Clinical Interpretation of Cancer Genomes

Transcription

1 IGENZ Ltd, Auckland, New Zealand Clinical Interpretation of Cancer Genomes Dr Amanda Dixon-McIver

2 1992 Slovenia and Croatia gain independence USA and Russia declare the Cold War over Steffi Graf and Andre Agassi win Wimbledon Los Angeles riots Annus horribilis Whitney Houston I Will Always Love You Nirvana Smells like Teen Spirit Mr Big To Be With You

3 Meanwhile back in the lab CGH arrays to detect CNVs of >10 Mb in solid tumours resolution limited by number and length of probes some chromosomal regions not well described probes evenly spaced across the genome

4 2012 Human Genome Project ( ) Produced a library of cloned DNA fragments Arrays now designed for specific applications Post-natal (Constitutional and Acquired), Prenatal ISCA (2007) [CCMG (2009)] >100 clinical laboratories worldwide >24,000 clinical cases (~500 per week)

5 Constitutional arrays A first-tier test for individuals with: Intellectual disability Autism spectrum disorder And/or multiple congenital anomalies Discovery of widespread CNVs Polymorphic variation in normal individuals Novel pathogenic copy number imbalances

6 An acquired approach Constitutional karyotype Acquired karyotype Constitutional genomics Cancer genomics Diagnoses have often already been made Sample source limitations Complexity/Clonal evolution Treatment/Prognosis dependent Recurrent changes - drug-targeted therapy

7 Same, same but different Rugby Union Rugby League Same number of players, same ball, same field but different rules, different interpretation

8 What is expected from our analysis? Confirmation of an established diagnosis Assistance with a differential Small round blue cell tumour?ewings?rhabdo?neuroblastoma Treatment direction Resistance to specific drug therapies Prognostic information High risk, intermediate risk, low risk

9 How are these expectations achieved? Identification of known/recognised genetic markers associated with: Disease phenotype Established treatment protocols Prognosis

10 How are these expectations achieved? Identification of known/recognised genetic markers associated with: Disease phenotype Established treatment protocols Prognosis

11 How are these expectations achieved? Identification of known/recognised genetic markers associated with: Disease phenotype Established treatment protocols Prognosis Knowing what is recurrent can be used for diagnosis, stratification and treatment

12 Obstacles in our way The entire genome is examined in great detail

13 Obstacles in our way The entire genome is examined in great detail The ability to discover genomic changes previously unknown

14 Obstacles in our way The entire genome is examined in great detail The ability to discover genomic changes previously unknown Understanding the significance of the data Benign germline aberrations

15 Obstacles in our way The entire genome is examined in great detail The ability to discover genomic changes previously unknown Understanding the significance of the data Benign germline aberrations Presenting the information in a meaningful way

16 Example 70 year old male with Multiple Myeloma FISH for t(4;14) and TP53 deletion performed

17 Example CGH changes that are potentially pathogenic

18 Example 3.9MB gain at 3p26.3 to 3p26.2 related to multiple sulfatase deficiency

19 Example 27 LOH regions of unknown significance

20 Example

21 Example Hyperdiploidy +3,+5,+9,+11,+15,+19,+21 Loss of 1p, Gain of 1q, Loss of 8p, Loss of 13q

22 To array or not to array? Some acquired abnormalities lend themselves to genomic testing by arrays Multiple Myeloma CLL MDS (?) Other traditional options should still be considered for those diseases which do not Balanced recurrent aberrations

23 Knowledge is power Knowledge of the genetics in the context of the disease is important

24 Knowledge is power Knowledge of the genetics in the context of the disease is important Additional copy of chromosome 8 AML intermediate risk MDS intermediate risk CMML high risk

25 Knowledge is power Knowledge of the genetics in the context of the disease is important Additional copy of chromosome 8 AML intermediate risk MDS intermediate risk CMML high risk Contribution to the CCMG database is crucial

26 Interpreting your findings Relate the findings to your disease-specific knowledge Consult the literature and appropriate databases Do not restrict your analysis solely to the deleted region Fusion genes do exist within the same chromosome Think FIP1LI-PDGFRA and HES Think complexity Chromothripsis Segments can evolve clonally Segmental/Interstitial UPD

27 Interpreting your findings Indicators for clonal heterogeneity Different log2 ratios for gains or losses Complex CGH Copy Number Peak Assignment Plots Peaks in CGH Copy Number Peak Assignment Plots not assigned Chromosome gains/losses not verified by SNP data Establish levels of detectable mosaicism Each tissue type has inherent differences in tumour burden Validation required for each specimen type

28 Anecdotal resistance How do you introduce array-testing into the diagnostic cancer environment?

29 Anecdotal resistance How do you introduce array-testing into the diagnostic cancer environment? Perseverance

30 Anecdotal resistance How do you introduce array-testing into the diagnostic cancer environment? Perseverance Data

31 A Clinician s Perspective I only want to know things of prognostic importance not all this other stuff.

32 A Clinician s Perspective I only want to know things of prognostic importance not all this other stuff. This other stuff may prove to be important Presentation of information

33 A Clinician s Perspective I only want to know things of prognostic importance not all this other stuff. This other stuff may prove to be important Presentation of information Software systems can allow you to perform a blinkered analysis

34 A Clinician s Perspective Do you have to write it using this ISCN jargon? I don t bother reading it, I m only interested in the summary/interpretation lines.

