G-protein gamma subunit GNG11 strongly regulates cellular senescence

PI3K/AKT/mTOR pathway and its related molecules participate in PROK1 silence-induced anti-tumor effects on pancreatic cancer

The PI3K/AKT/mTOR (phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin) pathway can be initiated by PROK1 (prokineticin 1), but its effect and mechanism of action in pancreatic carcinoma (PC) are not fully understood. In this study, we elucidated the roles of PROK1 and its related molecules in PC in vivo. PANC-1 cells with PROK1 knockdown were injected into BALB/c nude mice. The growth and weight of the tumor were monitored and measured, which was followed by TUNEL (terminal deoxynucleotidyl transferase biotin-dUTP nick end labeling), immunohistochemical staining, and hematoxylin and eosin staining. The key proteins related to proliferation, apoptosis, and the PI3K/AKT/mTOR pathway were determined by Western blotting. We also used public databases to identify the molecules related to PROK1. The reduction of PROK1 inhibited angiopoiesis and promoted apoptosis in vivo. PCNA-1, cyclin D1, and Bcl-2 decreased considerably, while Bax and cleaved caspase-3 increased significantly after PROK1 inhibition. The PI3K/AKT/mTOR signal inhibition was also closely associated with PROK1 knockdown. The possible related molecules of PROK1, such as von Willebrand factor, were screened and considered to be involved in the aberrant activation of PI3K/AKT. In conclusion, PROK1 knockdown significantly prevented tumor growth and promoted apoptosis of human PC cells in vivo, where the PI3K/AKT/mTOR pathway was probably inhibited. Therefore, PROK1, along with its related molecules, might be important targets for PC therapy.

Construction and experimental validation of a B cell senescence-related gene signature to evaluate prognosis and immunotherapeutic sensitivity in bladder cancer

Senescent B cells exhibit reduced antibody production and enhanced proinflammatory cytokine and chemokine secretion, exerting non-negligible functions in antitumor immunity. This study aims to clarify the prognosis value of B cell senescence-related genes in bladder cancer (BLCA). Twelve B cell senescence-related genes were identified based on previous studies and the single-cell RNA sequencing of a BLCA sample from Gene Expression Omnibus (GEO). The Cancer Genome Atlas BLCA cohort was used as the training dataset. Three cohorts from GEO, 35 clinical samples from the local hospital, and in vitro cell experiments were used for validation. The unsupervised clustering based on the 12 genes was associated with the prognosis and the tumor immunity. Through least absolute shrinkage and selection operator regression and random forest algorithm, G protein subunit gamma 11 (GNG11) and inhibitor of DNA binding 1 (ID1) of the 12 genes were determined as significant prognosis predictors and then included in the multivariate Cox regression model. The model was a reliable and robust prognosis biomarker across multiple large-scale cohorts (pooled HR = 1.76, 95% CI = 1.41-2.20). The tight association between the model and BLCA malignant degree was demonstrated in the local cohort (P < 0.01). The model could also predict the immunotherapeutic sensitivity, which was confirmed by the tumor immune dysfunction and exclusion algorithm (P < 0.0001) and IMvigor210 cohort (P < 0.0001). At last, in vitro cell experiments in IM-9 and GM12878 B cells indicated that GNG11 and ID1 were involved in the cellular aging process. Collectively, a B cell senescence-related gene signature was constructed to evaluate the prognosis and immunotherapeutic response in BLCA, providing novel insights into the biological mechanisms.

Histologic and Molecular Patterns in Responders and Non-responders With Chronic-Active Antibody-Mediated Rejection in Kidney Transplants

Introduction

There is no proven therapy for chronic-active antibody-mediated rejection (caABMR), the major cause of late kidney allograft failure. Histological and molecular patterns associated with possible therapy responsiveness are not known.

Methods

Based on rigorous selection criteria this single center, retrospective study identified 16 out of 1027 consecutive kidney transplant biopsies taken between 2008 and 2016 with pure, unquestionable caABMR, without other pathologic features. The change in estimated GFR pre- and post-biopsy/treatment were utilized to differentiate subjects into responders and non-responders. Gene sets reflecting active immune processes of caABMR were defined a priori, including endothelial, inflammatory, cellular, interferon gamma (IFNg) and calcineurin inhibitor (CNI) related-genes based on the literature. Transcript measurements were performed in RNA extracted from stored, formalin-fixed, paraffin-embedded (FFPE) samples using NanoString™ technology. Histology and gene expression patterns of responders and non-responders were compared.

Results

A reductionist approach applying very tight criteria to identify caABMR and treatment response excluded the vast majority of clinical ABMR cases. Only 16 out of 139 cases with a written diagnosis of chronic rejection fulfilled the caABMR criteria. Histological associations with therapy response included a lower peritubular capillaritis score (p = 0.028) along with less glomerulitis. In contrast, no single gene discriminated responders from non-responders. Activated genes associated with NK cells and endothelial cells suggested lack of treatment response.

Conclusion

In caABMR active microvascular injury, in particular peritubular capillaritis, differentiates treatment responders from non-responders. Transcriptome changes in NK cell and endothelial cell associated genes may further help to identify treatment response. Future prospective studies will be needed which include more subjects, who receive standardized treatment protocols to identify biomarkers for treatment response.

Clinical Trial Registration

[ClinicalTrials.gov], identifier [NCT03430414].

Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients

BACKGROUND

High-grade serous ovarian cancer (HGSOC) has poor survival rates due to a combination of diagnosis at advanced stage and disease recurrence as a result of chemotherapy resistance. In BRCA1 (Breast Cancer gene 1) - or BRCA2-wild type (BRCAwt) HGSOC patients, resistance and progressive disease occur earlier and more often than in mutated BRCA. Identification of biomarkers helpful in predicting response to first-line chemotherapy is a challenge to improve BRCAwt HGSOC management.

METHODS

To identify a gene signature that can predict response to first-line chemotherapy, pre-treatment tumor biopsies from a restricted cohort of BRCAwt HGSOC patients were profiled by RNA sequencing (RNA-Seq) technology. Patients were sub-grouped according to platinum-free interval (PFI), into sensitive (PFI > 12 months) and resistant (PFI < 6 months). The gene panel identified by RNA-seq analysis was then tested by high-throughput quantitative real-time PCR (HT RT-qPCR) in a validation cohort, and statistical/bioinformatic methods were used to identify eligible markers and to explore the relevant pathway/gene network enrichments of the identified gene set. Finally, a panel of primary HGSOC cell lines was exploited to uncover cell-autonomous mechanisms of resistance.

RESULTS

RNA-seq identified a 42-gene panel discriminating sensitive and resistant BRCAwt HGSOC patients and pathway analysis pointed to the immune system as a possible driver of chemotherapy response. From the extended cohort analysis of the 42 DEGs (differentially expressed genes), a statistical approach combined with the random forest classifier model generated a ten-gene signature predictive of response to first-line chemotherapy. The ten-gene signature included: CKB (Creatine kinase B), CTNNBL1 (Catenin, beta like 1), GNG11 (G protein subunit gamma 11), IGFBP7 (Insulin-like growth factor-binding protein 7), PLCG2 (Phospholipase C, gamma 2), RNF24 (Ring finger protein 24), SLC15A3 (Solute carrier family 15 member 3), TSPAN31 (Tetraspanin 31), TTI1 (TELO2 interacting protein 1) and UQCC1 (Ubiquinol-cytochrome c reductase complex assembly factor). Cytotoxicity assays, combined with gene-expression analysis in primary HGSOC cell lines, allowed to define CTNNBL1, RNF24, and TTI1 as cell-autonomous contributors to tumor resistance.

