Erkka Valo

Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme.

BackgroundCoordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed.MethodsWe introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available.ResultsWe have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website.ConclusionsOur results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to generally applicable novel methodology, our results provide several glioblastoma multiforme candidate genes for further studies.Anduril is available at http://csbi.ltdk.helsinki.fi/anduril/The glioblastoma multiforme analysis results are available at http://csbi.ltdk.helsinki.fi/anduril/tcga-gbm/

ErbB2-Driven Breast Cancer Cell Invasion Depends on a Complex Signaling Network Activating Myeloid Zinc Finger-1-Dependent Cathepsin B Expression

Aberrant ErbB2 receptor tyrosine kinase activation in breast cancer is strongly linked to an invasive disease. The molecular basis of ErbB2-driven invasion is largely unknown. We show that cysteine cathepsins B and L are elevated in ErbB2 positive primary human breast cancer and function as effectors of ErbB2-induced invasion in vitro. We identify Cdc42-binding protein kinase beta, extracellular regulated kinase 2, p21-activated protein kinase 4, and protein kinase C alpha as essential mediators of ErbB2-induced cysteine cathepsin expression and breast cancer cell invasiveness. The identified signaling network activates the transcription of cathepsin B gene (CTSB) via myeloid zinc finger-1 transcription factor that binds to an ErbB2-responsive enhancer element in the first intron of CTSB. This work provides a model system for ErbB2-induced breast cancer cell invasiveness, reveals a signaling network that is crucial for invasion in vitro, and defines a specific role and targets for the identified serine-threonine kinases.

Posttranscriptional regulation of angiotensin II type 1 receptor expression by glyceraldehyde 3-phosphate dehydrogenase

Regulation of angiotensin II type 1 receptor (AT1R) has a pathophysiological role in hypertension, atherosclerosis and heart failure. We started from an observation that the 3′-untranslated region (3′-UTR) of AT1R mRNA suppressed AT1R translation. Using affinity purification for the separation of 3′-UTR-binding proteins and mass spectrometry for their identification, we describe glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as an AT1R 3′-UTR-binding protein. RNA electrophoretic mobility shift analysis with purified GAPDH further demonstrated a direct interaction with the 3′-UTR while GAPDH immunoprecipitation confirmed this interaction with endogenous AT1R mRNA. GAPDH-binding site was mapped to 1–100 of 3′-UTR. GAPDH-bound target mRNAs were identified by expression array hybridization. Analysis of secondary structures shared among GAPDH targets led to the identification of a RNA motif rich in adenines and uracils. Silencing of GAPDH increased the expression of both endogenous and transfected AT1R. Similarly, a decrease in GAPDH expression by H2O2 led to an increased level of AT1R expression. Consistent with GAPDH having a central role in H2O2-mediated AT1R regulation, both the deletion of GAPDH-binding site and GAPDH overexpression attenuated the effect of H2O2 on AT1R mRNA. Taken together, GAPDH is a translational suppressor of AT1R and mediates the effect of H2O2 on AT1R mRNA.

Identification of a c-Jun N-terminal kinase-2-dependent signal amplification cascade that regulates c-Myc levels in ras transformation

Ras is one of the most frequently activated oncogenes in cancer. Two mitogen-activated protein kinases (MAPKs) are important for ras transformation: extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase 2 (JNK2). Here we present a downstream signal amplification cascade that is critical for ras transformation in murine embryonic fibroblasts. This cascade is coordinated by ERK and JNK2 MAPKs, whose Ras-mediated activation leads to the enhanced levels of three oncogenic transcription factors, namely, c-Myc, activating transcription factor 2 (ATF2) and ATF3, all of which are essential for ras transformation. Previous studies show that ERK-mediated serine 62 phosphorylation protects c-Myc from proteasomal degradation. ERK is, however, not alone sufficient to stabilize c-Myc but requires the cooperation of cancerous inhibitor of protein phosphatase 2A (CIP2A), an oncogene that counteracts protein phosphatase 2A-mediated dephosphorylation of c-Myc. Here we show that JNK2 regulates Cip2a transcription via ATF2. ATF2 and c-Myc cooperate to activate the transcription of ATF3. Remarkably, not only ectopic JNK2, but also ectopic ATF2, CIP2A, c-Myc and ATF3 are sufficient to rescue the defective ras transformation of JNK2-deficient cells. Thus, these data identify the key signal converging point of JNK2 and ERK pathways and underline the central role of CIP2A in ras transformation.

