Conference Talk BioSB 2015
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This study employs multi-omics and pathway analysis to examine the impact of vitamin D3 on mRNA and miRNA expression in prostate cancer cells. It finds significant down-regulation of various cell cycle and cancer-related pathways post-treatment, suggesting vitamin D may play a regulatory role through miRNAs. The research integrates several network analysis tools to enhance the understanding of these interactions in cancer biology.
Conference Talk BioSB 2015
- 1. Integrative network based analysis of mRNA and miRNA expression in vitamin D3-treated cancer cells Martina Summer-Kutmon, PhD Department of Bioinformatics (BiGCaT) Maastricht Centre for Systems Biology (MaCSBio) 20 May 2015, BioSB 2015
- 2. Nutritional Systems Biology ● Understanding nutritional processes at a systems level ● Integrating the effects of nutritional compounds at the gene expression level with information on the regulatory level. https://wellnessfx.files.wordpress.com/2011/06/picture-11.png
- 4. Vitamin D3 metabolism Deeb, KK, et al. "Vitamin D signalling pathways in cancer: potential for anticancer therapeutics." Nature Reviews Cancer (2007)
- 5. Vitamin D3-mediated regulation Deeb, KK, et al. "Vitamin D signalling pathways in cancer: potential for anticancer therapeutics." Nature Reviews Cancer (2007)
- 6. Goal of this study Pathway and network-based methods Integrate mRNA and microRNA expression data Investigate regulatory action of vitamin D in prostate cancer
- 7. Workflow
- 8. Multi-omics dataset Human prostate cancer cell line LNCaP - Lymph node metastasis in Caucasian male 100 nM 1,25 dihydroxyvitamin D3 control group (n=4) VitD-treated group (n=4) Transcriptomics Nimblegen-HG18-4plex whole genome microarrays GEO: GSE17461 MicroRNA-omics Agilent Human microRNA v3 microarrays GEO: GSE23814 RNA isolation Wang, WL, et al. “Effects of 1alpha,25 dihydroxyvitamin D3 and testosterone on miRNA and mRNA expression in LNCaP cells." Molecular Cancer (2013)
- 9. Gene-level statistics ● Quality control and statistical analysis were performed by Wang et al. ○ one-way ANOVA (p<0.05) ○ correction for multiple testing. ● Differentially expressed genes: ○ fold change cut-off at 1.5 ○ p-value < 0.05 ● Differentially expressed miRNAs: ○ fold change cut-off at 2.0 ○ p-value < 0.05 Up-regulated Down-regulated 420 413 Up-regulated Down-regulated 9 0
- 10. VDR targets Literature study (25 papers) ● 25 publications and books ● 178 human VDR targets ● 21 changed genes CYP24A1 - degradation of vitamin D3 ↑ ORM1/ORM2 - acute phase plasma protein ↑ CDKN2D/2C - cell growth regulator ↓
- 11. Workflow
- 12. PathVisio ○ Open source pathway analysis toolbox ○ Data visualization and over-representation analysis ○ www.pathvisio.org WikiPathways ○ Collaborative pathway database ○ 276 pathways in curated collection ○ www.wikipathways.org Pathway analysis Kelder, T, et al. "WikiPathways: building research communities on biological pathways." Nucleic Acids Res (2012) Kutmon, M, et al. "PathVisio 3: An Extendable Pathway Analysis Toolbox." PLoS Comput Biol. (2015)
- 13. Pathway analysis Transcriptomics dataset Pathway database WikiPathways Differentially expressed genes Calculates Z-Score for each pathway Overrepresentation analysis Ranked list of pathways Data visualization on pathway diagrams
- 14. Pathway analysis Pathway Z-Score Category DNA Replication 11.91 general Cell Cycle 11.04 general Histone Modifications 10.44 general G1 to S cell cycle control 9.12 general DNA damage response 5.40 general ATM Signaling pathway 4.87 general Fluoropyrimidine Activity 4.16 general AhR signaling pathway 2.47 general Pathway Z-Score Category Retinoblastoma (RB) in Cancer 12.63 cancer Gastric cancer network 1 10.44 cancer Gastric cancer network 2 5.13 cancer Integrated Pancreatic Cancer Pathway 4.08 cancer Integrated Cancer pathway 3.85 cancer Integrated Breast Cancer Pathway 3.41 cancer Signaling Pathways in Glioblastoma 2.02 cancer ● Significantly altered pathways: ○ 8 general cell cycle related pathways ○ 7 cancer related pathways
