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Why sequence tumors from mice?

Exome sequencing analysis of the mutational spectrum in carcinogen and genetic models of Kras -driven lung cancer. Peter Westcott, Kyle Halliwill, Minh To, David Quigley, Reyno Delrosario, Erik Fredlund, David Adams 1 , and Allan Balmain

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Why sequence tumors from mice?

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  1. Exome sequencing analysis of the mutational spectrum in carcinogen and genetic models of Kras-driven lung cancer Peter Westcott, Kyle Halliwill, Minh To, David Quigley, Reyno Delrosario, Erik Fredlund, David Adams1, and Allan Balmain UCSF Helen Diller Family Comprehensive Cancer Center, 1450 3rd Street, San Francisco. 1 Wellcome Trust Sanger Centre, Cambridge, England.

  2. Why sequence tumors from mice? Control! • Timing of initiation  collection • Initiating gene(s), carcinogen(s) • Can distinguish mutations involved in initiation from • progression

  3. Specific goals of this study Part of the MMHCC TCGA Pilot Project Characterize the utility of sequencing mouse tumors: • What is the effect of the causative carcinogen on • mutation spectrum? • Clean genetic induction (GEM) vs. carcinogen induction? • What mutations arise after Kras initiation?

  4. Exome sequencing Urethane MNU KrasLA2 (GEM) 44 lung tumors from 17 mice 26 lung tumors from 7 mice 13 lung tumors from 4 mice Kras+/- (FVB/Ola) KrasLA2 (FVB/Ola) Spontaneous lung tumors Kras+/- Kras+/+ Control tail DNA: 2 Kras+/+ tails

  5. Exome sequencing • Illumina paired-end sequencing (Wellcome Trust Sanger Centre) • Have aligned reads to mouse genome, called against multiple • controls and performed extensive QC (Kyle Hallilwill) • Have a confident list of somatic variants

  6. Exome sequencing

  7. Carcinogen models of Kras-driven lung cancer Urethane (ethyl carbamate) • Adenosine and cytidine DNA adducts lead to mispairing: Replication Mispairing T A • Kras Q61L (CAACTA), Q61R (CAACGA). • ~90% of lung tumors harbor Kras mutations.

  8. Carcinogen models of Kras-driven lung cancer MNU (methyl-nitroso urea) • Guanosine DNA adducts lead to GA transitions Replication Mispairing G A G G • Kras G12D (GGTGAT) • ~90% of lung tumors harbor Kras mutations Genome-wide spectrum of these carcinogen mutations not known

  9. Mutation spectrum Urethane MNU Light shade = Kras+/- LA2

  10. Mutation spectrum Slight bias for mutations at G/C nucleotide Strong bias for mutations at G nucleotide with flanking G or A Strong bias for mutations at A/T nucleotide

  11. Mutation spectrum Average counts per tumor 5’ A 5’ G • Purine bias at 5’ flanking base

  12. Mutation spectrum • Are non-carcinogen mutations separable? 670 Urethane MNU LA2 80 60 Average counts per tumor 40 20 0 NCG->T Other G->A A->T A->G A->C G->C G->T For the most part

  13. ARE CARCINOGEN MUTATIONS RELEVANT?

  14. Other driver mutations? • Analysis complicated: • High mutation rates: MNU – 21.2/Mb • Urethane – 6.4/Mb • LA2 – 1.9/Mb • Correlation between gene length and mutations • Start with variants within Vogelstein’s 2013 list of drivers: • Selected only consequential mutations at • highly conserved sites in expressed genes

  15. Other driver mutations? None of these mutations occur in LA2 tumors Slight enrichment for longer genes Modest increase in NS mutation ratio One S367 to F – required for autophosph. and activity Subclonal Myc T58P?

  16. Conclusions Mutation Spectrum • Clear recapitulation of expected carcinogen mutations • GEM shows few mutations • Mutations highly specific and distinguishable Driver Mutations • Kras • Interesting candidates in carcinogen-induced tumors

  17. Future work • Validate top 1000 interesting variants by Sequenom • (Wellcome Trust Sanger Centre). • Optimize list of potential driver mutations (relevant sites?). • InDel analysis. • Array CGH (copy number analysis). Inverse correlation of • point mutational burden and copy number changes?

  18. Acknowledgments Kyle Halliwill Minh To David Quigley Reyno Del Rosario Erik Fredlund ALLAN BALMAIN DAVID ADAMS (WELLCOME TRUST SANGER CENTRE) $: MMHCC $: NIH Training Grant T32 GM007175 $: NSF

  19. Supplemental (Kyle’s Pipeline) • Capture using Agilent mouse whole exome kit • Sequenced on illumina HiSeq • Paired end, 75 bp each, average read span of 180 bp • Converted back to FASTQ, then followed QC pipeline (next slide)

  20. Supplemental (Kyle’s Pipeline) Align to Mm10 with BWA Mark duplicates and fix mate information with picard QC and Variant Calling Strategy Base recalibration and realignment with GATK Alignment and coverage information with picard Variant calling with MuTect Filter for depth and previously observed variants with vcftools

  21. Supplemental (Kyle’s Pipeline) Variant Calling via MuTect Control1 .bam Variant Calling Details Variant List1 .vcf Intersect Filter, Annotate Candidate Variant List .vcf Candidate Variants Sample .bam Variant List2 .vcf Control2 .bam

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