigenesis and cancer progression. However, the prognostic value of ferroptosis-related genes in BCa remains unclear, and more accurate prognostic models are urgently needed.

METHODS

Gene expression profiles and clinical information of BCa patients were collected from public databases. LASSO and multivariate Cox regression analysis were utilized to construct the prognostic gene signature. Kaplan-Meier plotter, receiver operating characteristic (ROC) curves, and nomogram were used to validate the prognostic value of the gene signature. Gene set enrichment analysis was performed to explore the molecular functions and signaling pathways.

RESULTS

Differentially expressed ferroptosis-related genes between BCa samples and normal tissues were obtained. A novel five-gene signature including BCL2, SLC40A1, TFF1, APOOL, and PRAME was established for prognosis prediction. Patients stratified into high-risk or low-risk group displayed significantly different survival. Kaplan-Meier and ROC curves showed a good performance for survival prediction in different cohorts. Biological function analysis revealed that the five-gene signature was associated with cancer progression, immune infiltration, immune response, and drug resistance. Nomogram including the five-gene signature was established.

CONCLUSION

A novel five ferroptosis-related gene signature and nomogram could be used for prognostic prediction in BCa.

Targeting small GTPases: emerging grasps on previously untamable targets, pioneered by KRAS

Small GTPases including Ras, Rho, Rab, Arf, and Ran are omnipresent molecular switches in regulating key cellular functions. Their dysregulation is a therapeutic target for tumors, neurodegeneration, cardiomyopathies, and infection. However, small GTPases have been historically recognized as "undruggable". Targeting KRAS, one of the most frequently mutated oncogenes, has only come into reality in the last decade due to the development of breakthrough strategies such as fragment-based screening, covalent ligands, macromolecule inhibitors, and PROTACs. Two KRAS^G12C covalent inhibitors have obtained accelerated approval for treating KRAS^G12C mutant lung cancer, and allele-specific hotspot mutations on G12D/S/R have been demonstrated as viable targets. New methods of targeting KRAS are quickly evolving, including transcription, immunogenic neoepitopes, and combinatory targeting with immunotherapy. Nevertheless, the vast majority of small GTPases and hotspot mutations remain elusive, and clinical resistance to G12C inhibitors poses new challenges. In this article, we summarize diversified biological functions, shared structural properties, and complex regulatory mechanisms of small GTPases and their relationships with human diseases. Furthermore, we review the status of drug discovery for targeting small GTPases and the most recent strategic progress focused on targeting KRAS. The discovery of new regulatory mechanisms and development of targeting approaches will together promote drug discovery for small GTPases.

Association between Rab31/rs9965664 polymorphism and immunoglobulin therapy resistance in patients with Kawasaki disease

Background

Kawasaki disease (KD) is an acute febrile systemic vasculitis affecting infants and young children. A high dose of intravenous immunoglobulin (IVIG) is the first-line strategy for patients with KD to reduce persistent inflammation and the risk of coronary artery aneurysm (CAA) formation. Unfortunately, 10–20% of the patients showed no response to the treatment and were defined as resistant to IVIG. Rab31 has been reported to regulate innate immunity in several human diseases. However, whether single nucleotide polymorphism (SNP) in Rab31 gene could predispose to IVIG therapy response in KD was uncovered.

Methods

Rab31/rs9965664 polymorphism was genotyped in 1,024 Chinese patients with KD through TaqMan assay. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association between Rab31/rs9965664 polymorphism and IVIG therapeutic effects.

Results

Our results showed that Rab31/rs9965664 AA/GA genotype was significantly associated with an increased risk of IVIG resistance compared to GG genotype (GA vs. GG: p = 0.0249; AA vs. GG: p = 0.0016; AA/GA vs. GG: p = 0.0039; and AA vs. GG/GA: p = 0.0072). Moreover, the KD individuals carrying the rs9965664 A allele displayed lower Rab31 protein levels, and the expression level of Rab31 in the IVIG-resistant group was decreased significantly when compared to that observed in the response group. A mechanical study demonstrated that Rab31 modulated IVIG response through NLRP3 and p38 pathways.

Conclusion

These results suggested that Rab31/rs9965664 polymorphism might be associated with an increased risk of IVIG resistance in southern Chinese patients with KD. The possible mechanism is that Rab31 regulates the NLRP3 pathway negatively to inhibit IVIG response.

Reaction Mechanism of Human PAICS Elucidated by Quantum Chemical Calculations

Human PAICS is a bifunctional enzyme that is involved in the de novo purine biosynthesis, catalyzing the conversion of aminoimidazole ribonucleotide (AIR) into N-succinylcarboxamide-5-aminoimidazole ribonucleotide (SAICAR). It comprises two distinct active sites, AIR carboxylase (AIRc) where the AIR is initially converted to carboxyaminoimidazole ribonucleotide (CAIR) by reaction with CO₂ and SAICAR synthetase (SAICARs) in which CAIR then reacts with an aspartate to form SAICAR, in an ATP-dependent reaction. Human PAICS is a promising target for the treatment of various types of cancer, and it is therefore of high interest to develop a detailed understanding of its reaction mechanism. In the present work, density functional theory calculations are employed to investigate the PAICS reaction mechanism. Starting from the available crystal structures, two large models of the AIRc and SAICARs active sites are built and different mechanistic proposals for the carboxylation and phosphorylation–condensation mechanisms are examined. For the carboxylation reaction, it is demonstrated that it takes place in a two-step mechanism, involving a C–C bond formation followed by a deprotonation of the formed tetrahedral intermediate (known as isoCAIR) assisted by an active site histidine residue. For the phosphorylation–condensation reaction, it is shown that the phosphorylation of CAIR takes place before the condensation reaction with the aspartate. It is further demonstrated that the three active site magnesium ions are involved in binding the substrates and stabilizing the transition states and intermediates of the reaction. The calculated barriers are in good agreement with available experimental data.

Identification of the Antigens Recognised by Colorectal Cancer Patients Using Sera from Patients Who Exhibit a Crohn's-like Lymphoid Reaction

A Crohn’s-like lymphoid reaction (CLR) is observed in about 15% of colorectal cancer (CRC) patients and is associated with favourable outcomes. To identify the immune targets recognised by CRC CLR patient sera, we immunoscreened a testes cDNA library with sera from three patients. Immunoscreening of the 18 antigens identified by SEREX with sera from normal donors showed that only the heavy chain of IgG3 (IGHG3) and a novel antigen we named UOB-COL-7, were solely recognised by sera from CRC CLR patients. ELISA showed an elevation in IgG3 levels in patients with CRC (p = 0.01). To extend our studies we analysed the expression of our SEREX-identified antigens using the RNA-sequencing dataset (GSE5206). We found that the transcript levels of multiple IGHG probesets were highly significant (p < 0.001) in their association with clinical features of CRC while above median levels of DAPK1 (p = 0.005) and below median levels of GTF2H5 (p = 0.004) and SH3RF2 (p = 0.02) were associated with improved overall survival. Our findings demonstrate the potential of SEREX-identified CRC CLR antigens to act as biomarkers for CRC and provide a rationale for their further characterization and validation.

Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes

Purpose

Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model.

Patients and Methods

The data of LGG were downloaded from public databases. Through LASSO analysis of characteristic genes, a gene signature was constructed. Patients into were divided two groups based on risk score. Subsequently, survival, clinical phenotype, functional enrichment, immune cell infiltration and somatic mutation analysis were performed. In addition, whether ferroptosis-related genes (FRGs) signature can predict the patient's response to anti-PD-1/PD-L1 immunotherapy was also investigated.

Results

FRGs signature had strong prognostic assessment ability, and high risk score was associated with poor overall survival (OS) of LGG. The high risk score group had higher degree of immune cell infiltration, stronger stromal activity, higher immune score, and high expression of immune checkpoint. In low risk score group anti-PD-1/PD-L1 immunotherapy has significant therapeutic advantages and clinical response. Genes and frequency of somatic mutations and clinical phenotypes in the high and low risk score groups were significantly different.

