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Mutation hotspots are associated with gene expression, signaling pathways, protein domains and drug response
Theo Knijnenburg
Brady Bernard
Ilya Shmulevich
William Poole
The location of mutations in a gene matters
GDSC
Mutations in BRAF
Finding mutation hotspots
Finding mutation hotspots EGFR in PANCAN11
Amino Acid Position
Mutation count
Finding mutation hotspots EGFR in PANCAN11
Mutation count
Smoothed at multiple
bandwidths
Finding mutation hotspots EGFR in PANCAN11
Mutation count
Multiscale clusters
Smoothed at multiple
bandwidths
Finding mutation hotspots EGFR in PANCAN11
Pkinase_Tyr Recep_L_domain Furin-like
Amino Acid Position
Mutation count
Multiscale clusters
Smoothed at multiple
bandwidths
• 75% of the mutations in hotspots are inside protein domains
Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
• 84% of the OncoDrive clusters overlap with the Multiscale clusters
Are these mutation hotspots functional?
Are these mutation hotspots functional? Identify statistical associations with: • Protein domains • Gene expression • Signaling pathways • Drug response
Statistical association between hotspots and gene expression
Binary mutation
calls
Mutation hotspots
Sam
ples
Continuous gene expression profiles
Genes
Sam
ples
Statistical association between hotspots and gene expression
Binary mutation
calls
Mutation hotspots
Sam
ples
Continuous gene expression profiles
Genes
Sam
ples
Pairwise
Statistical Tests Pipeline
Pairwise Correlations and P-values between hotspots and genes
Mut
atio
n ho
tspo
ts
Genes
Statistical association between hotspots and gene expression in UCEC
P=4·10-8
P=1·10-7
Statistical association between hotspots and gene expression in UCEC
P=8·10-9 P=2·10-3
Statistical association between hotspots and gene expression in UCEC
Type # Significant associations
Only in hotspot (hotspot P<10-4, all mutations P>10-2)
60
Only in gene (all mutations P<10-4, hotspot P>10-2)
1350
Both in gene and hotspot (all mutations P<10-4, hotspot P<10-4)
1360
Statistical association between hotspots and signaling pathways
Pairwise Correlations and P-values between hotspots and genes
Mut
atio
n ho
tspo
ts
Genes
Pathway membership in NCI/PID
Genes
Pat
hway
s
Statistical association between hotspots and signaling pathways
Combine P-values of genes in a pathway using Brown’s
method
Pairwise Correlations and P-values between hotspots and genes
Mut
atio
n ho
tspo
ts
Genes
Pathway membership in NCI/PID
Genes
Pat
hway
s P-values between hotspots
and pathways M
utat
ion
hots
pots
Pathways
Statistical association between PTEN hotspots and signaling pathways in GBM
Mutations in PTEN
n=27 n=73 n=7 n=10 n=7 n=5 n=6 n=8
Statistical association between PTEN hotspots and signaling pathways in GBM
Mutations in PTEN
n=27 n=73 n=7 n=10 n=7 n=5 n=6 n=8
Statistical association between PTEN hotspots and signaling pathways in GBM
Mutations in PTEN
n=27 n=73 n=7 n=10 n=7 n=5 n=6 n=8
Statistical association between PTEN hotspots and signaling pathways in GBM
Mutations in PTEN
n=27 n=73 n=7 n=10 n=7 n=5 n=6 n=8
P Lo
op
cα2
cα2
WPD
Lo
op
TI Loop
TI L
oop
Lee et al. Crystal Structure of the PTEN Tumor Suppressor: Implications for Its Phosphoinositide Phosphatase Activity and
Membrane Association. Cell, 1999.
Statistical association between PTEN hotspots and signaling pathways in GBM
WPD Loop
P Loop
Phosphatase domain C2 domain
Drug response depends on mutation hotspots
GDSC Mutations in PIK3CA
EGFR/ERBB2 inhibitor
Drug response depends on mutation hotspots
GDSC Mutations in PIK3CA
PIK3CA inhibitor
Summary
• We have developed a novel multiscale clustering algorithm to robustly identify mutation hotspots in genes
• We uncovered statistical associations between many of these mutation hotspots and gene expression, signaling pathways and drug response
Future work
• From PANCAN11 to the PANCAN Atlas • Integrate the mutation hotspots into Regulome
Explorer (RE) • Make code and hotspots available
Acknowledgements
• William Poole • Brady Bernard • Ilya Shmulevich • Sheila Reynolds • Vesteinn Thorsson • TCGA Genome Data Analysis Center (GDAC)
for Systems Analysis of the Cancer Regulome (CSACR)
Poster: 57
Statistical association between hotspots and gene expression in UCEC
Statistical association between hotspots and gene expression in UCEC
Statistical association between hotspots and gene expression in UCEC
Statistical association between hotspots and gene expression in UCEC
Statistical association between hotspots and gene expression in UCEC
Statistical association between hotspots and gene expression in UCEC