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FAMILIAL CLL Ashkelon – 2006 Daniel Catovsky. 1887 +1953. 1884 +1996. 1894 +1968. 1895 +1984. 1897 +1928. 1900 +1980. 1903 +1968. CLL. 1907. 1909. 1912 +1912. 1915. 1917 +1980. 1925. 1919 +1994. Familial risks of CLL. The main evidence derives from:

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FAMILIAL CLL Ashkelon – 2006 Daniel Catovsky

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Familial cll ashkelon 2006 daniel catovsky

FAMILIAL CLL

Ashkelon – 2006

Daniel Catovsky


Familial cll ashkelon 2006 daniel catovsky

1887

+1953

1884

+1996

1894

+1968

1895

+1984

1897

+1928

1900

+1980

1903

+1968

CLL

1907

1909

1912

+1912

1915

1917

+1980

1925

1919

+1994


Familial cll ashkelon 2006 daniel catovsky

Familial risks of CLL

The main evidence derives from:

Cohort studies – risk 2.4-5.7(Gunz, 1975; Giles, 1984; Goldgar, 1994)

Case control studies – risk 2.3-4.3(Linet, 1989; Pattern, 1991; Cartwright, 1987)

Relatives of CLL patients have a six-fold increase in risk


Familial cll ashkelon 2006 daniel catovsky

Familial risks of B-cell LPDs Evidence of pleiotropism

Goldin et al., (2004) Blood 104:1850; Goldin et al., (2004) Cancer100; 1902

Goldin et al., (2004) Cancer Epid Bio Prev 13:1415


Familial cll ashkelon 2006 daniel catovsky

Monoclonal B-cell lymphocytosis (MBL)

  • Diagnostic criteria recently reported

  • (Marti et al, BJH 130:325, 2005)

  • Flow cytometry can detect ‘sub-clinical’ MBL in normal relatives of F-CLL and provides the possibility of extending the number of affecteds in linkage families

  • MBL is found in 3.5% of normal adults by flow cytometry

  • (Rawstron et al, Blood 100:2289 & 100:635, 2002)


Incidence of mbl in familial cll rawstrom et al 2002

CD5

Familial

Control

CD79b

CD20

Incidence of MBL in Familial CLL Rawstrom et al (2002)

25%

20%

15%

10%

5%

0%

years

<50

50-59

60-69

70+


Familial cll ashkelon 2006 daniel catovsky

MBL in F-CLL: young adults show the highest relative risk*

*Tute, Yuille, Rawstron et al (2006) Leukemia 20:728


Familial cll ashkelon 2006 daniel catovsky

  • The relationship between

  • MBL and CLL*

  • Cluster analysis with 18 antigens showed that MBL and CLL cases clustered together, separate from normal B-cells

  • Purified MBL B-cells showed:

  • 13q14 del in 16/35 cases

  • Trisomy 12 in 3/21 cases

  • Clonal homogeneity in 5/12

  • VH gene family usage as CLL

* Presented in IWCLL (2005) by Bennett, Hillmen, Rawstron et al


Familial cll ashkelon 2006 daniel catovsky

  • UK Familial CLL study

  • Families collected to date

  • 456 families documented (339 with 2 or more CLL cases)

  • 401 of these we have at least 1 sample from the family

  • 87 families have at least 1 case of CLL and 1 or more cases of LPD

  • 33 families with 2 or more NHL/HL cases


Familial cll ashkelon 2006 daniel catovsky

  • UK Familial CLL study

  • Contributing countries

  • Over 250 UK families

  • 112 from Europe (incl. 58 Italy, 26 Spain & Portugal)

  • 33 Australia & New Zealand

  • 12 USA & Canada (mostly self-referrals)

  • 14 Middle-Eastern (mainly Israel)


Familial cll ashkelon 2006 daniel catovsky

Family 005

Family 094

Family 037

Family 039


Familial cll ashkelon 2006 daniel catovsky

Videbaek’s pedigree 14 revisited

(1947-2004)*

Original family = 55 members

Current pedigree = 221 descendents

10 diagnosed with CLL; 1 T-cell lymphoma

18 non-haematological cancers (5 breast)

Relative risk for B-cell LPD = 7.9 (p < 0.001)

This family provides further support for an inherited predisposition to CLL

*Jønsson, Houlston, Catovsky et al (Leukemia, 19, 1025, 2005)


Anticipation in familial cll

Anticipation in Familial CLL

Yuille (1998) Goldin (1999) Wiernik (2001)

# families 10 13 10

Mean age 74 68 72

Mean age 52 51 51

A large epidemiological study showed no evidence of anticipation in CLL & NHL:

