The document discusses how cancer genomics is transforming cancer diagnosis. Next-generation sequencing technologies are enabling whole genome and exome sequencing of tumors at lower costs. This allows comprehensive genomic profiling of cancers to detect mutations, rearrangements, and biomarkers that provide diagnostic, prognostic and treatment information. However, challenges remain around technology, costs, data analysis and clinical integration. Pathologists will need to adapt training and integrate genomic data into diagnostic reporting to realize the potential of cancer genomics.

1. The changing face of cancer diagnosis George Vassiliou November 2011

2. Overview Today’s cancer diagnostic lab The era of cancer genomics Novel diagnostic applications Introducing genomics to cancer diagnosis

3. Today’s cancer diagnostic lab The era of cancer genomics Novel diagnostic applications Introducing genomics to cancer diagnosis Overview

4. The light microscope remains the central cancer diagnostic tool for 400 years Zacharias and Hans Jansen (ca 1595) Modern microscope (ca 1995)

5. Today’s cancer diagnostic lab Cellular Phenotyping Microscopy (histology/cytology) Immunohistochemistry Flow Cytometry Genetic tests Cytogenetics Molecular Genetics Genotyping for specific mutations (PCR/RT-PCR) Minimal Residual Disease monitoring (CGH and SNP/LOH genotyping) (Gene Expression Profiling)

6. Haemato-oncology lab Microscopy Immunophenotyping Cytogenetics Molecular Genetics Sample Integrated report MICROSCOPY: >80% undifferentiated blasts Morphology of acute lymphoblastic leukaemia Eosinophils, basophils and small megakaryocytes suggest blast phase of chronic myeloid leukaemia IMMUNOPHENOTYPE: Blast cells are CD10, CD19, CD79a, CD34, HLA-DR, TdT positive. Weak CD13. They do not express CD33 or myeloperoxidase. DNA index is 1.0 Phenotype of B lymphoblastic leukaemia or B lymphoblastic transformation of CML CYTOGENETICS: Karyotype: 46,XY,t(9;22)(q34;q11) in 10 of 10 metaphases FISH: BCR/ABL 92% positive MOLECULAR GENETICS: BCR-ABL fusion transcript type: p210 e13a2 by RT-PCR OVERALL CONCLUSION: B lymphoblastic blast crisis of chronic myeloid leukaemia Cytology Histology Immunohistochemistry Diagnostic panels Karyotyping FISH Mutational screening RT-PCR qPCR (MRD)

7. Diagnostic CGH/SNP genotyping

8. n= 241 Diagnostic gene expression profiling MammaPrint – 70 gene signature (NKI) Lymph node positive breast cancer

9. CR-UK stratified medicines initiative Tumour type Gene Mutation Drug Colorectal KRAS Codons 12, 13, 61, 146 Cetuximab/Panitumumab BRAF V600E/D/K/R/M Sorafenib/Cetuximab TP53 Exons 2-­‐11 PI3KCA Exons 9 and 20 PI3Kinase inhibitors UGT1A1 UGT1A1*28 Irinotecan toxicity Breast PI3KCA Exons 9 and 20 TP53 Exons 2-­‐11 PTEN LOH/mutation hotspots mTOR inhibitors CYP2D6 5 SNPs Response to tamoxifen Prostate PTEN LOH/mutation hotspots mTOR inhibitors TMPRSS-­‐ERG Junction fragment PCR TLR4 2 SNPs Lung EGFR Exons 18-21 Erlotinib/gefitinib EML4-­‐ALK Fusion product PF02341066 ALK/c-Met inhibitor XRCC2 5 SNPs Response to platinum agents ERCC1 mRNA expression RRMI mRNA expression Ovary PTEN LOH/mutation hotspots mTOR inhibitors PI3KCA Exons 9 & 20 BRAF V600E/D/K/R/M Sorafenib/Braf inhibitors Melanoma BRAF V600E/D/K/R/M Sorafenib/Braf inhibitors CKIT Exons 11,13,17