Conclusion

A prognostic model based on 7 FRGs can be used to predict the prognosis and immunotherapeutic response of LGG.

Molecular Insights and Prognosis Associated With RBM8A in Glioblastoma

Background: Glioblastoma (GBM) is the most invasive brain tumors, and it is associated with high rates of recurrence and mortality. The purpose of this study was to investigate the expression of RBM8A in GBM and the potential influence of its expression on the disease.

Methods: Levels of RBM8A mRNA in GBM patients and controls were examined in The Cancer Genome Atlas (TCGA), GSE16011 and GSE90604 databases. GBM samples in TCGA were divided into RBM8A^high and RBM8A^low groups. Differentially expressed genes (DEGs) between GBM patients and controls were identified, as were DEGs between RBM8A^high and RBM8A^low groups. DEGs common to both of these comparisons were analyzed for coexpression and regression analyses. In addition, we identified potential effects of RBM8A on competing endogenous RNAs, immune cell infiltration, methylation modifications, and somatic mutations.

Results: RBM8A is expressed at significantly higher levels in GBM than control samples, and its level correlates with tumor purity. We identified a total of 488 mRNAs that differed between GBM and controls as well as between RBM8A^high and RBM8A^low groups, which enrichment analysis revealed to be associated mainly with neuroblast proliferation, and T cell immune responses. We identified 174 mRNAs that gave areas under the receiver operating characteristic curve >0.7 among coexpression module genes, of which 13 were significantly associated with overall survival of GBM patients. We integrated 11 candidate mRNAs through LASSO algorithm, then nomogram, risk score, and decision curve analyses were analyzed. We found that RBM8A may compete with DLEU1 for binding to miR-128-1-5p, and aberrant RBM8A expression was associations with tumor infiltration by immune cells. Some mRNAs associated with GBM prognosis also appear to be methylated or mutated.

Conclusions: Our study strongly links RBM8A expression to GBM pathobiology and patient prognosis. The candidate mRNAs identified here may lead to therapeutic targets against the disease.

Recognition of a Novel Gene Signature for Human Glioblastoma

Glioblastoma (GBM) is one of the most common malignant and incurable brain tumors. The identification of a gene signature for GBM may be helpful for its diagnosis, treatment, prediction of prognosis and even the development of treatments. In this study, we used the GSE108474 database to perform GSEA and machine learning analysis, and identified a 33-gene signature of GBM by examining astrocytoma or non-GBM glioma differential gene expression. The 33 identified signature genes included the overexpressed genes COL6A2, ABCC3, COL8A1, FAM20A, ADM, CTHRC1, PDPN, IBSP, MIR210HG, GPX8, MYL9 and PDLIM4, as well as the underexpressed genes CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C, SHANK2 and VIPR2. Protein functional analysis by CELLO2GO implied that these signature genes might be involved in regulating various aspects of biological function, including anatomical structure development, cell proliferation and adhesion, signaling transduction and many of the genes were annotated in response to stress. Of these 33 signature genes, 23 have previously been reported to be functionally correlated with GBM; the roles of the remaining 10 genes in glioma development remain unknown. Our results were the first to reveal that GBM exhibited the overexpressed GPX8 gene and underexpressed signature genes including CHST9, CSDC2, ENHO, FERMT1, IGFN1, LINC00836, MGAT4C and SHANK2, which might play crucial roles in the tumorigenesis of different gliomas.

A Risk Score Signature Consisting of Six Immune Genes Predicts Overall Survival in Patients with Lower-Grade Gliomas

Background. Lower-grade gliomas (LGGs) are less aggressive with a long overall survival (OS) time span. Because of individualized genomic features, a prognostic system incorporating molecular signatures can more accurately predict OS. Methods. Differential expression analysis between LGGs and normal tissues was performed using the Gene Expression Omnibus (GEO) datasets (GSE4290 and GSE12657). Immune-related differentially expressed genes (ImmPort-DEGs) were analyzed for functional enrichment. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an immune risk score signature (IRSS). We extracted information from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) to establish and validate the model. The relationship of model gene sets with immune infiltration was analyzed based on gene set variation analysis (GSVA) scores. Patients were divided into low- and high-risk groups based on the median score. The time-dependent receiver-operating characteristic (ROC) curve and the Kaplan-Meier curve were used to evaluate the model. Then, a precise prognostic nomogram was established, and its efficacy was verified. Results. A total of 18 related immune genes were identified, building a 6-gene IRSS (BMP2, F2R, FGF13, PCSK1, PRKCB, and PTGER3). DEGs were enriched in T cell and NK cell regulatory pathways. Immune infiltration analysis confirmed that the gene signature correlated with a decrease in innate immune cells. In terms of model evaluation, ROC curves at 1, 3, and 5 years showed moderate predictive ability of IRSS ( $\text{AUC}=0.930$ , 0.797, and 0.728). The Cox regression analysis revealed that IRSS was an independent prognostic factor, and the nomogram model had good predictive ability ( $\text{C}-\text{index}=0.828$ ). Meanwhile, the predictive power of IRSS was also confirmed in the training cohort. The Kaplan-Meier results showed that the prognosis of the high-risk group was significantly worse in all cohorts. Conclusion. IRSS may serve as a novel survival prediction tool in the classification of LGG patients.

Construction of a prognostic classifier and prediction of the immune landscape and immunosuppressive molecules in gliomas based on combination of inflammatory response-related genes and angiogenesis-associated genes

Objective:We aimed to combine inflammatory response-related genes (IRRGs) and angiogenesis-associated genes (AAGs) to build a prognostic classifier and to predict immune landscapes and immunosuppressive molecules in gliomas.

Introduction: Gliomas, the commonest primary brain tumors, account for about 80% of cancerous tumors in the central nervous system (CNS), featuring rapid progression, high malignancy, and extremely poor prognosis. The induction of inflammatory responses and angiogenesis have been considered to be closely related to tumors. However, there are little publications systematically elaborating on their impacts on gliomas.

Methods: We downloaded the data of IRRGs and AAGs from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases, and retrieved 68 differentially expressed genes (DEGs), of which 13 DEGs pertained to the prognosis of glioma cases. Next, 9 DEGs were screened from the 13 major DEGs with predictive significance and utilized to build a 9-gene signature as a prognostic risk score model (PRSM) with the aid of univariate Cox regression analyses (CRA) and least absolute shrinkage and selection operator (LASSO)-CRA. On this basis, glioma patients fell into high-risk (HR) group and low-risk (LR) group. Later, we implemented Gene Set Enrichment Analysis (GSEA, Gene Set: WP_ANGIOGENESIS) and calculate the scores of cell infiltration and immune-associated function by harnessing single-sample GSEA (ssGSEA).

Results: The prognosis was compared between the two groups by introducing Kaplan-Meier (KM) analysis, which yielded that HR group exhibited poorer prognosis. Additionally, the predictive capacity and independent characteristics were proven by the receiver operating characteristic curve (ROC) and multivariate CRA. Further, We took an evaluation of immune profiles, which unraveled that immunosuppressive cell count was distinctively larger in HS group. Finally, a protein-protein interaction (PPI) network of DEGs was built, and 10 hub genes were obtained, of which epidermal growth factor receptor (EGFR) was closely related to poor prognosis.

Conclusion: A 9-gene signature was established on the strength of IRRGs and AAGs for predicting glioma prognosis, tumor microenvironment (TME), immune landscapes and immunosuppressive molecules. However, the molecular mechanism developed by this signature to function in tumor immunity needs further experimental research in the future and is expected to be a research target for glioma immunotherapy strategies.