CONCLUSIONS

Using machine-learning techniques we have identified a gene signature that could predict response to first-line chemotherapy in BRCAwt HGSOC patients, providing a useful tool towards personalized treatment modalities.

Gene-Level Germline Contributions to Clinical Risk of Recurrence Scores in Black and White Patients with Breast Cancer

Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. SIGNIFICANCE: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.

N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus

OBJECTIVE

The objective of this study was to reveal the potential crosstalk between immune infiltration and N⁶- methyladenosine (m⁶A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.

METHODS

We analyzed imbalanced immune infiltration and differentially expressed m⁶A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and validation sets, respectively.

RESULTS

Infiltration of monocytes was higher in GDM placentas than in control samples, while the infiltration of macrophages (M1 and M2) in GDM placentas was lower than in controls. A total of 14 DMRGs were strongly associated with monocyte infiltration, seven of which were significant in distinguishing patients with GDM from normal controls. These genes were CD81, CFH, FABP5, GBP1, GNG11, IL1RL1, and SLAMF6. The calibration curve, decision curve, clinical impact curve, and receiver operating characteristic curve showed that the nomogram recognized GDM with high accuracy in both the training and validation sets.

CONCLUSIONS

Our results provide clues that crosstalk between m⁶A modification and immune infiltration may have implications in terms of novel biomarkers and therapeutic targets for GDM.

Transmembrane signaling molecules play a key role in the pathogenesis of IgA nephropathy: a weighted gene co-expression network analysis study

BACKGROUND

Immunoglobulin A nephropathy (IgAN) is one of the most common primary glomerulonephritis and a serious health concern worldwide; though still the underlying molecular mechanisms of IgAN are yet to be known and there is no efficient treatment for this disease. The main goal of this study was to explore the IgAN underlying pathogenic pathways, plus identifying the disease correlated modules and genes using the weighted gene co-expression network analysis (WGCNA) algorithm.

RESULTS

GSE104948 dataset (the expression data from glomerular tissue of IgAN patients) was analyzed and the identified differentially expressed genes (DEGs) were introduced to the WGCNA algorithm for building co-expression modules. Genes were classified into six co-expression modules. Genes of the disease's most correlated module were mainly enriched in the immune system, cell-cell communication and transmembrane cell signaling pathways. The PPI network was constructed by genes in all the modules and after hub-gene identification and validation steps, 11 genes, mostly transmembrane proteins (CD44, TLR1, TLR2, GNG11, CSF1R, TYROBP, ITGB2, PECAM1), as well as DNMT1, CYBB and PSMB9 were identified as potentially key players in the pathogenesis of IgAN. In the constructed regulatory network, hsa-miR-129-2-3p, hsa-miR-34a-5p and hsa-miR-27a-3p, as well as STAT3 were spotted as top molecules orchestrating the regulation of the hub genes.

CONCLUSIONS

The excavated hub genes from the hearts of co-expressed modules and the PPI network were mostly transmembrane signaling molecules. These genes and their upstream regulators could deepen our understanding of IgAN and be considered as potential targets for hindering its progression.

Subtype-dependent regulation of Gβγ signalling

G protein-coupled receptors (GPCRs) transmit information to the cell interior by transducing external signals to heterotrimeric G protein subunits, Gα and Gβγ subunits, localized on the inner leaflet of the plasma membrane. Though the initial focus was mainly on Gα-mediated events, Gβγ subunits were later identified as major contributors to GPCR-G protein signalling. A broad functional array of Gβγ signalling has recently been attributed to Gβ and Gγ subtype diversity, comprising 5 Gβ and 12 Gγ subtypes, respectively. In addition to displaying selectivity towards each other to form the Gβγ dimer, numerous studies have identified preferences of distinct Gβγ combinations for specific GPCRs, Gα subtypes and effector molecules. Importantly, Gβ and Gγ subtype-dependent regulation of downstream effectors, representing a diverse range of signalling pathways and physiological functions have been found. Here, we review the literature on the repercussions of Gβ and Gγ subtype diversity on direct and indirect regulation of GPCR/G protein signalling events and their physiological outcomes. Our discussion additionally provides perspective in understanding the intricacies underlying molecular regulation of subtype-specific roles of Gβγ signalling and associated diseases.

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

GOLM1 predicts poor prognosis of patients with NSCLC and is associated with the proliferation and chemo-sensitivity of cisplatin in NSCLC cells: bioinformatics analysis and laboratory validation

Lung cancer is one of the deadliest malignant tumors with non-small cell lung cancer (NSCLC) being the most prevalent type. Patients with NSCLC usually were diagnosed at the advance clinical stages, and these patients often had high rate of tumor-recurrence, thus leading to poor prognosis. Yet, the molecular mechanisms underlying NSCLC progression and recurrence are largely unknown. This study aimed to identify potential hub genes associated with the pathophysiology of NSCLC by bioinformatics analysis and laboratory validation. The GSE51852, GSE52248 and GSE75037 datasets were downloaded from the Gene Expression Omnibus database. The overlapping differentially expressed genes (DEGs) were analyzed by GEO2R tool. Gene Ontology (GO) and KEGG pathway enrichment analysis were performed on these overlapping DEGs. The protein-protein interaction network was constructed to identify hub genes from DEGs. The expression and survival analysis of these hub genes were performed by using the integrated bioinformatics tools. Finally, the effects of GOLM1 on the proliferation and chemo-sensitivity of NSCLC cells were determined by in vitro functional assays. A total of 197 overlapping DEGs (37 up-regulated and 160 down-regulated) were identified from the microarray datasets. Furthermore, the PPI network with 89 nodes and 768 edges was constructed and 17 hub genes were identified from PPI network by using MCODE analysis. The survival analysis revealed that the expression of 5 hub genes (FGF2, GOLM1, GPC3, IL6 and SPP1) were significantly correlated with overall survival of patients with lung cancer. Furthermore, the in vitro functional studies showed that GOLM1 overexpression promoted the NSCLC cell proliferation and colony formation; while GOLM1 knockdown exerted the opposite effects. Importantly, GOLM1 overexpression reduced the chemo-sensitivity of cisplatin in NSCLC cells by attenuating the inhibitory effects of cisplatin on the cell proliferation and colony formation. In conclusion, the present study showed that 5 hub genes including FGF2, GOLM1, GPC3, IL6 and SPP1 were deregulated in NSCLC tissues and may predict the prognosis of patients with NSCLC. GOLM1 may play an important role in regulating the cell proliferation and chemo-sensitivity of cisplatin in NSCLC.

