Marit Holden

The Genomic HyperBrowser: inferential genomics at the sequence level

The immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. We propose a first principled approach to statistical analysis of sequence-level genomic information. We provide a growing collection of generic biological investigations that query pairwise relations between tracks, represented as mathematical objects, along the genome. The Genomic HyperBrowser implements the approach and is available at http://hyperbrowser.uio.no.

Deep Sequencing the MicroRNA Transcriptome in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading causes of cancer related deaths and the search for prognostic biomarkers that might improve treatment decisions is warranted. MicroRNAs (miRNAs) are short non-coding RNA molecules involved in regulating gene expression and have been proposed as possible biomarkers in CRC. In order to characterize the miRNA transcriptome, a large cohort including 88 CRC tumors with long-term follow-up was deep sequenced. 523 mature miRNAs were expressed in our cohort, and they exhibited largely uniform expression patterns across tumor samples. Few associations were found between clinical parameters and miRNA expression, among them, low expression of miR-592 and high expression of miR-10b-5p and miR-615-3p were associated with tumors located in the right colon relative to the left colon and rectum. High expression of miR-615-3p was also associated with poorly differentiated tumors. No prognostic biomarker candidates for overall and metastasis-free survival were identified by applying the LASSO method in a Cox proportional hazards model or univariate Cox. Examination of the five most abundantly expressed miRNAs in the cohort (miR-10a-5p, miR-21-5p, miR-22-3p, miR-143-3p and miR-192-5p) revealed that their collective expression represented 54% of the detected miRNA sequences. Pathway analysis of the target genes regulated by the five most highly expressed miRNAs uncovered a significant number of genes involved in the CRC pathway, including APC, TGFβ and PI3K, thus suggesting that these miRNAs are relevant in CRC.

Hypoxia-Induced Gene Expression in Chemoradioresistant Cervical Cancer Revealed by Dynamic Contrast-Enhanced MRI

Knowledge of the molecular background of functional magnetic resonance (MR) images is required to fully exploit their potential in cancer management. We explored the prognostic impact of dynamic contrast-enhanced MR imaging (DCE-MRI) parameters in cervical cancer combined with global gene expression data to reveal their underlying molecular phenotype and construct a representative gene signature for the relevant parameter. On the basis of 78 patients with cervical cancer subjected to curative chemoradiotherapy, we identified the prognostic DCE-MRI parameter A(Brix) by pharmacokinetic analysis of pretreatment images based on the Brix model, in which tumors with low A(Brix) appeared to be most aggressive. Gene set analysis of 46 tumors with pairwise DCE-MRI and gene expression data showed a significant correlation between A(Brix) and the hypoxia gene sets, whereas gene sets related to other tumor phenotypes were not significant. Hypoxia gene sets specific for cervical cancer created in cell culture experiments, including both targets of the hypoxia inducible factor (HIF1α) and the unfolded protein response, were the most significant. In the remaining 32 tumors, low A(Brix) was associated with upregulation of HIF1α protein expression, as assessed by immunohistochemistry, consistent with increased hypoxia. On the basis of the hypoxia gene sets, a signature of 31 genes that were upregulated in tumors with low A(Brix) was constructed. This DCE-MRI hypoxia gene signature showed prognostic impact in an independent validation cohort of 109 patients. Our findings reveal the molecular basis of an aggressive hypoxic phenotype and suggest the use of DCE-MRI to noninvasively identify patients with hypoxia-related chemoradioresistance.

Eight genes are highly associated with BMD variation in postmenopausal Caucasian women

Low bone mineral density (BMD) is an important risk factor for skeletal fractures which occur in about 40% of women >/=50 years in the western world. We describe the transcriptional changes in 84 trans-iliacal bone biopsies associated with BMD variations in postmenopausal females (50 to 86 years), aiming to identify genetic determinants of bone structure. The women were healthy or having a primary osteopenic or osteoporotic status with or without low energy fractures. The total cohort of 91 unrelated women representing a wide range of BMDs, were consecutively registered and submitted to global gene Affymetrix microarray expression analysis or histomorphometry. Among almost 23,000 expressed transcripts, a set represented by ACSL3 (acyl-CoA synthetase long-chain family member 3), NIPSNAP3B (nipsnap homolog 3B), DLEU2 (Deleted in lymphocytic leukemia, 2), C1ORF61 (Chromosome 1 open reading frame 61), DKK1 (Dickkopf homolog 1), SOST (Sclerostin), ABCA8, (ATP-binding cassette, sub-family A, member 8), and uncharacterized (AFFX-M27830-M-at), was significantly correlated to total hip BMD (5% false discovery rate) explaining 62% of the BMD variation expressed as T-score, 53% when adjusting for the influence of age (Z-score) and 44% when further adjusting for body mass index (BMI). Only SOST was previously associated to BMD, and the majority of the genes have previously not been associated with a bone phenotype. In molecular network analyses, SOST shows a strong, positive correlation with DKK1, both being members of the Wnt signaling pathway. The results provide novel insight in the underlying biology of bone metabolism and osteoporosis which is the ultimate consequence of low BMD.