A Novel Risk Signature with Seven Pyroptosis-Related Genes for Prognosis Prediction in Glioma

BACKGROUND

Increasing evidence indicates that pyroptosis is closely linked to the occurrence and progression of cancer. However, the expression and prognostic role of most pyroptosis-related genes in glioma have not been fully elucidated.

METHODS

Herein, we explored the expression profiles and prognostic value of 33 pyroptosis-related genes in glioma. LASSO regression analysis was then used to construct a risk signature to predict glioma outcomes in The Cancer Genome Atlas (TCGA) cohort. Furthermore, we constructed a nomogram based on independent prognostic factors and performed external validation. Finally, functional enrichment analysis was performed to explore the potential biological role of the pyroptosis-related signature in glioma.

RESULTS

The expression of most pyroptosis-related genes (31/33) was significantly different between normal brain and glioma tissue. By univariate Cox regression analysis, 24 genes were found to be significantly correlated with glioma overall survival (OS). Subsequently, we constructed a 7-gene risk signature in the TCGA training cohort, which demonstrated good performance in predicting glioma survival through multidatabase validation. Moreover, a nomogram was established based on independent prognostic factors (age, WHO grade, IDH status and signature) and confirmed to be more effective and accurate through internal evaluation and external validation. Finally, functional enrichment analyses suggested that the signature might be related to invasion ability and immune function.

CONCLUSIONS

The risk signature based on seven pyroptosis-related genes can effectively predict the clinical outcomes of glioma patients. Our study provides novel insights for further understanding the association between pyroptosis-related genes and glioma prognosis.

Whole-exome sequencing, EGFR amplification and infiltration patterns in human glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. This cancer shows rapid, highly infiltrative growth, that invades individually or in small groups the surrounding tissue. The aggressive tumor biology of GBM has devastating consequences with a median survival of 15 months. GBM often has Epidermal Growth Factor Receptor (EGFR) abnormalities. Despite recent advances in the study of GBM tumor biology, it is unclear whether mutations in GBM are related to EGFR amplification and relevant phenotypes like tumor infiltration. This study aimed to perform whole-exome sequencing analysis in 30 human GBM samples for identifying mutational portraits associated with EGFR amplification and infiltrative patterns. Our results show that EGFR-amplified tumors have overall higher mutation rates than EGFR-no-amplified. Six genes out of 2029 candidate genes show mutations associated with EGFR amplification status. Mutations in these genes for GBM are novel, not previously reported in GBM, and with little presence in the TCGA database. GPR179, USP48, and BLK show mutation only in EGFR-amplified cases, and all the affected cases exhibit diffuse infiltrative patterns. On the other hand, mutations in ADGB, EHHADH, and PTPN13, were present only in the EGFR-no-amplified group with a more diverse infiltrative phenotype. Overall, our work identified different mutational portraits of GBM related to well-established features like EGFR amplification and tumor infiltration.

Fast mutual exclusivity algorithm nominates potential synthetic lethal gene pairs through brute force matrix product computations

Mutual Exclusivity analysis of genomic aberrations contributes to the exploration of potential synthetic lethal (SL) relationships thus guiding the nomination of specific cancer cells vulnerabilities. When multiple classes of genomic aberrations and large cohorts of patients are interrogated, exhaustive genome-wide analyses are not computationally feasible with commonly used approaches. Here we present Fast Mutual Exclusivity (FaME), an algorithm based on matrix multiplication that employs a logarithm-based implementation of the Fisher's exact test to achieve fast computation of genome-wide mutual exclusivity tests; we show that brute force testing for mutual exclusivity of hundreds of millions of aberrations combinations can be performed in few minutes. We applied FaME to allele-specific data from whole exome experiments of 27 TCGA studies cohorts, detecting both mutual exclusivity of point mutations, as well as allele-specific copy number signals that span sets of contiguous cytobands. We next focused on a case study involving the loss of tumor suppressors and druggable genes while exploiting an integrated analysis of both public cell lines loss of function screens data and patients' transcriptomic profiles. FaME algorithm implementation as well as allele-specific analysis output are publicly available at https://github.com/demichelislab/FaME.

DNA Methylation-based Diagnostic and Prognostic Biomarkers for Glioblastoma

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

A Prognostic Model for Brain Glioma Patients Based on 9 Signature Glycolytic Genes

Objective

To screen glycolytic genes linked to the glioma prognosis and construct the prognostic model.

Methods

The relevant data of glioma were downloaded from TCGA and GTEx databases. GSEA of glycolysis-related pathways was carried out, and enriched differential genes were extracted. Screening out prognostic-related genes with conspicuous significance and construction of the prognostic model were conducted by multivariate Cox regression analysis and Lasso regression analysis. The model was evaluated, and cBioPortal was used to analyze the mutation of the model gene. The expression of the model gene in tumor and normal colon tissue was analyzed. The model was used to evaluate the prognosis of patients in different groups to verify the applicability of the model.

Results

339 differentially glycolytic-related genes were enriched in REACTOME_GLYCOLYSIS, GLYCOLYTIC_PROCESS, HALLMARK_GLYCOLYSIS, and other pathways. We obtained 9 key prognostic genes and constructed the prognostic evaluation model. The 3-year AUC values of the ROC curve display model are greater than 0.75, which indicates that the accuracy of the model is good. The relation of age and risk score to prognosis is shown by univariate and multivariate Cox analysis. The expression of SRD5A3, MDH2, and B3GAT3 genes was significantly upregulated in the tumor tissues, while the HDAC4 and G6PC2 genes were downregulated. The mutation rate of MDH2 and HDAC4 genes was the highest. This model could effectively distinguish the risk of poor prognosis of patients in any age stage.

Conclusion

The prognostic assessment models based on glycolysis-related nine-gene signature could accurately predict the prognosis of patients with GBM.

Identifying the miRNA Signature Association with Aging-Related Senescence in Glioblastoma

Glioblastoma (GBM) is the most common malignant brain tumor and its malignant phenotypic characteristics are classified as grade IV tumors. Molecular interactions, such as protein–protein, protein–ncRNA, and protein–peptide interactions are crucial to transfer the signaling communications in cellular signaling pathways. Evidences suggest that signaling pathways of stem cells are also activated, which helps the propagation of GBM. Hence, it is important to identify a common signaling pathway that could be visible from multiple GBM gene expression data. microRNA signaling is considered important in GBM signaling, which needs further validation. We performed a high-throughput analysis using micro array expression profiles from 574 samples to explore the role of non-coding RNAs in the disease progression and unique signaling communication in GBM. A series of computational methods involving miRNA expression, gene ontology (GO) based gene enrichment, pathway mapping, and annotation from metabolic pathways databases, and network analysis were used for the analysis. Our study revealed the physiological roles of many known and novel miRNAs in cancer signaling, especially concerning signaling in cancer progression and proliferation. Overall, the results revealed a strong connection with stress induced senescence, significant miRNA targets for cell cycle arrest, and many common signaling pathways to GBM in the network.

Identification of Latent Oncogenes with a Network Embedding Method and Random Forest

Oncogene is a special type of genes, which can promote the tumor initiation. Good study on oncogenes is helpful for understanding the cause of cancers. Experimental techniques in early time are quite popular in detecting oncogenes. However, their defects become more and more evident in recent years, such as high cost and long time. The newly proposed computational methods provide an alternative way to study oncogenes, which can provide useful clues for further investigations on candidate genes. Considering the limitations of some previous computational methods, such as lack of learning procedures and terming genes as individual subjects, a novel computational method was proposed in this study. The method adopted the features derived from multiple protein networks, viewing proteins in a system level. A classic machine learning algorithm, random forest, was applied on these features to capture the essential characteristic of oncogenes, thereby building the prediction model. All genes except validated oncogenes were ranked with a measurement yielded by the prediction model. Top genes were quite different from potential oncogenes discovered by previous methods, and they can be confirmed to become novel oncogenes. It was indicated that the newly identified genes can be essential supplements for previous results.

