The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.

Epithelial ovarian cancer (EOC) has a 5-year relative survival of 50%, partly because markers of early-stage disease are not available in current clinical diagnostics. The aim of the present study was to investigate whether EOC is associated with transcriptional profiles in blood collected up to 7 years before diagnosis. For this, we used RNA-stabilized whole blood, which contains circulating immune cells, from a sample of EOC cases from the population-based Norwegian Women and Cancer (NOWAC) postgenome cohort. We explored case-control differences in gene expression in all EOC (66 case-control pairs), as well as associations between gene expression and metastatic EOC (56 pairs), serous EOC (45 pairs, 44 of which were metastatic), and interval from blood sample collection to diagnosis (≤3 or >3 years; 34 and 31 pairs, respectively). Lastly, we assessed differential expression of genes associated with EOC in published functional genomics studies that used blood samples collected from newly diagnosed women. After adjustment for multiple testing, this nested case-control study revealed no significant case-control differences in gene expression in all EOC (false discovery rate q>0.96). With the exception of a few probes, the log2 fold change values obtained in gene-wise linear models were below ±0.2. P-values were lowest in analyses of metastatic EOC (80% of which were serous EOC). No common transcriptional profile was indicated by interval to diagnosis; when comparing the 100 genes with the lowest p-values in gene-wise tests in samples collected ≤3 and >3 years before EOC diagnosis, no overlap in these genes was observed. Among 86 genes linked to ovarian cancer in previous publications, our data contained expression values for 42, and of these, tests of LIME1, GPR162, STAB1, and SKAP1, resulted in unadjusted p<0.05. Although limited by sample size, our findings indicated less variation in blood gene expression between women with similar tumor characteristics.

Transcriptomic signals in blood prior to lung cancer focusing on time to diagnosis and metastasis.

Recent studies have indicated that there are functional genomic signals that can be detected in blood years before cancer diagnosis. This study aimed to assess gene expression in prospective blood samples from the Norwegian Women and Cancer cohort focusing on time to lung cancer diagnosis and metastatic cancer using a nested case-control design. We employed several approaches to statistically analyze the data and the methods indicated that the case-control differences were subtle but most distinguishable in metastatic case-control pairs in the period 0-3 years prior to diagnosis. The genes of interest along with estimated blood cell populations could indicate disruption of immunological processes in blood. The genes identified from approaches focusing on alterations with time to diagnosis were distinct from those focusing on the case-control differences. Our results support that explorative analyses of prospective blood samples could indicate circulating signals of disease-related processes.

Global blood gene expression profiles following a breast cancer diagnosis-Clinical follow-up in the NOWAC post-genome cohort.

OBJECTIVE: This explorative study aimed to assess if there are any time-dependent blood gene expression changes during the first one to eight years after breast cancer diagnosis, which can be linked to the clinical outcome of the disease. MATERIAL AND METHODS: A random distribution of follow-up time from breast cancer diagnosis till blood sampling was obtained by a nested, matched case-control design in the Norwegian Women and Cancer Post-genome Cohort. From 2002-5, women were invited to donate blood samples, regardless of any cancer diagnosis. At end of the study period in 2015, any cancer diagnoses in the 50 000 participants were obtained via linkage to the Norwegian Cancer Registry. For each breast cancer patient (n = 415), an age- and storage time-matched control was drawn. The design gave a uniform, random length of follow-up time, independent of cancer stage. Differences in blood gene expression between breast cancer cases and controls were identified using the Bioconductor R-package limma, using a moving window in time, to handle the varying time elapsed from diagnosis to blood sample. RESULTS: The number of differentially expressed genes between cases and controls were close to 2,000 in the first year after diagnosis, but fell sharply the second year. During the next years, a transient second increase was observed, but only in women with metastatic disease who later died, both compared to invasive cases that survived (p<0,001) and to metastatic cases that survived (p = 0.024). Among the differentially expressed genes there was an overrepresentation of heme metabolism and T cell-related processes. CONCLUSION: This explorative analysis identified changing trajectories in the years after diagnosis, depending on clinical stage. Hypothetically, this could represent the escape of the metastatic cancer from the immune system.

User-Intended Doppler Measurement Type Prediction Combining CNNs With Smart Post-Processing.

