The Colorectal cancer disease-specific transcriptome may facilitate the discovery of more biologically and clinically relevant information

BACKGROUND: To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome.

METHODS: DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information.

RESULTS: The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance.

CONCLUSIONS: Analysis from our in vitro and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including IGF2BP2, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear; however, the numbers that have been detected by the disease-specific microarray would suggest that they may be important regulatory transcripts. This study has demonstrated the power of a disease-specific transcriptome-based approach and highlighted the potential novel biologically and clinically relevant information that is gained when using such a methodology.

New prognostic markers, determined using gene expression analyses, reveal two distinct subtypes of chronic myelomonocytic leukaemia patients

Chronic myelomonocytic leukaemia (CMML) is a heterogeneous haematopoietic disorder characterized by myeloproliferative or myelodysplastic features. At present, the pathogenesis of this malignancy is not completely understood. In this study, we sought to analyse gene expression profiles of CMML in order to characterize new molecular outcome predictors. A learning set of 32 untreated CMML patients at diagnosis was available for TaqMan low-density array gene expression analysis. From 93 selected genes related to cancer and cell cycle, we built a five-gene prognostic index after multiplicity correction. Using this index, we characterized two categories of patients with distinct overall survival (94% vs. 19% for good and poor overall survival, respectively; P = 0.007) and we successfully validated its strength on an independent cohort of 21 CMML patients with Affymetrix gene expression data. We found no specific patterns of association with traditional prognostic stratification parameters in the learning cohort. However, the poor survival group strongly correlated with high-risk treated patients and transformation to acute myeloid leukaemia. We report here a new multigene prognostic index for CMML, independent of the gene expression measurement method, which could be used as a powerful tool to predict clinical outcome and help physicians to evaluate criteria for treatments.

A genome-wide association study provides evidence for association of chromosome 8p23 (MYP10) and 10q21.1 (MYP15) with high myopia in the French population.

PURPOSE. Myopia is a complex trait affected by both genetic and environmental factors. High myopia is associated with increased risk of sight-threatening eye disorders such as retinal detachment. The purpose of this genome-wide association study was to identify susceptibility genes contributing to high myopia in the French population. METHODS. High myopic cases were genotyped using Affymetrix SNP 6.0 chips and population controls were selected from the GABRIEL French dataset in which samples were genotyped by Illumina Human610 quad array. The association study was conducted using 152,234 single nucleotide polymorphisms that were present on both manufacturers' chips in 192 high myopic cases and 1064 controls to identify associated regions. Imputation was performed on peak regions. RESULTS. Associations were found at known myopia locus MYP10 on chromosome 8p23 and MYP15 on chromosome 10q21.1. Rs189798 (8p23) and rs10825992 (10q21.1) showed the strongest associations in these regions (P=6.32x10-7 and P=2.17x10-5, respectively). The imputed results at 8p23 showed 2 peaks of interest. The first spanned 30kb including rs189798 between MIR4660 and PPP1R3B with the most significant association at rs17155227 (P=1.07x10-10). The second novel peak was 4kb in length, encompassing MIR124-1 and the MSRA gene, with the strongest association at rs55864141 (P=1.30x10-7). The peak of imputed data at 10q21.1 was 70kb in length between ZWINT and MIR3924, with rs3107503 having the lowest P value (P=1.54x10-7). CONCLUSION. We provide evidence for the association of MYP10 at 8p23 and MYP15 at 10p21.1 with high myopia in the French population and refine these regions of association.

NuGO contributions to GenePattern

NuGO, the European Nutrigenomics Organization, utilizes 31 powerful computers for, e.g., data storage and analysis. These so-called black boxes (NBXses) are located at the sites of different partners. NuGO decided to use GenePattern as the preferred genomic analysis tool on each NBX. To handle the custom made Affymetrix NuGO arrays, new NuGO modules are added to GenePattern. These NuGO modules execute the latest Bioconductor version ensuring up-to-date annotations and access to the latest scientific developments. The following GenePattern modules are provided by NuGO: NuGOArrayQualityAnalysis for comprehensive quality control, NuGOExpressionFileCreator for import and normalization of data, LimmaAnalysis for identification of differentially expressed genes, TopGoAnalysis for calculation of GO enrichment, and GetResultForGo for retrieval of information on genes associated with specific GO terms. All together, these NuGO modules allow comprehensive, up-to-date, and user friendly analysis of Affymetrix data. A special feature of the NuGO modules is that for analysis they allow the use of either the standard Affymetrix or the MBNI custom CDF-files, which remap probes based on current knowledge. In both cases a .chip-file is created to enable GSEA analysis. The NuGO GenePattern installations are distributed as binary Ubuntu (.deb) packages via the NuGO repository.

