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Search Results: 1 - 10 of 308 matches for " Olli Kallioniemi "
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Analysis of Kinase Gene Expression Patterns across 5681 Human Tissue Samples Reveals Functional Genomic Taxonomy of the Kinome
Sami Kilpinen,Kalle Ojala,Olli Kallioniemi
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0015068
Abstract: Kinases play key roles in cell signaling and represent major targets for drug development, but the regulation of their activation and their associations with health and disease have not been systematically analyzed. Here, we carried out a bioinformatic analysis of the expression levels of 459 human kinase genes in 5681 samples consisting of 44 healthy and 55 malignant human tissues. Defining the tissues where the kinase genes were transcriptionally active led to a functional genomic taxonomy of the kinome and a classification of human tissues and disease types based on the similarity of their kinome gene expression. The co-expression network around each of the kinase genes was defined in order to determine the functional context, i.e. the biological processes that were active in the cells and tissues where the kinase gene was expressed. Strong associations for individual kinases were found for mitosis (69 genes, including AURKA and BUB1), cell cycle control (73 genes, including PLK1 and AURKB), DNA repair (49 genes, including CHEK1 and ATR), immune response (72 genes, including MATK), neuronal (131 genes, including PRKCE) and muscular (72 genes, including MYLK2) functions. We then analyzed which kinase genes gain or lose transcriptional activity in the development of prostate and lung cancers and elucidated the functional associations of individual cancer associated kinase genes. In summary, we report here a systematic classification of kinases based on the bioinformatic analysis of their expression in human tissues and diseases, as well as grouping of tissues and tumor types according to the similarity of their kinome transcription.
Chemical Biology Drug Sensitivity Screen Identifies Sunitinib as Synergistic Agent with Disulfiram in Prostate Cancer Cells
Kirsi Ketola, Olli Kallioniemi, Kristiina Iljin
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0051470
Abstract: Background Current treatment options for castration- and treatment-resistant prostate cancer are limited and novel approaches are desperately needed. Our recent results from a systematic chemical biology sensitivity screen covering most known drugs and drug-like molecules indicated that aldehyde dehydrogenase inhibitor disulfiram is one of the most potent cancer-specific inhibitors of prostate cancer cell growth, including TMPRSS2-ERG fusion positive cancers. However, the results revealed that disulfiram alone does not block tumor growth in vivo nor induce apoptosis in vitro, indicating that combinatorial approaches may be required to enhance the anti-neoplastic effects. Methods and Findings In this study, we utilized a chemical biology drug sensitivity screen to explore disulfiram mechanistic details and to identify compounds potentiating the effect of disulfiram in TMPRSS2-ERG fusion positive prostate cancer cells. In total, 3357 compounds including current chemotherapeutic agents as well as drug-like small molecular compounds were screened alone and in combination with disulfiram. Interestingly, the results indicated that androgenic and antioxidative compounds antagonized disulfiram effect whereas inhibitors of receptor tyrosine kinase, proteasome, topoisomerase II, glucosylceramide synthase or cell cycle were among compounds sensitizing prostate cancer cells to disulfiram. The combination of disulfiram and an antiangiogenic agent sunitinib was studied in more detail, since both are already in clinical use in humans. Disulfiram-sunitinib combination induced apoptosis and reduced androgen receptor protein expression more than either of the compounds alone. Moreover, combinatorial exposure reduced metastatic characteristics such as cell migration and 3D cell invasion as well as induced epithelial differentiation shown as elevated E-cadherin expression. Conclusions Taken together, our results propose novel combinatorial approaches to inhibit prostate cancer cell growth. Disulfiram-sunitinib combination was identified as one of the potent synergistic approaches. Since sunitinib alone has been reported to lack efficacy in prostate cancer clinical trials, our results provide a rationale for novel combinatorial approach to target prostate cancer more efficiently.
