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TranSMART presentation
- 1. tranSMART v1.2 Case Study for PredicTox April 2015
- 2. Agenda What is PredicTox? Brief tranSMART overview Answering scientific questions with tranSMART’s help: A case study maximizing data value Questions? Agenda
- 3. A public private partnership, led by the Reagan- Udall Foundation for the FDA, with the goals of: Applying systems-based approaches to better understand Adverse Events (AEs) Developing predictive models Pilot project --- one drug class &AE Use TranSMART as platform for Integration of clinical, preclinical and molecular data PredictTox
- 4. Agenda What is PredicTox? Brief tranSMART overview Answering scientific questions with tranSMART’s help: A case study maximizing data value Questions? Agenda
- 5. tranSMART Data Warehouse Structure Szalma S.; Koka, VC.; Khasanova, T.; Perakslis, E. :Effective knowledge management in translational medicine Journal of Translational Medicine 2010, 8:68 Analytical and visualization tools Security Access (enterprise vs. project level) Patient Privacy Diverse Data Warehouse structure
- 6. PredictTox tranSMART Data for PredicTox (so far) 18 gene expression data sets from GEO Human white blood cells having to do with left ventricular dysfunction, and the drugs Imantinib, Sunitinib, and Trastuzumab. Preclinical studies with gene expression data from heart tissue of rats dosed with imatinib. These datasets may provide confirmatory gene expression profiles as it differentiates left ventricular dysfunction from other cardiac disease. Information gleaned from these data may provide mechanistic insight into the cardiotoxicity of tyrosine kinase inhibitors.
- 7. Agenda What is PredicTox? Brief tranSMART overview Answering scientific questions with tranSMART’s help: A case study maximizing data value Questions? Agenda
- 8. Case Study GSE21125 Blood Signature of Pre-heart Failure: A Microarray Study (Smih et al) Human white blood cells from healthy, heart failure risk patients, asymptomatic left ventricular dysfunction patients, chronic heart failure, acute heart failure patients Platform - RNG-MRC_HU25k_NICE PLoS ONE 6(6): e20414. doi:10.1371/journal.pone.0020414 GSE2535 In chronic myeloid leukemia white cells from cytogenetic responders and non-responders to imatinib have very similar gene expression signatures (Crossman et al) Analysis of peripheral blood and bone marrow of chronic myelogenous leukemia (CML) patients prior to imatinib (Gleevec) treatment. This study attempts to determine transcriptional signature of imatinib non-responders. Platform - Affymetrix Human Genome U95 Version 2 Array Haematologica 2005; 90:459-464 Case Study Data
- 9. Analytical Rationale Imatinib is the first targeted therapy used to treat Philadelphia chromosome positive CML Targets and inhibits the catalytic activity of constitutively active tyrosine kinase Bcr-Alb. Also associated with reduced left ventricular ejection volume indicative of left ventricular dysfunction With data loaded into tranSMART we investigated the correlation between gene expression signatures of patients with ALVD and those associated with imatinib response Do these profiles have overlapping genes? What are the functions of the overlapping genes? Do these profiles show effects on similar pathways? Can apply the signature of one data set to cluster gene expression profiles from the other? Case Study
- 10. Analysis Workflow Marker Selection Analyses Gene Lists Investigate the Role of Shared Genes Biomarkers? Pathway Enrichment Analysis Mechanistic Similarities? Clustering Analysis Hierarchical clustering using swapped gene list Case Study
- 11. GSE2535 Marker Selection Calculates the most differentiating genes between two datasets Case Study
- 12. Gene List Creation Gene lists gathered using Marker Selection workflow in tranSMART were edited to remove control genes, repeats, unrecognized loci and ORFs GSE21125 Marker Selection list yielded 54 recognizable gene symbols when loaded into tranSMART when comparing healthy controls with ALVD patients GSE2535 Marker Selection list yielded 92 recognizable gene symbols when loaded into tranSMART when comparing responders vs. non-responders Case Study
