1. Network analysis for AML data
Dr. Habil Zare, PhD
Oncinfo Lab
Texas State University
14 Jan 2015

2. Bayesian networks are useful in modeling genes interactions

3. CCLE provides expression data useful for learning the network

4. First application Biological interpretation
Gene hubs, causal relationships, interaction between pathways, ….

5. Data cleaning FKPM values less than 1
Are considered noise and technical artifact.

6. Differential expression
We used limma and ranked the transcripts based on their differential expression in AML vs. MDS.
We used the top third for further analysis that included 913 non-coding RNAs.
Length of non-coding RNAs

7. Gene modules Size of module identified by WGCNA. 44 AML cases
24 MDS cases
The difference is the number of size of modules is most likely due to different sample size in each group

8. Gene modules 30 random AML cases 30 random MDS cases
MDS is expected to have more modules because of higher heterogeneity.

9. Gene hubs in modules
Hubs are the transcripts that have the highest correlation (interaction) with other transcripts in a module.

10. Gene hubs in modules
We looked at the hubs in the modules and found that:
A) PBX3, HOXA9, HOXA10, and MEIS1 are among the top 10 hubs in AML-36 module. They are know to be associated with AML.
PBX3 is a cofactor for HOXA9 and both of them are targets for AML therapy. The cluster of HOXA genes are known to be very well associated with leukemia; "Artificial overexpression of HOXA7, HOXA9, or HOXA10 in combination with MEIS1 caused leukemia in animal models.” (Bach et al. 2010)

11. Gene hubs in modules
We looked at the hubs in the modules and found that:
B) 9 isotopes of HLA-DPA1 are hubs of AML-20 reported to be associated with AML in 10 studies according to Miler HLA-DPA1 is also a hub in MDS-35 module.

12. Gene hubs in modules
C) The other hub of AML-20 module is HLA-DMA. Can HLA-DMA be interesting for us too? They both have a high correlation of 0.94 over all AML and MDS cases.

13. Gene hubs in modules HLA-DPA1 and HLA-DMA are under-expressed in AML.
HLA-DMA was reported in 5 studies in the review paper but is its role in AML understood as much as the other gene in this module?

14. Genes in module 36 correlate differently in AML vs. MDS

15. AML-related genes in the modules
Distribution of 4000 known,
AML-related genes in the modules
Other than module 36, module 46 that is also enriched in interesting genes.

16. Genes in module 46 correlate differently in AML vs. MDS too

17. One striking difference
2 HOXB cluster antisense RNA, NR_ and NR_033201, have almost no correlation in MDS.
AML
MDS

18. NR_ and NR_033201
~0.5 Kbs long. Both are expressed in more than 1/3 of AML cases and rarely in MDS case. Are they associated with an AML subtype?

19. NR_ and NR_033201
They are associated with therapy-related AML or MDS.
NR_033201:
40% of tAML cases have expression > 1 (above noise level) while subtypes AML-MEGA, AML-MPN, AML-NK, MDS have 0 expression.
Expressed in AML-M6:1 AML-MDS :1 tAML:12 tMDS : 2
NR_033202:
AML-M6:1 AML-MDS:3 tAML:11 tMDS:3

20. Next steps Controlling for confounding variables such as age and sex
Study other gene hubs
Learning a Bayesian Network for each module and studying the most influential genes (recognized as N-hob-down-stream nodes)
Introducing a new binary variable to the network that indicates whether the sample is AML and MDS. The genes connected to this new random variable are useful in explaining the biological difference between AML and MDS.