Coronary artery disease: differential expression of ceRNAs and interaction analyses

Background

Previous studies have demonstrated associations between cardiovascular disease and the expression of various messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). This study aimed to investigate the differential expression of mRNAs, lncRNAs, and miRNAs between tissues from patients with coronary artery disease (CAD) and healthy controls, and to determine the interactions between these molecules in CAD.

Methods

We investigated the differential expression of competitive endogenous RNAs (ceRNAs) between patients with CAD and healthy controls by collecting data from Gene Expression Omnibus (GEO) microarrays. We also investigated the biological function of these differentially expressed ceRNAs by performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. We then created a protein-protein interaction (PPI) network to identify the hub genes. Biosystems and literature searches were also carried out to identify relevant signaling pathways and the potential function of the differentially expressed ceRNAs.

Results

We identified 456 expression profiles for miRNAs, 16,325 mRNA expression profiles, and 2,869 lncRNA expression profiles. With regards to connectivity, GO and KEGG analyses (count ≥9) identified the top 11 PPI network nodes in rank order. We also identified the top 15 significant nodes for the ceRNAs identified according to degree centrality (DC) (P<0.05). Collectively, our analyses confirmed that the differential expression of certain ceRNAs, and their respective signaling pathways were associated with CAD.

Conclusions

Data arising from 11 GO and KEGG pathways, the top 15 PPI network nodes with the best connectivity rank, and the top 15 ceRNA network nodes, as determined by DC rank in CAD population, indicated that the differential expression of these ceRNAs plays a key role in the CAD. Our findings highlight new molecular mechanisms for CAD and provide new options for the development of therapeutic targets.

Assessment of Significant Pathway Signaling and Prognostic Value of GNG11 in Ovarian Serous Cystadenocarcinoma

BACKGROUND

GNG11 (G protein subunit gamma 11) is a member of guanine nucleotide-binding protein (G protein) gamma family. Few studies elucidated the role of GNG11 in human disease, especially in tumors. The present study initially analyzed the function of GNG11 in ovarian serous cystadenocarcinoma.

METHODS

The differential expression of GNG11 mRNA in ovarian cancer and normal tissues was evaluated through Oncomine, CCLE, Gepia, UCSC Xena and UALCAN databases. The protein expression of GNG11 was assessed via HPA database. Prognosis analysis was performed by Kaplan-Meier Plotter. Restrict survival analysis to subtypes including tumor grade, cancer stage and TP53 mutation status was then carried out. GSEA enrichment analysis was performed to explore the significant pathways associated with GNG11 in ovarian cancer. Finally, the upstream miRNAs of GNG11 were predicted by DIANA, Target Scan, miRDB and miRWalk databases, and the potential key KEGG pathways were subsequently determined by DIANA.

RESULTS

The mRNA expression of GNG11 was down-regulated in ovarian cancer patients (P<0.05). The cancer stage of patients correlated with the expression of GNG11 (P<0.05). Survival analysis indicated that GNG11 high expression statistically shortened the overall survival time of patients (HR=1.26, P=0.0043) compared with low expression group, especially for the patients with earlier stage (HR=2.48, P=0.035) and lower grade (HR=1.72, P=0.0016). Subsequently, the consistent upstream miRNA of GNG11, hsa-miR-22-5p, was predicted from 4 databases. The differential expression profile of hsa-miR-22-5p in blood was observed in ovarian cancer patients. According to the GSEA analysis on GNG11 and KEGG analysis on hsa-miR-22-5p, the consistent pathway of ECM-receptor interaction was observed (all P<0.01). ECM-receptor interaction pathway and differential expression of hsa-miR-22-5p in blood suggested the migration risk of ovarian cancer.

CONCLUSION

High expression of GNG11 indicated the poor prognosis of ovarian cancer patients. GNG11 might play a crucial role in the biological process of ovarian serous cystadenocarcinoma by ECM-receptor interaction pathway, thus affecting the prognosis of patients.

Integration of gene profile to explore the hub genes of lung adenocarcinoma: A quasi-experimental study

BACKGROUND

Lung cancer is a leading cause of morbidity diseases worldwide, but the key mechanisms of lung cancer remain elusive. This study aims to integrate of GSE 118370 and GSE 32863 profile and identify the key genes and pathway involved in human lung adenocarcinoma.

METHODS

R software (RStudio, Version info: R 3.2.3, Forrester, USA) were utilized to find the differentially expressed genes. All the differentially expressed genes were analyzed by gene ontology, kyoto encyclopedia of genes and genomes. Protein-protein interaction networks were constructed by STRING database and analyzed by Cytohubber and Module. The cancer genome atlas database was used to verification the expression of hub genes. Quantitative reverse transcription-PCR was used to verify the bio-information results.

RESULTS

Sixty-four lung adenocarcinoma and 64 adjacent normal tissues were used for integration analysis. Five hundred ninety-nine co-expression genes were locked. Biological processes mainly enriched in angiogenesis. Cellular component focused on extracellular exosome and molecular function aimed on protein disulfide isomerase activity. Cytohubber analysis showed that GNG11, FPR2, P4HB, PIK3R1, CDC20, ADCY4, TIMP1, IL6, CXC chemokine ligand (CXCL)12, and GAS6 acted as the hub genes during lung adenocarcinoma. Module analysis presented Chemokine signaling pathway was a key pathway. Quantitative reverse transcription-PCR showed that the expression level of GNG11, FPR2, PIK3R1, ADCY4, IL6, CXCL12, and GAS6 were significantly decreased and P4HB, CDC20 and TIMP1 were increased in human adenocarcinoma tissues (P < .05). The cancer genome atlas online analysis showed GNG11 was not associated with survival.

CONCLUSIONS

This study firstly reported GNG11 acting as a hub gene in adenocarcinoma. GNG11 could be used as a biomarker for human adenocarcinoma. Chemokine signaling pathway might play important roles in lung adenocarcinoma.

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

Candesartan Neuroprotection in Rat Primary Neurons Negatively Correlates with Aging and Senescence: a Transcriptomic Analysis

Preclinical experiments and clinical trials demonstrated that angiotensin II AT₁ receptor overactivity associates with aging and cellular senescence and that AT₁ receptor blockers (ARBs) protect from age-related brain disorders. In a primary neuronal culture submitted to glutamate excitotoxicity, gene set enrichment analysis (GSEA) revealed expression of several hundred genes altered by glutamate and normalized by candesartan correlated with changes in expression in Alzheimer's patient's hippocampus. To further establish whether our data correlated with gene expression alterations associated with aging and senescence, we compared our global transcriptional data with additional published datasets, including alterations in gene expression in the neocortex and cerebellum of old mice, human frontal cortex after age of 40, gene alterations in the Werner syndrome, rodent caloric restriction, Ras and oncogene-induced senescence in fibroblasts, and to tissues besides the brain such as the muscle and kidney. The most significant and enriched pathways associated with aging and senescence were positively correlated with alterations in gene expression in glutamate-injured neurons and, conversely, negatively correlated when the injured neurons were treated with candesartan. Our results involve multiple genes and pathways, including CAV1, CCND1, CDKN1A, CHEK1, ICAM1, IL-1B, IL-6, MAPK14, PTGS2, SERPINE1, and TP53, encoding proteins associated with aging and senescence hallmarks, such as inflammation, oxidative stress, cell cycle and mitochondrial function alterations, insulin resistance, genomic instability including telomere shortening and DNA damage, and the senescent-associated secretory phenotype. Our results demonstrate that AT₁ receptor blockade ameliorates central mechanisms of aging and senescence. Using ARBs for prevention and treatment of age-related disorders has important translational value.

Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy

Background

Lung squamous cell carcinoma (LUSC) is the second most common histological subtype of lung cancer (LC), and the prognoses of most LUSC patients are so far still very poor. The present study aimed at integrating lncRNA, miRNA and mRNA expression data to identify lncRNA signature in competitive endogenous RNA (ceRNA) network as a potentially prognostic biomarker for LUSC patients.

Methods

Gene expression data and clinical characteristics of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database, and were integratedly analyzed using bioinformatics methods including Differentially Expressed Gene Analysis (DEGA), Weighted Gene Co-expression Network Analysis (WGCNA), Protein and Protein Interaction (PPI) network analysis and ceRNA network construction. Subsequently, univariate and multivariate Cox regression analyses of differentially expressed lncRNAs (DElncRNAs) in ceRNA network were performed to predict the overall survival (OS) in LUSC patients. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of multivariate Cox regression model. Gene expression profiling interactive analysis (GEPIA) was used to validate key genes.

Results

WGCNA showed that turquoise module including 1,694 DElncRNAs, 2,654 DEmRNAs as well as 113 DEmiRNAs was identified as the most significant modules (cor=0.99, P<1e-200), and differentially expressed RNAs in the module were used to subsequently analyze. PPI network analysis identified FPR2, GNG11 and ADCY4 as critical genes in LUSC, and survival analysis revealed that low mRNA expression of FPR2 and GNG11 resulted in a higher OS rate of LUSC patients. A lncRNA-miRNA-mRNA ceRNA network including 121 DElncRNAs, 18 DEmiRNAs and 3 DEmRNAs was established, and univariate and multivariate Cox regression analysis of those 121 DElncRNAs showed a group of 3 DElncRNAs (TTTY16, POU6F2-AS2 and CACNA2D3-AS1) had significantly prognostic value in OS of LUSC patients. ROC analysis showed that the area under the curve (AUC) of the 3-lncRNA signature associated with 3-year survival was 0.629.

Conclusions

The current study provides novel insights into the lncRNA-related regulatory mechanisms underlying LUSC, and identifying 3-lncRNA signature may serve as a potentially prognostic biomarker in predicting the OS of LUSC patients.

Identification of differentially expressed genes, associated functional terms pathways, and candidate diagnostic biomarkers in inflammatory bowel diseases by bioinformatics analysis

Inflammatory bowel diseases (IBDs), including ulcerative colitis (UC) and Crohn's disease (CD), are chronic inflammatory disorders caused by genetic influences, the immune system and environmental factors. However, the underlying pathogenesis of IBDs and the pivotal molecular interactions remain to be fully elucidated. The aim of the present study was to identify genetic signatures in patients with IBDs and elucidate the potential molecular mechanisms underlying IBD subtypes. The gene expression profiles of the GSE75214 datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in UC and CD patients compared with controls using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs were performed using DAVID. Furthermore, protein-protein interaction (PPI) networks of the DEGs were constructed using Cytoscape software. Subsequently, significant modules were selected and the hub genes were identified. In the GO and KEGG pathway analysis, the top enriched pathways in UC and CD included Staphylococcus aureus infection, rheumatoid arthritis, complement and coagulation cascades, PI3K/Akt signaling pathway and osteoclast differentiation. In addition, the GO terms in the category biological process significantly enriched by these genes were inflammatory response, immune response, leukocyte migration, cell adhesion, response to molecules of bacterial origin and extracellular matrix (ECM) organization. However, several other biological processes (GO terms) and pathways (e.g., ‘chemotaxis’, ‘collagen catabolic process’ and ‘ECM-receptor interaction’) exhibited significant differences between the two subtypes of IBD. The top 10 hub genes were identified from the PPI network using respective DEGs. Of note, the hub genes G protein subunit gamma 11 (GNG11), G protein subunit beta 4 (GNB4), Angiotensinogen (AGT), Phosphoinositide-3-kinase regulatory subunit 3 (PIK3R3) and C-C motif chemokine receptor 7 (CCR7) are disease-specific and may be used as biomarkers for differentiating UC from CD. Furthermore, module analysis further confirmed that common significant pathways involved in the pathogenesis of IBD subtypes were associated with chemokine-induced inflammation, innate immunity, adapted immunity and infectious microbes. In conclusion, the present study identified DEGs, key target genes, functional pathways and enrichment analysis of IBDs, enhancing the understanding of the pathogenesis of IBDs and also advancing the clarification of the underlying molecular mechanisms of UC and CD. Furthermore, these results may provide potential molecular targets and diagnostic biomarkers for UC and CD.

In utero exposure to diesel exhaust is associated with alterations in neonatal cardiomyocyte transcription, DNA methylation and metabolic perturbation

BACKGROUND

Developmental exposure to particulate matter air pollution is harmful to cardiovascular health, but the mechanisms by which this exposure mediates susceptibility to heart disease is poorly understood. We have previously shown, in a mouse model, that gestational exposure to diesel exhaust (DE) results in increased cardiac hypertrophy, fibrosis and susceptibility to heart failure in the adult offspring following transverse aortic constriction.

RESULTS

In this study, we have analyzed gene expression in neonatal cardiomyocytes after gestational exposure by RNA-sequencing and have identified 300 genes that are dysregulated, including many involved in cardiac metabolism. We subsequently determined that these cardiomyocytes exhibit reduced metabolic activity as measured by Seahorse extracellular flux analysis. We also surveyed for modifications in DNA methylation at global regulatory regions using reduced representation bisulfite sequencing and found hypomethylation of DNA in neonatal cardiomyocytes isolated from in utero DE exposed neonates.

CONCLUSION

We have demonstrated that in utero exposure to diesel exhaust alters the neonatal cardiomyocyte transcriptional and epigenetic landscapes, as well as the metabolic capability of these cells. Understanding how exposure alters the developing heart through dysregulation of gene expression, metabolism and DNA methylation is vital for identifying therapeutic interventions for air pollution-related heart failure.

Identification of Key Genes and Pathways in Female Lung Cancer Patients Who Never Smoked by a Bioinformatics Analysis

Smoking is considered the major risk factor for lung cancer, but only a small portion of female lung adenocarcinoma patients are associated with smoking. Thus, identifying crucial genes and pathways related to nonsmoking female lung cancer patients is of great importance. Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. The R software packages were applied to screen the differentially expressed genes (DEGs). GO term enrichment and KEGG pathway analyses were carried out using DAVID tools. The protein-protein interaction (PPI) network was constructed by Cytoscape software. In total, 487 downregulated and 199 upregulated DEGs were identified. The down-regulated DEGs were mainly enriched for behavior and response to wounding, and the upregulated DEGs were significantly enriched for multicellular organismal metabolic process and cell division. The KEGG pathway analysis revealed that the downregulated DEGs were significantly enriched for cell adhesion molecules and neuroactive ligand-receptor interaction, while the upregulated DEGs were mainly enriched for cell cycle and the p53 signaling pathway. The top 10 hub genes and top 3 gene interaction modules were selected from the PPI network. Of the ten hub genes, a high expression of five genes was related to a poor OS in female lung cancer patients who never smoked, including IL6, CXCR2, FPR2, PPBP and HBA1. However, a low expression of GNG11, LRRK2, CDH5, CAV1 and SELE was associated with a worse OS for the female lung cancer patients who never smoked. In conclusion, our study provides novel insight for a better understanding of the pathogenesis of nonsmoking female lung cancer, and these identified DEGs may serve as biomarkers for diagnostics and treatment.

