analysis of microarray genomic data of breast cancer patients hui liu, ms candidate department of...
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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)