Analysis of Microarray Genomic Data of Breast Cancer Patients

Hui Liu, MS candidate Department of statistics

Prof. Eric Suess, faculty mentor Department of statistics

Introduction

• Many biomedical tests assay only one or two gene expression activities.

• Microarray (Gene Chip) assays thousands of gene expression at the same time.

• Does microarray provide us a better technique to understand clinical research?

Two-color fluorescent hybridization for the analysis of gene expression by microarray

Reverse transcribe each sample using a different fluoresce

nucleotide(Cy3 or Cy5)

Mix the complex togetherHybridize overnight

mRNA from Sample 2(Experimental Sample)

mRNA from Sample 1(Reference Sample)

Scan and determine

fluorescence intensities at

each spot

Two-color fluorescent hybridization for assaying gene expression by microarray

Research Project Goals• Independently analyze the Stanford genome

database breast cancer microarray data. • To learn CLUSTER and TREEVIEW

microarray analysis software programs (Michael Eisen, 1998-1999).

• To confirm the previous study result (Sorlie et al, PNAS: Sept 2001, Vol. 98, no. 19, 10869-10874).

• To test if microarray analysis is a better approach for breast cancer clinical research.

Stanford Microarray Database

• Clustering analysis:85 cDNA microarray experiments: 78 cancers, 3 fibroadenomas, 4 normal breast tissues

• Survial analysis: 49 patients in a cohort study in which advanced breast cancers without metastasis were uniformly treated

Methods

• CLUSTER program hierarchical clustering was applied and the results were displayed by using TREEVIEW software.

• SAS procedures-PROC PHREG and PROC LIFETEST-were used for the survival analysis.

Hierarchical Clustering Analysis• Hierarchical Clustering Algorithm used by the

CLUSTER program is to compute a dendrogram that assembles all items (genes or arrays) into a single tree by repeated cycles of clustering process.

• The Pearson correlation coefficient is used to measure similarity/distance between the expression of two genes.

• The clustering process groups together genes with similar patterns of expression basing on the similarity matrix.

Y

i

x

i

S

YY

S

XX

Nr

1

Red: transcript level > medianGreen: transcript level<medianBlack: transcript level=medianGrey: inadequate or missing data

Basal epithelial cell-enriched cluster

Normal breast-like cluster

Luminal epithelial gene cluster containing ER

Novel unknown cluster

Hierarchical clustering of 456 intrinsic cDNA clones

ERBB2 amplicor cluster

Cluster dendrogram showing the five subtypes of tumors

Basal-like ERBB2+ Luminal Subtype C

Luminal Subtype A + B Normal Breast-like

Basal epithelial cell-enriched cluster

Normal breast-like cluster

Luminal epithelial gene cluster containing ER

Novel unknown cluster

Hierarchical clustering of 456 intrinsic cDNA clones

ERBB2+: genes in the ERBB2 amplicon: ERBB2, GRB7, etc.Luminal subtype C: a novel set of genesBasal-like: Keratins 5 and 17, laminin, and fatty acid binding protein 7Normal breast like: genes expressed in adipose and other nonepithelial cell typeLuminal subtype A+B: ER gene, GATA binding protein 3, X-box binding protein 1

Basal Erbb2+ C A B Normal

ERBB2 amplicor cluster

Cluster dendrogram showing the five subtypes of tumors

Basal-like ERBB2+ Luminal Subtype C

Luminal Subtype A + B Normal Breast-like

Coordinated function of genes cluster

Breast cancer prognosis

Survival analysis: breast CA patient Survival Time or tumor Relapse Free Time

Basal epithelial cell-enriched cluster

Normal breast-like cluster

Luminal epithelial gene cluster containing ER

Novel unknown cluster

Hierarchical clustering of 456 intrinsic cDNA clones

ERBB2+: genes in the ERBB2 amplicon: ERBB2, GRB7, etc.Luminal subtype C: a novel set of genesBasal-like: Keratins 5 and 17, laminin, and fatty acid binding protein 7Normal breast like: genes expressed in adipose and other nonepithelial cell typeLuminal subtype A+B: ER gene, GATA binding protein 3, X-box binding protein 1

Basal Erbb2+ C A B Normal

ERBB2 amplicor cluster

Conclusion• Confirmed the previous study results (Sorlie et al,

Sept. 2001)* Clinical outcome of Luminal subtype A+B group

is statistically different from Luminal subtype C group although they are both ER positive.

* There are no significant difference in clinical outcome between Luminal subtype C group and Basal-like group probably because they share the expression of a set of novel genes.

• Learned modern advanced statistical technique for microarray analysis: CLUSTER, TREEVIEW

Conclusion Gene expression

Tumor classification

Clinical outcome

Microarray

Hierarchical Cluster Analysis

Survival analysis

Microarray analysis allows us to understand the coordinated function of groups of genes in disease prognosis, diagnosis and therapeutic resistance. It is a valuable approach to clinical research.

Analysis of Microarray Genomic Data of Breast Cancer Patients

Hui Liu, MS candidate Department of statistics

Prof. Eric Suess, faculty mentor Department of statistics

Survival time (months)

Proportion of patients survived

Overall survival analysis

Proportion of patients survived

Relapse Free time (months)

Relapse Free Survival analysis

Cluster dendrogram showing the five subtypes of tumors

Basal-like ERBB2+ Luminal Subtype C

Luminal Subtype A + B Normal Breast-like

(from Sorlie et al, PNAS, Septemer 2001)