Spectral Doppler measurements are an important part of the standard echocardiographic examination. These measurements give insight into myocardial motion and blood flow, providing clinicians with parameters for diagnostic decision making. Many of these measurements are performed automatically with high accuracy, increasing the efficiency of the diagnostic pipeline. However, full automation is not yet available because the user must manually select which measurement should be performed on each image. In this work, we develop a pipeline based on convolutional neural networks (CNNs) to automatically classify the measurement type from cardiac Doppler scans. We show how the multi-modal information in each spectral Doppler recording can be combined using a meta parameter post-processing mapping scheme and heatmaps to encode coordinate locations. Additionally, we experiment with several architectures to examine the tradeoff between accuracy, speed, and memory usage for resource-constrained environments. Finally, we propose a confidence metric using the values in the last fully connected layer of the network and show that our confidence metric can prevent many misclassifications. Our algorithm enables a fully automatic pipeline from acquisition to Doppler spectrum measurements. We achieve 96% accuracy on a test set drawn from separate clinical sites, indicating that the proposed method is suitable for clinical adoption.

Distinct Subsets of Noncoding RNAs Are Strongly Associated With BMD and Fracture, Studied in Weight-Bearing and Non-Weight-Bearing Human Bone.

We investigated mechanisms resulting in low bone mineral density (BMD) and susceptibility to fracture by comparing noncoding RNAs (ncRNAs) in biopsies of non-weight-bearing (NWB) iliac (n = 84) and weight bearing (WB) femoral (n = 18) postmenopausal bone across BMDs varying from normal (T-score > -1.0) to osteoporotic (T-score ≤ -2.5). Global bone ncRNA concentrations were determined by PCR and microchip analyses. Association with BMD or fracture, adjusted by age and body mass index, were calculated using linear and logistic regression and least absolute shrinkage and selection operator (Lasso) analysis. At 10% false discovery rate (FDR), 75 iliac bone ncRNAs and 94 femoral bone ncRNAs were associated with total hip BMD. Eight of the ncRNAs were common for the two sites, but five of them (miR-484, miR-328-3p, miR-27a-5p, miR-28-3p, and miR-409-3p) correlated positively to BMD in femoral bone, but negatively in iliac bone. Of predicted pathways recognized in bone metabolism, ECM-receptor interaction and proteoglycans in cancer emerged at both sites, whereas fatty acid metabolism and focal adhesion were only identified in iliac bone. Lasso analysis and cross-validations identified sets of nine bone ncRNAs correlating strongly with adjusted total hip BMD in both femoral and iliac bone. Twenty-eight iliac ncRNAs were associated with risk of fracture (FDR < 0.1). The small nucleolar RNAs, RNU44 and RNU48, have a function in stabilization of ribosomal RNAs (rRNAs), and their association with fracture and BMD suggest that aberrant processing of rRNAs may be involved in development of osteoporosis. Cis-eQTL (expressed quantitative trait loci) analysis of the iliac bone biopsies identified two loci associated with microRNAs (miRNAs), one previously identified in a heel-BMD genomewide association study (GWAS). In this comprehensive investigation of the skeletal genetic background in postmenopausal women, we identified functional bone ncRNAs associated to fracture and BMD, representing distinct subsets in WB and NWB skeletal sites. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

Each pregnancy linearly changes immune gene expression in the blood of healthy women compared with breast cancer patients.

BACKGROUND: There is a large body of evidence demonstrating long-lasting protective effect of each full-term pregnancy (FTP) on the development of breast cancer (BC) later in life, a phenomenon that could be related to both hormonal and immunological changes during pregnancies. In this work, we studied the pregnancy-associated differences in peripheral blood gene expression profiles between healthy women and women diagnosed with BC in a prospective design. METHODS: Using an integrated system epidemiology approach, we modeled BC incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort (165,000 women) and then tested the resulting mathematical model using gene expression profiles in blood in a nested case-control study (460 invasive case-control pairs) of women from the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. RESULTS: A linear trend fitted the dataset precisely showing an 8% decrease in risk of BC for each FTP, independent of stratification on other risk factors and lasting for decades after a woman's last FTP. Women with six children demonstrated 48% reduction in the incidence of BC compared to nulliparous. When we looked at gene expression, we found that 756 genes showed linear trends in cancer-free controls (false discovery rate [FDR] 5%), but this was not the case for any of the genes in BC cases. Gene set enrichment analysis of immunologic gene sets (C7 collection in Molecular Signatures Database) revealed 215 significantly enriched human gene sets (FDR 5%). CONCLUSION: We found marked differences in gene expression and enrichment profiles of immunologic gene sets between BC cases and healthy controls, suggesting an important protective effect of the immune system on BC risk.