Balancing Inflammatory, Lipid, and Xenobiotic Signaling Pathways by VSL#3, a Biotherapeutic Agent, in the Treatment of Inflammatory Bowel Disease

Background: The interleukin 10 knockout mouse (IL10-KO) is a model of human inflammatory bowel disease (IBD) used to Study host microbial interactions and the action of potential therapeutics. Using Affymetrix data analysis, important signaling pathways and transcription factors relevant to gut inflammation and antiinflammatory probiotics were identified.

Methods: Affymetrix microarray analysis on both wildtype (WT) and IL10-KO mice orally administered with and without the probiotic VSL#3 was performed and the results validated by real-time polymerase chain reaction (PCR), immunocytochemistry, proteomics, and histopathology. Changes in metabolically active bacteria were assessed with denaturing gradient gel electrophoresis (DGGE).

Results: Inflammation in IL10-KO mice was characterized by differential regulation of inflammatory, nuclear receptor, lipid, and xenobiotic signaling pathways. Probiotic intervention resulted in downregulation of CXCL9 (fold change [FC] = -3.98, false discovery rate [FDR] = 0.019), CXCL10 (FC = -4.83, FDR = 0.0008), CCL5 (FC -3.47 FDR = 0.017), T-cell activation (Itgal [FC = -4.72, FDR = 0.00009], Itgae [FC = -2.54 FDR = 0.0044]) and the autophagy gene IRGM (FC = -1.94, FDR = 0.01), a recently identified susceptibility gene in human IBD. Consistent with a marked reduction in integrins, probiotic treatment decreased the number of CCL5+ CD3+ double-positive T Cells and upregulated galectin2, which triggers apoptosis of activated T cells. Importantly, genes associated with lipid and PPAR signaling (PPAR alpha [FC = 2.36, FDR = 0.043], PPARGC1 alpha [FC 2.58, FDR = 0.016], Nrld2 [FC = 3.11, FDR = 0.0067]) were also upregulated. Altered microbial diversity was noted in probiotic-treated mice.

Conclusions: Bioinformatics analysis revealed important immune response. phagocytic and inflammatory pathways dominated by elevation of T-helper cell 1 type (TH1) transcription factors in IL10-KO mice. Probiotic intervention resulted in a site-specific reduction of these pathways but importantly upregulated PPAR, xenobiotic, and lipid signaling genes. potential antagonists of NF-kappa B inflammatory pathways.

Molecular similarity between myelodysplastic form of chronic myelomonocytic leukemia and refractory anemia with ring sideroblasts

Chronic myelomonocytic leukemia is similar to but a separate entity from both myeloproliferative neoplasms and myelodysplastic syndromes, and shows either myeloproliferative or myelodysplastic features. We ask whether this distinction may have a molecular basis. We established the gene expression profiles of 39 samples of chronic myelomonocytic leukemia (including 12 CD34-positive) and 32 CD34-positive samples of myelodysplastic syndromes by using Affymetrix microarrays, and studied the status of 18 genes by Sanger sequencing and array-comparative genomic hybridization in 53 samples. Analysis of 12 mRNAS from chronic myelomonocytic leukemia established a gene expression signature of 122 probe sets differentially expressed between proliferative and dysplastic cases of chronic myelomonocytic leukemia. As compared to proliferative cases, dysplastic cases over-expressed genes involved in red blood cell biology. When applied to 32 myelodysplastic syndromes, this gene expression signature was able to discriminate refractory anemias with ring sideroblasts from refractory anemias with excess of blasts. By comparing mRNAS from these two forms of myelodysplastic syndromes we derived a second gene expression signature. This signature separated the myelodysplastic and myeloproliferative forms of chronic myelomonocytic leukemias. These results were validated using two independent gene expression data sets. We found that myelodysplastic chronic myelomonocytic leukemias are characterized by mutations in transcription/epigenetic regulators (ASXL1, RUNX1, TET2) and splicing genes (SRSF2) and the absence of mutations in signaling genes. Myelodysplastic chronic myelomonocytic leukemias and refractory anemias with ring sideroblasts share a common expression program suggesting they are part of a continuum, which is not totally explained by their similar but not, however, identical mutation spectrum. © 2013 Ferrata Storti Foundation.

