# Presentation: 341551

## Microarray Technology Developmentfor Molecular Profiling 

**Dr. David J. Munroe**
**Director, Laboratory of Molecular Technology****Advanced Technology Program****SAIC-Frederick, Inc.****National Cancer Institute at Frederick**
**Cancer Biotechnology (CB) 2007 **
**Frederick, MD**
**May 3, 2007**

## Outline:

- LMT overview
- Why is molecular profiling important?
- Microarray technology development at the LMT
- Cancer Gene Sequencing Microarray
- Mutation detection on an electronic microarray platform
- Virus microarray
- miRNA microarray
- Protein microarrays

## LMT Overview:

- _Scientific effort:_
- Technology Development
- Contracts and core service
- ODRS and OSTP sponsored research

- _Facility / staff:_
- ~8000 sq. ft.
- 28 FTE
- Typically ~40 ‘heads’
- 1 NCI Sr. Investigator
- 3 graduate students
- 3 post docs
- 2-3 guest researchers

***LMT Overview:***

- _FY2006:_
- DNA sequencing: 	325,000 samples
- Microarray: 		2000+ hybridizations
- Genotyping: 		180,000 genotypes
- Mutation detection: 	5000 samples

- Revenue: 	$1,700,000.00
- Publications:    28

## 100% cost recovery
Complete Microarray Service
All Affymetrix commercial microarrays
All Agilent commercial microarrays
LMT Custom Microarrays
LMT aCGH Microarray – complete service or array only
LMT miRNA Microarray – complete service or array only
LMT Virus Microarray – complete service only 
Current volume – 2000+ arrays processed or distributed / year
Current head count – 3 FTE
Currently over 50 active accounts
Turnaround
Average turn around time – 1-4 weeks*

- 100% cost recovery
- Complete Microarray Service
- All Affymetrix commercial microarrays
- All Agilent commercial microarrays
- LMT Custom Microarrays
- LMT aCGH Microarray – complete service or array only
- LMT miRNA Microarray – complete service or array only
- LMT Virus Microarray – complete service only
- Current volume – 2000+ arrays processed or distributed / year
- Current head count – 3 FTE
- Currently over 50 active accounts
- Turnaround
- Average turn around time – 1-4 weeks*

***Microarray Core***

**2 BioRobotics Printers**

**3 Axon Scanners**

**1 Agilent Scanner**

**2 Affymetrix Workstations**
**1 Affymetrix Scanner**
**1 Affymetrix HTA Scanner**
**1 Sciclone ALH 3000 Workstation**

## Profiling – Data set integration

**Scherf et al.; Nature Genetics, 24: 236-244 (2000)**

## Profiling – Data set integration

**Scherf et al.; Nature Genetics, 24: 236-244 (2000)**

## Profiling – Data set integration

**Scherf et al.; Nature Genetics, 24: 236-244 (2000)**

## Profiling – gene expression

**Nature 403: 503  2000**

**Hierarchical clustering:**
**96 samples****	****-DLBCL**
**	****-FL**
**	****-CLL**
**	****-normal lymph node**
**	****-activated B cell**
**	****-resting/activated T cell**
**	****-germinal center B-cell**
**	****-cell lines**

**Expression signatures**
**Disease classification**
**Cell origin**

## Profiling – gene expression

**Nature 403: 503  2000**

**Expression signatures**
**Disease classification**
**Cell origin**

**DLBCL sub-classification**

## Profiling – gene expression

**Nature 403: 503  2000**

## Profiling - mutation 

- K-ras codon 12 mutations:
- Mutations in codon 12 or 13 can be sufficient to disrupt the structure of
- the guanine nucleotide binding pocket
- Impaired GTPase activity
- Most K-ras mutations in tumors involve codons 12 or 13
- Mutations in codon 12 or 13 can be prognostic for drug response

## Technology Development

- Focus on strengths – i.e. sequencing, RealTime PCR, microarray
- Build on existing platforms
- Modularize workflows
- Automate workflows
- Key areas of focus:
- Mutation detection / profiling
- Diagnostics
- Molecular profiling

## Technology Development

- Microarray platform development
- Microarray data analysis / management tools
- Microarray automation
- DNA Microarrays
**Cancer Gene Sequencing microarray**
**Mutation detection on electronic microarrays**
**aCGH**
**Virus microarray**
**miRNA microarray**
- Protein Microarrays
**Monoclonal antibody microarray**
**Self-assembling protein microarray**

## Mutation detection / profiling

- Sequencing
- ~5000 samples in FY06
_*Issues*_
- High-throughput
- Mutation profiling
- Sample heterogeneity

## 300K Cancer Gene Sequencing Microarray

- 300kb of target DNA sequence
- Affymetrix plarform
- Affymetrix early access
- 90 genes known to be mutated in cancer
- All exons, splice sites, and promoters (1kb upstream of start)
- Virtual gene including all known splice variants

**Nature Reviews - Cancer 4: 177 (2004)**

## 300K Cancer Gene Sequencing Microarray

- 300kb of target DNA sequence
- 8 X 25-base overlapping features for each base represented
- Forward and reverse strands
- 300,000 X 8 = _2,400,000_ individual features

## 300K Cancer Gene Sequencing Microarray

- All genes represented by _1100_ PCR products
- Automated primer picking – Applied Bioinformatics 5: 119-120 (2006)
- All primers ‘tailed’ for subsequent validation via standard sequencing
- 90% of PCRs optimized for a single condition
- As little as 1ug of DNA template required
- Automated PCR product QC, re-array and pooling functions

## 300K Cancer Gene Sequencing Microarray

- 2 breast and 2 colon cancer cell lines sequenced
- 2 of these cell line have also been sequenced as part of the TCGA and Sanger Center Cancer Genome Sequencing Projects
- All SNPs and mutations verified via standard sequencing
- All known SNPs detected
- All known mutations detected........plus more!!!