Classification of unknown primary tumors with a data-driven method based on a large microarray reference database
Kalle A Ojala, Sami K Kilpinen, Olli P Kallioniemi
Genome Medicine , 2011, DOI: 10.1186/gm279
Abstract: Cancer of unknown primary origin (CUP) is a classification given to a malignant neoplasm when a metastasis is discovered but the source of the primary tumor remains hidden. If counted together as a single clinical entity, CUP is one of the most common cancer types diagnosed in the world. Some 3 to 5% of all newly diagnosed cancers are CUPs, which qualifies this disease entity as one of the ten most common cancer types, with an incidence that is greater than that of, for example, leukemia or pancreatic cancers [1,2]. Even at autopsy, the location of the primary tumor remains a mystery in up to 70% of CUP cases [1,3]. CUPs present a significant challenge for physicians, since many of the current treatment regimes rely on knowledge of the type and origin of the primary tumor.Several methods for identifying CUP samples based on their gene expression profiles have been developed. Talantov et al. [4] and Varadhachary et al. [5] presented an RT-PCR based method that measures the expression of ten signature genes. Ma et al. [6] proposed a similar method based on 92 genes, which resulted in an overall accuracy of 82% among 39 cancer types. Tothill et al. [7] presented a support vector machine-based method for classifying cancer types, and selected 79 genes for an RT-PCR test reaching a total accuracy of 89% but only among 13 cancer types. Rosenfeld et al. [8] applied a similar approach, but instead of measuring traditional gene expression, they looked at microRNA expression to classify CUP samples. For a majority of the samples, they achieved approximately 90% classification accuracy.Since the development and adoption of gene expression microarrays, there has been interest in developing a microarray-based cancer classification, including a test to identify the origin of CUP cases. Microarrays provide a robust way to measure the expression of a large number of genes, and recently have been proven to be applicable in the clinical setting as well [9-12]. At least two custom mic
Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data
Sami K Kilpinen, Kalle A Ojala, Olli P Kallioniemi
BioData Mining , 2011, DOI: 10.1186/1756-0381-4-5
Abstract: AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database).Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation.The AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as proven here by the definition of tissue- and disease-specific changes in gene expression as well as during cellular differentiation. The capability to quantitatively compare data from individual samples against a large-scale annotated reference database represents a widely applicable paradigm for the analysis of all types of high-throughput data. AGEP enables systematic and quantitative comparison of gene expression data from test samples against a comprehensive collection of different cell/tissue types previously studied by the entire research community.Gene expression microarray data published by the entire biomedical community ha
A Multicenter, Randomized, Placebo-Controlled Study to Evaluate the Efficacy and Safety of Long-Acting Injectable Formulation of Vanoxerine (Vanoxerine Consta 394.2 mg) for Cocaine Relapse Prevention  [PDF]
Sead Kadric, Hanns Mohler, Olli Kallioniemi, Karl Heinz Altmann
World Journal of Neuroscience (WJNS) , 2019, DOI: 10.4236/wjns.2019.93008
Abstract: Objective: To determine the efficacy and tolerability of a long-acting intramuscular formulation of Vanoxerine (Vanoxerine Consta 394.2 mg) for treatment of cocaine-dependent patients. Design, Setting, and Participants: A 12-week, A multicenter, randomized, placebo-controlled trial conducted between June 2009-July 2011, at 17 Hospital-based drug clinics, in the 15 countries. Participants were 18 years or older, had Diagnostic and Statistical Manual of Mental Disorders-5 cocaine use disorder. Of the 2800 patients who were assessed between March 10, 2009 to August 10, 2010, 2600 (93%) were eligible and willing to take part in the trial and were enrolled: 1300 were randomly assigned to