Identification of key genes in Ankylosing spondylitis

Ankylosing spondylitis (AS) is a common form of seronegative spondyloarthritis. We had identified differentially expressed genes (DEGs) in AS based on our previous RNA-sequencing results. Our study aimed to identify key genes in AS by integrated microarray analysis. In this present study, we identified 1328 DEGs between AS and normal control by using integrated analysis of two datasets derived from the Gene Expression Omnibus (GEO) database. Functional annotation of DEGs were performed. Pathways in cancer, Pancreatic cancer and Natural killer cell mediated cytotoxicity were significantly enriched pathways for DEGs. Based on the shared DEGs of AS in both integrated analysis and our previous RNA-sequencing results, we constructed the protein and protein interaction (PPI) network. BIRC2, MAPILC3A and MAGED1 were hub proteins. Validation of gene expression by qRT-PCR were performed and the results were consistent with our integrated analysis generally. Our finding provided new clues for understanding the mechanism of AS.

Clearance of a persistent picornavirus infection is associated with enhanced pro-apoptotic and cellular immune responses

Long-term persistent viral infections cause substantial morbidity and associated economic losses in human and veterinary contexts. Yet, the mechanisms associated with establishment of persistent infections are poorly elucidated. We investigated immunomodulatory mechanisms associated with clearance versus persistence of foot-and-mouth disease virus (FMDV) in micro-dissected compartments of the bovine nasopharynx by microarray. The use of laser-capture microdissection allowed elucidation of differential gene regulation within distinct anatomic compartments critical to FMDV infection. Analysis of samples from transitional and persistent phases of infection demonstrated significant differences in transcriptome profiles of animals that cleared infection versus those that became persistently infected carriers. Specifically, it was demonstrated that clearance of FMDV from the nasopharyngeal mucosa was associated with upregulation of targets associated with activation of T cell-mediated immunity. Contrastingly, gene regulation in FMDV carriers suggested inhibition of T cell activation and promotion of Th2 polarization. These findings were corroborated by immunofluorescence microscopy which demonstrated relative abundance of CD8⁺ T cells in the nasopharyngeal mucosa in association with clearance of FMDV. The findings presented herein emphasize that a critical balance between Th1 and Th2 -mediated immunity is essential for successful clearance of FMDV infection and should be considered for development of next-generation vaccines and antiviral products.

Identification of novel gene expression signature in lung adenocarcinoma by using next-generation sequencing data and bioinformatics analysis

Lung adenocarcinoma is one of the leading causes of cancer-related death worldwide. We showed transcriptomic profiles in three pairs of tumors and adjacent non-tumor lung tissues using next-generation sequencing (NGS) to screen protein-coding RNAs and microRNAs. Combined with meta-analysis from the Oncomine and Gene Expression Omnibus (GEO) databases, we identified a representative genetic expression signature in lung adenocarcinoma. There were 9 upregulated genes, and 8 downregulated genes in lung adenocarcinoma. The analysis of the effects from each gene expression on survival outcome indicated that 6 genes (AGR2, SPDEF, CDKN2A, CLDN3, SFN, and PHLDA2) play oncogenic roles, and 7 genes (PDK4, FMO2, CPED1, GNG11, IL33, BTNL9, and FABP4) act as tumor suppressors in lung adenocarcinoma. In addition, we also identified putative genetic interactions, in which there were 5 upregulated microRNAs with specific targets - hsa-miR-183-5p-BTNL9, hsa-miR-33b-5p-CPED1, hsa-miR-429-CPED1, hsa-miR-182-5p-FMO2, and hsa-miR-130b-5p-IL33. These 5 microRNAs have been shown to be associated with tumorigenesis in lung cancer. Our findings suggest that these genetic interactions play important roles in the progression of lung adenocarcinoma. We propose that this molecular change of genetic expression may represent a novel signature in lung adenocarcinoma, which may be developed for diagnostic and therapeutic strategies in the future.

Genomewide association of piglet responses to infection with one of two porcine reproductive and respiratory syndrome virus isolates

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease in the swine industry. Identification of host genetic factors that enable selection for improved performance during PRRS virus (PRRSV) infection would reduce the impact of this disease on animal welfare and production efficiency. We conducted genomewide association study (GWAS) analyses of data from 13 trials of approximately 200 commercial crossbred nursery-age piglets that were experimentally infected with 1 of 2 type 2 isolates of PRRSV (NVSL 97-7985 [NVSL] and KS2006-72109 [KS06]). Phenotypes analyzed were viral load (VL) in blood during the first 21 d after infection (dpi) and weight gain (WG) from 0 to 42 dpi. We accounted for the previously identified QTL in the region on SSC4 in our models to increase power to identify additional regions. Many regions identified by single-SNP analyses were not identified using Bayes-B, but both analyses identified the same regions on SSC3 and SSC5 to be associated with VL in the KS06 trials and on SSC6 in the NVSL trials ( < 5 × 10); for WG, regions on SSC5 and SSC17 were associated in the NVSL trials ( < 3 × 10). No regions were identified with either method for WG in the KS06 trials. Except for the region on SSC4, which was associated with VL for both isolates (but only with WG for NVSL), identified regions did not overlap between the 2 PRRSV isolate data sets, despite high estimates of the genetic correlation between isolates for traits based on these data. We also identified genomic regions whose associations with VL or WG interacted with either PRRSV isolate or with genotype at the SSC4 QTL. Gene ontology (GO) annotation terms for genes located near moderately associated SNP ( < 0.003) were enriched for multiple immunologically (VL) and metabolism- (WG) related GO terms. The biological relevance of these regions suggests that, although it may increase the number of false positives, the use of single-SNP analyses and a relaxed threshold also increased the identification of true positives. In conclusion, although only the SSC4 QTL was associated with response to both PRRSV isolates, genes near associated SNP were enriched for the same GO terms across PRRSV isolates, suggesting that host responses to these 2 isolates are affected by the actions of many genes that function together in similar biological processes.