The Genetic Landscape of Renal Complications in Type 1 Diabetes

Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10-5) and the risk of type 2 diabetes (P=6.1×10-4) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10-6), and pentose and glucuronate interconversions (P=3.0×10-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

Rituximab regulates signaling pathways and alters gene expression associated with cell death and survival in diffuse large B-cell lymphoma

Rituximab, a CD20-specific antibody, is used with chemotherapy as a treatment for diffuse large B cell lymphoma (DLBCL). Although many patients benefit from the addition of rituximab to chemotherapy, a favourable response is not achieved in approximately 30% of cases. This sets a prerequisite to better understand the response and resistance mechanisms of rituximab. To do so, we analyzed the gene expression profiles of one rituximab unresponsive and two responsive DLBCL cell lines. In the responsive cells, rituximab affected the expression of genes related to apoptosis, lymphocyte signaling and cytokine response. Our data show rituximab-response to be associated with gene expression in classical signaling cascades involved in cell growth and differentiation, such as previously identified MAPK and completely novel Wnt and TGF-β pathways. Furthermore, our findings support earlier observations that rituximab can induce direct apoptosis and suggest the cell of origin to be associated with the cellular outcome. After validation of cellular results, we used a cohort of 233 R-CHOP treated DLBCL patients and found several of the most differentiating genes to have impact on survival. Together, the results provide an advanced picture of the CD20 mediated signaling of DLBCL cells and may provide new targets in future treatment protocols.

Signal Transducers and Activators of Transcription 5a–Dependent Cross-talk between Follicular Lymphoma Cells and Tumor Microenvironment Characterizes a Group of Patients with Improved Outcome after R-CHOP

Purpose: Tumor microenvironment has a strong effect on the survival of follicular lymphoma (FL) patients. The aim of this study was to determine what are the signaling pathways that mediate the cross-talk between lymphoma cells and tumor-infiltrating inflammatory cells and contribute to the clinical outcome of FL patients. Experimental Design: Gene expression profiling and pathway impact analyses were done from pretreatment lymphoma tissue of 24 patients. The findings were validated immunohistochemically in an independent cohort of 81 patients. All patients were treated with the combination of rituximab and cyclophoshamide-doxorubicin-vincristine-prednisone chemotherapy. In addition, microarray was used to screen the genes differentially expressed between control and rituximab-stimulated B-cell lymphoma cells in culture. Results: Among the transcripts differentially expressed in the FL tissues between the patients with favorable or adverse outcomes, an overrepresentation of genes associated with the signal transducers and activators of transcription (STAT)5a pathway was observed. In a validation set, a better progression-free survival was observed among the patients with high STAT5a protein expression. In the FL tissue, STAT5a positivity was barely detectable in the neoplastic B cells, but a subpopulation of follicular dendritic cells and T lymphocytes showed prominent STAT5a expression. Rituximab was found to induce the expression of STAT5a-associated interleukin-15 in B-lymphoma cells in culture, thereby providing a possible explanation for the cross-talk between rituximab-stimulated FL cells and their microenvironment. Conclusion: The findings suggest that STAT5a activity in immunologically active nonmalignant cells acts as molecular predictor for rituximab and cyclophoshamide-doxorubicin-vincristine-prednisone–treated FL patients. Clin Cancer Res; 16(9); 2615–23. ©2010 AACR.

