MOLECULAR GENETICS OFB CELL LYMPHOMAS:

AN UPDATE

Michel Trudel, MD, FRCPC

Shaikh Khalifa Medical Center

B CELL LYMPHOMAS:MOLECULAR PATHWAYS

Pasqualucci & Dalla-Favera, 2002

MICROARRAY EXPRESSION PROFILING:PLATFORMS

MICROARRAY EXPRESSION PROFILING:MOLECULAR INTERACTIONS

MICROARRAY EXPRESSION PROFILINGMICROARRAY EXPRESSION PROFILING

IDENTIFICATION OF: genes involved in pathogenesis / progression, localization / spread, etc

novel genes / disease categories (“class discovery”)

known cell lineage, differentiation stage, etc (“class prediction”)

genes involved in sensitivity / resistance

risk factors / prognostic groups

novel molecular targets for therapy

FOLLICULAR LYMPHOMA:MORPHOLOGY & PHENOTYPE

Grogan, LYMPHOMAS, 1998

FOLLICULAR LYMPHOMA:FOLLICULAR LYMPHOMA:MOLECULAR GENETICSMOLECULAR GENETICS

Ig genes rearranged; IgV genes extensively mutated (intraclonal heterogeneity)

KARYOTYPE GENE FREQUENCY FEATURES

t(14;18) (q32;q21) BCL2 80% anti-apoptosis sole abnormality in ~ 10%

6q21-26 15-20% deletions of ? suppressor genes at q21,q23,q25-27 most common 2nd abnormality in cells with t(14;18)

3q27 BCL6 transcriptional repressor 40% 5‘ mutations

15% translocations

p15, p16 deletions, mutations

17p p53 15% deletions, mutations progression to DLBCL

+7, +18 20%

FOLLICULAR LYMPHOMA:FOLLICULAR LYMPHOMA:EXPRESSION PROFILINGEXPRESSION PROFILING

6 FL (relapsed; no Rx for prior 6 months)vs. GC B-cells (immunomagnetic bead separation) from 6 tonsils

Clontech microarray (588 cDNA’s)

microarray RQ-PCR verification

37 genes 2428 genes 8

Husson et al, Blood, 2002

FOLLICULAR LYMPHOMA: FOLLICULAR LYMPHOMA: DIFFERENTIALLY EXPRESSED GENESDIFFERENTIALLY EXPRESSED GENES

UPREGULATED GENES

• cell cycle control: CDK10, p120, CDKNIA(p21), CDK2A (p16)

• transcription factors: PAX5, ID2 (B cell differentiation)

• cell-cell interaction: TNF, IL-2R, IL-4R• signal transduction: MLK3

DOWNREGULATED GENES

• cell adhesion / communication: MRP 8/14, CD40, thymosin 10

FOLLICULAR LYMPHOMA :FOLLICULAR LYMPHOMA :CHROMOSOMAL LOCALIZATION OF CHROMOSOMAL LOCALIZATION OF DIFFERENTIALLY EXPRESSED GENESDIFFERENTIALLY EXPRESSED GENES

GENES INCREASED LOCUS

BCL2 18q21CDKNIAC (p21) 6p21TNF 6p21JUN 1p32-p31HSF1 8q24XPB 2q21MLK3 11q13HSP27 7qPAX5 9p13

GENES DECREASED

S-100 A 8/9 (MRP 8/14) 1q12-q22PAGA 1p34

DIFFUSE LARGE B CELL LYMPHOMA:MORPHOLOGY

DIFFUSE LARGE B CELL LYMPHOMA :DIFFUSE LARGE B CELL LYMPHOMA :

MOLECULAR GENETICSMOLECULAR GENETICS

Ig genes rearranged; IgV genes mutated

KARYOTYPE GENE FREQUENCY FEATURES

3 q 27 BCL6 POZ/zinc finger transcriptional repressor required for - GC formation - Ab affinity maturation - TH2-dependent immune response

70-75% mutations ( 5' regulatory sequences )

35% translocations multiple partners

( 5' region truncated, juxtaposed to heterologous promoters)

Dalla-Favera et al, 1996, 2000

BCL 6:PROMISCUOUS TRANSLOCATIONS

Gaidano et al, 2000

DIFFUSE LARGE B CELL LYMPHOMA : DIFFUSE LARGE B CELL LYMPHOMA : MOLECULAR GENETICSMOLECULAR GENETICS

KARYOTYPE GENE FREQUENCY FEATURES

t (14;18) (q32;q21) BCL-2 25% anti-apoptosis transformed FL

unfavorable prognosis

17p p53 mutations, deletionstransformed FL

p15, p16 mutations, deletionshypermethylation

REL, NFB2 transcription factors 20% amplification

REL: extranodal lymphoma

DIFFUSE LARGE B CELL LYMPHOMA:GENE PROFILES

Alizadeh et al, Nature, 2000

DIFFUSE LARGE B CELL LYMPHOMA:DIFFUSE LARGE B CELL LYMPHOMA:EXPRESSION PROFILINGEXPRESSION PROFILING

2 distinct groups identified by microarray analysis

5-year OS germinal center B-like 76% activated peripheral B-like 16%

Note:

prognostic significance independent of IPI residual clinical variability within each type NF-B pathway constitutively active in “activated peripheral” type ? therapeutic approach to poor prognosis group

Alizadeh et al, Nature, 2000

Davis et al, J Exp Med, 2001

MICROARRAY EXPRESSION PROFILING : MICROARRAY EXPRESSION PROFILING : ISSUES / PROBLEMSISSUES / PROBLEMS

Quality of tumor banking, RNA retrieved Type of platform: spotted (cDNA), Affymetrix Standardization / validation of results Data analysis / management:

- large data sets generated on small sample numbers- different clustering algorithms- bioinformatics capabilities

- selection of endpoints Intercurrent variables: therapies, etc Discrimination of primary from secondary events, epiphenomena, spurious results (false + / – )

Genomics vs proteomics

Experience suggests that diseases will continue to be defined by combination of parameters: clinical, morphologic, phenotypic, genotypic