- 13. Analysis Workflow Marker Selection Analyses Gene Lists Investigate the Role of Shared Genes Biomarkers? Pathway Enrichment Analysis Mechanistic Similarities? Clustering Analysis Hierarchical clustering using swapped gene list Case Study
- 14. Venn Diagram GSE21125 and GSE2535 Compared gene lists from GSE21125 and GSE2535 Shared gene CACNA2D2 CACNA2D2 – voltage-dependent calcium channel Homozygous mutation is associated with epileptic encephalopathy Null mutants in mice display seizures, cardiac abnormalities and premature death. Known to promote tumorigenesis and over expression is associated with increased cell proliferation. Oncogene. 2015 Jan 26. doi: 10.1038/onc.2014.467 Search in PubMed for CACNA2D2 and left ventricular dysfunction yielded no results Case Study
- 15. CACNA2D2 Expression CACNA2D2 down-regulated in patients with ALVD p=6.41 x 10-6 GSE21125 GSE2535 • CACNA2D2 slightly down-regulated in patients unresponsive to imatinib treatment p= 0.011 • Gene expression data for CACNA2D2 show a statistically significant difference in these comparisons Case Study
- 16. CACNA2D2 in GSE21125 CACNA2D2 seems to highly differentiate the investigated pathologies. Not part of the blood gene expression signature in Smih et al Pairwise t-Test Case Study
- 17. Analysis Workflow Marker Selection Analyses Gene Lists Investigate the Role of Shared Genes Biomarkers? Pathway Enrichment Analysis Mechanistic Similarities? Clustering Analysis Hierarchical clustering using swapped gene list Case Study
- 18. Pathway Enrichment Analysis GSE21125 Smih et al GSE2535 Crossman et al -log 0.05≈ 1.3 Case Study
- 19. Analysis Workflow Marker Selection Analyses Gene Lists Investigate the Role of Shared Genes Biomarkers? Pathway Enrichment Analysis Mechanistic Similarities? Clustering Analysis Hierarchical clustering using swapped gene list Case Study
- 20. GSE21125 Hierarchical Clustering with GSE2535 Marker Selection List Clustering based on the GSE2535 gene list shows separation of Control profiles but does not effectively differentiate ALVD patients. Case Study
- 21. GSE2535 Hierarchical Clustering with GSE21125 Marker Selection List Applying the GSE21125 Marker Selection List does not distinguish imatinib responders vs non-responders Case Study
- 22. Further inspection of GSE2535 GSM48360 GSM48357 GSM48368 GSM48354 41806_at 38013_at 39583_at 1968_g_at 36397_at 35923_at 34582_at 38767_at 1892_s_at 37866_at 39015_f_at 526_s_at 41476_at 1114_at 32331_at 680_s_at 1197_at 41542_at 40340_at 32918_at 593_s_at 36475_at 31520_at 37745_s_at 36094_at 37346_at 41559_at 40842_at 38371_at 37739_at 41060_at 40242_at 39096_at 1894_f_at 33325_at 1011_s_at AFFX-HUMGAPDH/M33197_5_at 256_s_at Column13 Column15 Cluster1(n=6877) GSM48360 GSM48355 GSM48357 GSM48373 GSM48368 GSM48369 GSM48354 1194_g_at 41032_at 39326_at 34042_at 36139_at 34029_at 37880_at 40006_at 40280_at 40986_s_at 37251_s_at 405_at 32258_r_at 32733_at 34120_r_at 846_s_at 38591_at 41256_at 1929_at 31862_at 36566_at 40236_at 32622_at 35825_s_at 37162_at 1284_at 41409_at 38802_at 201_s_at 33326_at 1512_at 717_at 38824_at 41202_s_at 32119_at 37603_at 40853_at 195_s_at Column13 Column15 Cluster2(n=5748) -4.00 4.00 Column13 Non-responder Responder Column15 Leipzig Mannheim Batch effect Case Study
- 23. Summary Marker Selection analysis GEO data sets GSE21125 and GSE2535 in tranSMART yielded gene lists of 54 and 92 gene respectively These lists had one gene in common CACNA2D2 voltage- dependent calcium channel This gene is down regulated in GSE21125 in patients with ALVD and distinguishes ALVD from the other pathologies studied Down regulated in non-responders to imatinib Null mutants in mice display seizures, cardiac abnormalities and premature death Case Study
- 24. Summary Pathway enrichment analysis GSE21125 – pathways involved in cell adhesion and cytoskeleton remodeling GSE2535 – pathways involved in VEGF signaling and ESR1 activation The datasets share one pathway – “Cytoskeleton remodeling Role of PKA in cytoskeleton reorganization” the significance of which remains to be investigated Hierarchical clustering analysis shows poor performance with swapped gene lists Case Study
