reconstructing tumour evolution: reconstructing the evolution of a drug-resistant liposarcoma -...
DESCRIPTION
Tumours are a collection of genetically distinct cellular lineages related that must compete against each other and the external environment. Many cell lineages die out, while those with phenotypes that are advantageous expand. A major clinical consequence of this evolutionary process is the emergence of drug resistant tumour cells. We have established an in vitro model system in which we can induce the human well-differentiated liposarcoma (WDLPS) cell line 778 to acquire resistance to the MDM2 inhibitor Nutlin-3a. I will detail we have applied bioinformatics and evolutionary principles to reconstruct major evolutionary events that occurred as this line acquired drug resistance. Integration of SNP array and exome sequencing data from different time points during the evolution of Nutlin resistance allow us to infer the relative order of genetic changes and how the rate of evolution fluctuated during the course of the experiment.TRANSCRIPT
Reconstructing the evolution of a
drug-resistant liposarcoma
David Goode
Sarcoma Genetics & Genomics
Peter MacCallum Cancer Centre
March 28, 2014
Evolution of Drug Resistance in Tumours
“Clonal cell lineage (clone)”
+2.5 μM Nutlin
95 days
in Nutlin
252 days
in Nutlin
778
(liposarcoma)
Experimental Outline
R95
R252
(‘resistant’)
Copy-number (CN)
profiling using SNP
genotyping arrays
778
(‘parental’)
SNP genotyping arrays
• B Allele Frequency (BAF)
• Relative frequency of the B allele [0 – 1]
• Log R Ratio (LRR)
• Copy-number relative to normal diploid genomes
A/B
B A
Localised but frequent changes in
CN observed in Nutlin-resistant lines
R252 - 778
R95 - 778
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y
Change in allelic ratios on chr15 in R252
(red) from 778 (black)
Change in allelic ratios on chr15 occurred between R95 & R252
+2.5 μM Nutlin
Loss of one
copy of chr15
778
(‘parental’)
Ordering chromosomal CN changes
R95
R252
(‘resistant’)
Gain of section of chr11q in resistant lines
+2.5 μM Nutlin
Gain of part
of 11q
Gain of one
copy of chr15
778
(‘parental’)
Ordering chromosomal CN changes
R95
R252
(‘resistant’)
Exome sequencing
• 12 clones each from R252 (resistant) and 778 (parental)
• Clones derived from single cells
• Nimblegen exome capture
• Illumina Hi-Seq (100X+ coverage)
• SNVs called with GATK’s Unified Genotyper
• Use frequency of alternate (non-reference) allele to
identify CN polymorphisms
BAF pattern on chr11 not present in
any clones from 778
778 Clone 1 (8/12) 778 Clone 2 (4/12) All R252 clones
+2.5 μM Nutlin
Gain of part
of 11q
Gain of one
copy of chr15
778
(‘parental’)
Ordering chromosomal CN changes
R95
R252
(‘resistant’)
BAF pattern on chr5 present in
minority 778 clone
778 Clone 1 (11/12) 778 Clone 2 (1/12) All R252 clones
Most likely ancestor
of resistant clones
+2.5 μM Nutlin
Gain of part
of 11q
Gain of one
copy of chr15
778
(‘parental’)
Ordering chromosomal CN changes
R95
R252
(‘resistant’)
Gain one copy
of chr5
778
(‘parental’)
Ordering observed copy-number (CN) changes [relative to 778 SNP arrays]
R95
R252
(‘resistant’)
8 (4, 3, 1)
3 (2, 1, 0)
6 (3, 2, 1)
# of CN changes
(Loss, Gain, Other)
+2.5 μM Nutlin
Phylogeny of 778 and R252 clones
Phylip (DNApars)
0.87
1.93
0.66
2.79
2.99
2.65
2.45
3.31
2.38
2.16
2.45
2.42
2.32
2.12
1.2
0.7
0.99
0.88
0.96
0.94
1.33
1.06
0.95
1.005
Clone phylogeny labeled with Nutlin IC50 values
*share a non-syn
TP53 SNV (C238F)
Arcadi Cipponi
+2.5 μM Nutlin
Slowing of CN
mutation rate
778
(‘parental’)
R95
R252
(‘resistant’)
Minor clones
potentially
Nutlin resistant
Evolutionary history of R252
Clones
Acquired null
TP53 mutation Many CN changes
in quick succession
Summary
• BAFs to identify major CN changes occuring during
evolution of Nutlin resistance
• Sequencing individual clones improves resolution of
evolutionary events and reveals population substructure
• Selection for CN changes early in evolution
• Point mutations in clonal subpopulations later on
• Next: WGS on experimental replicates and on other cell
line/drug combinations
Acknowledgements
• David Thomas
• Arcadi Cipponi
• Tiffany Pang
• Kevin Mills
• Natnicha Inthavong
• Bioinformatics Core
• Maria Doyle
• Joshy George
• Jason Li
• Jason Ellul
• Molecular Genomics Core
• LSCC/VLSCI
• Gayle Philip
• Jessica Chung
• Andrew Lonie
• Leonardo Meza-Zapeda (Oslo) • microarrays