Predictive Biomarkers and Drug Resistance

1. Acquisition of tumour multidrug resistance inevitable in most advanced solid tumours Failing to cure the majority of advanced solid tumours Declining therapeutic benefits at higher drug cost Drug resistance highly complex: Approx 10% of kinases alter resistance to one or more drugs (Swanton et al 2007 Cancer Cell ; Swanton et al 2007 Cell Cycle) Failure of Biomarker Validation 150,000 biomarkers only 100 for clinical use Predictive Biomarkers and Drug Resistance

2. Intratumour Heterogeneity • Evidence of intratumour heterogeneity • Possible Implications for biomarker studies • Practical approaches to address heterogeneity

3. Breast Cancer Intra-tumour HeterogeneitySector Ploidy Profiling and DNA Copy Number Analysis • Multiple intermixed cell subpopulations within one tumour differ by large genomic events/focal amplifications/ deletions Geyer and Reis-Filho J Path 2010 Shah and Aparicio Nature 2012 Navin N, et al. Genome Res 2010 Navin N, et al Nature 2011

4. Does a Single Tumour Biopsy: • Represent the tumour somatic/transcriptomic landscape ? • Provide robust biomarkers of outcome ? • Demonstrate that all mutations are ubiquitously present in every region of a tumour • Predicted by a linear/clonal sweep model of tumour evolution • Provide reliable data following Deep Sequencing Analysis to stratify patients for trials ?

5. Primary Mets Ubiquitous Shared Primary Shared Mets Private 65% mutations are heterogeneous and not present in every biopsy

6. Re-construct Phylogenetic Evolution of Tumour

7. Evidence for Convergent EvolutionSETD2 Loss of Function: H3K36 tri-methylation Normal 3 distinct SETD2 mutations associated with loss of function: Mutational capacity?

8. Evidence intratumour heterogeneity may impact upon drug response? • 6 weeks of Everolimus therapy • Assess status of mTOR pathway across different regions of the tumour • Evidence of Differential Pathway Activity post-Everolimus exposure?

9. mTOR active in all primary regions except R4 and metastases

10. Heterogeneous Kinase Domain mTOR mutation L2431P mTOR mutation L2431P

11. Kinase Domain mTOR mutation L2431P Associated with Constitutive Activation of the mTOR Kinase

12. Kinase Domain mTOR mutation L2431P Lies in A Repressor Domain Close to Activation Loop of Kinase

13. Tracking Tumour Growth R9 Normal Perinephric Metastasis Chest Wall Metastasis M1 M2a,b Seeding of metastatic sites can be tracked to one tumour region

14. Primary Tumour Regions Metastatic Sites Primary Tumour Regions Metastatic Sites Allelic Imbalance: ITH within Chest wall metastasis R9 Chest Wall Metastasis Perinephric Metastasis M2a,b M1 Only somatic mutations with >20x coverage were included Only somatic mutations with >20x coverage were included

15. Primary Tumour Regions Metastatic Sites Primary Tumour Regions Metastatic Sites Heterogeneity of RCC Prognostic Signature Expression Genes in ccB Median ccA 103 months ccB 24 months Genes upregulated in ccA Only somatic mutations with >20x coverage were included Only somatic mutations with >20x coverage were included

16. Darwin and cancer branched evolution

17. Relevance of ITH and Cancer Branched Evolution • Tumour Diversity Supports Evolutionary Fitness • (Maley et al 2006) • Tumour Adaptation and Selection for • Drug resistance (Su et al 2012; Lee et al 2011) • Metastatic growth (Yachidaand Campbell 2010, Shah 2009) • Tumour Sampling Bias • Different tumour biopsies different results • Sites of disease evolve independently • Clonal Dominance and Actionable Mutations? • Mutations present at one site but not another Patient 1