Msc Thesis - Presentation

Identification Of Gene Expression Modules In Colorectal Cancer

1. September 08, 2009
Manikhandan A V Mudaliar
MSc Thesis
Supervisors: Dr. Daniel Crowther and Dr. Keith Vass
Identification of Gene
Expression Modules
in Colorectal Cancer

2. Outline
•Introduction
•Aims and Objectives
•Review of Literature
•Methods
•Results
•Conclusions
•Summary

3. Introduction
•Colorectal Cancer is the second leading cause of cancer
death
•Gene expression profiling using microarrays is one of
the effective methods to infer molecular mechanisms
•The main purpose: To identify gene expression modules
that conclusively exist in colorectal cancer
•The outcome: Emphatically identified functional gene
expression modules and mapped with other studies

4. Aims and Objectives
•To identify gene expression modules that are common
to many colorectal cancer microarray datasets using
three different methods
•To find biological relevance of the modules using
BiNGO, NetAffix and KEGG pathway online tools
•Mapping with other studies:
•Predict probability of tumour relapse in colorectal
cancer patients
•Predict probability of survival in breast cancer
patients

5. Review of Literature
•Ruan et al.
1
successfully identified co-expression
modules enriched with cancer related Gene Ontology
categories from colon cancer microarray data
•Staub et al.
2
successfully classified various cancer
patient populations using the genes present in WIPF1
co-expression module

6. Methods and Materials
•Data Collection from public databases
•Analytical methods
•Normalisation
•Multi-cluster comparison using Eigen Decomposition
•Correlation Similarity Pooled Co-expression Network –
Clustering by Eigen Decomposition
•Correlation Similarity Pooled Co-expression Network –
Clustering by Cytoscape – MCODE plug-in
•Analysis of the modules using BiNGO ,NetAffix and
KEGG Pathway online tools
•Kaplan-Meier Survival Analysis

7. Results and Discussion
•The nodes (probe
sets) are shown as
red circles and the
edges are shown as
blue lines. The
modules are named
after their MCODE
cluster ranks
•The number of
nodes present in the
modules 1 to 4 is 40,
32, 24 and 17
respectively
Visualisation of gene expression modules in Cytoscape

8. Results and Discussion
•Gene Ontology
categories
overrepresented in
the modules are
shown in darker
shades
•This module is
highly enriched for
genes present in
cell cycle pathway
BiNGO Gene Ontology enrichment results visualised in
Cytoscape

9. Results and Discussion
Kaplan-Meier Survival Analysis Plot showing probability of tumour
relapse over time: predictability using MCODE cluster No.8 (RAS
signalling pathway) as classifier on Wang et al.
3
Colorectal Cancer
dataset
No of samples = 74
Class Samples Relapse
Cluster 1 42 15
Cluster 2 32 16
p-value = 0.3817
Red curve = Cluster 1 (under expressed)
Blue curve = Cluster 2 (over expressed)

10. Result and Discussion
No of samples = 235
Class Samples Death
Class=0 47 9
Class=1 94 29
Class=2 94 17
p-value = 0.0168
Blue curve = Class 1 (over expressed)
Black curve = Class 2 (under expressed)
Kaplan-Meier Survival Analysis Plot showing probability of survival
over time: predictability using MCODE cluster No.1 (Focal adhesion
pathway) as classifier on GSE 3494 Breast Cancer dataset

11. Conclusions
•Emphatically identified gene expression
modules that regularly occur in colorectal
cancer
•Conclusively found functional significance of
the modules
•Mapped with other studies to show their
biological relevance
•Suggestions for future work

12. Summary
•The main purpose
•Three different methods
•Results
•Conclusions

13. References
1. Ruan, X. G., Wang, J. L. and Li, J. G. (2006), "A network partition algorithm for mining
gene functional modules of colon cancer from DNA microarray data", Genomics,
proteomics & bioinformatics / Beijing Genomics Institute, vol. 4, no. 4, pp. 245-252
•Staub, E., Groene, J., Heinze, M., Mennerich, D., Roepcke, S., Klaman, I., Hinzmann,
B., Castanos-Velez, E., Pilarsky, C., Mann, B., Brummendorf, T., Weber, B., Buhr, H. J.
and Rosenthal, A. (2009), "An expression module of WIPF1-coexpressed genes
identifies patients with favourable prognosis in three tumour types", Journal of
Molecular Medicine (Berlin, Germany), vol. 87, no. 6, pp. 633-644.
•Wang, Y., Jatkoe, T., Zhang, Y., Mutch, M. G., Talantov, D., Jiang, J., McLeod, H. L.
and Atkins, D. (2004), "Gene expression profiles and molecular markers to predict
recurrence of Dukes' B colon cancer", Journal of clinical oncology : official journal of the
American Society of Clinical Oncology, vol. 22, no. 9, pp. 1564-1571.

14. Acknowledgements
•Thanks to Translational Medicine Research
Collaboration (TMRC), Dundee
•Thanks to Scottish Bioinformatics Forum
Thank you