Minor allele frequency of myeloproliferative neoplasm mutations in the Irish blood donor population

Myeloproliferative neoplasms (MPNs) are rare diseases that include classic entities; polycythaemia vera, essential thrombocythaemia and primary myelofibrosis. In this short report, minor allele frequencies of common MPN mutations are compared between the Irish blood donor population and other populations of European descent using data from the Haplotype Map project. The Affymetrix array 6.0 platform was utilised identifying nine single nucleotide polymorphisms (SNPs) and six proxy SNPs. The variability of allele frequencies for MPN mutations could account for the different incidence rates seen between populations of European ancestry, giving a better understanding of the genetic predisposition to MPNs. 

Novel Hypoxia-Associated Markers of Chemoresistance in Ovarian Cancer

Background:
Ovarian cancer is the fifth leading cause of cancer in women and has poor
long-term survival, in part, due to chemoresistance. Tumour hypoxia is associated with
chemoresistance in ovarian cancer. However, relatively little is known about the genes
activated in ovarian cancer which cause chemoresistance due to hypoxia. This study
aimed to firstly identify genes whose expression is associated with hypoxia-induced
chemoresistance, and secondly select hypoxia-associated biomarkers and evaluate their
expression in ovarian tumours.
Design:
Cisplatin-sensitive (A2780) and cisplatin-resistant (A2780cis) ovarian cancer
cell lines were exposed to combinations of hypoxia and/or cisplatin as part of a matrix
designed to reflect clinically relevant scenarios. RNA was extracted and interrogated
on Affymetrix Human Gene arrays. Differential gene expression was analysed for cells
exposed to hypoxia and/or treated with cisplatin. Potential markers of chemoresistance
were selected for evaluation in a cohort of ovarian tumour samples by R
T-PCR.
Results:
A wide range of genes associated with chemoresistance were differentially
expressed in cells exposed to hypoxia and/or cisplatin. Selected genes [ANGPTL4,
HER3 and HIF-1
α
] were chosen for further validation in a cohort of ovarian tumour
samples. High expression of ANGPTL4 trended towards reduced progression-free and
overall survival. High expression of HER3 trended to increased progression-free but
reduced overall survival, while high expression of HIF-1
α
trended towards reduced
progression-free and increased overall survival.
Conclusions:
In conclusion, this study has further characterized the relationship between
hypoxia and chemoresistance in an ovarian cancer model. We have also identified many
potential biomarkers of hypoxia and platinum resistance and provided initial validation
of a subset of these markers in ovarian cancer tissues.

Genome-wide DNA profiling of marginal zone lymphomas identifies subtype-specific lesions with an impact on the clinical outcome

Marginal zone B-cell lymphomas (MZLs) have been divided into 3 distinct subtypes (extranodal MZLs of mucosa-associated lymphoid tissue [MALT] type, nodal MZLs, and splenic MZLs). Nevertheless, the relationship between the subtypes is still unclear. We performed a comprehensive analysis of genomic DNA copy number changes in a very large series of MZL cases with the aim of addressing this question. Samples from 218 MZL patients (25 nodal, 57 MALT, 134 splenic, and 2 not better specified MZLs) were analyzed with the Affymetrix Human Mapping 250K SNP arrays, and the data combined with matched gene expression in 33 of 218 cases. MALT lymphoma presented significantly more frequently gains at 3p, 6p, 18p, and del(6q23) (TNFAIP3/A20), whereas splenic MZLs was associated with del(7q31), del(8p). Nodal MZLs did not show statistically significant differences compared with MALT lymphoma while lacking the splenic MZLs-related 7q losses. Gains of 3q and 18q were common to all 3 subtypes. del(8p) was often present together with del(17p) (TP53). Although del(17p) did not determine a worse outcome and del(8p) was only of borderline significance, the presence of both deletions had a highly significant negative impact on the outcome of splenic MZLs.