Signalling pathways identified in salivary glands from primary Sjögren's syndrome patients reveal enhanced adipose tissue development.

A characteristic feature of primary Sjögren's syndrome (pSS) is the destruction of salivary and lacrimal glands mediated by mononuclear cell infiltration. Adipocytes can also occupy a large portion of the salivary gland (SG) tissue area, although little is known about their significance in pSS. We have previously investigated adipose tissue infiltration in SG biopsies from pSS patients and non-SS sicca controls. Our findings indicated the distinct incidence of adipose tissue replacement in pSS patients, where adipocytes were detected in interleukin (IL) 6 rich regions. We now aimed to examine the development of adipocytes in the SG microenvironment, and delineate their possible involvement in immune reactions. A microarray analysis was performed on SG from 6 pSS patients and 6 non-SS controls, where the expression levels of genes involved in adipose tissue development, inflammatory responses, and lymphoma development were assessed. Real-time PCR was carried out on SG from 14 pSS patients and 15 non-SS controls to account for IL6, IL10, and IL17 mRNA levels. Immunohistochemical staining of frozen SG tissue using IL17 was also conducted. Our results indicate signalling pathways identified in SG of pSS patients displayed genes leading to prominent adipose tissue development and reduced mitochondrial fatty acid beta-oxidation (ARID5B, OXCT1, BDH1, SOX8, HMGCS2, FTO, ECHS1, PCCA, ACADL and ACADVL), inflammatory responses (IL1R1, IL7R, IL10RA, IL15, IL18RAP, CCL2, CCL5, CCL22, CXCR6, CD14, and CD48), and lymphoma development via JAK-STAT signalling (STAT2, TYK2, EBI3, FAS, TNFRSF1B, MAP3K8, HMOX1, LTB, TNF, STAT1, and BAK1). Genes involved in interferon production and signalling were also detected (IRF1, IRF9, and IRF7), in addition to IL6, IL10, and IL17. Higher mRNA levels of IL6, IL17 and IL10 were observed in the SG of pSS patients compared to controls. Moreover, IL17 positive cells were detected mostly interstitially in the SG and around adipocytes, also within the focal infiltrates. In conclusion, adipocyte development seems to be more prominent in the SG of pSS patients, where adipose tissue replacement is also evident. Whether this is due to disease progression, or the repair process, remains to be investigated. Detection of IL17 positive adipocytes in the target organ suggests their involvement in immune reactions.

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome.

Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

The PBMC transcriptome profile after intake of oxidized versus high-quality fish oil: an explorative study in healthy subjects.

BACKGROUND: Marine long-chain polyunsaturated fatty acids are susceptible to oxidation, generating a range of different oxidation products with suggested negative health effects. The aim of the present study was to utilize sensitive high-throughput transcriptome analyses to investigate potential unfavorable effects of oxidized fish oil (PV: 18 meq/kg; AV: 9) compared to high-quality fish oil (PV: 4 meq/kg; AV: 3). METHODS: In a double-blinded randomized controlled study for seven weeks, 35 healthy subjects were assigned to 8 g of either oxidized fish oil or high quality fish oil. The daily dose of EPA+DHA was 1.6 g. Peripheral blood mononuclear cells were isolated at baseline and after 7 weeks and transcriptome analyses were performed with the illuminaHT-12 v4 Expression BeadChip. RESULTS: No gene transcripts, biological processes, pathway or network were significantly changed in the oxidized fish oil group compared to the fish oil group. Furthermore, gene sets related to oxidative stress and cardiovascular disease were not differently regulated between the groups. Within group analyses revealed a more prominent effect after intake of high quality fish oil as 11 gene transcripts were significantly (FDR < 0.1) changed from baseline versus three within the oxidized fish oil group. CONCLUSION: The suggested concern linking lipid oxidation products to short-term unfavorable health effects may therefore not be evident at a molecular level in this explorative study. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01034423.

A new statistical method for curve group analysis of longitudinal gene expression data illustrated for breast cancer in the NOWAC postgenome cohort as a proof of principle.

