Multi-dimensional Genomic Profiling of Acute Leukemias Characterized by

MLL gene rearrangements

Eunice S. Wang MD (Medicine) and

Norma J. Nowak PhD (Cancer Genetics)

Roswell Park Cancer Institute

2008 Estimated US Cancer Cases*

*Excludes basal and squamous cell skin cancers and in situ carcinomas except urinary bladder.Source: American Cancer Society, 2008.

Men745,180

Women692,000

26% Breast

14% Lung & bronchus

10% Colon & rectum

6% Uterine corpus

4% Non-Hodgkin lymphoma

4% Thyroid

4% Melanoma of skin

3% Ovary

3% Kidney & renal pelvis

3% Leukemia

23% All Other Sites

Prostate 25%

Lung & bronchus 15%

Colon & rectum 10%

Urinary bladder 7%

Non-Hodgkin5% lymphoma

Melanoma of skin 5%

Kidney & renal pelvis 4%

Oral cavity 3%

Leukemia 3%

Pancreas 3%

All Other Sites 20%

Jordan C et al. N Engl J Med 2006;355:1253-1261

Blood cancers are normal blood cells gone “bad”

Acute Lymphocytic Leukemia (ALL)

Clonal expansion of immature lymphoblasts

Acute Lymphocytic Leukemia (ALL)

• Blood cancer characterized by uncontrolled growth of immature abnormal white blood cells.

• The most common pediatric cancer with 75% of cases occurring in children < 6 yrs old

• Comprise up to 20% of acute leukemia in adults

• Cure rates following standard chemotherapy and bone marrow transplantation depend on the particular genetics of the ALL cells.

Diagnosis of blood cancers

Cancer cell

1. Appearance (morphology)

Prote

in

2. Abnormal protein expression (flow cytometry) (histochemistry)

Pro

tein

3.Chromosome abnormalities (cytogenetics)

XX

4. Specific gene mutations

Chromosomes, genes, and DNA

22 chromosomes,X and Y

Mixed Lineage Leukemia (MLL) Gene Rearrangement

4 and 11

11 and 19

Transfer of genes fromchromosome 11 to another one

Acute leukemias associated with MLL gene rearrangements do poorly with therapy

No MLL

MLL positive

MLL fusion proteins function to modify DNA transcription and induce leukemia

Need for new therapies for ALL

Multi-dimensional genomic profiling of acute leukemia characterized by MLL

gene rearrangements

The goal of this project is to identify and characterize the key genes and pathways underlying MLL-associated leukemia for

future translation into novel clinical therapies.

Multi-dimensional genomic profiling

Using cutting-edge multi-dimensional genomic profiling, we will perform in depth genetic analyses of MLL leukemia patient cells from individuals treated at RPCI:

- Change in expression of all known human genes

- Submicroscopic DNA gains/losses (aCGH)

- Alterations in non-coding RNAs regulating genes (microRNA or miRs)

- Single nucleotide DNA sequence variations (SNPs)

- Attachment of DNA methyl groups (methylation)

Studies of Copy Number Variation (CNV)

Differences in the number of copies of large segments of DNA have been found between individuals at many sites of the human genome.

Studies of CNV have revealed that:

– CNV can drive genetic disease;

– parts of the genome are polymorphic for copy number.

Cataloging of these variants in disease and in reference populations is underway, using both sequencing and microarray hybridization.

Traditional CGH Array CGH

Control Test Control Test

Picture courtesy of Brynn Levy, Ph.D.

Metaphase CGH to aCGH

Oligonucleotide arrays (25 – 85mer)

BAC arrays (175Kb)

G-Banding

Diagnostics

Discovery

Resolution Coverage

>10Mb 100%

>175Kb 96%

>40Kb <1%

Single Nucleotide Polymorphisms

Illumina HumanCytoSNP-12 BeadChip

All Markers 299,671

Markers within 10kb of a Gene 148,666

nsSNPs 3,480

MHC / ADME / Indel SNPs 761 / 2,382 / 0

Spacing kb (Mean/Median) 9.6 / 6.2

SNPs in Mitochondrial Genome 0

X-chr / Y-chr / PAR Loci 15,056 / 2,679 / 10

DNA Input Requirement 200 ng

Number of samples per BeadChip 12

Content Number

A Wide Spectrum of Aberrations Can Be Detected

A

C

B

D

MicroRNAs (Mirs)

Single-strandedRNAs capable of

regulating gene expression in cells

Illumina MicroRNA Profiling

Human– 1146 human mature miRNA

sequences are targeted

Content– Sanger miRBase v12

(September 2008 Release) and recent literature

– Targeted

Sample– 200ng total RNA input– R2 >0.99 even for FFPE

samples

24 MLL Leukemia Patient Samples

Frozen Samples

RNA & DNA extraction

-aCGH

-microRNA

-SNPs

-methylation

Pts

24 MLL Patient CNV/SNP Data

24 MLL Patient MicroArray Data

Statistical Analysis

Results of these arrays will be- Compared with normal cells (when

available) from the same patients- Subjected to statistical analysis using

specialized software in order to determine which corresponding target genes and pathways represent potential therapeutic targets.

Jacquie Hirsch for ALL Foundation Research