Genomic instability in cancers and cancer predispositions. Popova Tatiana Inserm U830 Institut Curie

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1 Genomic instability in cancers and cancer predispositions Popova Tatiana Inserm U830 Institut Curie

2 Time-scale in a tumor genome discovery Bovery HYP Cancer genome Knudson 2 hit HYP Tumor DNA has transforming potential Mapping RB tumor suppressor By LOH RB tumor suppressor Discovery of APC tumor suppressor Discovery BRCA1 and BRCA2 predisposition genes Draft of Human genome Translocation in leukemia Protooncogenes in viruses P53 Telomeric sequence P53 is tumor suppressor Discovery of microsatellite instability MSH2 TERT And telomerase Balmain, A., Nature review cancer, 2001

3 Measuring tumor genome Sky image NGS SNP Array

4 Each tumor has more or less altered genome If tumor genome is altered Genetic alterations Tumor??? Tumor genome is unstable What does it mean??? It is necessary to distinguish STATE and RATE of alterations Genomic instability, if the RATE of alterations is higher than in normal cells within SIMILAR conditions Genomic instability IF stability genes are inactivated.

5 Cancer genes: Tumor suppressors and Oncogenes Tumor suppressors: "brakes" inhibiting cell growth and division RB1, Oncogenes: gas pedals" promoting cell growth and division KRAS, ERBB2, EGFR

6 Cancer genes: Stability genes or genome guardians Control fidelity of DNA replication, maintenance, repair, correct cell division, etc. If inactivated, increased rate of mistakes in DNA processing faster evolution to malignancy

7 Why we are interested by Genomic Instability The concept of synthetic lethality

8 Mutator phenotype hypothesis of Lawrence LOEB Loeb (mid 70s) suggested that the rate of mutations in normal cells is NOT enough to get highly altered tumor genome They introduced plenty of mathematical evolutionary models to explain how mutator phenotype promote tumor Discovery of tumor predisposition stability genes, such as BRCA1 and BRCA2 (breast and ovarian cancer), MSH2, APC (colon cancer), drove forward the idea of mutator phenotype.

9 Tumor suppressors need to be inactivated

10 Genetic instability gives advantage instable A+/+ A+/- A-/- stable A+/+ A-/- A+/-

11 Some types of genomic instability Microsatellite instability MIN (low fidelity in repeats maintenance) Chromosomal instability CIN (Copy number variation) Chromosomal structural instability CSI (Inter-chromosomal translocations) Mitotic instability MI ACACACACA ACAACACACA A A B A B A B B A B MIN CIN CSI MI Curr.Op.Genet.Dev Apr;17(2):

12 Two possible scenario of tumor evolution Genome stabilization??

13 Two possible scenario of tumor evolution 1. Sequencing efforts showed some success in deciphering tumor genome complexity. What s up?? and 2. Some strategies how we can distinguish this two scenarios based on the tumor genome analysis?? Genome stabilization??

14 Cancer genome acquire alterations during evolution Normal genome Mutations Chromosome gain / loss Chromosome translocation Cancer genome The end point of evolution, genomic SCAR The story is unknown.

15 Tumors show whole genome duplication pattern

16 Recurrent mutations versus CN variation

17 Point mutation distribution shows local events

18 Single structural catastrophic events: chromo-thripsis

19 Mutational signatures Prevalence of one or another type of mutations may evidence disruption of some stability pathway. The study is ongoing.

