Download Analysis of Microarray Genomic Data of Breast Cancer Patients

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
Two-color fluorescent
fluorescent hybridization
hybridization for
for the
analysis
gene
expression
microarray
assayingof
gene
expression
byby
microarray
mRNA from Sample 2
(Experimental Sample)
mRNA from Sample 1
(Reference Sample)
Reverse transcribe each sample
using a different fluoresce
nucleotide
(Cy3 or Cy5)
Mix the complex together
Hybridize overnight
Scan and
determine
fluorescence
intensities at
each spot
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, 1086910874).
• 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.
 X i  X  Yi  Y 
1
r


N

Sx


 S 
 Y 
• The clustering process groups together genes with
similar patterns of expression basing on the
similarity matrix.
Red: transcript level > median
Green: transcript level<median
Black: transcript level=median
Grey: inadequate or missing data
Hierarchical clustering of 456 intrinsic cDNA clones
ERBB2 amplicor cluster
Novel unknown cluster
Basal epithelial cell-enriched cluster
Normal breast-like cluster
Luminal epithelial gene cluster containing ER
Cluster dendrogram showing the five subtypes of tumors
Basal-like ERBB2+ Luminal
Subtype C
Luminal Subtype A +
B
Normal
Breast-like
Hierarchical clustering of 456 intrinsic cDNA clones
Basal Erbb2+ C
A
B Normal
ERBB2+: genes in the
ERBB2 amplicor cluster
ERBB2 amplicon:
ERBB2, GRB7, etc.
Luminal subtype C: Novel unknown cluster
a novel set of genes
Basal-like: Keratins 5
and 17, laminin, and
Basal epithelial cell-enriched cluster
fatty acid binding
protein 7
Normal breast like:
genes expressed in
Normal breast-like cluster
adipose and other
nonepithelial cell type
Luminal subtype
Luminal epithelial gene cluster containing ER
A+B: ER a gene,
GATA binding protein
3, X-box binding
protein 1
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
Hierarchical clustering of 456 intrinsic cDNA clones
Basal Erbb2+ C
A
B Normal
ERBB2+: genes in the
ERBB2 amplicor cluster
ERBB2 amplicon:
ERBB2, GRB7, etc.
Luminal subtype C: Novel unknown cluster
a novel set of genes
Basal-like: Keratins 5
and 17, laminin, and
Basal epithelial cell-enriched cluster
fatty acid binding
protein 7
Normal breast like:
genes expressed in
Normal breast-like cluster
adipose and other
nonepithelial cell type
Luminal subtype
Luminal epithelial gene cluster containing ER
A+B: ER a gene,
GATA binding protein
3, X-box binding
protein 1
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
Microarray
Gene expression
Hierarchical Cluster Analysis
Tumor classification
Survival analysis
Clinical outcome
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
Overall survival analysis
Survival time (months)
Relapse Free Survival analysis
Proportion of patients survived
Relapse Free time (months)
Cluster dendrogram showing the five subtypes of tumors
Basal-like ERBB2+ Luminal
Subtype C
Luminal Subtype A +
(from Sorlie et al, PNAS, Septemer 2001)
B
Normal
Breast-like