Increased RAB31 Expression in Cancer-Associated Fibroblasts Promotes Colon Cancer Progression Through HGF-MET Signaling

RAB family proteins participate in the dynamic regulation of cellular membrane compartments and are dysregulated in a variety of tumor types, which may alter the biological properties of cancer cells such as proliferation, migration, and invasion. In our previous study, we found that Ras-related protein Rab-31 (RAB31) expression was increased in late-stage colorectal cancer (CRC). The role of RAB31 has never been investigated in CRC. In this study, we found that expression of RAB31 in the tumor stroma but not cancer cells of colon cancer predicted poor survival. RAB31 can be detected in primary cancer-associated fibroblasts (CAFs) and paired normal fibroblasts. Conditioned medium (CM) from RAB31 overexpressing CAFs significantly promoted migration of colon cancer cell lines in vitro and in vivo. This process may be mediated by paracrine action of hepatocyte growth factor (HGF), which was increased in the CM of RAB31-overexpressing CAFs. Blockade of HGF/MET signaling by drug inhibition, knockdown of mesenchymal to epithelial transition factor (MET) in RKO, or antibody neutralization of HGF abolished migration of RKO cells mediated by RAB31 expression in CAFs. We propose that in colon cancer, increased RAB31 expression in CAFs may contribute to tumor progression by regulating the secretion of HGF in the tumor stroma.

Lasting and Sex-Dependent Impact of Maternal Immune Activation on Molecular Pathways of the Amygdala

The prolonged and sex-dependent impact of maternal immune activation (MIA) during gestation on the molecular pathways of the amygdala, a brain region that influences social, emotional, and other behaviors, is only partially understood. To address this gap, we investigated the effects of viral-elicited MIA during gestation on the amygdala transcriptome of pigs, a species of high molecular and developmental homology to humans. Gene expression levels were measured using RNA-Seq on the amygdala for 3-week-old female and male offspring from MIA and control groups. Among the 403 genes that exhibited significant MIA effect, a prevalence of differentially expressed genes annotated to the neuroactive ligand-receptor pathway, glutamatergic functions, neuropeptide systems, and cilium morphogenesis were uncovered. Genes in these categories included corticotropin-releasing hormone receptor 2, glutamate metabotropic receptor 4, glycoprotein hormones, alpha polypeptide, parathyroid hormone 1 receptor, vasointestinal peptide receptor 2, neurotensin, proenkephalin, and gastrin-releasing peptide. These categories and genes have been associated with the MIA-related human neurodevelopmental disorders, including schizophrenia and autism spectrum disorders. Gene network reconstruction highlighted differential vulnerability to MIA effects between sexes. Our results advance the understanding necessary for the development of multifactorial therapies targeting immune modulation and neurochemical dysfunction that can ameliorate the effects of MIA on offspring behavior later in life.

Crystal structures of human PAICS reveal substrate and product binding of an emerging cancer target

The bifunctional human enzyme phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccinocarboxamide synthetase (PAICS) catalyzes two essential steps in the de novo purine biosynthesis pathway. PAICS is overexpressed in many cancers and could be a promising target for the development of cancer therapeutics. Here, using gene knockdowns and clonogenic survival and cell viability assays, we demonstrate that PAICS is required for growth and survival of prostate cancer cells. PAICS catalyzes the carboxylation of aminoimidazole ribonucleotide (AIR) and the subsequent conversion of carboxyaminoimidazole ribonucleotide (CAIR) and l-aspartate to N-succinylcarboxamide-5-aminoimidazole ribonucleotide (SAICAR). Of note, we present the first structures of human octameric PAICS in complexes with native ligands. In particular, we report the structure of PAICS with CAIR bound in the active sites of both domains and SAICAR bound in one of the SAICAR synthetase domains. Moreover, we report the PAICS structure with SAICAR and an ATP analog occupying the SAICAR synthetase active site. These structures provide insight into substrate and product binding and the architecture of the active sites, disclosing important structural information for rational design of PAICS inhibitors as potential anticancer drugs.

Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets

Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein-protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools' user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.

Whole Blood Transcriptome Analysis for Lifelong Monitoring in Elite Sniffer Dogs Produced by Somatic Cell Nuclear Transfer

Reproductive cloning by somatic cell nuclear transfer (SCNT) is a valuable method to propagate service dogs with desirable traits because of higher selection rates in cloned dogs. However, incomplete reprogramming is a major barrier to SCNT, and the assessment of reprogramming is limited to preimplantation embryos and tissues from dead and/or adult tissue. Thus, lifelong monitoring in SCNT dogs can be useful to evaluate the SCNT service dogs for propagation. We applied microarray and qRT-PCR to profile of mRNA and miRNA in whole blood samples collected from four cloned dogs (S), three age-matched control dogs (A), and a donor dog (D). In the analysis of differentially expressed genes in S-A, A-D, and S-D pairs, most genomes were completely reprogrammed and rejuvenated in the cloned offspring. However, several RNAs were differentially expressed. Interestingly, the altered genes are associated with aging and senescence. Furthermore, we identified potential biomarkers such as mirR-223 (NFIB; CLIC4), miRN-494 (ARHGEF12), miR-106b (PPP1R3B; CC2D1A), miR-20a (CC2D1A; PPP1R3B), miR-30e (IGJ; HIRA), and miR-19a (TNRC6A) by miRNA-target mRNA pairing for monitoring rejuvenation, aging/senescence, and reprogramming in cloned dogs. The novel comparative transcriptomic information about SCNT and age-matched dogs can be used to assess the lifelong health of cloned dogs and to facilitate the selection of training animals with minimal invasive procedures.

High gene expression levels of VEGFA and CXCL8 in the peritumoral brain zone are associated with the recurrence of glioblastoma: A bioinformatics analysis

The present study aimed to identify differentially regulated genes between the peritumoral brain zone (PBZ) and tumor core (TC) of glioblastoma (GBM), to elucidate the underlying molecular mechanisms and provide a target for the treatment of tumors. The GSE13276 and GSE116520 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) for the PBZ and TC were obtained using the GEO2R tool. The bioinformatics and evolutionary genomics online tool Venn was used to identify common DEGs between the two datasets. The Database for Annotation, Visualization, and Integrated Discovery online tool was used to analyze enriched pathways of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The Search Tool for the Retrieval of Interacting Genes/Proteins online tool was used to construct a protein-protein interaction (PPI) network of DEGs. Hub genes were identified using Cytohubba, a plug-in for Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was utilized to perform survival analysis. In total, 75 DEGs, including 12 upregulated and 63 downregulated genes, were identified. In the GO term analysis, these DEGs were mainly enriched in ‘regulation of angiogenesis’ and ‘central nervous system development’. Furthermore, in the KEGG pathway analysis, the DEGs were mainly enriched in ‘bladder cancer’ and ‘endocytosis’. When filtering the results of the PPI network analysis using Cytohubba, a total of 10 hub genes, including proteolipid protein 1, myelin associated oligodendrocyte basic protein, contactin 2, myelin oligodendrocyte glycoprotein, myelin basic protein, myelin associated glycoprotein, SRY-box transcription factor 10, C-X-C motif chemokine ligand 8 (CXCL8), vascular endothelial growth factor A (VEGFA) and plasmolipin, were identified. These hub genes were further subjected to GO term and KEGG pathway analysis, and were revealed to be enriched in ‘central nervous system development’, ‘bladder cancer’ and ‘rheumatoid arthritis’. These hub genes were used to perform survival analysis using the GEPIA database, and it was determined that VEGFA and CXCL8 were significantly associated with a reduction in the overall survival of patients with GBM. In conclusion, the results suggest that the recurrence of GBM is associated with high gene expression levels VEGFA and CXCL8, and the development of the central nervous system.