10. Today’s cancer diagnostic lab The era of cancer genomics Novel diagnostic applications Introducing genomics to cancer diagnosis Overview

11. Advances in DNA sequencing technologies 10 2 10 4 10 6 10 8 10 10 10 12 10 14 10 16 Output kbp / run 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Ion Torrent Capillary (Sanger) Sequencing Next Generation Sequencing (NGS) 454 pyroseq Solexa/ Illumina ABI SOLID Illumina HiSeq Technologies Roche/454 Titanium ABI SOLID 3.0 ABI capillary

12. Rapid reduction in sequencing costs

13. Sanger Institute Total yield by week (Gigabases) 2008 2009 2010 2011

14. How Fast is That? 6000 Gb per week (6 Tb) = 10,000,000 bases per second ½ hour per 6Gb (= 1x Human Genome)

15. Genome Sequencing 2015 ? ~1day ?? $100 Cancer Genomics Sanger (capillary) sequencing 2005 ~3 years ~$ 20million 2010 ~1month $9,500 (Illumina) AML Melanoma Small-cell lung Breast 2008 ~4 months ~$ 1.5million Lung (NSS) 2000 ~10 years ~$ 3.5 billion Myeloma Hepatocellular CLL Mouse AML Next generation sequencing

16. Analysing cancer genomes From Ding et al, Hum Mol Gen, 2010

17. Genomic Circos Plot Circos Plot from Pleasance et al, Nature 2010 Deletions/Insertions Substitution density (het) Substitution density (homo) Coding Substitutions Silent Missense Nonsense Splice site Copy number Regions of LOH Structural rearrangements Intrachromosomal Interchromosomal Genomic coordinates

18. 1000s of individual cancer genomes 100s of recurrent mutations Aetiological links Clinico-pathological correlates Delineation of effects of many mutations Development of new therapies > Increasing use of genomics in cancer diagnosis, prognosis & therapy This decade

19. Today’s cancer diagnostic lab The era of cancer genomics Novel diagnostic applications Introducing genomics to cancer diagnosis Overview

20. The clinical process in oncology        Pre-clinical phase Presentation Diagnosis Treatment Assessment of response Follow-up Relapse

21. Whole genome sequencing (~6Gb) Exome sequencing (~60Mb) Selected gene/exon DNA sequencing Residual disease monitoring (plasma DNA) New diagnostic applications

22. Whole genome sequencing A B C D

23. Diagnostic whole genome sequencing Clinical Report Constitutional genome Cancer genome Compare Other diagnostic data Somatic mutations Subclonal heterogeneity Substitutions Indels Copy number changes Translocations Inherited mutations & polymorphisms

24. Exome sequencing: target enrichment Chr1 NRAS regions covered “ Baits” or PCR amplicons

25. Diagnostic whole exome sequencing Clinical Report Constitutional exome Cancer exome Compare Other diagnostic data Somatic mutations Subclonal heterogeneity Substitutions Indels Copy number changes Translocations Inherited mutations & polymorphisms

26. Selective sequencing example : an AML toolkit ~ 20 genes known to be recurrently mutated Prognostic/treatment implications known for some Target enrichment by “pull down” Can detect: Sequence changes Copy number (UPD/LOH) ASXL1 NF1 CBL NPM1 CEBPA NRAS CSF1R RUNX1 DNMT3A TET2 FLT3 WT1 IDH1 EZH2 IDH2 KIT JAK2 KDM6A KRAS TP53 MLL PTPN11 BRAF IKZF1 HPRT1 PAX5 PIK3CA UGT1A1 CYP2D6 TLR4 EGFR XRCC2 PTEN