Effects of mRNA amplification on gene expression ratios in cDNA experiments estimated by analysis of variance

BackgroundA limiting factor of cDNA microarray technology is the need for a substantial amount of RNA per labeling reaction. Thus, 20–200 micro-grams total RNA or 0.5–2 micro-grams poly (A) RNA is typically required for monitoring gene expression. In addition, gene expression profiles from large, heterogeneous cell populations provide complex patterns from which biological data for the target cells may be difficult to extract. In this study, we chose to investigate a widely used mRNA amplification protocol that allows gene expression studies to be performed on samples with limited starting material. We present a quantitative study of the variation and noise present in our data set obtained from experiments with either amplified or non-amplified material.ResultsUsing analysis of variance (ANOVA) and multiple hypothesis testing, we estimated the impact of amplification on the preservation of gene expression ratios. Both methods showed that the gene expression ratios were not completely preserved between amplified and non-amplified material. We also compared the expression ratios between the two cell lines for the amplified material with expression ratios between the two cell lines for the non-amplified material for each gene. With the aid of multiple t-testing with a false discovery rate of 5%, we found that 10% of the genes investigated showed significantly different expression ratios.ConclusionAlthough the ratios were not fully preserved, amplification may prove to be extremely useful with respect to characterizing low expressing genes.

Gene Dosage, Expression, and Ontology Analysis Identifies Driver Genes in the Carcinogenesis and Chemoradioresistance of Cervical Cancer

Integrative analysis of gene dosage, expression, and ontology (GO) data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q) associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1) and 13q (FAM48A, MED4) correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Blood cell gene expression associated with cellular stress defense is modulated by antioxidant-rich food in a randomised controlled clinical trial of male smokers

BackgroundPlant-based diets rich in fruit and vegetables can prevent development of several chronic age-related diseases. However, the mechanisms behind this protective effect are not elucidated. We have tested the hypothesis that intake of antioxidant-rich foods can affect groups of genes associated with cellular stress defence in human blood cells. Trial registration number: NCT00520819 http://clinicaltrials.gov.MethodsIn an 8-week dietary intervention study, 102 healthy male smokers were randomised to either a diet rich in various antioxidant-rich foods, a kiwifruit diet (three kiwifruits/d added to the regular diet) or a control group. Blood cell gene expression profiles were obtained from 10 randomly selected individuals of each group. Diet-induced changes on gene expression were compared to controls using a novel application of the gene set enrichment analysis (GSEA) on transcription profiles obtained using Affymetrix HG-U133-Plus 2.0 whole genome arrays.ResultsChanges were observed in the blood cell gene expression profiles in both intervention groups when compared to the control group. Groups of genes involved in regulation of cellular stress defence, such as DNA repair, apoptosis and hypoxia, were significantly upregulated (GSEA, FDR q-values < 5%) by both diets compared to the control group. Genes with common regulatory motifs for aryl hydrocarbon receptor (AhR) and AhR nuclear translocator (AhR/ARNT) were upregulated by both interventions (FDR q-values < 5%). Plasma antioxidant biomarkers (polyphenols/carotenoids) increased in both groups.ConclusionsThe observed changes in the blood cell gene expression profiles suggest that the beneficial effects of a plant-based diet on human health may be mediated through optimization of defence processes.

