Identification of Gene Copy Number Alterations in Human Non-small Cell Lung Cancer

Elinor Velasquez San Francisco State University

& Department of Pathology

Stanford University, School of Medicine

Introduction

Non-small lung cancer cells have abundant cytoplasm while small lung cancer cells have almost only the blue nucleus.

Both photos are from www.lungsurgeon.com

Introduction •  80% of all lung cancers

are non-small cell lung cancers

•  Treatment options include: –  Surgical resection –  Chemotherapy –  Localized radiation

•  The survival rate is only 15% over five years

Photo from www.besttreatments.co.uk

Clinical Significance •  Genomic instability is an inherent feature of cancer: Amplification

and deletion of genes (Copy number alterations) contribute to the development and progression of cancer.

•  We can direct therapies by achieving a better diagnosis from knowledge of the gene copy number alterations and pinpointing the genetic changes underlying cancer.

C H R O M O S O M E S

Photo from PubMed

Objective

•  Perform wet bench work to study 24 human lung cancer samples from cell lines via microarrays

•  Automate data preparation by writing software program to handle large database

•  Examine data for regions of gene amplification and gene deletions

- amplification = oncogene - deletion = tumor suppressor gene

Microarray photo from www.csiro.au

Methodology

Copy Automated Scanning

Number Data

Analysis Preparation

Labeling of DNA

Hybridization onto microarray

DNA digestion

Preparation of Comparative Genomic Hybridization microarray

1. Digest and label DNA

2. Mix and hybridize DNA fragments onto a glass slide containing an array of DNA clones with known genes

Tumor

DNA

Non-tumor

DNA Base-pairing to the homologous genes

Data Retrieval and Preparation

laser

Pseudocolor image

Ratio of red to green:

Red = amplified gene Green = deleted gene Yellow = normal gene

Automated data preparation using new computer program

Treeview software

Glass slide

Caryoscope software

Automated data analysis

The computer program accomplished the following:

•  Extracted red and green ratios •  Assigned map positions for the genes •  Averaged redundant genes •  Normalized genes within arrays •  Final preparation of data for analysis by

TreeView software

Photo from www.fec.gov

Confirmation of known oncogene Erbb2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X

Regions of deletion Regions of amplification

Regions of deletion

Erbb2 oncogene

C H R O M O S O M E S

Discovery of novel candidate oncogene region on chromosome 14

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X C H R O M O S O M E S

Regions of amplification

Regions of deletion

Novel candidate oncogene region

Copy Number changes show candidate novel oncogenes

G

E

N

E

S

SAMPLES Regions of gene amplification

MBIP LOC253970 TITF1 NKX2-8 PAX9

Orange box depicts minimal region for novel candidate oncogenes

TreeView software image

Conclusions •  Studied 24 human lung cancer

samples •  Wrote computer program to

prepare data for TreeView software

•  Found several regions of gene deletions and gene amplifications:

Photo from http://www.coll-outao.qc.ca

Known Oncogene

Novel Oncogene candidate region

EGFR (7p) 11p

Myc (8q24) 14q overlap

CDK4 (12q) 20q11

ERbb2 (17q) 21q21

Future Studies •  Narrow recurrent regions of amplifications

and deletions •  Characterize candidate cancer genes such

as 14q overlap on chromosome 14. •  Apply knowledge for improved diagnosis or

therapies

Photo from www1.wfubmc.edu

Acknowledgements •  Jonathan Pollack •  Kevin Kwei •  Young Kim •  The Pollack lab •  Ki Goosens •  Anika Green •  Velessa Peairs •  SSRPers