GNG11 (G-protein subunit γ 11) suppresses cell growth with induction of reactive oxygen species and abnormal nuclear morphology in human SUSM-1 cells

Enforced expression of GNG11, G-protein subunit γ 11, induces cellular senescence in normal human diploid fibroblasts. We here examined the effect of the expression of GNG11 on the growth of immortalized human cell lines, and found that it suppressed the growth of SUSM-1 cells, but not of HeLa cells. We then compared these two cell lines to understand the molecular basis for the action of GNG11. We found that expression of GNG11 induced the generation of reactive oxygen species (ROS) and abnormal nuclear morphology in SUSM-1 cells but not in HeLa cells. Increased ROS generation by GNG11 would likely be caused by the down-regulation of the antioxidant enzymes in SUSM-1 cells. We also found that SUSM-1 cells, even under normal culture conditions, showed higher levels of ROS and higher incidence of abnormal nuclear morphology than HeLa cells, and that abnormal nuclear morphology was relevant to the increased ROS generation in SUSM-1 cells. Thus, SUSM-1 and HeLa cells showed differences in the regulation of ROS and nuclear morphology, which might account for their different responses to the expression of GNG11. Thus, SUSM-1 cells may provide a unique system to study the regulatory relationship between ROS generation, nuclear morphology, and G-protein signaling.

Tissue Remodelling following Resection of Porcine Liver

AIM

To study genes regulating the extracellular matrix (ECM) and investigate the tissue remodelling following liver resection in porcine.

METHODS

Four pigs with 60% partial hepatectomy- (PHx-) induced liver regeneration were studied over six weeks. Four pigs underwent sham surgery and another four pigs were used as controls of the normal liver growth. Liver biopsies were taken upon laparotomy, after three and six weeks. Gene expression profiles were obtained using porcine-specific oligonucleotide microarrays. Immunohistochemical staining was performed and a proliferative index was assessed.

RESULTS

More differentially expressed genes were associated with the regulation of ECM in the resection group compared to the sham and control groups. Secreted protein acidic and rich in cysteine (SPARC) and collagen 1, alpha 2 (COL1A2) were both upregulated in the early phase of liver regeneration, validated by immunopositive cells during the remodelling phase of liver regeneration. A broadened connective tissue was demonstrated by Masson's Trichrome staining, and an immunohistochemical staining against pan-Cytokeratin (pan-CK) demonstrated a distinct pattern of migrating cells, followed by proliferating cell nuclear antigen (PCNA) positive nuclei.

CONCLUSIONS

The present study demonstrates both a distinct pattern of PCNA positive nuclei and a deposition of ECM proteins in the remodelling phase of liver regeneration.

Gene Expression Profiling in Peripheral Blood Cells and Synovial Membranes of Patients with Psoriatic Arthritis

Background

Psoriatic arthritis (PsA) is an inflammatory arthritis whose pathogenesis is poorly understood; it is characterized by bone erosions and new bone formation. The diagnosis of PsA is mainly clinical and diagnostic biomarkers are not yet available. The aim of this work was to clarify some aspects of the disease pathogenesis and to identify specific gene signatures in paired peripheral blood cells (PBC) and synovial biopsies of patients with PsA. Moreover, we tried to identify biomarkers that can be used in clinical practice.

Methods

PBC and synovial biopsies of 10 patients with PsA were used to study gene expression using Affymetrix arrays. The expression values were validated by Q-PCR, FACS analysis and by the detection of soluble mediators.

Results

Synovial biopsies of patients showed a modulation of approximately 200 genes when compared to the biopsies of healthy donors. Among the differentially expressed genes we observed the upregulation of Th17 related genes and of type I interferon (IFN) inducible genes. FACS analysis confirmed the Th17 polarization. Moreover, the synovial trascriptome shows gene clusters (bone remodeling, angiogenesis and inflammation) involved in the pathogenesis of PsA. Interestingly 90 genes are modulated in both compartments (PBC and synovium) suggesting that signature pathways in PBC mirror those of the inflamed synovium. Finally the osteoactivin gene was upregulared in both PBC and synovial biopsies and this finding was confirmed by the detection of high levels of osteoactivin in PsA sera but not in other inflammatory arthritides.

Conclusions

We describe the first analysis of the trancriptome in paired synovial tissue and PBC of patients with PsA. This study strengthens the hypothesis that PsA is of autoimmune origin since the coactivity of IFN and Th17 pathways is typical of autoimmunity. Finally these findings have allowed the identification of a possible disease biomarker, osteoactivin, easily detectable in PsA serum.

Gene Expression Signatures Predictive of Bevacizumab/Erlotinib Therapeutic Benefit in Advanced Nonsquamous Non-Small Cell Lung Cancer Patients (SAKK 19/05 trial)

PURPOSE

We aimed to identify gene expression signatures associated with angiogenesis and hypoxia pathways with predictive value for treatment response to bevacizumab/erlotinib (BE) of nonsquamous advanced non-small cell lung cancer (NSCLC) patients.

EXPERIMENTAL DESIGN

Whole-genome gene expression profiling was performed on 42 biopsy samples (from SAKK 19/05 trial) using Affymetrix exon arrays, and associations with the following endpoints: time-to-progression (TTP) under therapy, tumor-shrinkage (TS), and overall survival (OS) were investigated. Next, we performed gene set enrichment analyses using genes associated with the angiogenic process and hypoxia response to evaluate their predictive value for patients' outcome.

RESULTS

Our analysis revealed that both the angiogenic and hypoxia response signatures were enriched within the genes predictive of BE response, TS, and OS. Higher gene expression levels (GEL) of the 10-gene angiogenesis-associated signature and lower levels of the 10-gene hypoxia response signature predicted improved TTP under BE, 7.1 months versus 2.1 months for low versus high-risk patients (P = 0.005), and median TTP 6.9 months versus 2.9 months (P = 0.016), respectively. The hypoxia response signature associated with higher TS at 12 weeks and improved OS (17.8 months vs. 9.9 months for low vs. high-risk patients, P = 0.001).

CONCLUSIONS

We were able to identify gene expression signatures derived from the angiogenesis and hypoxia response pathways with predictive value for clinical outcome in advanced nonsquamous NSCLC patients. This could lead to the identification of clinically relevant biomarkers, which will allow for selecting the subset of patients who benefit from the treatment and predict drug response.

HES6 promotes prostate cancer aggressiveness independently of Notch signalling

Notch signalling is implicated in the pathogenesis of a variety of cancers, but its role in prostate cancer is poorly understood. However, selected Notch pathway members are overrepresented in high-grade prostate cancers. We comprehensively profiled Notch pathway components in prostate cells and found prostate cancer-specific up-regulation of NOTCH3 and HES6. Their expression was particularly high in androgen responsive lines. Up- and down-regulating Notch in these cells modulated expression of canonical Notch targets, HES1 and HEY1, which could also be induced by androgen. Surprisingly, androgen treatment also suppressed Notch receptor expression, suggesting that androgens can activate Notch target genes in a receptor-independent manner. Using a Notch-sensitive Recombination signal binding protein for immunoglobulin kappa J region (RBPJ) reporter assay, we found that basal levels of Notch signalling were significantly lower in prostate cancer cells compared to benign cells. Accordingly pharmacological Notch pathway blockade did not inhibit cancer cell growth or viability. In contrast to canonical Notch targets, HES6, a HES family member known to antagonize Notch signalling, was not regulated by Notch signalling, but relied instead on androgen levels, both in cultured cells and in human cancer tissues. When engineered into prostate cancer cells, reduced levels of HES6 resulted in reduced cancer cell invasion and clonogenic growth. By molecular profiling, we identified potential roles for HES6 in regulating hedgehog signalling, apoptosis and cell migration. Our results did not reveal any cell-autonomous roles for canonical Notch signalling in prostate cancer. However, the results do implicate HES6 as a promoter of prostate cancer progression.