receive injections of Long-acting depot formulations of Vanoxerine (Vanoxerine Consta 394.2 mg) given intramuscularly once in 12 weeks and 1300 to receive Placebo injections, given intramuscularly once in 12 weeks. Only 100 of 2800 patients (3.6%) did not meet the inclusion criteria. Main Outcomes and Measures: The primary endpoints (protocol) were: Confirmed Cocaine abstinence (percentage i.e. the number of patients who achieved complete abstinence during 12 weeks). Confirmed abstinence or “cocaine-free” was defined as a negative urine drug test for cocaines and no self-reported cocaine use. Secondary end points included a number of days in treatment, treatment retention and craving. The study also investigated, on 275 participants, degree and time course of Central Dopamine transporter receptor occupancy following single doses of long-acting intramuscular formulation of Vanoxerine (Vanoxerine Consta 394.2 mg) as well as the plasma concentration of Vanoxerine and 17-hydroxyl Vanoxerine. Safety was assessed by adverse event reporting. Results: Of 2600 participants, mean (SD) age was 28.5 (±5.5) years and 598 (23%) were women. 1300 individuals were randomized to receive injections of Long-acting depot formulations of Vanoxerine (Vanoxerine Consta 394.2 mg) and 1300 to receive injections of Placebo. 1417 participants (54.5.0%) completed the trial. Primary Endpoints: Confirmed Cocaine Abstinence: Complete abstinence was sustained by 72% (n = 936) of Vanoxerine patients (patients treated with Vanoxerine Consta 394.2 mg, long-acting depot formulations) compared with 37% (n = 481) of patients treated with Placebo, during weeks 5 - 12. The difference was significant as evaluated using a Chi-square test (χ2 = 672.34, P < 0.0001). Secondary Endpoint: Craving: A statistically and
Efficacy and Tolerability of Long-Acting Injectable Formulation of Nalmefene (Nalmefene Consta 393.1 mg) for Opioid Relapse Prevention: A Multicentre, Open-Label, Randomised Controlled Trial  [PDF]
Sead Kadric, Hanns Mohler, Olli Kallioniemi, Karl Heinz Altmann
World Journal of Neuroscience (WJNS) , 2019, DOI: 10.4236/wjns.2019.93006
Abstract:
Objective: To determine the efficacy and tolerability of a long-acting intramuscular formulation of Nalmefene (Nalmefene Consta 393.1 mg) for the treatment of opioid-dependent patients. Design, Setting, and Participants: A 12 weeks, open-label, randomised controlled trial conducted between June 2009-July 2011, at 14 Hospital-based drug clinics, in the 12 countries. Participants were 18 years or older, had Diagnostic and Statistical Manual of Mental Disorders-5 opioid use disorder. Of the 3200 individuals screened, 3000 (93.7%) adults were randomized 1500 participants to receive injections of Long-acting depot formulations ofNalmefene (Nalmefene Consta 393.1 mg) given intramuscularly once in 12 weeks and 1500participants to receive extended-release Naltrexone (Vivitrol 380 mg), administered intramuscularly every fourth week for 12 weeks. Main Outcomes and Measures: The primary endpoints (protocol) were: Confirmed Opioid abstinence (percentage i.e. the number of patients who achieved complete abstinence during week 12). Confirmed abstinence or “opioid-free” was defined as a negative urine drug test for opioids and no self-reported opioid use. Weeks 1 - 4 were omitted from this endpoint to allow for stabilization of abstinence. Secondary end points included a number of days in treatment, treatment retention and craving. The study also investigated, on 275 participants, degree and time course of mu-opioid receptor occupancy following single doses of Nalmefene extended-release injection (Nalmefene Consta 393.1 mg) as well as the plasma concentration of Nalmefene and Nalmefene-3-O-glucuronide. Safety was assessed by adverse event reporting. Results: Of 3000 participants, mean (SD) age was 27.1 (±4.8) years and 831 (27.7%) were women. 1500 individuals were randomized to receive injections of Long-acting depot
Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms
Sara Kangaspeska, Susanne Hultsch, Henrik Edgren, Daniel Nicorici, Astrid Murum?gi, Olli Kallioniemi
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0048745
Abstract: RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.