- 25. Agenda What is PredicTox? Brief tranSMART overview Answering scientific questions with tranSMART’s help: A case study maximizing data value Questions? Agenda
- 26. How to Get Involved Looking for partners: data, expertise, funding, and other resources Steering Committee and work groups forming soon--- stay tuned for updates No membership fee --- funding is raised from a variety of public and private sources For more info: contact nbeck@reaganudall.org or see her after the talk
- 27. Extra Slides
- 28. Lessons learned The more attributes for the samples the better The more data the better! Need same tissue, same species, similar treatments, and similar measurements! Case Study
- 29. Current Project Activities Securing data sharing agreements with pharma companies Gathering publically available data Building the ontology of Cardiac Adverse Events Establishing the project governance structure Building out tranSMART instance Rancho developed use case using GEO data sets to demonstrate utility…
- 30. Pilot project – develop centralized knowledge base that includes publically available clinical and molecular data having to do with tyrosine kinase inhibitors (TKIs) and mAbs and cardiac AEs; specifically left ventricular dysfunction. Data goes into tranSMART infrastructure Integrated knowledgebase Mine information on biomarkers, non-clinical and clinical screens Assist in hypothesis generation and mechanistic level understanding PredictTox
- 31. Concept of tranSMART on data level tranSMART
- 32. Examples Of Data Stored In tranSMART Data from clinical trials Demographics, medical history Treatment information Clinical outcomes, including AEs OMICs type data (gene expression, proteomics, RBM, SNPs) Pre-clinical Studies PK/PD data OMICs type data for animal models and cell lines Toxicology data Warehouse structure
- 33. Concept of tranSMART Discovery Group Preclinical Group Clinical Development tranSMART
- 34. Cytoskeleton remodeling Role of PKA in cytoskeleton reorganization Case Study
- 35. Conclusions We went over tranSMART and explored main functionality of the platform We used platform to answer a scientific question Great sets from GEO were curated and loaded into this tranSMART instance – they serve as a starting point and will provide useful comparisons for new, exciting data that is yet to come We need more data! Case Study
- 36. Marker Selection vs. Signature from Smih et al. Tested the performance of the blood signature from supporting reference and the Marker Selection gene list Performed hierarchical clustering analysis using “Marker selection list” generated by comparing gene expression from healthy controls and ALVD patients 7 gene list from the paper Case Study
- 37. GSE21125 Clustering with Marker Selection List • The marker selection list was able to differentiate patient samples based on pathology Case Study
- 38. Clustering with Smih et al Gene List The list from Smih et al. performs well at clustering samples from patients with ALVD Case Study
Editor's Notes
- TKI = tyrosine kinase inhibitors mAbs = monoclonal antibodies
- Actin cytoskeletal, LBC, BETA-PIX, cAMP, c-Abl, PAK1, Beta adducin, LIMK1, CDC42, PLC-beta3, G-protein alpha-s, ROCK, 14-3-3 beta/alpha, 3.1.4.11, Ca(2+) endoplasmic reticulum lumen, LASP1, MLCP (reg), alpha-4/beta-1 integrin, DAG, Cofilin, RhoA, PKA-cat (cAMP-dependent), Paxillin, Rac1, IP3, Adenylate cyclase, 4.6.1.1, PKA-reg (cAMP-dependent), Fodrin (spectrin), ATP cytosol, Calmodulin, Ca(2+) cytosol, <endoplasmic reticulum lumen> Ca('2+) = <cytosol> Ca('2+), G-protein beta/gamma, MLCK, VASP, Alpha adducin, MELC, IP3 receptor, MLCP (cat) Role of PKA in cytoskeleton reorganisation A wide variety of soluble signaling mediators utilize the Protein kinase cAMP-dependent ( PKA ) pathway to regulate cellular processes including intermediary metabolism, ion channel conductivity, and transcription. PKA plays a central role in cytoskeletal regulation and cell migration. Moreover, the role of PKA in cytoskeletal organization and cell migration, exerting both negative (i.e. inhibitory) and positive (i.e. required or enhancing) effects. GNAS complex locus coupled receptor ( G-protein alpha-s coupled receptor ) interaction with the trimeric G-protein alpha-s/ Guanine nucleotide binding protein beta and gamma ( G-protein