A Novel DNA Methylation-Based Signature Can Predict the Responses of MGMT Promoter Unmethylated Glioblastomas to Temozolomide

Glioblastoma (GBM) is the most malignant glioma, with a median overall survival (OS) of 14–16 months. Temozolomide (TMZ) is the first-line chemotherapy drug for glioma, but whether TMZ should be withheld from patients with GBMs that lack O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is still under debate. DNA methylation profiling holds great promise for further stratifying the responses of MGMT promoter unmethylated GBMs to TMZ. In this study, we studied 147 TMZ-treated MGMT promoter unmethylated GBM, whose methylation information was obtained from the HumanMethylation27 (HM-27K) BeadChips (n = 107) and the HumanMethylation450 (HM-450K) BeadChips (n = 40) for training and validation, respectively. In the training set, we performed univariate Cox regression and identified that 3,565 CpGs were significantly associated with the OS of the TMZ-treated MGMT promoter unmethylated GBMs. Functional analysis indicated that the genes corresponding to these CpGs were enriched in the biological processes or pathways of mitochondrial translation, cell cycle, and DNA repair. Based on these CpGs, we developed a 31-CpGs methylation signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. In both training and validation datasets, the signature identified the TMZ-sensitive GBMs in the MGMT promoter unmethylated GBMs, and only the patients in the low-risk group appear to benefit from the TMZ treatment. Furthermore, these identified TMZ-sensitive MGMT promoter unmethylated GBMs have a similar OS when compared with the MGMT promoter methylated GBMs after TMZ treatment in both two datasets. Multivariate Cox regression demonstrated the independent prognostic value of the signature in TMZ-treated MGMT promoter unmethylated GBMs. Moreover, we also noticed that the hallmark of epithelial–mesenchymal transition, ECM related biological processes and pathways were highly enriched in the MGMT unmethylated GBMs with the high-risk score, indicating that enhanced ECM activities could be involved in the TMZ-resistance of GBM. In conclusion, our findings promote our understanding of the roles of DNA methylation in MGMT umethylated GBMs and offer a very promising TMZ-sensitivity predictive signature for these GBMs that could be tested prospectively.

Effect of RAB31 silencing on osteosarcoma cell proliferation and migration through the Hedgehog signaling pathway

Osteosarcoma (OS) is a prevalent cancer that plagues people worldwide. Identifying prognostic markers would be useful in treating human OS. In this study, we aimed to explore the functions of Ras-related protein Rab-31 (RAB31) in OS-cell proliferation, migration, and invasion as well as its roles in the Hedgehog signaling pathway for better understanding of the mechanism. To assess the detailed regulatory mechanism of RAB31 silencing on OS, both RT-qPCR and Western blot analysis were employed to evaluate the expressions of RAB31 as well as the Hedgehog signaling pathway-related genes. Besides, we also investigated the effects of silenced RAB31 both in vitro and in vivo. First, we found that in OS tissues, both mRNA and protein expressions of RAB31 and PCNA had a significant increase. Second, the Hedgehog signaling pathway was detected to play an integral role in OS progression. Finally, after transfection of RAB31-siRNA to reduce the expression of RAB31, the Hedgehog signaling pathway was suppressed, along with cell proliferation, invasion, and migration. Therefore, we conclude that RAB31 plays an important role in OS development and its silencing delays the OS progression via suppression of the Hedgehog signaling pathway.

Opioid-Induced Hyperalgesia Is Associated with Dysregulation of Circadian Rhythm and Adaptive Immune Pathways in the Mouse Trigeminal Ganglia and Nucleus Accumbens

The benefits of opioid-based treatments to mitigate chronic pain can be hindered by the side effects of opioid-induced hyperalgesia (OIH) that can lead to higher consumption and risk of addiction. The present study advances the understanding of the molecular mechanisms associated with OIH by comparing mice presenting OIH symptoms in response to chronic morphine exposure (OIH treatment) relative to control mice (CON treatment). Using RNA-Seq profiles, gene networks were inferred in the trigeminal ganglia (TG), a central nervous system region associated with pain signaling, and in the nucleus accumbens (NAc), a region associated with reward dependency. The biological process of nucleic acid processing was over-represented among the 122 genes that exhibited a region-dependent treatment effect. Within the 187 genes that exhibited a region-independent treatment effect, circadian rhythm processes were enriched among the genes over-expressed in OIH relative to CON mice. This enrichment was supported by the differential expression of the period circadian clock 2 and 3 genes (Per2 and Per3). Transcriptional regulators in the PAR bZip family that are influenced by the circadian clock and that modulate neurotransmission associated with pain and drug addiction were also over-expressed in OIH relative to CON mice. Also notable was the under-expression in OIH relative to CON mice of the Toll-like receptor, nuclear factor-kappa beta, and interferon gamma genes and enrichment of the adaptive immune processes. The results from the present study offer insights to advance the effective use of opioids for pain management while minimizing hyperalgesia.

Fstl1/DIP2A/MGMT signaling pathway plays important roles in temozolomide resistance in glioblastoma

Temozolomide was recognized as the first-line therapy for glioblastoma to prolong the survival of patients noticeably, while recent clinical studies found that some patients were not sensitive to temozolomide treatment. The possible mechanisms seemed to be methylguanine-DNA-methyltransferase (MGMT), mismatch repair, PARP, etc. And the abnormal expression of MGMT might be the most direct factor. In this study, we provide evidence that Fstl1 plays a vital role in temozolomide resistance by sequentially regulating DIP2A protein distribution, H3K9 acetylation (H3K9Ac), and MGMT transcription. As a multifunctional protein widely distributed in cells, DIP2A cooperates with the HDAC2-DMAP1 complex to enhance H3K9Ac deacetylation, prevent MGMT transcription, and increase temozolomide sensitivity. Fstl1, a glycoprotein highly expressed in glioblastoma, competitively binds DIP2A to block DIP2A nuclear translocation, so as to hinder DIP2A from binding the HDAC2-DMAP1 complex. The overexpression of Fstl1 promoted the expression of MGMT in association with increased promoter H3K9Ac. Upregulation of Fstl1 enhanced temozolomide resistance, whereas Fstl1 silencing obviously sensitized GBM cells to temozolomide both in vivo and in vitro. Moreover, DIP2A depletion abolished the effects of Fstl1 on MGMT expression and temozolomide resistance. These findings highlight an important role of Fstl1 in the regulation of temozolomide resistance by modulation of DIP2A/MGMT signaling.

Disruption of microglia histone acetylation and protein pathways in mice exhibiting inflammation-associated depression-like symptoms

BACKGROUND

Peripheral immune challenge can elicit microglia activation and depression-related symptoms. The balance of inflammatory signals in the tryptophan pathway can skew the activity of indoleamine-pyrrole 2,3 dioxygenase (IDO1) towards the metabolization of tryptophan into kynurenine (rather than serotonin), and towards neuroprotective or neurotoxic metabolites. The proteome changes that accompany inflammation-associated depression-related behaviors are incompletely understood.

METHODS

The changes in microglia protein abundance and post-translational modifications in wild type (WT) mice that exhibit depression-like symptoms after recovery from peripheral Bacille Calmette-Guerin (BCG) challenge were studied. This WT_BGG group was compared to mice that do not express depression-like symptoms after BCG challenge due to IDO1 deficiency by means of genetic knockout (BCG_KO group), and to WT Saline-treated (Sal) mice (WT_Sal group) using a mass spectrometry-based label-free approach.