Identification of potential transcriptomic markers in developing ankylosing spondylitis: a meta-analysis of gene expression profiles

The goal of this study was to identify potential transcriptomic markers in developing ankylosing spondylitis by a meta-analysis of multiple public microarray datasets. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed (DE) genes in ankylosing spondylitis and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DE genes identified in the meta-analysis. Three microarray datasets (26 cases and 29 controls in total) were collected for meta-analysis. 905 consistently DE genes were identified in ankylosing spondylitis, among which 482 genes were upregulated and 423 genes were downregulated. The upregulated gene with the smallest combined rank product (RP) was GNG11 (combined RP = 299.64). The downregulated gene with the smallest combined RP was S100P (combined RP = 335.94). In the gene ontology (GO) analysis, the most significantly enriched GO term was “immune system process” (P = 3.46 × 10⁻²⁶). The most significant pathway identified in the pathway analysis was antigen processing and presentation (P = 8.40 × 10⁻⁵). The consistently DE genes in ankylosing spondylitis and biological pathways associated with those DE genes identified provide valuable information for studying the pathophysiology of ankylosing spondylitis.

Ras-mediated deregulation of the circadian clock in cancer

Circadian rhythms are essential to the temporal regulation of molecular processes in living systems and as such to life itself. Deregulation of these rhythms leads to failures in biological processes and eventually to the manifestation of pathological phenotypes including cancer. To address the questions as to what are the elicitors of a disrupted clock in cancer, we applied a systems biology approach to correlate experimental, bioinformatics and modelling data from several cell line models for colorectal and skin cancer. We found strong and weak circadian oscillators within the same type of cancer and identified a set of genes, which allows the discrimination between the two oscillator-types. Among those genes are IFNGR2, PITX2, RFWD2, PPARγ, LOXL2, Rab6 and SPARC, all involved in cancer-related pathways. Using a bioinformatics approach, we extended the core-clock network and present its interconnection to the discriminative set of genes. Interestingly, such gene signatures link the clock to oncogenic pathways like the RAS/MAPK pathway. To investigate the potential impact of the RAS/MAPK pathway - a major driver of colorectal carcinogenesis - on the circadian clock, we used a computational model which predicted that perturbation of BMAL1-mediated transcription can generate the circadian phenotypes similar to those observed in metastatic cell lines. Using an inducible RAS expression system, we show that overexpression of RAS disrupts the circadian clock and leads to an increase of the circadian period while RAS inhibition causes a shortening of period length, as predicted by our mathematical simulations. Together, our data demonstrate that perturbations induced by a single oncogene are sufficient to deregulate the mammalian circadian clock.

Living systems possess an endogenous time-generating system – the circadian clock - accountable for a 24 hours oscillation in the expression of about 10% of all genes. In mammals, disruption of oscillations is associated to several diseases including cancer. In this manuscript, we address the following question: what are the elicitors of a disrupted clock in cancer? We applied a systems biology approach to correlate experimental, bioinformatics and modelling data and could thereby identify key genes which discriminate strong and weak oscillators among cancer cell lines. Most of the discriminative genes play important roles in cell cycle regulation, DNA repair, immune system and metabolism and are involved in oncogenic pathways such as the RAS/MAPK. To investigate the potential impact of the Ras oncogene in the circadian clock we generated experimental models harbouring conditionally active Ras oncogenes. We put forward a direct correlation between the perturbation of Ras oncogene and an effect in the expression of clock genes, found by means of mathematical simulations and validated experimentally. Our study shows that perturbations of a single oncogene are sufficient to deregulate the mammalian circadian clock and opens new ways in which the circadian clock can influence disease and possibly play a role in therapy.

Integrated next-generation sequencing and avatar mouse models for personalized cancer treatment

BACKGROUND

Current technology permits an unbiased massive analysis of somatic genetic alterations from tumor DNA as well as the generation of individualized mouse xenografts (Avatar models). This work aimed to evaluate our experience integrating these two strategies to personalize the treatment of patients with cancer.

METHODS

We performed whole-exome sequencing analysis of 25 patients with advanced solid tumors to identify putatively actionable tumor-specific genomic alterations. Avatar models were used as an in vivo platform to test proposed treatment strategies.

RESULTS

Successful exome sequencing analyses have been obtained for 23 patients. Tumor-specific mutations and copy-number variations were identified. All samples profiled contained relevant genomic alterations. Tumor was implanted to create an Avatar model from 14 patients and 10 succeeded. Occasionally, actionable alterations such as mutations in NF1, PI3KA, and DDR2 failed to provide any benefit when a targeted drug was tested in the Avatar and, accordingly, treatment of the patients with these drugs was not effective. To date, 13 patients have received a personalized treatment and 6 achieved durable partial remissions. Prior testing of candidate treatments in Avatar models correlated with clinical response and helped to select empirical treatments in some patients with no actionable mutations.

CONCLUSION

The use of full genomic analysis for cancer care is encouraging but presents important challenges that will need to be solved for broad clinical application. Avatar models are a promising investigational platform for therapeutic decision making. While limitations still exist, this strategy should be further tested.

Genome-wide profiling of in vivo LPS-responsive genes in splenic myeloid cells

Lipopolysaccharide (LPS), the major causative agent of bacterial sepsis, has been used by many laboratories in genome-wide expression profiling of the LPS response. However, these studies have predominantly used in vitro cultured macrophages (Macs), which may not accurately reflect the LPS response of these innate immune cells in vivo. To overcome this limitation and to identify inflammatory genes in vivo, we have profiled genome-wide expression patterns in non-lymphoid, splenic myeloid cells extracted directly from LPS-treated mice. Genes encoding factors known to be involved in mediating or regulating inflammatory processes, such as cytokines and chemokines, as well as many genes whose immunological functions are not well known, were strongly induced by LPS after 3 h or 8 h of treatment. Most of the highly LPS-responsive genes that we randomly selected from the microarray data were independently confirmed by quantitative RT-PCR, implying that our microarray data are quite reliable. When our in vivo data were compared to previously reported microarray data for in vitro LPS-treated Macs, a significant proportion (∼20%) of the in vivo LPS-responsive genes defined in this study were specific to cells exposed to LPS in vivo, but a larger proportion of them (∼60%) were influenced by LPS in both in vitro and in vivo settings. This result indicates that our in vivo LPS-responsive gene set includes not only previously identified in vitro LPS-responsive genes but also novel LPS-responsive genes. Both types of genes would be a valuable resource in the future for understanding inflammatory responses in vivo.

Gene set enrichment analysis highlights different gene expression profiles in whole blood samples X-irradiated with low and high doses

PURPOSE

Health risks from exposure to low doses of ionizing radiation (IR) are becoming a concern due to the rapidly growing medical applications of X-rays. Using microarray techniques, this study aims for a better understanding of whole blood response to low and high doses of IR.

MATERIALS AND METHODS

Aliquots of peripheral blood samples were irradiated with 0, 0.05, and 1 Gy X-rays. RNA was isolated and prepared for microarray gene expression experiments. Bioinformatic approaches, i.e., univariate statistics and Gene Set Enrichment Analysis (GSEA) were used for analyzing the data generated. Seven differentially expressed genes were selected for further confirmation using quantitative real-time PCR (RT-PCR).