Novel Genetic Determinants of Diabetic Kidney Disease

1-OR Gene Expression Changes during the Progression of Diabetic Neuropathy in a Murine Model of Type 2 Diabetes MEEYOUNG PARK, LUCY M. HINDER, BEN MURDOCK, DIANE BENDER, PHILLIPE O’BRIEN, EVA L. FELDMAN, Ann Arbor, MI, St. Louis, MO Diabetic neuropathy (DN) is the most common complication in type 2 diabetes (T2D), affecting up to 50% of diabetic patients. Analysis of microarray and RNA-Seq data has identifi ed genes and pathways associated with DN in murine models; however, these previous transcriptome studies only examined specifi c time-points and longitudinal studies of DN pro gression are lacking. In the current study, we examined genes and path ways related to DN progression over time in dorsal root ganglia (DRG) and sciatic nerve (SCN) of C57BKS db/db mice, a well-characterized murine model of T2D. Peripheral nerve function was assessed at 8 (early neuropathy), 16 (intermediate neuropathy), and 24 (late neuropathy) weeks of age in control db/+ and diabetic db/db mice, and microarray data from each cohort were used to examine gene expression changes throughout the course of DN. Self-Organizing Maps (SOM), an unbiased clustering method, was used to identify genes demonstrating expression changes that coincided with DN progression in DRG and SCN. Functional and pathway enrichment analyses were performed for gene sets with patterns of interest. Results demonstrated that diabetic mice exhibit robust and progressive neuropathy compared to db/+ mice, with signifi cant changes in hindpaw withdrawal latency, intraepidermal nerve fi ber density, and sciatic motor nerve conduction velocity. SOM analysis identifi ed clusters of genes showing expression patterns correlated with the severity of neuropathy, with increasing or decreasing fold-changes as DN progressed. Specifi cally, the genes IL-2, IL-13, IL-17a, and Csf2 were enriched in infl ammation-associated pathways at 8 weeks in DRG and at 24 weeks in SCN. In addition, there was a 2-fold change in expression of genes enriched in cell death at 24 weeks in DRG and SCN. Together, these analyses identifi ed gene and pathway signatures that may play an important role in DN progression in T2D, and suggest potential pharmaceutical targets to prevent DN development. Supported By: American Diabetes Association (1-16-PDF-084 to M.P.); Novo Nordisk Inc.A key United Kingdom policy initiative in the management of diabetes is empowerment through structured education. Nonetheless, motivating attendance in Diabetes Education Centres remain problematic. The central aim of this study was to identify barriers and enabling factors associated with uptake of structured patient education for type 2 diabetes in a Primary Care Trust in South East of England. This three tier mixed methods study used a focus group interview to collect data from (n=10) diabetes educators (Dieticians, podiatrists and diabetes specialist nurses), questionnaire survey of 207 patients (102 attenders and 105 non-attenders), and finally individual face-to-face interviews (n=9) of referring practitioners (practice nurses) in different General Practitioners surgeries. The findings of the qualitative data yielded five key themes: healthcare beliefs, personal circumstances of the patient, ineffective communication, organisation of care and bureaucratic processes. The Chi-square tests run on the quantitative data relating to the health beliefs held by both groups suggested differences between attenders and non-attenders attitudes towards the uptake of Diabetes Education Programmes. Independent T-test, t (165.69) = 12.43, p < .001 results indicated that attenders in this study reported a more positive belief about self-care, importance of the diabetes education session and belief about the seriousness of diabetes as a medical condition in comparison to non-attenders. Logistic regression analysis of key demographic variables on attendance suggested that living arrangements (p < .001), employment (p < .001) and family history of diabetes (p = .05) can be used to predict non-attendance and the odd ratios also supported these findings. Whilst, it may be difficult to completely avoid non-attendance, positive steps to promote attendance include enhanced communication, organisational efficiency and offering adequate support to develop a positive attitude towards diabetes education.

Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme

Background: Cancers are complex diseases whose comprehensive characterization requires genome-scale molecular data at multiple levels from genetics to transcriptomics and clinical data. Using our recently published Anduril bioinformatics framework and novel computational approaches, such as dependency analysis, we identify key variables at miRNA, copy number variation, expression, methylation, and pathway levels in glioblastoma multiforme (GBM) progression and drug resistance. Furthermore, we identify characteristics of clinically relevant subgroups, such as patients treated with temozolomide and patients with an EGFRvIII mutation, which is a constitutively active variant of EGFR. Results: We identify several novel genomic regions and transcript profiles that may contribute to GBM progression and drug resistance. All results and Anduril scripts are available at http://csbi.ltdk.helsinki.fi/camda/. Conclusions: Our results highlight the need for approaches that define context at several levels in order to identify genomic regions or transcript profiles playing key roles in cancer progression and drug resistance.

Confirmation of GLRA3 as a susceptibility locus for albuminuria in Finnish patients with type 1 diabetes

Urinary albumin excretion is an early sign of diabetic kidney disease, affecting every third individual with diabetes. Despite substantial estimated heritability, only variants in the GLRA3 gene have been genome-wide significantly associated (p-value < 5 × 10−8) with diabetic albuminuria, in Finnish individuals with type 1 diabetes; However, replication attempt in non-Finnish Europeans with type 1 diabetes showed nominally significant association in the opposite direction, suggesting a population-specific effect, but simultaneously leaving the finding controversial. In this study, the association between the common rs10011025 variant in the GLRA3 locus, and albuminuria, was confirmed in 1259 independent Finnish individuals with type 1 diabetes (p = 0.0013), and meta-analysis of all Finnish individuals yielded a genome-wide significant association. The association was particularly pronounced in subjects not reaching the treatment target for blood glucose levels (HbA1c > 7%; N = 2560, p = 1.7 × 10−9). Even though further studies are needed to pinpoint the causal variants, dissecting the association at the GLRA3 locus may uncover novel molecular mechanisms for diabetic albuminuria irrespective of population background.