Daugherty et al ,Cancer Epidemiol Biomarkers Prev.(2005) 14:1245


Familial cll ashkelon 2006 daniel catovsky

Familial CLL

No differences from sporadic CLL in:

  • Age, M:F ratio, incidence of Zap-70+ *

  • IgVH usage and frequency of somatic mutation *

  • ATM mutations

  • Frequency of 6q21, 11q23, 13q14 and p53 deletions or trisomy 12

* Rassenti et al (2003) Blood 102:670a

A study from the USA CLL Research Consortium


Familial cll ashkelon 2006 daniel catovsky

  • Strategies for identifying CLL predisposition genes

  • 1: Linkage analysis of families to identify moderate-high penetrance alleles

  • 2: Association studies of SNPs to identify low penetrance alleles

  • 3: Screening familial cases for mutations in candidate genes


Familial cll ashkelon 2006 daniel catovsky

CLL linkage analysis: method

  • Examines regions of haplotype sharing in the DNA of affected individuals within each family

  • This determines the areas which deviate from the expected normal ratios 25 : 50 : 25 across the genome

  • A positive linkage score is established if affecteds share 1 or 2 alleles more than expected in a given region


Familial cll ashkelon 2006 daniel catovsky

CLL linkage analysis: method

  • Analysis of families segregating CLL/B-Cell LPDs using DNA polymorphisms

  • 2 types of DNA polymorphisms can be used:

  • microsatellites (simple repeats eg. CACACACA)

  • SNPs (eg. C/T)

  • Until recently microsatellites were the most popular marker of choice for whole genome scans in order to identify predisposition loci


Familial cll ashkelon 2006 daniel catovsky

Linkage analysis in Familial CLL

  • One previous whole genome linkage search, undertaken in 18 CLL families studied using microsatellites, was extended recently to 28 (16 families were the same in both)

  • No regions were identified that attained statistical significance in these studies focusing on chromosomes 1, 3, 6, 12, 13 and 17

  • Chromosome 13q21-q23 remains of interest but was not statistically significant for linkage in the context of a whole genome scan

Goldin et al., Br J Haem 121:866 (2003); Ng et al Br J Haem 133:59 (2006)


Familial cll ashkelon 2006 daniel catovsky

Linkage analysis in Familial CLL

A high density single nucleotide polymorphism (SNP) - based genomewide linkage search was undertaken on 115 CLL families by our group using the Affymetrix Mapping 10K Array (11,555 markers)


Familial cll ashkelon 2006 daniel catovsky

Comparison of Affymetrix 10K SNP array marker coverage to 400 ABI marker microsatellite panel

SNPsMicrosatellites

The SNP array offers greater density of markers with the flexibility of adding more samples at any time in the analysis as they are recruited


Familial cll ashkelon 2006 daniel catovsky

Linkage analysis in Familial CLL

  • Sample set used for SNP linkage analysis:

  • 115 CLL/CLL-LPD families

  • 80 families with 2 affecteds

  • 28 families with 3 affecteds

  • 5 families with 4 affecteds

  • 2 families with 5+ affecteds

  • Median age at diagnosis of CLL 61 years

Sellick et al, Am J Hum Genetics (2005) 77:420-9


Familial cll ashkelon 2006 daniel catovsky

Plots of linkage statistics after the removal of high-LD SNPs*

*Sellick et al, Am J Hum Genet, 77: 420 (2005)


Familial cll ashkelon 2006 daniel catovsky

Familial CLL – linkage analysis

Sellick et al, Am J Hum Genet, 77, 420 (2005)


Familial cll ashkelon 2006 daniel catovsky

  • Linkage analysis: future work

  • Genotyping an additional 40 families

  • Screening family members for MBL status

  • Currently undertaking mutation screening of genes mapping to linked regions e.g. the 11p11 locus: SPI1 and MADD


Familial cll ashkelon 2006 daniel catovsky

  • Strategies for identifying CLL predisposition genes

  • 1: Linkage analysis of families to identify moderate-high penetrance alleles

  • 2: Association studies of SNPs to identify low penetrance alleles

  • 3: Screening familial cases for mutations in candidate genes


Familial cll ashkelon 2006 daniel catovsky

  • Genetic association studies

  • Part of the susceptibility to B-cell LPDs is likely to be polygenic

  • The identification of low penetrance alleles are contingent on association studies with significant statistical power


Familial cll ashkelon 2006 daniel catovsky

Genetic association studies

An issue of power

Houlston & Peto, Human Genetics112: 434 (2003)