## 300K Cancer Gene Sequencing Microarray

| Gene | bp | Het/ homo | Refseq | Wild type
AA | MutSeq | Mut
AA | SangerCenter | LMT
Chip | Validated |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| APC_exon16 | 50 | het | TCTACAAACT TTA TTACAACACT | (Leu) | TCTACAAACT TAA TTACAACACT | (Ter) | Yes | Yes | Yes |
| APC_exon16 | 2404 | het | TCAAACCAAG CGA GAAGTACCTA | (Arg) | TCAAACCAAG TGA GAAGTACCTA | (Ter) | Yes | Yes | Yes |
| KRAS2_exon5 | 160 | het | TGAAACATCA GCA AAGACAAGAC | (Ala) | TGAAACATCA ACA AAGACAAGAC | (Thr) | Yes | Yes | Yes |
| RB1_exon4 | 43 | het | CTTACTAAAA GAA ATTGATACCA | (Glu) | CTTACTAAAA TAA ATTGATACCA | (Ter) | Yes | Yes | Yes |
| TP53_exon6 | 92 | het | AAACACTTTT CGA CATAGTGTGG | (Arg) | AAACACTTTT TGA CATAGTGTGG | (Ter) | Yes | Yes | Yes |
| APC_exon16 | 4556 | het | AGGCCCACGA ATT CTAAAACCAG | (Ile) | AGGCCCACGA AGT CTAAAACCAG | (Ser) |  | Yes | Yes |
| BRCA2_exon10 | 83 | het | AAAGTCAATG CCA AATGTCCTAG | (Pro) | AAAGTCAATG TCA AATGTCCTAG | (Ser) |  | Yes | Yes |
| BRCA2_exon11 | 1048 | het | GAATATAGAT AAA ATACCAGAAA | (Lys) | GAATATAGAT AAC ATACCAGAAA | (Asn) |  | Yes | Yes |
| BRCA2_exon11 | 1634 | het | TGGTCAGGTA GAC AGCAGCAAGC | (Asp) | TGGTCAGGTA AAC AGCAGCAAGC | (Asn) |  | Yes | Yes |
| BRCA2_exon11 | 4511 | het | ATCAAATAAC TTA AATGTTGAAG | (Leu) | ATCAAATAAC GTA AATGTTGAAG | (Val) |  | Yes | Yes |
| BRCA2_exon21 | 68 | het | ACAGCAAGTT CGT GCTTTGCAAG | (Arg) | ACAGCAAGTT TGT GCTTTGCAAG | (Cys) |  | Yes | Yes |
| CDH1_exon5 | 148 | het | GCCTCTGGAT AGA GAACGCATTG | (Arg) | GCCTCTGGAT ATA GAACGCATTG | (Ile) |  | Yes | Yes |
| FLT3_exon10 | 26 | het | CATATCCAAG TTT TGCAATCATA | (Phe) | CATATCCAAG TGT TGCAATCATA | (Cys) |  | Yes | Yes |
| FLT3_exon6 | 59 | het | GGAGGAAAAA GTG CTTCATGAAT | (Val) | GGAGGAAAAA GGG CTTCATGAAT | (Gly) |  | Yes | Yes |
| PTEN_exon5 | 150 | het | TGGAAAGGGA CGA ACTGGTGTAA | (Arg) | TGGAAAGGGA CAA ACTGGTGTAA | (Gln) |  | Yes | Yes |
| PTEN_exon8 | 234 | het | TTCTCCAAAT TTT AAGGTCAGTT | (Phe) | TTCTCCAAAT GTT AAGGTCAGTT | (Val) |  | Yes | Yes |
| RB1_exon15 | 43 | het | CATTCAAAAT TTT AGGTAAATTT | (Phe) | CATTCAAAAT TGT AGGTAAATTT | (Cys) |  | Yes | Yes |
| RB1_exon2 | 117 | het | AACTTGGGAG AAA GTTTCATCTG | (Lys) | AACTTGGGAG AAC GTTTCATCTG | (Asn) |  | Yes | Yes |

- Colon cancer cell line HCC2998

## Nanogen Electronic Microarray

- Mutation detection
- tumor sections are heterogeneous (i.e contain both ‘normal and cancer cells)
- tumor sections contain infiltrating normal lymphocytes and stroma

## Nanogen Electronic Microarray

- front

- back

***Nanogen Electronic Microarray***