RESULTS

Functional analysis of genes differentially expressed at 0.05 Gy showed the enrichment of chemokine and cytokine signaling. However, responsive genes to 1 Gy were mainly involved in tumor suppressor protein 53 (p53) pathways. In a second approach, GSEA showed a higher statistical ranking of inflammatory and immune-related gene sets that are involved in both responding and/or secretion of growth factors, chemokines, and cytokines. This indicates the activation of the immune response. Whereas, gene sets enriched at 1 Gy were 'classical' radiation pathways like p53 signaling, apoptosis, DNA damage and repair. Comparative RT-PCR studies showed the significant induction of chemokine-related genes (PF4, GNG11 and CCR4) at 0.05 Gy and DNA damage and repair genes at 1 Gy (DDB2, AEN and CDKN1A).

CONCLUSIONS

This study moves a step forward in understanding the different cellular responses to low and high doses of X-rays. In addition to that, and in a broader context, it addresses the need for more attention to the risk assessment of health effects resulting from the exposure to low doses of IR.

Gene expression changes of interconnected spared cortical neurons 7 days after ischemic infarct of the primary motor cortex in the rat

After cortical injury resulting from stroke, some recovery can occur and may involve spared areas of the cerebral cortex reorganizing to assume functions previously controlled by the damaged cortical areas. No studies have specifically assessed gene expression changes in remote neurons with axonal processes that terminate in the infarcted tissue, i.e., the subset of neurons most likely to be involved in regenerative processes. By physiologically identifying the primary motor area controlling forelimb function in adult rats (caudal forelimb area = CFA), and injecting a retrograde tract-tracer, we labeled neurons within the non-primary motor cortex (rostral forelimb area = RFA) that project to CFA. Then, 7 days after a CFA infarct (n = 6), we used laser capture microdissection techniques to harvest labeled neurons in RFA. Healthy, uninjured rats served as controls (n = 6). Biological interactions and functions of gene profiling were investigated by Affymetrix Microarray, and Ingenuity Pathway Analysis. A total of 143 up- and 128 down-regulated genes showed significant changes (fold change ≥1.3 and p < 0.05). The canonical pathway, "Axonal Guidance Signaling," was overrepresented (p value = 0.002). Significantly overrepresented functions included: branching of neurites, organization of cytoskeleton, dendritic growth and branching, organization of cytoplasm, guidance of neurites, development of cellular protrusions, density of dendritic spines, and shape change (p = 0.000151-0.0487). As previous studies have shown that spared motor areas are important in recovery following injury to the primary motor area, the results suggest that these gene expression changes in remote, interconnected neurons may underlie reorganization and recovery mechanisms.

Alteration of Golgi structure in senescent cells and its regulation by a G protein γ subunit

Cellular senescence is a process wherein proliferating cells undergo permanent cell cycle arrest while remaining viable. Senescence results in enhanced secretion of proteins that promote cancer and inflammation. We report here that the structure of the Golgi complex which regulates secretion is altered in senescent cells. In cells where senescence is achieved by replicative exhaustion or in cells wherein senescence has been induced with BrdU treatment dependent stress, the Golgi complex is dispersed. The expression of a G protein γ subunit, γ11, capable of translocation from the plasma membrane to the Golgi complex on receptor activation increases with senescence. Knockdown of γ11 or overexpression of a dominant negative γ3 subunit inhibits Golgi dispersal induced by senescence. Overall these results suggest that in cellular senescence an upregulated G protein gamma subunit mediates alterations in the structure of the Golgi.

Resolution of infection promotes a state of dormancy and long survival of CD4 memory T cells

Memory T cells survive throughout the lifetime of an individual and are protective upon recall. It is not clear how memory T cells can live so long. Here, we demonstrate that at the resolution of a viral infection, low levels of antigen are captured by B cells and presented to specific CD4⁺ memory T cells to render a state of unresponsiveness. We demonstrate in two systems that this process occurs naturally during the fall of antigen and is associated with a global gene expression program initiated with the clearance of antigen. Our study suggests that in the absence of antigen, a state of dormancy associated with low energy utilization and proliferation can help memory CD4⁺ T cells to survive nearly throughout the lifetime of mice. The dormant CD4⁺ memory T cells become activated by stimulatory signals generated by a subsequent infection. We propose that quiescence might be a mechanism necessary to regulate long-term survival of CD4 memory T cells and to prevent cross-reactivity to self, hence autoimmunity.

Comparison of global DNA methylation profiles in replicative versus premature senescence

DNA methylation is considered to play an essential role in cellular senescence. To uncover the mechanism underlying cellular senescence, we established the model of premature senescence induced by hydrogen peroxide (H(2)O(2)) in human embryonic lung fibroblasts and investigated the changes of genome methylation, DNA methyltransferases (DNMTs) and DNA-binding domain proteins (MBDs) in comparison with those observed during normal replicative senescence. We found that premature senescence triggered by H(2)O(2) exhibited distinct morphological characteristics and proliferative capacity which were similar to those of replicative senescence. The genome methylation level decreased gradually during the premature as well as replicative senescence, which was associated with the reduction in the expression of DNMT1, reflecting global hypomethylation as a distinct feature of senescent cells. The levels of DNMT3b and methyl-CpG binding protein 2 (MeCP2) increased in both mid-aged and replicative senescent cells, while DNMT3a and MBD2 were upregulated in the mid-aged cells. Only DNMT3b was elevated in the cells in the premature senescence persistence status. Additionally, the expression for DNMTs, MBD2 and MeCP2 was increased rapidly upon H(2)O(2) treatment. These results indicate that H(2)O(2)-induced premature senescence share some features of replicative senescence, such as basic biological characteristics and global hypomethylation while there are slight differences in the profile of methylation-associated enzyme expression. Oxidative damage may hence be a causative factor in epigenetic alteration partly responsible for cellular senescence.

Comparative analysis of microarray data identifies common responses to caloric restriction among mouse tissues

Caloric restriction has been extensively investigated as an intervention that both extends lifespan and delays age-related disease in mammals. In mice, much interest has centered on evaluating gene expression changes induced by caloric restriction (CR) in particular tissue types, but the overall systemic effect of CR among multiple tissues has been examined less extensively. This study presents a comparative analysis of microarray datasets that have collectively examined the effects of CR in 10 different tissue types (liver, heart, muscle, hypothalamus, hippocampus, white adipose tissue, colon, kidney, lung and cochlea). Using novel methods for comparative analysis of microarray data, detailed comparisons of the effects of CR among tissues are provided, and 28 genes for which expression response to CR is most shared among tissues are identified. These genes characterize common responses to CR, which consist of both activation and inhibition of stress-response pathways. With respect to liver tissue, transcriptional effects of CR exhibited surprisingly little overlap with those of aging, and a variable degree of overlap with the potential CR-mimetic drug resveratrol. These analyses shed light on the systemic transcriptional activity associated with CR diets, and also illustrate new approaches for comparative analysis of microarray datasets in the context of aging biology.