Cancer Genomics. Nic Waddell. Winter School in Mathematical and Computational Biology. July th
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1 Cancer Genomics Nic Waddell Winter School in Mathematical and Computational Biology 6th July 2015
2 Time Line of Key Events in Cancer Genomics Michael R. Stratton Science 2011;331:
3 The Cancer Genome Michael R. Stratton et al. Nature 2009
4 The Hallmarks of Cancer Hanahan and Weinberg, Cell 2000
5 The Hallmarks of Cancer: The Next Generation Hanahan and Weinberg, Cell 2011
6 Next Generation Sequencing: Cancer TCGA The Cancer Genome Atlas (cancergenome.nih.gov) ICGC International Cancer Genome Consortium (icgc.org) Comprehensive genomic characterization of tumours Identify driver genes Understand molecular aetiology and disease progression Stratify tumours Explore options for therapy Improve patient outcome
7 ICGC and TCGA Projects
8 Cancer Genomics SNPs and Indels ABCC9 ADAMTS20 AMAC1L2 B3GALT4 BLID BRCC3 C3orf62 C11orf94 CACNA1C CAPN11 CENPE COLEC11 CTCF FRMD6 GPR137B IQCH KIR3DX1 KLKB1 LEMD2 PIK3CD PXDN RPA1 SIGLECP3 SLC26A5 TIMELESS ZNF432 ZNF132 Genes affected by breakpoint 133 genes Expressed Fusion transcript ATE1 KLRAQ1 Differential Methylation & Expression 1800 genes
9 Mutation Burden in Cancer Which mutations are driving the disease? Which mutations are actionable? Alexandrov et al. Nature 2013
10 Identification of Driver Genes Identification of Mutated Genes Identify recurrent mutations Exact same mutation ie KRAS G12D, BRAF V600E etc Identify recurrently mutated genes Need to correct for bias eg gene length, ratio synonymous: non- synonymous Are there cluster of mutations within a gene? Functional impact of mutation Is the mutation a known cancer mutation? Predict the functional impact of the mutation ie activating or deleterious? Several informatics tools which use different approaches are available
11 Non Coding Driver Mutations TERT promoter mutations G>A somatic mutations located at 124 to 149 bp from TSS Create Ets/TCF binding motifs Horn et al. Science 2013;339:
12 Mutation Scars or Footprints in Cancer Genomes Helleday et al. Nature Reviews Genetics 2014
13 Mutational Signatures 6 Classes of Base Substitutions C>A C>G C>T T>A T>C T>G Bases immediately 5 and 3 C>A ACA ACC ACG ACT CCA CCC CCG CCT GCA GCC GCG GCT TCA TCC TCG TCT 16 possible sequence contexts for each mutated base = 96 possible mutated trinucleotides Alexandrov et al Nature 2013
14 Mutation probability Mutational Signatures ACA, ACC, ACG, ACT, CCA, CCC, CCG,CCT,GCA,GCC, GCG, GCT, TCA, TCC, TCG, TCT ncg Mutation frequency across 96 trinucleotides context Nik-Zainal et al. Cell 2012 Alexandrov et al. Nature 2013
15 Mutational Signatures Age Age APOBEC BRCA Smoking MMR UV Alexandrov et al. Nature 2013
16 Mutational Signatures in Different Cancers Alexandrov et al. Nature 2013
17 Structural Rearrangements
18 SVs and Gene Consequence Disruption of gene loci Deletion of gene loci Amplification of gene loci Fusion of two gene loci
19 Patterns of Chromosome Rearrangements
20 Chromothripsis Stephens et al. Cell 2011
21 Chromothripsis: A Driving Event First reported as occurring in ~2-3% of cancers Now: Bone cancer 25% Acute Myeloid Leukaemia 36% Neuroblastoma 18% Oesophageal 35% Catastrophic event that may affect several genes in only a few cell cycles Stephens et al. Cell 2011 and Korbel and Campbell 2013
22 Cancer Development: Stepwise Model Normal cell division Cancer cell division Cell damage No repair Stepwise accumulation of mutations Cell Suicide Or Apoptosis Relaxed DNA repair Over-ride built in senescence Acquire a continuous Growth Signal Turn off internal Suicide system First mutation Second mutation Third mutation Fourth or later mutation Uncontrolled growth
23 Cancer Development: Rapid Transformation Normal cell division Cancer cell division Cell damage No repair Rapid Transformation Cell Suicide Or Apoptosis Genomic Catastrophe leading to several driving events simultaneously First mutation Second mutation Third mutation Uncontrolled growth
24 Pan-cancer Analysis The Cancer Genome Atlas (TCGA) Pan-Cancer analysis project Nature Genetics 45, (2013)
25 Tumour Challenges Heterogeneity for Cancer Genomics Tumour heterogeneity and tumour clonality Inter tumour heterogeneity Subclone 1 Intra tumour heterogeneity Subclone 2 Clonal heterogeneity Subclone 3 Burrell et al. Nature 2013
26 Challenges for Cancer Genomics Tumour heterogeneity and tumour clonality Resistance to therapy Consequence of mutations Identification of actionable mutations Application of genomics to diagnostics and therapeutics
27 Clinical Genomics England 300 million, 100,000 patients USA Precision Medicine Initiative USD 215 million, 1 million patients
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Name: Date: Block: BIOLOGY 621 Identification of the Snorks INTRODUCTION: In this simulation activity, you will examine the DNA sequence of a fictitious organism - the Snork. Snorks were discovered on