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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
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The location of mutations in a gene matters
GDSC
Mutations in BRAF
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Finding mutation hotspots
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Finding mutation hotspots EGFR in PANCAN11
Amino Acid Position
Mutation count
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Finding mutation hotspots EGFR in PANCAN11
Mutation count
Smoothed at multiple
bandwidths
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Finding mutation hotspots EGFR in PANCAN11
Mutation count
Multiscale clusters
Smoothed at multiple
bandwidths
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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
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Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
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Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
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Mutation hotspots vary substantially in size ~15,000 hotspots in ~2500 genes in PANCAN11
• 84% of the OncoDrive clusters overlap with the Multiscale clusters
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Are these mutation hotspots functional?
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Are these mutation hotspots functional? Identify statistical associations with: • Protein domains • Gene expression • Signaling pathways • Drug response
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Statistical association between hotspots and gene expression
Binary mutation
calls
Mutation hotspots
Sam
ples
Continuous gene expression profiles
Genes
Sam
ples
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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
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Statistical association between hotspots and gene expression in UCEC
P=4·10-8
P=1·10-7
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Statistical association between hotspots and gene expression in UCEC
P=8·10-9 P=2·10-3
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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
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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
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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
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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
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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
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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
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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
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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
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Drug response depends on mutation hotspots
GDSC Mutations in PIK3CA
EGFR/ERBB2 inhibitor
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Drug response depends on mutation hotspots
GDSC Mutations in PIK3CA
PIK3CA inhibitor
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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
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Future work
• From PANCAN11 to the PANCAN Atlas • Integrate the mutation hotspots into Regulome
Explorer (RE) • Make code and hotspots available
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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)
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Poster: 57
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Statistical association between hotspots and gene expression in UCEC
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Statistical association between hotspots and gene expression in UCEC
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Statistical association between hotspots and gene expression in UCEC
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Statistical association between hotspots and gene expression in UCEC
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Statistical association between hotspots and gene expression in UCEC
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Statistical association between hotspots and gene expression in UCEC