Familial cll ashkelon 2006 daniel catovsky

Genetic association studies

No genetic linkage or allelic association

detected with:

  • Dok1 gene (2p13)

  • P2X7 gene polymorphisms (12q24)

  • MTHF gene polymorphisms (1p36)

  • ARLTS1 coding SNPs (13q14)

  • proposed by Calin et al N Eng J Med 352:1667 (2005)


Familial cll ashkelon 2006 daniel catovsky

  • Germline variants of ARLTS1 and risk of F-CLL

  • ARLTS1 is a putative tumour-suppressor gene, a member of the RAS superfamily at 13q14, a region commonly deleted in CLL

  • Calin et al (2005) proposed that a truncating sequence change in ARLTS1, G446A (Trp149Stop), predisposes to CLL and other malignancies based on findings in 17 familial CLL cases of mixed ethnicity


Familial cll ashkelon 2006 daniel catovsky

  • Germline variants of ARLTS1 and risk of CLL*

  • We conducted an association study to determine if the proposed variant, or 5 other coding SNPs in ARLTS1,predispose to CLL

  • We studied germline DNA from 413 CLLs (all British Caucasians) and 471 matched controls by direct sequencing

* Sellick et al, NEJM 2006: letter & Leukemia Research, 2006 (in press)


Familial cll ashkelon 2006 daniel catovsky

Germline variants of ARLTS1 and risk of CLL*

  • All 6 ARLTS1 SNPs were polymorphic in patients and controls with no evidence of population stratification

  • No association was found between any of the 6 cSNPs and risk of CLL

  • In addition, no evidence for an association between ARLTS1 haplotypes and risk of CLL nor with familial CLL (158 cases of F-CLL included) was identified

* Sellick et al, NEJM 2006: letter & Leukemic Research, 2006 (in press)


Familial cll ashkelon 2006 daniel catovsky

  • Pathogenesis of Familial CLL

  • High-penetrance mutations

  • [Genome-wide linkage analysis]

  • OR

  • Polygenic model of low penetrance alleles

  • [Association studies in ethnically matched cases and controls comparing the frequency of polymorphic genotypes]


Familial cll ashkelon 2006 daniel catovsky

  • Pathogenesis of CLL

  • New association study

  • We adopted a candidate gene-based approach through an association study evaluating cSNPs from genes likely to be involved in cancer

  • We genotyped coding non-synonymous SNPs that alter the amino acid sequence

    • greater likelihood of influencing gene function and/or expression


Familial cll ashkelon 2006 daniel catovsky

  • Variants in the ATM-BRCA2-CHEK2 axis confer susceptibility to CLL*

  • Large scale association study in UK Caucasians to identify low penetrance susceptibility alleles for CLL: we tested 992 CLLs and 2707 controls

  • To increase the likelihood of identifying disease-causing alleles we genotyped a set of 1467 non-synonymous SNPs from 865 candidate cancer genes using Illumina Arrays

* Rudd, Sellick et al, Blood, 2006 (in press)


Familial cll ashkelon 2006 daniel catovsky

Variants in the ATM-BRCA2-CHEK2 axis confer susceptibility to CLL*

  • Significant associations were identified in SNPs mapping to 9 genes pivotal to DNA damage-response and cell-cycle pathways including:

  • ATM, BRCA2, CHEK2, BUB1B, EGF & MMP9

  • Main associations were seen between risk of CLL and minor alleles of ATM, CHEK2, BRCA2 & BUB1B strongly suggesting that variants in the DNA damage-response axis are implicated in predisposition to CLL

* Rudd, Sellick et al, Blood, 2006 (in press)


Familial cll ashkelon 2006 daniel catovsky

Rudd et al, Blood 2006 (in press)

Inter-relationship between genes involved in the DNA damage-response axis for which cSNPs were associated with risk of CLL


Familial cll ashkelon 2006 daniel catovsky

  • UK Familial CLL study

  • Top collaborators worldwide

  • UK: RMH/ICR - 59 families

  • Prof Dyer – 14

  • Italy: Dr Mauro – 30

  • Dr Capalbo – 6

  • Australia: Prof Wiley – 11

    • Drs Westerman/Seymour - 5

  • Norway/Denmark: Prof Jønsson - 11

  • Portugal: Dr Ribeiro - 7

  • Israel: Drs Berrebi/Stark - 5


  • Familial cll ashkelon 2006 daniel catovsky

    Work supported by:

    ARBIB FOUNDATION

    ICR Section of Cancer Genetics

    Prof Richard Houlston (team leader)

    Dr Gabrielle Sellick (principal investigator)

    Dr Ruwani Gunaratne (data manager)


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