27. Selective sequencing example : an AML toolkit Type A (Transcription Factor) Type B (DNA modification) Type C (Signal transduction) PROGNOSIS AML1 NPM1 DNMT3A R882C FLT3-TKD Intermediate AML2 TET2 KRAS K117N Intermediate AML3 CEBPA NRAS G12D Intermediate AML4 NPM1 IDH1 R132H FLT3-TKD Favourable AML5 ASXL1 KRAS G12D Poor AML6 IDH2 R172K Poor

28. Plasma DNA Cancer Normal tissues DNA with tumour-specific mutation Slide courtesy of Dr Peter Campbell

29. Tumour-specific rearrangements Individual Breast Cancer Genome 1 st round PCR Nested real-time PCR Chr20 Chr10

30. Relapsing breast cancer Slide courtesy of Dr Peter Campbell 0.1 0.01 1 0.05 0.5 Undiluted patient plasma 1:10 1:100 1:1000 1:10,000 1:100,000 Normal Water 0 5 10 15 20 25 30 35 40 Cycles of real-time PCR Intensity Non-rearranged genomic region 0.1 0.01 1 0.05 0.5 0 5 10 15 20 25 30 35 40 Cycles of real-time PCR Intensity Tumour-specific rearrangement

31. Serial measurements 150 Months after diagnosis Estimated tumour DNA / mL serum (pg) 25 50 75 100 125 Undetectable Detectable at limit of sensitivity 6 7 8 9 10 11 12 13 14 15 16 17 5 Rearrangement 1 Rearrangement 2 First-line chemotherapy Second-line Paclitaxel CT scan: Localised deposits around T9-10 Chemotherapy: CT scan: Widespread soft-tissue metastases Slide courtesy of Dr Peter Campbell

32. Multiple biomarker MRD Methylomics Transcriptomics (RNAseq) Cancer screening / Biomarker assays Other applications of NGS

33. Today’s cancer diagnostic lab The era of cancer genomics Novel diagnostic applications Introducing genomics to cancer diagnosis Overview

34. Hurdles to the introduction of diagnostic cancer genome sequencing Technology Sample choice/compatibility FFPE, other Cost $10,000/genome Sample to sequence delay 8-10 days Mutation calling Specificity / Sensitivity Laboratory Sequencing equipment Choice/Cost New personnel Bioinformaticians Computer storage Petabytes (10 15 ) Education/training Pathologists, Clinicians Clinic Clinical relevance/utility Evolving Personal genomes/Ethics Being tested

35. Genome Campus Data storage & analysis Sulston Building Morgan Building Research Support Facility Data Centre European Bioinformatics Institute

36. Training of pathologists Core training in genomics New sub-specialty e.g. Molecular Pathology? Impact on other aspects of training How will the training be delivered? Training/role of laboratory scientists Keeping control of the agenda

37. Diagnostic reporting of genomic data Communicating the cancer genome to the clinician Diagnosis Recurrently mutated genes Non-recurrent/private mutations / pathways Prognostic relevance Therapeutic relevance Pharmacogenomics Constitutional genome Mutational signatures Summary / Imagery

38. Implications for cancer classification Cellular origin Morphology Differentiation/grading Mutations: Diagnosis Prognosis Treatment Unified Classification?

39. Acute Myeloid Leukaemia – a paradigm of evolving classification Morphology Single entity Various 1950s Morphology & cytochemistry M0-M7 FAB 1976 Morphology, AML with recurrent cytogenetic translocations WHO 2002 Immunophenotyping & AML with multilineage dysplasia Cytogenetics AML, therapy related AML not otherwise categorized Morphology, AML with recurrent genetic abberations WHO 2008 Immunophenotyping , Provisional entity: AML with mutated NPM1 Cytogenetics & Provisional entity: AML with mutated CEBPA Genetics Otherwise as 2002

40. Will there be a paradigm shift ? ?

41. Summary The advent of cancer genomics is changing cancer medicine Changes will transform cancer diagnosis and the role of pathologists Pathologists need to understand what is coming in order to lead and formulate the future for cancer diagnosis