BACKGROUND: The understanding of changes in temporal processes related to human carcinogenesis is limited. One approach for prospective functional genomic studies is to compile trajectories of differential expression of genes, based on measurements from many case-control pairs. We propose a new statistical method that does not assume any parametric shape for the gene trajectories. METHODS: The trajectory of a gene is defined as the curve representing the changes in gene expression levels in the blood as a function of time to cancer diagnosis. In a nested case-control design it consists of differences in gene expression levels between cases and controls. Genes can be grouped into curve groups, each curve group corresponding to genes with a similar development over time. The proposed new statistical approach is based on a set of hypothesis testing that can determine whether or not there is development in gene expression levels over time, and whether this development varies among different strata. Curve group analysis may reveal significant differences in gene expression levels over time among the different strata considered. This new method was applied as a "proof of concept" to breast cancer in the Norwegian Women and Cancer (NOWAC) postgenome cohort, using blood samples collected prospectively that were specifically preserved for transcriptomic analyses (PAX tube). Cohort members diagnosed with invasive breast cancer through 2009 were identified through linkage to the Cancer Registry of Norway, and for each case a random control from the postgenome cohort was also selected, matched by birth year and time of blood sampling, to create a case-control pair. After exclusions, 441 case-control pairs were available for analyses, in which we considered strata of lymph node status at time of diagnosis and time of diagnosis with respect to breast cancer screening visits. RESULTS: The development of gene expression levels in the NOWAC postgenome cohort varied in the last years before breast cancer diagnosis, and this development differed by lymph node status and participation in the Norwegian Breast Cancer Screening Program. The differences among the investigated strata appeared larger in the year before breast cancer diagnosis compared to earlier years. CONCLUSIONS: This approach shows good properties in term of statistical power and type 1 error under minimal assumptions. When applied to a real data set it was able to discriminate between groups of genes with non-linear similar patterns before diagnosis.

Age and pro-inflammatory gene polymorphisms influence adjacent segment disc degeneration more than fusion does in patients treated for chronic low back pain.

PURPOSE: Does lumbar fusion lead to accelerated adjacent segment disc degeneration (ASDD) or is it explained by genetics and aging? The influence of genetics on ASDD remains to be explored. This study assesses whether the disc space height adjacent to a fused segment is associated with candidate gene single nucleotide polymorphisms (SNPs). METHODS: Patients with low back pain from four RCTs (N = 208 fusion; 77 non-operative treatment) underwent standing plain radiography and genetic analyses at 13 ± 4 years follow-up. Disc space height was measured using a validated computer-assisted distortion-compensated roentgen analysis technique and reported in standard deviations from normal values. Genetic association analyses included 34 SNPs in 25 structural, inflammatory, matrix degrading, apoptotic, vitamin D receptor and OA-related genes relevant to disc degeneration. These were analysed for their association with disc space height (after adjusting for age, gender, smoking, duration of follow-up and treatment group) first, separately, and then together in a stepwise multivariable model. RESULTS: Two SNPs from the IL18RAP gene (rs1420106 and rs917997) were each associated with a lower disc space height at the adjacent level (B = -0.34, p = 0.04 and B = -0.35, p = 0.04, respectively) and the MMP-9 gene SNP rs20544 was associated with a greater disc space height (B = 0.35, p = 0.04). Age (p < 0.001) and fusion (p < 0.008) were also significant variables in each analysis. The total explained variance in disc space height was for each SNP model 13-14 %, with 11-12 % of this being accounted for by the given SNP, 64-67 % by age and 19-22 % by fusion. In the multivariable regression analysis (with nine SNPs selected for entry, along with the covariates) the total explained variance in disc space height was 23 %, with the nine SNPs, age and fusion accounting for 45, 45 and 7 % of this, respectively. CONCLUSIONS: Age was the most significant determinant of adjacent segment disc space height followed by genetic factors, specifically inflammatory genes. Fusion explained a statistically significant but small proportion of the total variance. Much of the variance remained to be explained.

Gene expression profiling of Gram-negative bacteria-induced inflammation in human whole blood: The role of complement and CD14-mediated innate immune response.