35 A Clinician s Perspective Do you have to write it using this ISCN jargon? I don t bother reading it, I m only interested in the summary/interpretation lines. arrxp22.33p11.1(984,576-58,543,823)x1,xp22.33(1,233,875-2,656,392)x1,xp22.2p22.13(10,367,564-17,257,492)x1,xq11.1q28(61,781, ,135,934)x1,1q21.1q23.1(143,730, ,802,759)x3,1q21.1(144,009, ,500,340)x3,1q21.2(149,041, ,202,620)x1,1q21.2q23.1(150,299, ,391,029)x3,1q23.1(157,529, ,802,759)x3,1q23.1q23.2(157,843, ,961,129)x3,1q24.2q25.1(170,053, ,085,993)x4,1q31.1q31.2(187,593, ,609,961)x2,1q31.3(197,752, ,493,907)x3,1q32.1(200,122, ,030,739)x3,1q32.1(200,460, ,787,364)x3,1q41(218,334, ,720,218)x4,1q42.2(233,814, ,246,545)x4,1q43(237,418, ,784,734)x2,1q43q44(242,692, ,224,147)x3,1q44(244,105, ,384,492)x3,2p12p11.2(76,316,196-84,089,013)x2,2q22.1q22.2(140,018, ,126,171)x2,3q26.1q26.2(161,577, ,693,004)x2,4p16.3(1,790,580-1,809,469)x2,4p16.3(1,874,120-1,903,002)x1,4q12q13.2(58,850,992-67,055,049)x2,4q13.2(69,374,729-69,482,146)x4,5q34(161,837, ,644,322)x2,6p12.3(47,939,487-51,018,097)x2,6q13(73,887,446-74,709,819)x2,7p12.1p11.2(51,520,174-55,270,319)x2,7q21.11(78,854,392-86,325,406)x2,8p22(15,954,386-16,021,744)x5,8p11.22(39,258,894-39,381,514)x10,9q34.3(139,391, ,418,283)x2,10q11.21(45,218,780-45,309,495)x1,10q11.22(46,938,469-47,897,498)x3,11p12(36,899,212-42,771,741)x2,11q14.3(89,909,492-92,575,700)x2,11q24.3q25(130,450, ,816,320)x2(12)x2,13q11q34(19,276, ,107,245)x1,13q12.11q14.3(19,590,141-52,643,741)x1,13q12.11q34(19,611, ,064,542)x2hmz13q14.3q21.33(54,981,366-72,877,486)x1,13q31.1q31.2(82,054,039-89,434,770)x1,14q11.2(19,728,641-20,421,677)x3,14q32.33(106,243, ,318,032)x1,14q32.33(106,269, ,304,840)x1,14q32.33(106,331, ,552,084)x3,14q32.33(106,357, ,392,806)x3,14q32.33(106,416, ,449,894)x3,14q32.33(106,469, ,513,022)x3,14q32.33(106,531, ,552,084)x3,14q32.33(106,636, ,943,374)x3,15q11.2(22,318,597-22,558,756)x1,15q13.2(30,441,097-30,954,785)x1,15q13.3(32,037,769-32,509,926)x3,16p13.3(2,106,222-2,138,073)x2,16p11.2p11.1(32,573,808-35,130,646)x2,16q21(59,804,745-65,569,348)x2,17q21.33(48,263,136-48,273,777)x2(18)x2,19p13.3(1,121,303-1,869,075)x2(20)x2,21p11.2p11.1(10,710,871-10,972,874)x2,22q11.1q13.33(16,854,776-51,059,792)x1,22q11.1q13.33(17,450,515-51,103,692)x2hmz22q11.21(18,293,951-18,847,248)x1,22q11.22(23,056,562-23,220,800)x3,22q11.23(23,603,190-23,632,565)x1,22q12.2(30,099,380-31,592,433)x1,22q12.3(36,680,285-36,716,311)x1,22q13.2(41,575,036-43,707,285)x1,22q13.31q13.33(45,258,546-51,059,792)x1,22q13.33(51,080,647-51,224,252)x1

36 A Clinician s Perspective How much will it cost?

37 A Clinician s Perspective How much will it cost? When establishing the cost of array testing in the acquired environment, it MUST reflect the complexity involved

38 A Clinician s Perspective How much will it cost? When establishing the cost of array testing in the acquired environment, it MUST reflect the complexity involved Looking at the whole genome, when complexity is the norm, is not an easy task

39 The road ahead Cancer microarray analysis is the ultimate challenge Know your software parameters and its limitations Know your diseases Submit your results to the CCMC database

40 The cancer genome is challenging but there are exciting times ahead...

41 Proof of Principle CCMC multi-platform/multi-centre studies Performance of cytogenomic arrays on multiple sample types Comparison of results to gold standard Intra-laboratory reproducibility Inter-laboratory reproducibility Cross-platform reproducibility (3 platforms)

42 Preliminary Findings Detected clinically actionable genomic changes compatible to gold standard Further defined cytogenetic aberrations origin, size and genetic content Identified submicroscopic genomic alterations and LOH Consistent results within and between laboratories and different platforms