RESULTS

The comparison of WT_BCG relative to WT_Sal and KO_BCG mice uncovered patterns of protein abundance and acetylation among the histone families that could influence microglia signaling and transcriptional rates. Members of the histone clusters 1, 2 and 3 families were less abundant in WT_BCG relative to WT_Sal whereas members in the H2A family exhibited the opposite pattern. Irrespective of family, the majority of the histones were less abundant in WT_BCG relative to KO_BCG microglia. Homeostatic mechanisms may temper the potentially toxic effects of high histone levels after BCG challenge to levels lower than Sal. Histone acetylation was highest in WT_BCG and the similar levels observed in WT_Sal and KO_BCG. This result suggest that histone acetylation levels are similar between IDO1 deficient mice after immune challenge and unchallenged WT mice. The over-abundance of tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation proteins (14-3-3 series) in WT_BCG relative to KO_BCG is particularly interesting because these proteins activate another rate-limiting enzyme in the tryptophan pathway. The over-representation of alcoholism and systemic lupus erythematosus pathways among the proteins exhibiting differential abundance between the groups suggest that these disorders share microglia activation pathways with BCG challenge. The over-representation of phagosome pathway among proteins differentially abundant between WT_BCG and KO_BCG microglia suggest an association between IDO1 deficiency and phagocytosis. Likewise, the over-representation of the gap junction pathway among the differentially abundant proteins between KO_BCG and WT_Sal suggest a multifactorial effect of BCG and IDO1 deficiency on cell communication.

CONCLUSIONS

The present study of histone acetylation and differential protein abundance furthers the understanding of the long lasting effects of peripheral immune challenges. Our findings offer insights into target proteins and mechanisms that provide clues for therapies to ameliorate inflammation-associated depression-related behaviors.

GeneExpressScore Signature: a robust prognostic and predictive classifier in gastric cancer

Although several prognostic signatures have been developed for gastric cancer (GC), the utility of these tools is limited in clinical practice due to lack of validation with large and multiple independent cohorts, or lack of a statistical test to determine the robustness of the predictive models. Here, a prognostic signature was constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model and a training dataset with 300 GC patients. The signature was verified in three independent datasets with a total of 658 tumors across multiplatforms. A nomogram based on the signature was built to predict disease-free survival (DFS). Based on the LASSO model, we created a GeneExpressScore signature (GES_GC ) classifier comprised of eight mRNA. With this classifier patients could be divided into two subgroups with distinctive prognoses [hazard ratio (HR) = 4.00, 95% confidence interval (CI) = 2.41-6.66, P < 0.0001]. The prognostic value was consistently validated in three independent datasets. Interestingly, the high-GES_GC group was associated with invasion, microsatellite stable/epithelial-mesenchymal transition (MSS/EMT), and genomically stable (GS) subtypes. The predictive accuracy of GES_GC also outperformed five previously published signatures. Finally, a well-performed nomogram integrating the GES_GC and four clinicopathological factors was generated to predict 3- and 5-year DFS. In summary, we describe an eight-mRNA-based signature, GES_GC , as a predictive model for disease progression in GC. The robustness of this signature was validated across patient series, populations, and multiplatform datasets.

Knockdown of PAICS inhibits malignant proliferation of human breast cancer cell lines

BACKGROUND

Phosphoribosylaminoimidazole carboxylase, phosphoribosylaminoimidazole succinocarboxamide synthetase (PAICS), an enzyme required for de novo purine biosynthesis, is associated with and involved in tumorigenesis. This study aimed to evaluate the role of PAICS in human breast cancer, which remains the most frequently diagnosed cancer and the leading cause of cancer-related death among women in less developed countries.

RESULTS

Lentivirus-based short hairpin RNA targeting PAICS specifically depleted its endogenous expression in ZR-75-30 and MDA-MB-231 breast cancer cells. Depletion of PAICS led to a significant decrease in cell viability and proliferation. To ascertain the mechanisms through which PAICS modulates cell proliferation, flow cytometry was performed, and it was confirmed that G1-S transition was blocked in ZR-75-30 cells through PAICS knockdown. This might have occurred partly through the suppression of Cyclin E and the upregulation of Cyclin D1, P21, and CDK4. Moreover, PAICS knockdown obviously promoted cell apoptosis in ZR-75-30 cells through the activation of PARP and caspase 3 and downregulation of Bcl-2 and Bcl-xl expression in ZR-75-30 cells.

CONCLUSIONS

These findings demonstrate that PAICS plays an essential role in breast cancer proliferation in vitro, which provides a new opportunity for discovering and identifying novel effective treatment strategies.

Bayesian variable selection with graphical structure learning: Applications in integrative genomics

Significant advances in biotechnology have allowed for simultaneous measurement of molecular data across multiple genomic, epigenomic and transcriptomic levels from a single tumor/patient sample. This has motivated systematic data-driven approaches to integrate multi-dimensional structured datasets, since cancer development and progression is driven by numerous co-ordinated molecular alterations and the interactions between them. We propose a novel multi-scale Bayesian approach that combines integrative graphical structure learning from multiple sources of data with a variable selection framework—to determine the key genomic drivers of cancer progression. The integrative structure learning is first accomplished through novel joint graphical models for heterogeneous (mixed scale) data, allowing for flexible and interpretable incorporation of prior existing knowledge. This subsequently informs a variable selection step to identify groups of co-ordinated molecular features within and across platforms associated with clinical outcomes of cancer progression, while according appropriate adjustments for multicollinearity and multiplicities. We evaluate our methods through rigorous simulations to establish superiority over existing methods that do not take the network and/or prior information into account. Our methods are motivated by and applied to a glioblastoma multiforme (GBM) dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, copy number and methylation data. We find a high concordance between our selected prognostic gene network modules with known associations with GBM. In addition, our model discovers several novel cross-platform network interactions (both cis and trans acting) between gene expression, copy number variation associated gene dosing and epigenetic regulation through promoter methylation, some with known implications in the etiology of GBM. Our framework provides a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers.

Identification and functional analysis of SOX10 phosphorylation sites in melanoma

The transcription factor SOX10 plays an important role in vertebrate neural crest development, including the establishment and maintenance of the melanocyte lineage. SOX10 is also highly expressed in melanoma tumors, and SOX10 expression increases with tumor progression. The suppression of SOX10 in melanoma cells activates TGF-β signaling and can promote resistance to BRAF and MEK inhibitors. Since resistance to BRAF/MEK inhibitors is seen in the majority of melanoma patients, there is an immediate need to assess the underlying biology that mediates resistance and to identify new targets for combinatorial therapeutic approaches. Previously, we demonstrated that SOX10 protein is required for tumor initiation, maintenance and survival. Here, we present data that support phosphorylation as a mechanism employed by melanoma cells to tightly regulate SOX10 expression. Mass spectrometry identified eight phosphorylation sites contained within SOX10, three of which (S24, S45 and T240) were selected for further analysis based on their location within predicted MAPK/CDK binding motifs. SOX10 mutations were generated at these phosphorylation sites to assess their impact on SOX10 protein function in melanoma cells, including transcriptional activation on target promoters, subcellular localization, and stability. These data further our understanding of SOX10 protein regulation and provide critical information for identification of molecular pathways that modulate SOX10 protein levels in melanoma, with the ultimate goal of discovering novel targets for more effective combinatorial therapeutic approaches for melanoma patients.

Novel miRNA-mRNA interactions conserved in essential cancer pathways

Cancer is a complex disease in which unrestrained cell proliferation results in tumour development. Extensive research into the molecular mechanisms underlying tumorigenesis has led to the characterization of oncogenes and tumour suppressors that are key elements in cancer growth and progression, as well as that of other important elements like microRNAs. These genes and miRNAs appear to be constitutively deregulated in cancer. To identify signatures of miRNA-mRNA interactions potentially conserved in essential cancer pathways, we have conducted an integrative analysis of transcriptomic data, also taking into account methylation and copy number alterations. We analysed 18,605 raw transcriptome samples from The Cancer Genome Atlas covering 15 of the most common types of human tumours. From this global transcriptome study, we recovered known cancer-associated miRNA-targets and importantly, we identified new potential targets from miRNA families, also analysing the phenotypic outcomes of these genes/mRNAs in terms of survival. Further analyses could lead to novel approaches in cancer therapy.