20 Tumor 1 Tumor 2

21 Tumor 3 Tumor 4 Tumor 5 Tumor 5 Blue: Amplifications Purple: Translocations Red: Tandem duplications

22 Genetic structural alterations in tumors Zhang et al, Genes and Development

23 Genetic structural alterations in tumors Chromo-thripsis Chromo-anasynthesis Chromo-plexis Zhang et al, Genes and Development

24 To conclude: To prove Genomic instability and find the genes responsible for this effect we need to describe and quantify the genetic alterations of each particular type. Find tumors enriched for some type of alterations Check the current status of tumor, does it show on-going genomic instability Try to find deregulation of some molecular pathway leading to this type of instability Then, at least for tumors with obvious complex genetic architecture, conclude about Past or Present genomic instability

25 Structural chromosomal instability in breast cancers: BRCA1 and BRCA2 predisposition genes Hereditary breast and ovarian cancer syndrome: GERMLINE MUTATIONS BRCA1 or BRCA2, The lifetime risk for these cancers in individuals with a mutation in BRCA1 or BRCA2: 40-80% for breast cancer 11-40% for ovarian cancer 1-10% for male breast cancer Up to 39% for prostate cancer 1-7% for pancreatic cancer

26 BRCA1/2 inactivation and breast cancer Sporadic cases ~90% Epidemiology of Breast cancer Familial clustering ~10% Hereditary cases without familial clustering X% BRCAXs 80% BRCA1 & BRCA2 TP53, PTEN, LKB1 FGFR2, TOX3, MAK3K1, LSP1, 8q, 2q, CASP8 ATM, CHEK2, BRIP1, PALB2 Hypothesis: BRCA1/2 inactivation genomic instability breast cancer homologous recombination deficiency or BRCAness Mainly, DNA repair genes Question: Accurate identification of BRCA1/2 associated breast tumors

27 Function of BRCA1 Homologous Recombination Narod & Foulkes. Nat Rev Cancer, 2004

28 Double strand break DNA repair DSB DSB signaling BRCA1 Homologous recombination (HR) BRCA2 Non-homologous end joining (NHEJ) Donor-dependent: High fidelity Donor-independent: Variable fidelity

29 Problem: detection of BRCA1 -/- based on the tumor genome BRCA1/2 inactivation genomic instability BUT Breast tumor genomes are known to be highly rearranged We need: Extraction of BRCA1/2 associated genomic instability We use: SNP arrays to measure genetic alterations SNP Array of a tumor genome Copy Number Variation AND Allelic Content profiles allow precise annotation of alterations and control for false positives

30 We developed a GAP method for mining SNP arrays Genome Alteration Print (GAP) for mining cancer SNP array profiles LRR BAF Popova et al. Genome Biol bioinfo-out.curie.fr/projects/snp_gap/

31 We developed a GAP method for mining SNP arrays Genome Alteration Print (GAP) for mining cancer SNP array profiles LRR BAF Popova et al. Genome Biol bioinfo-out.curie.fr/projects/snp_gap/

32 SNP array measurements of genomic architecture SNP Array of a tumor genome B LOH BBB BB AABBB breakpoints AABBB Number of chromosomes DNA index = mean CN / 2 SNP array profile CN recognition Hypothesis: Genomic profile could indicate disrupted DNA repair pathways What we can deduce from genomic scar?

33 We annotated genomic alterations with GAP and validated the method GT Chromosome number = sum(copy Number at centromere) AD LR DNA index = average(copy Number)/2 DNA index FCM DNA index by SNP arrays 20/23 (87%) correct DNA index Average error < 2 chr in 25 cell lines

34 We suggested a way to treat aneuploidy Frequency Frequency 270 near-diploid 200 over-diploid DNA index DNAi How to treat over-diploid tumors? Conclusion: Over-diploid 2 x Near-diploid Near-tetraploid

35 Genomic signature of homologous recombination deficiency in tumors Tumor 1 BRCA1-/- Tumor 2 BRCA1/2 wt Genetic alterations could arise due to various processes in tumorigenesis. How to detect homologous recombination deficiency???