Non-sterile pathogen-induced sepsis and sterile inflammation like in trauma or ischemia-reperfusion injury may both coincide with the life threatening systemic inflammatory response syndrome and multi-organ failure. Consequently, there is an urgent need for specific biomarkers in order to distinguish sepsis from sterile conditions. The overall aim of this study was to uncover putative sepsis biomarkers and biomarker pathways, as well as to test the efficacy of combined inhibition of innate immunity key players complement and Toll-like receptor co-receptor CD14 as a possible therapeutic regimen for sepsis. We performed whole blood gene expression analyses using microarray in order to profile Gram-negative bacteria-induced inflammatory responses in an ex vivo human whole blood model. The experiments were performed in the presence or absence of inhibitors of complement proteins (C3 and CD88 (C5a receptor 1)) and CD14, alone or in combination. In addition, we used blood from a C5-deficient donor. Anti-coagulated whole blood was challenged with heat-inactivated Escherichia coli for 2 h, total RNA was isolated and microarray analyses were performed on the Affymetrix GeneChip Gene 1.0 ST Array platform. The initial experiments were performed in duplicates using blood from two healthy donors. C5-deficiency is very rare, and only one donor could be recruited. In order to increase statistical power, a technical replicate of the C5-deficient samples was run. Subsequently, log2-transformed intensities were processed by robust multichip analysis and filtered using a threshold of four. In total, 73 microarray chips were run and analyzed. The normalized and filtered raw data have been deposited in NCBI's Gene Expression Omnibus (GEO) and are accessible with GEO Series accession number GSE55537. Linear models for microarray data were applied to estimate fold changes between data sets and the respective multiple testing adjusted p-values (FDR q-values). The interpretation of the data has been published by Lau et al. in an open access article entitled "CD14 and Complement Crosstalk and Largely Mediate the Transcriptional Response to Escherichia coli in Human Whole Blood as revealed by DNA Microarray" (Lau et al., 2015).

Multi-focus cluster labeling.

Document collections resulting from searches in the biomedical literature, for instance, in PubMed, are often so large that some organization of the returned information is necessary. Clustering is an efficient tool for organizing search results. To help the user to decide how to continue the search for relevant documents, the content of each cluster can be characterized by a set of representative keywords or cluster labels. As different users may have different interests, it can be desirable with solutions that make it possible to produce labels from a selection of different topical categories. We therefore introduce the concept of multi-focus cluster labeling to give users the possibility to get an overview of the contents through labels from multiple viewpoints. The concept for multi-focus cluster labeling has been established and has been demonstrated on three different document collections. We illustrate that multi-focus visualizations can give an overview of clusters along axes that general labels are not able to convey. The approach is generic and should be applicable to any biomedical (or other) domain with any selection of foci where appropriate focus vocabularies can be established. A user evaluation also indicates that such a multi-focus concept is useful.

Catechol-O-methyltransferase (COMT) gene polymorphisms are associated with baseline disability but not long-term treatment outcome in patients with chronic low back pain.

PURPOSE: To examine the association between COMT and OPRM1 gene polymorphisms and pain and disability at baseline and long-term follow-up in patients treated for chronic low back pain (LBP). METHODS: 371 of 767 unrelated European patients recruited from four randomised trials underwent genetic analyses at mean 11.4 years follow-up. 274 patients had fusion and 97 had non-operative treatment. Association analyses included disability, pain, five single nucleotide polymorphisms (SNPs) in the COMT gene, and one SNP in the OPRM1 gene. Analyses were adjusted for age, gender, smoking, analgesics and treatment. RESULTS: Disability at baseline was significantly associated with COMT SNPs rs4818 (p = 0.02), rs6269 (p = 0.007), rs4633 (p = 0.04) rs2075507 (p = 0.009), two haplotypes (p < 0.002), age, gender and smoking (p ≤ 0.002). No significant associations with clinical variables were observed for OPRM1, or for COMT at long-term follow-up. CONCLUSIONS: Results suggest that genetic factors are partly responsible for the variation in disability levels in patients presenting with chronic LBP being considered for surgery; in contrast, genetics has no influence on the long-term outcome of treatment.

CD14 and complement crosstalk and largely mediate the transcriptional response to Escherichia coli in human whole blood as revealed by DNA microarray.

Systemic inflammation like in sepsis is still lacking specific diagnostic markers and effective therapeutics. The first line of defense against intruding pathogens and endogenous damage signals is pattern recognition by e.g., complement and Toll-like receptors (TLR). Combined inhibition of a key complement component (C3 and C5) and TLR-co-receptor CD14 has been shown to attenuate certain systemic inflammatory responses. Using DNA microarray and gene annotation analyses, we aimed to decipher the effect of combined inhibition of C3 and CD14 on the transcriptional response to bacterial challenge in human whole blood. Importantly, combined inhibition reversed the transcriptional changes of 70% of the 2335 genes which significantly responded to heat-inactivated Escherichia coli by on average 80%. Single inhibition was less efficient (p<0.001) but revealed a suppressive effect of C3 on 21% of the responding genes which was partially counteracted by CD14. Furthermore, CD14 dependency of the Escherichia coli-induced response was increased in C5-deficient compared to C5-sufficient blood. The observed crucial distinct and synergistic roles for complement and CD14 on the transcriptional level correspond to their broad impact on the inflammatory response in human blood, and their combined inhibition may become inevitable in the early treatment of acute systemic inflammation.