beta/gamma ) causes the exchange of GDP for GTP bound to G-protein alpha subunits and the dissociation of the G-protein beta/gamma heterodimers. G-protein alpha-s activates Adenylate cyclases. Upon stimulation, Adenylate cyclases increase the level of Cyclic Adenosine 3',5'-monophosphate ( cAMP ) in cells and activate the PKA-cat and PKA-reg complex that results in PKA activation [1]. Negative effects of PKA on cell migration have been reported for integrin-dependent endothelial cell migration. Also, matrix-specific down-regulation of cAMP/ PKA signaling appears to be required for collagen-induced Actin synthesis and stress fiber formation in endothelial cells [2]. PKA -dependent phosphorylation of complex Integrin alpha 4 and beta 1 ( Alpha-4/beta-1 integrin ) is important for migration and other integrin function. Phosphorylation of Alpha-4/beta-1 integrin blocks Paxillin binding, which activates cell migration and increases lamellipodial stability [3]. The cytoskeletal regulatory protein Vasodilator-stimulated phosphoprotein ( VASP ) localizes to focal adhesions, largely through interaction with proteins such as Vinculin, Zyxin, and KIAA1274. PKA phosphorylates VASP and disrupts its interaction with C-abl oncogene 1 receptor tyrosine kinase ( c-Abl ) [4]. A relative newcomer to the list, the LIM and SH3 protein 1 ( LASP1 ), was identified as a potential cytoskeletal PKA substrate in gastric fibroblasts and gastric parietal cells. LASP1 regulates its translocation to areas of dynamic actin filaments synthesis. Phosphorylation of LASP1 by PKA decreases its interaction with Actin [5]. Adducin s promote association of Spectrin non-erythrocytic ( Fodrin (spectrin) ) with Actin to facilitate capping of the fast growing end of Actin filaments. PKA phosphorylates Alpha adducin and Beta adducin and reduces their affinity for Fodrin (spectrin)/ Actin complexes as well as the activity of Adducin s in promoting binding of Fodrin (spectrin) to Actin filaments [6]. PKA directly phosphorylates monomeric Actin, which causes a significant decrease in monomer 'polymerizibility'. Myosin-based contractility is important for several aspects of cell movement, including retraction of the trailing edge and less well-defined functions within the leading edge, where Myosin light chain ( MELC ) interaction with Actin and myosin-dependent contractility are positively regulated by phosphorylation. MELC phosphorylation is proximally controlled by the ratio of Myosin light chain kinase ( MLCK ) and Protein phosphatase 1 catalytic subunit beta isoform ( MLCP ) activities. The regulation of MLCK and MLCP is intensely complex, and involves cAMP -dependent PKA signaling. MLCK is activated by the Ca(2+)/ Calmodulin binding. PKA can regulate Ca(2+) release through phosphorylation and inhibition of Phospholipase C ( PLC-beta ), resulting in the inactivation of receptors for Inositol trisphosphate ( IP3 ). cAMP and PKA can up-regulate MLCP activity through the Rho-associated, coiled-coil containing protein kinase ( ROCK )-dependent inhibition of MLCP phosphorylation and inhibition of Ras homolog gene family, member A ( RhoA ). The influence of PKA on MLCK and MLCP has the same effect on decreasing MELC phosphorylation and stress fibers formation [2]. A kinase (PRKA) anchor protein 13 ( LBC ) activity can be inhibited by the anchoring both PKA and Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein beta polypeptide ( 14-3-3 beta/alpha ) proteins. LBC has a close functional link with the actin cytoskeleton through its interaction with the RhoA and ability to promote G-protein coupled receptors-dependent stress fiber formation. Conversely, elevation of cAMP level and activation of PKA have been shown to be required for efficient cell migration, or hallmark steps of migration, in several systems as well. These include: formation of filopodia and lamellipodia, which are governed by the activation of Cell division cycle 42 ( CDC42 ) and Ras-related C3 botulinum toxin substrate 1 ( Rac1 ) respectively. Stimulation of PKA by cAMP results in Rho guanine nucleotide exchange factor 7 ( BETA-PIX ) phosphorylation, which in turn controls BETA-PIX translocation to focal complexes and Rac1 and CDC42 activation [7].