36 Genomic signatures of BRCAness in breast cancer Unrepaired Double Strand Breaks Replication associated Double Strand Break A A B B B Hypothesis A A B B mitosis Normal A B A B Loss UPD A B A B Gain A B A B Readout Copy number alterations AB BB LOH AB ABB AB B A B A B LOH Obvious assumption: BRCA1 -/- tumors have more alterations

37 Broken stick model and segments size distribution Chromosome from breast cancer genome GT AD LR Segments size distribution in a set of breast cancers Starting from app. 3 Mb fits Brocken stick model

38 Genomic architecture of breast cancer Segments size frequency ~3 Mb Small-scale <3Mb Large-scale >3Mb Segments <3Mb Segments < 3Mb Ploidy 2 ns Ploidy 4 ns Segments >3Mb Segments > 3Mb Ploidy 2 ** * Ploidy 4 * *

39 Large-scale State Transitions (LST) to account for DSB All variation less than 3 Mb is smoothed, after, number of LSTs are defined as number of chromosomal breaks between two segments of at least S Mb each GT >S Mb >S Mb >S Mb BA CN

40 We demonstrated that number of LSTs in a tumor genome is related to BRCA1/2 inactivation Number of LSTs One line represents one tumor genome Number of LSTs in breast and ovarian tumors shows robustly at least two modes Number of LSTs LST hi BRCA1/2 cases some found a posteriori LST low LST, Mb No proven BRCA1/2 cases LST hi is a genomic signature of BRCAness, displaying 97% accuracy in TNBC

41 LSTs vs rearrangements found by NGS validated in NGS; validated in NGS and Sanger sequencing/pcr; fine resolution of the break not found 70% of detected LSTs correspond to inter-chromosomal translocations

42 Basal-like subtype of breast carcinoma Number of LSTs 10Mb BLC Series of 65 BLC/TNBC : 23 BRCA1 tumors (BRCA1) 11 sporadic tumors with BRCA1 methylation 31 sporadic tumors without BRCA1 methylation neardiploid neartetraploid Only one tumor left with BRCAness and no BRCA1/2 inactivation found

43 Basal-like cell lines follow the same LST distribution Evidence for functional homologous recombination pathway Number of LSTs in a tumor genome indicates functionality of homologous recombination pathway

44 Response to cisplatin in clinical trial (Birkbak et all, 2012) LST_high LST_low BRCA1/ NON BRCA1/ p< Responders Non Responders BRCA1/2 9 8 NON BRCA1/ p<0.06 LST_high LST_low Non Responders Responders 18 1 p<0.0001

45 Genomic architecture of high grade ovarian carcinoma Near-diploid Frequency Near-tetraploid Over-tetraploid DNA index Similar to breast cancer in general Pattern of whole genome duplication Some tumors underwent several rounds of genome duplication Some genomes display high variation in copy number We applied the same procedure for LST calculation.

46 LST in high grade/stage ovarian tumors Ploidy 2N Ploidy 4N LST_lo Frequency LST_lo LST_hi Frequency LST_hi BRCA1 meth BRCA1 mut BRCA2 mut BRCA1/2 wt LST_10Mb LST_10Mb Majority of BRCA1/2 inactivated tumors are LST_high But some LST_high tumors do not found inactivated in BRCA1/2

47 Survival depending on the mutation status Overall survival p.value<10-7 LST_low XX[ttlow]=-1 BRCA1 XX[ttlow]=0 methyl XX[ttlow]=1 BRCA1 mut XX[ttlow]=2 BRCA2 mut XX[ttlow]=3 LST_high Time, month LST_high tumors without detected inactivation of BRCA1/2 display better survival. So, probably at least some of them have also HR deficiency.

48 Conclusions BRCA1/2 inactivation in breast and ovarian tumors results in increased number of large-scale chromosomal breaks. These breaks occur quasi-randomly in the genome and lead to chromosomal translocations. Number of large-scale breaks is a good indicator of the status of HR pathways. BRCA1/2 mutated status is not sufficient to predict response to DNA damaging agents.