A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions.

Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.

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, TGFß and PI3K, thus suggesting that these miRNAs are relevant in CRC.

The Genomic HyperBrowser: an analysis web server for genome-scale data.

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.

Treatment outcome of chronic low back pain and radiographic lumbar disc degeneration are associated with inflammatory and matrix degrading gene variants: a prospective genetic association study.

BACKGROUND: Inflammatory and matrix degrading gene variants have been reported to be associated with disc degeneration. Some of these variants also modulate peripheral pain. This study examines the association of these genetic variants with radiographic lumbar disc degeneration and changes in pain and disability at long-term after surgical and cognitive behavioural management. METHODS: 93 unrelated patients with chronic low back pain (CLBP) for duration of >1 year and lumbar disc degeneration were treated with lumbar fusion or cognitive intervention and exercises. Standardised questionnaires included the Oswestry Disability Index (ODI) and Visual Analog Score (VAS) for CLBP, were filled in by patients both at baseline and at 9 years follow-up. Degenerative changes at baseline Magnetic Resonance Imaging and Computed Tomography scans, were graded as moderate and severe (N=79). Yield and quality of blood and saliva DNA was assessed by nano drop spectrophotometry. Eight SNPs in 5 inflammatory and matrix degrading genes were successfully genotyped. Single marker and haplotype association with severity of degeneration, number of discs involved, changes in ODI and VAS CLBP, was done using Haploview, linear regression and R-package Haplostats. RESULTS: Association analysis of individual SNPs revealed association of IL18RAP polymorphism rs1420100 with severe degeneration (p = 0.05) and more than one degenerated disc (p = 0.02). From the same gene two SNPs, rs917997 and rs1420106, were found to be in strong linkage disequilibrium (LD) and were associated with post treatment improvement in disability (p = 0.02). Haplotype association analysis of 5 SNPs spanning across IL18RAP, IL18R1 and IL1A genes revealed significant associations with improvement in disability (p=0.02) and reduction in pain (p=0.04). An association was found between MMP3 polymorphism rs72520913 and improvement in pain (p = 0.03) and with severe degeneration (p = 0.006). CONCLUSIONS: The findings of the current study suggest a role of variation at inflammatory and matrix degrading genes with severity of lumbar disc degeneration, pain and disability.

Identification of eight candidate target genes of the recurrent 3p12-p14 loss in cervical cancer by integrative genomic profiling.

The pathogenetic role, including its target genes, of the recurrent 3p12-p14 loss in cervical cancer has remained unclear. To determine the onset of the event during carcinogenesis, we used microarray techniques and found that the loss was the most frequent 3p event, occurring in 61% of 92 invasive carcinomas, in only 2% of 43 high-grade intraepithelial lesions (CIN2/3), and in 33% of 6 CIN3 lesions adjacent to invasive carcinomas, suggesting a role in acquisition of invasiveness or early during the invasive phase. We performed an integrative DNA copy number and expression analysis of 77 invasive carcinomas, where all genes within the recurrent region were included. We selected eight genes, THOC7, PSMD6, SLC25A26, TMF1, RYBP, SHQ1, EBLN2, and GBE1, which were highly down-regulated in cases with loss, as confirmed at the protein level for RYBP and TMF1 by immunohistochemistry. The eight genes were subjected to network analysis based on the expression profiles, revealing interaction partners of proteins encoded by the genes that were coordinately regulated in tumours with loss. Several partners were shared among the eight genes, indicating crosstalk in their signalling. Gene ontology analysis showed enrichment of biological processes such as apoptosis, proliferation, and stress response in the network and suggested a relationship between down-regulation of the eight genes and activation of tumourigenic pathways. Survival analysis showed prognostic impact of the eight-gene signature that was confirmed in a validation cohort of 74 patients and was independent of clinical parameters. These results support the role of the eight candidate genes as targets of the 3p12-p14 loss in cervical cancer and suggest that the strong selection advantage of the loss during carcinogenesis might be caused by a synergetic effect of several tumourigenic processes controlled by these targets.