- 15. Pathway analysis ● Most of the pathways are down-regulated after vitamin D treatment down upCell Cycle Pathway Gastric Cancer Network 1
- 16. Pathway analysis ● Most of the pathways are down-regulated after vitamin D treatment down upG1 to S Cell Cycle Control RB in Cancer
- 17. Workflow
- 18. Cytoscape ○ Network visualization and analysis tool ○ Extendable through apps ○ www.cytoscape.org Network building WikiPathways App WikiPathways web service client and GPML file format importer Shannon, P et al. "Cytoscape: a software environment for integrated models of biomolecular interaction networks." Genome research (2003)
- 19. Network building WikiPathways App Central genes: TP53, CDKN1A and CDK2 linking 5 out of 8 pathways Kutmon, M, et al. "WikiPathways App for Cytoscape: making biological pathways amenable to network analysis and visualization." F1000Research (2014)
- 20. Workflow
- 21. ● Problem: Only ~50% of protein coding genes are in pathways Network extension changed genes in complete dataset changed genes in all pathways changed genes in altered general pathways 833 420 up + 413 down 390 205 up + 185 down 73 14 up + 59 down What about all the differentially expressed genes that are not in the altered pathways?
- 22. Network extension ● Identify known protein-protein interaction partners of the genes in the selected pathways Database First neighbours STRING database http://string-db.org/ 443 changed genes Database First neighbours ENCODE http://encodenets.gersteinlab.org/ 67 changed genes ● Identify known transcription factor-target interactions of the genes in the selected pathways support from Georg Summer
- 23. VitD-extended network ● 583 out of 833 changed genes (~70%) ● 238 up ● 345 down up-regulated down-regulated
- 24. Workflow
- 25. ● Connected sub-networks that are regulated by Vitamin D treatment ● jActiveModules finds multiple active networks with different scores ○ robust down-regulated module ○ 193 nodes ○ 41 from altered pathways Active network modules jActiveModules App
- 26. Active network modules Module in vitD-extended network jActiveModules App
- 27. ● 195 genes ○ 192 changed genes, all down-regulated ○ 1 gene not changed (E2F4) ● Functional enrichment: ○ Cell cycle activity ○ DNA processing ○ Cytoskeleton organization Active network modules jActiveModules App
- 28. Workflow
- 29. ● TargetScan + miRTarBase ○ 1,439 miRNAs → 25,886 miRNA-target interactions ● 6 out of 9 DE miRNAs present in vitD-microRNA network VitD-microRNA network ● Extend biological network with regulatory information ○ microRNAs, transcription factors, drugs, ... CyTargetLinker App Kutmon, M, et al. "CyTargetLinker: a cytoscape app to integrate regulatory interactions in network analysis." PloS one (2013)
- 30. VitD-microRNA network CyTargetLinker App 31 targets up-regulated (3 in pathways) 23 targets down-regulated (4 in pathways) Targeted by multiple microRNAs: CLSPN - cell cycle FZD5 - receptor for Wnt proteins CACNG4 - calcium channel
- 31. Conclusions ● Data integration ○ Multi-omics datasets ○ Pathway and interaction resources ● Cell cycle related and several cancer-related pathways are down-regulated after vitamin D treatment ● Possible regulatory mechanism of vitamin D through microRNAs
- 32. Conclusion ● Combination of the network-based tools PathVisio and Cytoscape ● Straightforward, in-depth and biological meaningful ● Integration of different multi-omics data
- 33. Acknowledgments I would like to thank: Department of Bioinformatics, Maastricht University Susan Coort Kim de Nooijer Claire Lemmens Chris Evelo Department of Cardiology, Maastricht University Georg Summer Dataset: Wei-Lin Wang et al.
- 34. Questions