Limitations of mRNA amplification from small-size cell samples

BackgroundGlobal mRNA amplification has become a widely used approach to obtain gene expression profiles from limited material. An important concern is the reliable reflection of the starting material in the results obtained. This is especially important with extremely low quantities of input RNA where stochastic effects due to template dilution may be present. This aspect remains under-documented in the literature, as quantitative measures of data reliability are most often lacking. To address this issue, we examined the sensitivity levels of each transcript in 3 different cell sample sizes. ANOVA analysis was used to estimate the overall effects of reduced input RNA in our experimental design. In order to estimate the validity of decreasing sample sizes, we examined the sensitivity levels of each transcript by applying a novel model-based method, TransCount.ResultsFrom expression data, TransCount provided estimates of absolute transcript concentrations in each examined sample. The results from TransCount were used to calculate the Pearson correlation coefficient between transcript concentrations for different sample sizes. The correlations were clearly transcript copy number dependent. A critical level was observed where stochastic fluctuations became significant. The analysis allowed us to pinpoint the gene specific number of transcript templates that defined the limit of reliability with respect to number of cells from that particular source. In the sample amplifying from 1000 cells, transcripts expressed with at least 121 transcripts/cell were statistically reliable and for 250 cells, the limit was 1806 transcripts/cell. Above these thresholds, correlation between our data sets was at acceptable values for reliable interpretation.ConclusionThese results imply that the reliability of any amplification experiment must be validated empirically to justify that any gene exists in sufficient quantity in the input material. This finding has important implications for any experiment where only extremely small samples such as single cell analyses or laser captured microdissected cells are available.

Molecular disease map of bone characterizing the postmenopausal osteoporosis phenotype

Genome‐wide gene expressions in bone biopsies from patients with postmenopausal osteoporosis and healthy controls were profiled, to identify osteoporosis candidate genes. All osteoporotic patients (n = 27) in an unbiased cohort of Norwegian women presented with bone mineral density (BMD) T‐scores of less than −2.5 SD and one or more confirmed low‐energy fracture(s). A validation group (n = 18) had clinical and laboratory parameters intermediate to the control (n = 39) and osteoporosis groups. RNA from iliac crest bone biopsies were analyzed by Affymetrix microarrays and real‐time reverse‐transcriptase polymerase chain reaction (RT‐PCR). Differentially expressed genes in osteoporosis versus control groups were identified using the Bayesian ANOVA for microarrays (BAMarray) method, whereas the R‐package Limma (Linear Models for Microarray Data) was used to determine whether these transcripts were explained by disease, age, body mass index (BMI), or combinations thereof. Laboratory tests showed normal ranges for the cohort. A total of 609 transcripts were differentially expressed in osteoporotic patients relative to controls; 256 transcripts were confirmed for disease when controlling for age or BMI. Most of the osteoporosis susceptibility genes (80%) also were confirmed to be regulated in the same direction in the validation group. Furthermore, 217 of 256 transcripts were correlated with BMD (adjusted for age and BMI) at various skeletal sites (|r| > 0.2, p < .05). Among the most distinctly expressed genes were Wnt antagonists DKK1 and SOST, the transcription factor SOX4, and the bone matrix proteins MMP13 and MEPE, all reduced in osteoporosis versus control groups. Our results identify potential osteoporosis susceptibility candidate genes adjusted for confounding factors (ie, age and BMI) with or without a significant correlation with BMD.

Whole blood gene expression in infants with respiratory syncytial virus bronchiolitis

BackgroundRespiratory syncytial virus (RSV) is a major cause of viral bronchiolitis in infants worldwide, and environmental, viral and host factors are all of importance for disease susceptibility and severity. To study the systemic host response to this disease we used the microarray technology to measure mRNA gene expression levels in whole blood of five male infants hospitalised with acute RSV, subtype B, bronchiolitis versus five one year old male controls exposed to RSV during infancy without bronchiolitis. The gene expression levels were further evaluated in a new experiment using quantitative real-time polymerase chain reaction (QRT-PCR) both in the five infants selected for microarray and in 13 other infants hospitalised with the same disease.ResultsAmong the 30 genes most differentially expressed by microarray nearly 50% were involved in immunological processes. We found the highly upregulated interferon, alpha-inducible protein 27 (IFI27) and the highly downregulated gene Charcot-Leyden crystal protein (CLC) to be the two most differentially expressed genes in the microarray study. When performing QRT-PCR on these genes IFI27 was upregulated in all but one infant, and CLC was downregulated in all 18 infants, and similar to that given by microarray.ConclusionThe gene IFI27 is upregulated and the gene CLC is downregulated in whole blood of infants hospitalised with RSV, subtype B, bronchiolitis and is not reported before. More studies are needed to elucidate the specificity of these gene expressions in association with host response to this virus in bronchiolitis of moderate severity.