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors.

PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma

Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue (n = 70) and normal brain tissue (n = 19) found PPIC, EMP3 and CHI3L1 were up-regulated in glioma tissue. Survival value validation showed that the three genes correlated with patient survival by Kaplan-Meir analysis, including grades, age and therapy.

Prioritizing cancer-related microRNAs by integrating microRNA and mRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs regulating the expression of target genes, and they are involved in cancer initiation and progression. Even though many cancer-related miRNAs were identified, their functional impact may vary, depending on their effects on the regulation of other miRNAs and genes. In this study, we propose a novel method for the prioritization of candidate cancer-related miRNAs that may affect the expression of other miRNAs and genes across the entire biological network. For this, we propose three important features: the average expression of a miRNA in multiple cancer samples, the average of the absolute correlation values between the expression of a miRNA and expression of all genes, and the number of predicted miRNA target genes. These three features were integrated using order statistics. By applying the proposed approach to four cancer types, glioblastoma, ovarian cancer, prostate cancer, and breast cancer, we prioritized candidate cancer-related miRNAs and determined their functional roles in cancer-related pathways. The proposed approach can be used to identify miRNAs that play crucial roles in driving cancer development, and the elucidation of novel potential therapeutic targets for cancer treatment.

A new correlation clustering method for cancer mutation analysis

MOTIVATION

Cancer genomes exhibit a large number of different alterations that affect many genes in a diverse manner. An improved understanding of the generative mechanisms behind the mutation rules and their influence on gene community behavior is of great importance for the study of cancer.

RESULTS

To expand our capability to analyze combinatorial patterns of cancer alterations, we developed a rigorous methodology for cancer mutation pattern discovery based on a new, constrained form of correlation clustering. Our new algorithm, named C³ (Cancer Correlation Clustering), leverages mutual exclusivity of mutations, patient coverage and driver network concentration principles. To test C³, we performed a detailed analysis on TCGA breast cancer and glioblastoma data and showed that our algorithm outperforms the state-of-the-art CoMEt method in terms of discovering mutually exclusive gene modules and identifying biologically relevant driver genes. The proposed agnostic clustering method represents a unique tool for efficient and reliable identification of mutation patterns and driver pathways in large-scale cancer genomics studies, and it may also be used for other clustering problems on biological graphs.

AVAILABILITY AND IMPLEMENTATION

The source code for the C³ method can be found at https://github.com/jackhou2/C3 CONTACTS: jianma@cs.cmu.edu or milenkov@illinois.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Global analysis of transcriptome in dorsal root ganglia following peripheral nerve injury in rats

Peripheral nervous system has intrinsic regeneration ability after injury, accompanied with the coordination of numerous cells, molecules and signaling pathways. These post-injury biological changes are complex with insufficient understanding. Thus, to obtain a global perspective of changes following nerve injury and to elucidate the mechanisms underlying nerve regeneration are of great importance. By RNA sequencing, we detected transcriptional changes in dorsal root ganglia (DRG) neurons at 0 h, 3 h, 9 h, 1 d, 4 d and 7 d following sciatic nerve crush injury in rats. Differentially expressed genes were then selected and classified into major clusters according to their expression patterns. Cluster 2 (with genes high expressed before 9 h and then down expressed) and cluster 6 (combination of cluster 4 and 5 with genes low expressed before 1 d and then up expressed) were underwent GO annotation and KEGG pathway analysis. Gene act networks were then constructed for these two clusters and the expression of pivotal genes was validated by quantitative real-time PCR. This study provided valuable information regarding the transcriptome changes in DRG neurons following nerve injury, identified potential genes that could be used for improving axon regeneration after nerve injury, and facilitated to elucidate the biological process and molecular mechanisms underlying peripheral nerve injury.

4G/5G and A-844G Polymorphisms of Plasminogen Activator Inhibitor-1 Associated with Glioblastoma in Iran--a Case-Control Study

BACKGROUND

Glioblastoma is a highly aggressive and malignant brain tumor. Risk factors are largely unknown however, although several biomarkers have been identified which may support development, angiogenesis and invasion of tumor cells. One of these biomarkers is PAI-1. 4G/5G and A-844G are two common polymorphisms in the gene promotor of PAI 1 that may be related to high transcription and expression of this gene. Studies have shown that the prevalence of the 4G and 844G allele is significantly higher in patients with some cancers and genetic disorders.

MATERIALS AND METHODS

We here assessed the association of 4G/5G and A-844G polymorphisms with glioblastoma cancer risk in Iranians in a case-control study. All 71 patients with clinically confirmed and 140 volunteers with no history and symptoms of glioblastoma as control group were screened for 4G/5G and A-844G polymorphisms of PAI-1, using ARMS-PCR. Genotype and allele frequencies of case and control groups were analyzed using the DeFinetti program.

RESULTS

Our results showed significant associations between 4G/5G (p=0.01824) and A-844G (p=0.02012) polymorphisms of the PAI-1 gene with glioblastoma cancer risk in our Iranian population.

CONCLUSIONS

The results of this study supporting an association of the PAI-1 4G/5G (p=0.01824) and A-844G (p=0.02012) polymorphisms with increasing glioblastoma cancer risk in Iranian patients.

Copy Number Profiling of Brazilian Astrocytomas

Copy number alterations (CNA) are one of the driving mechanisms of glioma tumorigenesis, and are currently used as important biomarkers in the routine setting. Therefore, we performed CNA profiling of 65 astrocytomas of distinct malignant grades (WHO grade I–IV) of Brazilian origin, using array-CGH and microsatellite instability analysis (MSI), and investigated their correlation with TERT and IDH1 mutational status and clinico-pathological features. Furthermore, in silico analysis using the Oncomine database was performed to validate our findings and extend the findings to gene expression level. We found that the number of genomic alterations increases in accordance with glioma grade. In glioblastomas (GBM), the most common alterations were gene amplifications (PDGFRA, KIT, KDR, EGFR, and MET) and deletions (CDKN2A and PTEN). Log-rank analysis correlated EGFR amplification and/or chr7 gain with better survival of the patients. MSI was observed in 11% of GBMs. A total of 69% of GBMs presented TERT mutation, whereas IDH1 mutation was most frequent in diffuse (85.7%) and anaplastic (100%) astrocytomas. The combination of 1p19q deletion and TERT and IDH1 mutational status separated tumor groups that showed distinct age of diagnosis and outcome. In silico validation pointed to less explored genes that may be worthy of future investigation, such as CDK2, DMRTA1, and MTAP. Herein, using an extensive integrated analysis, we indicated potentially important genes, not extensively studied in gliomas, that could be further explored to assess their biological and clinical impact in astrocytomas.

Differential Transcriptome Networks between IDO1-Knockout and Wild-Type Mice in Brain Microglia and Macrophages

Microglia in the brain and macrophages in peripheral organs are cell types responsible for immune response to challenges. Indoleamine 2,3-dioxygenase 1 (IDO1) is an immunomodulatory enzyme of the tryptophan pathway that is expressed in the brain. The higher activity of IDO1 in response to immune challenge has been implicated in behavioral disorders. The impact of IDO1 depletion on the microglia transcriptome has not been studied. An investigation of the transcript networks in the brain microglia from IDO1-knockout (IDO1-KO) mice was undertaken, relative to peripheral macrophages and to wild-type (WT) mice under unchallenged conditions. Over 105 transcript isoforms were differentially expressed between WT and IDO1-KO within cell type. Within microglia, Saa3 and Irg1 were over-expressed in IDO1-KO relative to WT. Within macrophages, Csf3 and Sele were over-expressed in IDO1-KO relative to WT. Among the genes differentially expressed between strains, enriched biological processes included ion homeostasis and ensheathment of neurons within microglia, and cytokine and chemokine expression within macrophages. Over 11,110 transcript isoforms were differentially expressed between microglia and macrophages and of these, over 10,800 transcripts overlapped between strains. Enriched biological processes among the genes over- and under-expressed in microglia relative to macrophages included cell adhesion and apoptosis, respectively. Detected only in microglia or macrophages were 421 and 43 transcript isoforms, respectively. Alternative splicing between cell types based on differential transcript isoform abundance was detected in 210 genes including Phf11d, H2afy, and Abr. Across strains, networks depicted a predominance of genes under-expressed in microglia relative to macrophages that may be a precursor for the different response of both cell types to challenges. The detected transcriptome differences enhance the understanding of the role of IDO1 in the microglia transcriptome under unchallenged conditions.