49 Chromosomal instability exists as increased rate of alterations, but NO gene was found responsible so far

50 Various alteration patterns in breast cancer genome Short interstitial losses Short interstitial gains

51 Tandem duplication pattern The pattern of instability was found on-going but no mutation to explain it was found

52 Clonal evolution of tumors

53 Clonal evolution of tumors: various scenarios

54 Evolutionary aspects of genomic instability J. Breivik / Seminars in Cancer Biology 15 (2005) 51 60

55 TO CONCLUDE Landscape of tumor genome start to emerge We start to realize the complexity Research program: Genomic instabilities need to be classified and proven Synthetic lethality is very bright and promising concept, but not yet developed Tumor heterogeneity represent a huge challenge in treatment and could be also a result of genomic instability

56 Question: Why BRCA1 and BRCA2 stability genes mainly related to germline predispositions and rather rare inactivated somatically???

57 Thanks to Inserm U830 : MH Stern, E Manié, G Rieunier, F Mechta-Grigoriou, O Delattre U900 E Barillot, A Zinovyev, V Boeva, I Kuperstein Service de Génétique : D Stoppa-Lyonnet, M Belotti Service de Pathologie : A Vincent-Salomon CRB : X Sastre, I Lebigot, M Galut Dpt Trasfert: T Dubois CNRS UMR 7151 : H de Thé, E Turpin, J Lehmann-Che Cancéropole Ile-de-France et Région Ile-de-France Institut Curie Transfert Institut Curie Inserm And you for attention!

58 Major genomic pathway to over-diploid genome is LATE tetraploidization Model of genomic rearrangements AAAB 2/3 1/3 AAB AABB ABBB 1/3 2/3 ABB AA 1/2 1/2 AB 1/2 1/2 A B BB and Formalized genomic architecture, as a vector of proportions Tumor = (B, AB, BB, ABB, BBB, AABB, ABBB, BBBB,, BBBBBBB) example: Tumor = (20, 50, 5, 10, 2, 3, 1, 0, 0)

59 Major genomic pathway to over-diploid genome is LATE tetraploidization Model of genomic rearrangements AAAB 2/3 1/3 AAB AABB ABBB 1/3 2/3 ABB AA 1/2 1/2 AB 1/2 1/2 A B BB and Formalized genomic architecture, as a vector of proportions Tumor = (B, AB, BB, ABB, BBB, AABB, ABBB, BBBB,, BBBBBBB) example: Tumor = (20, 50, 5, 10, 2, 3, 1, 0, 0)

60 Model of genomic rearrangements Near-diploid mode Near-tetraploid mode AABBB ABBBB BBBBB 1 ABBB AABB ABBB BBBB 1/3 2/3 AABB ABBB BBBB 1 ABB BBB 1 ABB BBB AB BB AB 2/3 1/3 BB 1 B B

61 Distribution of ABBB and AABB proportions in over-diploid tumors contradicts to the near-diploid mode Each point is one breast tumor genome Conclusion: majority of over-diploid genomes are consistent with tetraploidization pattern

62 Distribution of BB and AB proportions in most over-diploid tumors contradicts to the near-tetraploid mode BB >> AB Each point is one breast tumor genome Conclusion: Unexpectedly high proportion of AA/BB state in near-tetraploid genome needs another model

63 Model of genomic rearrangements: Late tetraploidization fits! Near-diploid mode Late duplication mode AABBBB AABBB ABBBB BBBBB ABBB AABB ABBB BBBB AABB ABBB BBBB ABB BBB ABB BBB AB BB AB BB B explains excess of AA/BB state

64 In general, proportions of genomic states displays a cluster structure Principal component n 2n 2n+ Near-Diploid Near-Tetraploid Principal component 1 Conclusion: Two populations of breast tumor genomes was observed. One group is consistent with near-diploid pattern, we denote them neardiploid Another group is consistent with tetraploidization pattern and we denoted them near-tetraploid. Rather rare exceptions are possible