The document describes a study that integrated mRNA and microRNA expression data to investigate the regulatory effects of vitamin D3 in prostate cancer cells. Pathway analysis revealed several cell cycle and cancer-related pathways were downregulated after vitamin D3 treatment. A network approach identified an active subnetwork of 193 downregulated genes related to cell cycle processes. The network was extended with microRNA regulatory interactions, showing 6 microRNAs targeted genes in the network, suggesting a possible regulatory mechanism of vitamin D3 through microRNAs.

1. Integrative network based analysis
of mRNA and microRNA expression
in vitamin D3-treated cancer cells
Susan Steinbusch-Coort, PhD
Dept. Bioinformatics-BiGCaT, NUTRIM, Maastricht University
susan.coort@maastrichtuniversity.nl

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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

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Nutrigenomics
http://www.alive.com/articles/view/23381/the_nutrigenomics_frontier

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Nutrition and Epigenetics
www.int.laborundmore.de

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Vitamin D3 metabolism
Deeb, KK, et al. "Vitamin D signalling pathways in cancer: potential for anticancer therapeutics." Nature Reviews Cancer (2007)

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Vitamin D3-mediated regulation
Deeb, KK, et al. "Vitamin D signalling pathways in cancer: potential for anticancer therapeutics." Nature Reviews Cancer (2007)

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Goal of this study
Pathway and network-based methods
Integrate mRNA and microRNA
expression data
Investigate regulatory action of
vitamin D3 in prostate cancer

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Workflow

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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
48h treatment

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Gene-level statistics
Quality Control and statistical analysis
o performed by Wang et al.
o one way ANOVA (p-value < 0.05)
o correction for multiple testing
Transcriptomics data
o fold change > 1.5
o p-value < 0.05
MicroRNA data
o fold change > 2
o p-value < 0.05
Up-
regulated
Down-
regulated
420 413
Up-
regulated
Down-
regulated
9 0

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VDR targets
CYP24A1 - degradation of vitamin D3 ↑
ORM1/ORM2 - acute phase plasma
protein ↑
CDKN2D/2C - cell growth regulator ↓
Literature study
● 25 publications and books
● 178 human VDR targets
● 21 changed genes

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Workflow

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Pathway analysis
PathVisio
o Open source pathway analysis toolbox
o Data visualization and over-representation analysis
o www.pathvisio.org
WikiPathways
o Collaborative pathway database
o 276 pathways in curated collection
o www.wikipathways.org
Kutmon, M, et al. "WikiPathways: capturing the full diversity of pathway knowledge." Nucleic Acids Res (2015)
Kutmon, M, et al. "PathVisio 3: An Extendable Pathway Analysis Toolbox." PLoS Comput Biol. (2015)

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Pathway analysis
Transcriptomics
dataset
Pathway
database
WikiPathways
Differentially
expressed genes
Calculates Z-Score
for each pathway
Over-representation
analysis
Ranked list of
pathways
Data
visualization
on pathway
diagrams

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Pathway analysis
● Significantly altered pathways:
o 8 general cell cycle related pathways
o 7 cancer related pathways
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

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Pathway analysis
● Most of the pathways are down-regulated after
vitamin D treatment
Cell Cycle Pathway Gastric Cancer Network 1
down
up

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Workflow

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Network building
Cytoscape
o Network visualization and analysis tool
o Extendable through apps
o www.cytoscape.org
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)

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Network building
Central genes:
TP53, CDKN1A and CDK2
linking 5 out of 8 pathways
WikiPathways App

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Network building
Kutmon, M, et al. "WikiPathways App for Cytoscape: making biological pathways amenable to network analysis and visualization."
F1000Research (2014)
up
down
VDR
WikiPathways App

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Workflow

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Network extension
● Problem:
Only ~50% of protein coding genes are in
pathways
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?

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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

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VitD-extended network
● 583 out of 833
changed genes
(~70%)
● 238 up
● 345 down
up-regulated
down-
regulated

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Workflow

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Active network modules jActiveModules App
Finds clusters where
member nodes show
significant changes in
expression levels
● Connected sub-networks that are regulated by
Vitamin D treatment
● jActiveModules finds multiple active networks
with different scores
o robust highest scoring down-regulated
module
o 193 nodes
o 41 from altered pathways

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Active network modules jActiveModules App
Module in vitD-extended network

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Active network modules jActiveModules App
● 193 genes
o 192 DE genes, all down-regulated
o 1 gene not DE (E2F4)
● 41 genes from pathway network
o 22 in more than one pathway
What is the function of all genes in this
active sub-network?

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Functional enrichment
● Find GO processes in which the 193 genes
of the active sub-network are over-
represented
● ClueGO creates network of related GO
terms
ClueGO App

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Workflow

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Vit D3-microRNA network CyTargetLinker
App
Extends biological networks
with regulatory interactions
● TargetScan + miRTarBase
o 1,439 miRNAs → 25,886 miRNA-target
interactions
● 6 out of 9 changed miRNAs present
in vitD-microRNA network
● Extend biological network with regulatory
information
o microRNAs, transcription factors, drugs, ...

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Vit D3-microRNA network
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
CyTargetLinker
App

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Summary
● Data integration
o Multi-omics datasets
o Pathway and interaction resources
● Several cell cycle related and cancer-
related pathways are down-regulated
after vitamin D treatment
● Possible regulatory mechanism of
vitamin D through microRNAs

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Summary
● Combination of the network-based
tools PathVisio and Cytoscape
● Straightforward, in-depth and
biological meaningful analysis
● Integration of different multi-omics
data in a network-based approach

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Acknowledgments
Department of Bioinformatics, Maastricht University
Martina Summer-Kutmon
Kim de Nooijer
Claire Lemmens
Chris Evelo
Lars Eijssen, Egon Willighagen, Linda Rieswijk, Frederieke
Ehrhart, Anwesha Bohler-Dutta, Elisa Cirillo, Nuno Nunes,
Jonathan Mélius, Ryan Miller.
Department of Cardiology, Maastricht University
Georg Summer
Dataset: Wei-Lin Wang et al.

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Questions