Naringin suppresses the development of glioblastoma by inhibiting FAK activity

As the most common and lethal primary malignant brain cancer, glioblastoma is hard to timely diagnose and sensitive therapeutic monitoring. It is essential to develop new and effective drugs for glioblastoma multiform. Naringin belongs to citrus flavonoids and was found to display strong anti-inflammatory, antioxidant and antitumor activities. In this report, we found that naringin can specifically inhibit the kinase activity of FAK and suppress the FAK^p-Try397and its downstream pathway in glioblastoma cells. Our study showed out that naringin can inhibit cell proliferation by inhibiting FAK/cyclin D1 pathway, promote cell apoptosis through influencing FAK/bads pathway, at the same time, it can also inhibit cell invasion and metastasis by inhibiting the FAK/mmps pathway. All these showed that naringin exerts the anti-tumor effects in U87 MG by inhibiting the kinase activity of FAK.

High CHI3L1 expression is associated with glioma patient survival

Background

Survival of glioma patients with the same tumor histology and grade can vary significantly, and some low-grade gliomas transform to a more malignant phenotype. There is a need of molecular signatures, which are better predictors of the patient diagnosis, outcome of treatment, and prognosis than the diagnosis provided by histopathology. We propose CHI3L1 mRNA expression as a prognostic biomarker for patients with glioma.

Methods

We measured CHI3L1 expression with quantitative real time-polymerase chain reaction (qRT-PCR) in the cohort of 98 patients with different grade glioma: 10 grade I pylocytic astrocytomas, 30 grade II diffuse astrocytomas, 20 grade III anaplastic astrocytomas, and 38 grade IV astrocytomas (glioblastomas). Statistical analyses were conducted to investigate the association between CHI3L1 mRNA expression levels and patient clinical variables.

Results

We demonstrated that mRNA expression of CHI3L1 was evidently higher in glioblastoma than in lower grade glioma tissues. We evaluated correlations between CHI3L1 expression, clinicopathological characteristics, and the outcomes of the patients. Patients with high CHI3L1 expression had a shorter overall survival (p < 0.001).

Conclusions

Findings presented in our study showed that increased mRNA level of CHI3L1 could be associated with the progression of astrocytoma and poor patient survival not only for glioblastoma, but for lower grade astrocytoma tumors as well. Further investigation will be required to evaluate CHI3L1 value as a molecular marker for astrocytoma prognoses and for novel treatment strategies against all grade astrocytomas.

Microglia Transcriptome Changes in a Model of Depressive Behavior after Immune Challenge

Depression symptoms following immune response to a challenge have been reported after the recovery from sickness. A RNA-Seq study of the dysregulation of the microglia transcriptome in a model of inflammation-associated depressive behavior was undertaken. The transcriptome of microglia from mice at day 7 after Bacille Calmette Guérin (BCG) challenge was compared to that from unchallenged Control mice and to the transcriptome from peripheral macrophages from the same mice. Among the 562 and 3,851 genes differentially expressed between BCG-challenged and Control mice in microglia and macrophages respectively, 353 genes overlapped between these cells types. Among the most differentially expressed genes in the microglia, serum amyloid A3 (Saa3) and cell adhesion molecule 3 (Cadm3) were over-expressed and coiled-coil domain containing 162 (Ccdc162) and titin-cap (Tcap) were under-expressed in BCG-challenged relative to Control. Many of the differentially expressed genes between BCG-challenged and Control mice were associated with neurological disorders encompassing depression symptoms. Across cell types, S100 calcium binding protein A9 (S100A9), interleukin 1 beta (Il1b) and kynurenine 3-monooxygenase (Kmo) were differentially expressed between challenged and control mice. Immune response, chemotaxis, and chemokine activity were among the functional categories enriched by the differentially expressed genes. Functional categories enriched among the 9,117 genes differentially expressed between cell types included leukocyte regulation and activation, chemokine and cytokine activities, MAP kinase activity, and apoptosis. More than 200 genes exhibited alternative splicing events between cell types including WNK lysine deficient protein kinase 1 (Wnk1) and microtubule-actin crosslinking factor 1(Macf1). Network visualization revealed the capability of microglia to exhibit transcriptome dysregulation in response to immune challenge still after resolution of sickness symptoms, albeit lower than that observed in macrophages. The persistent transcriptome dysregulation in the microglia shared patterns with neurological disorders indicating that the associated persistent depressive symptoms share a common transcriptome basis.

The Critical Role of Rab31 in Cell Proliferation and Apoptosis in Cancer Progression

Rab31, a member of the Ras superfamily, is reported to play a role in tumor development and progression. However, the detailed role of Rab31 in proliferation and apoptosis of cancer cells is still unclear. Here, we used different cell lines, such as glioblastoma, and cervical cancer, to investigate the role of Rab31 in cancer progression. We found that Rab31 promotes U87 and SiHa cell proliferation via activation of G1/S checkpoint transitions, accompanied with an increase of cyclin D1, cyclin A, and cyclin B1. Meanwhile, Rab31 inhibits U87 and SiHa cell apoptosis, and decreased the BAX and PIG3 expression, but enhanced BCL2 expression. In addition, Rab31 induces N-cadherin, Vimentin, and Snail expression, and inhibits E-cadherin expression to regulate proliferation and migration. Besides, we observed that ERK1/2 and PI3k/AKT pathways are required for Rab31-induced cell proliferation and migration. In vivo, the knockdown of Rab31 suppresses tumor mass growth. In conclusion, our data highlight the crucial role of Rab31 in cancer progression, proliferation, and apoptosis, and indicates that Rab31 may be a useful and effective target for the clinical therapy of most cancers.

Rab31 promoted hepatocellular carcinoma (HCC) progression via inhibition of cell apoptosis induced by PI3K/AKT/Bcl-2/BAX pathway

Rab31 belongs to the Ras superfamily of small GTP-binding proteins, which has been found to regulate the vesicle transport from the Golgi apparatus to early and late endosomes. The investigation here detected the expression of Rab31 in 96 patients with hepatocellular carcinoma (HCC) and tried to identify its significance on outcome of HCCs after liver resection. By immunohistochemistry staining, it was found that Rab31 expression in HCC tissues was remarkably higher than that in adjacent liver tissues. Aberrant Rab31 overexpression in HCC tissues was identified to be associated with worse prognosis after liver resection. Univariate analysis showed that advanced tumor-nodes-metastasis (TNM) staging of HCC, intrahepatic metastases, portal vein invasion, and higher Rab31 were the predictive factors of poor prognosis. Multivariate analysis demonstrated that intrahepatic metastases and higher Rab31 were the independent prognostic factors. Furthermore, forced expression of Rab31 in Huh7 cells was found to promote cell growth via upregulation of Bcl-2/BAX ratio induced by PI3K/AKT. Correspondingly, silencing Rab31 induced cell apoptosis and in turn suppressed the growth capacity of MHCC97 cells in vitro. Taken together, this study provides the evidence of Rab31 overexpression in HCC, and Rab31 is potentially used as a novel biomarker of poor prognosis in patients with HCC. PI3K/AKT/Bcl-2/BAX axis was involved in Rab31-promoting HCC progression.