Genomic lesions associated with a different clinical outcome in diffuse large B-Cell lymphoma treated with R-CHOP-21

Despite recent therapeutic improvements, the clinical course of diffuse large B-cell lymphoma (DLBCL) still differs considerably among patients. We conducted this retrospective multi-centre study to evaluate the impact of genomic aberrations detected using a high-density genome wide-single nucleotide polymorphism-based array on clinical outcome in a population of DLBCL patients treated with R-CHOP-21 (rituximab, cyclophosphamide, doxorubicine, vincristine and prednisone repeated every 21_d). 166 DNA samples were analysed using the GeneChip Human Mapping 250K NspI. Genomic anomalies were analysed regarding their impact on the clinical course of 124 patients treated with R-CHOP-21. Unsupervised clustering was performed to identify genetically related subgroups of patients with different clinical outcomes. Twenty recurrent genetic lesions showed an impact on the clinical course. Loss of genomic material at 8p23.1 showed the strongest statistical significance and was associated with additional aberrations, such as 17p- and 15q-. Unsupervised clustering identified five DLBCL clusters with distinct genetic profiles, clinical characteristics and outcomes. Genetic features and clusters, associated with a different outcome in patients treated with R-CHOP, have been identified by arrayCGH.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

Uncovering functionally relevant signaling pathways using microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has fundamentally altered the way in which we now address basic biomedical questions. Microarrays technology facilitates a more complete and inclusive experimental approach where alterations in the transcript level of entire genomes can be simultaneously assayed in response to a variety of stimuli. Conceptually different approaches to the development of microarray technology have resulted in the generation of two different array formats: oligonucleotide arrays and cDNA arrays. The application of microarray and related technologies to identify specific targets of defined genes that have clearly been implicated in cancer progression requires a specific experimental approach. The objective of tiffs approach is to define changes in transcriptional profile that occur in response to modulating the expression level of the gene to be studied. The resulting altered expression profile can then be viewed as a blueprint by which that gene effects its cellular function. We have used oligonucleotide array-based expression profiling in collaboration with Affymetrix to identify downstream transcriptional targets of the BRCA1 tumor-suppressor gene as a means of defining its function. BRCA1 has been implicated in at least three functional pathways, namely, mediating the cellular response to DNA damage, as a cell cycle checkpoint protein and in the regulation of transcription. The physiological significance of these properties and their implications for the function of BRCA1 as a tumor-suppressor gene remain to be defined.

RMA with quantile normalization mixes biological signals between different sample groups in microarray data analysis

Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

Genome-wide linkage and association analyses to identify genes influencing adiponectin levels: the GEMS Study.

Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10(-7)). These two SNPs were in high linkage disequilibrium (r(2) = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 x 10(-5)) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.

Pregnancy-induced chromatin remodeling in the breast of postmenopausal women.

Early pregnancy and multiparity are known to reduce the risk of women to develop breast cancer at menopause. Based on the knowledge that the differentiation of the breast induced by the hormones of pregnancy plays a major role in this protection, this work was performed with the purpose of identifying what differentiation-associated molecular changes persist in the breast until menopause. Core needle biopsies (CNB) obtained from the breast of 42 nulliparous (NP) and 71 parous (P) postmenopausal women were analyzed in morphology, immunocytochemistry and gene expression. Whereas in the NP breast, nuclei of epithelial cells were large and euchromatic, in the P breast they were small and hyperchromatic, showing strong methylation of histone 3 at lysine 9 and 27. Transcriptomic analysis performed using Affymetrix HG_U133 oligonucleotide arrays revealed that in CNB of the P breast, there were 267 upregulated probesets that comprised genes controlling chromatin organization, transcription regulation, splicing machinery, mRNA processing and noncoding elements including XIST. We concluded that the differentiation process induced by pregnancy is centered in chromatin remodeling and in the mRNA processing reactome, both of which emerge as important regulatory pathways. These are indicative of a safeguard step that maintains the fidelity of the transcription process, becoming the ultimate mechanism mediating the protection of the breast conferred by full-term pregnancy.