The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition
Erik Fredlund, Johan Staaf, Juha K Rantala, Olli Kallioniemi, ?ke Borg, Markus Ringnér
Breast Cancer Research , 2012, DOI: 10.1186/bcr3236
Abstract: Modules of highly connected genes were extracted from a gene co-expression network that was constructed based on Pearson correlation, and module activities were then calculated using a pathway activity score. Functional annotations of modules were experimentally validated with an siRNA cell spot microarray system using the KPL-4 breast cancer cell line, and by using gene expression data from functional studies. Modules were derived using gene expression data representing 1,608 breast cancer samples and validated in data sets representing 971 independent breast cancer samples as well as 1,231 samples from other cancer forms.The initial co-expression network analysis resulted in the characterization of eight tightly regulated gene modules. Cell cycle genes were divided into two transcriptional programs, and experimental validation using an siRNA screen showed different functional roles for these programs during proliferation. The division of the two programs was found to act as a marker for tumor protein p53 (TP53) gene status in luminal breast cancer, with the two programs being separated only in luminal tumors with functional p53 (encoded by TP53). Moreover, a module containing fibroblast and stroma-related genes was highly expressed in fibroblasts, but was also up-regulated by overexpression of epithelial-mesenchymal transition factors such as transforming growth factor beta 1 (TGF-beta1) and Snail in immortalized human mammary epithelial cells. Strikingly, the stroma transcriptional program related to less malignant tumors for luminal disease and aggressive lymph node positive disease among basal-like tumors.We have derived a robust gene expression landscape of breast cancer that reflects known subtypes as well as heterogeneity within these subtypes. By applying the modules to TP53-mutated samples we shed light on the biological consequences of non-functional p53 in otherwise low-proliferating luminal breast cancer. Furthermore, as in the case of the stroma module
Identification of structural features in chemicals associated with cancer drug response: A systematic data-driven analysis
Suleiman A Khan,Seppo Virtanen,Olli P Kallioniemi,Krister Wennerberg,Antti Poso,Samuel Kaski
Quantitative Biology , 2013,
Abstract: Motivation: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug thera-pies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models. Results: In this paper, we present the first comprehensive multi-set analysis on how the chemical structure of drugs impacts on ge-nome-wide gene expression across several cancer cell lines (CMap database). The task is formulated as searching for drug response components across multiple cancers to reveal shared effects of drugs and the chemical features that may be responsible. The com-ponents can be computed with an extension of a very recent ap-proach called Group Factor Analysis (GFA). We identify 11 compo-nents that link the structural descriptors of drugs with specific gene expression responses observed in the three cell lines, and identify structural groups that may be responsible for the responses. Our method quantitatively outperforms the limited earlier studies on CMap and identifies both the previously reported associations and several interesting novel findings, by taking into account multiple cell lines and advanced 3D structural descriptors. The novel observations include: previously unknown similarities in the effects induced by 15-delta prostaglandin J2 and HSP90 inhibitors, which are linked to the 3D descriptors of the drugs; and the induction by simvastatin of leukemia-specific anti-inflammatory response, resem-bling the effects of corticosteroids.
Identification of MicroRNAs Inhibiting TGF-β-Induced IL-11 Production in Bone Metastatic Breast Cancer Cells
Sirkku Pollari, Suvi-Katri Leivonen, Merja Per?l?, Vidal Fey, Sanna-Maria K?k?nen, Olli Kallioniemi
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0037361
Abstract: Development of bone metastases is dependent on the cancer cell-bone cell interactions in the bone microenvironment. Transforming growth factor β (TGF-β) is released from bone during osteoclastic bone resorption and induces production of osteolytic factors, such as interleukin 11 (IL-11), in breast cancer cells. IL-11 in turn increases osteolysis by stimulating osteoclast function, launching a vicious cycle of cancer growth and bone destruction. We aimed to identify and functionally characterize microRNAs (miRNAs) that mediate the bone metastatic process, focusing on miRNAs that regulate the TGF-β induction of IL-11. First, we profiled the expression of 455 miRNAs in a highly bone metastatic MDA-MB-231(SA) variant as compared to the parental MDA-MB-231 breast cancer cell line and found 16 miRNAs (3.5%) having a >3-fold expression difference between the two cell types. We then applied a cell-based overexpression screen with Pre-miRNA constructs to functionally identify miRNAs regulating TGF-β-induced IL-11 production. This analysis pinpointed miR-204, miR-211, and miR-379 as such key regulators. These miRNAs were shown to directly target IL11 by binding to its 3′ UTR. MiR-379 also inhibited Smad2/3/4-mediated transcriptional activity. Gene expression analysis of miR-204 and miR-379-transfected cells indicated that these miRNAs downregulated the expression of several genes involved in TGF-β signaling, including prostaglandin-endoperoxide synthase 2 (PTGS2). In addition, there was a significant correlation between the genes downregulated by miR-379 and a set of genes upregulated in basal subtype of breast cancer. Taken together, the functional evidence and clinical correlations imply novel mechanistic links between miRNAs and the key steps in the bone metastatic process in breast cancer, with potential clinical relevance.
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