Download Slides 2016-09-28:Computational modeling of cancer micro

Center for Computational
Biology and Bioinformatics
Computational modeling of cancer
micro-environment by using large
scale data analysis
Chi Zhang, Ph.D.
Center for Computational Biology and Bioinformatics
Department of Medical and Molecular Genetics
09/28/2016
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Research Interests
Computational modeling of the:
1) Tissue level characteristics
2) Cellular and biochemical level changes (metabolism)
3) Genomics alterations
by integrative analysis of multiple omics data types, to
i) Identify key biological mechanisms related to cancer
initiation, progression and metastasis.
ii) Predict biomarkers for diagnosis and selection of
therapies
Google: Chi Zhang, Indiana University
Webpage: csbl.bmb.uga.edu/~zhangchi/
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Study cancer micro-environment
through omics data modeling
Cancer microenvironment
Cell line and animal models:
i)1.Cellular
characteristics
Micro-environment
of
ii) Responses to certain treatment
real cancer tissue vs.
iii) Responses under certain conditions
… experimental conditions
2. Highly unstable microenvironmental factors
Immune response
Oxygen level
Acidity level
H Douglas, and R Weinberg. Cell (2000)
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Decipher the cell components in tissue
samples
by
transcriptomics
data
It is critical to decipher the signals from different cell
• Interactionscomponents
among the cancer
cells,tissue
immune
cells and
in the
samples
stromal cells, play critical roles in the progression of cancer.
Lisa M. Coussens and Zena Werb, Nature, (2002)
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Tissue based omics data
g1
g2
g3
g4
g5
……
T cell
Cancer
cell
Macrophage
Tissue
gene
expression
• By a regression based cell deconvolution analysis, we can solve
(estimate) the relative proportion of each cell type in each
tissue sample.
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Applications in colon cancer and Implications
• A subgroup of colon cancer samples
• Elevated CD4+ T cells, tumor associated macrophages,
neutrophils
• Decreased CD8+ T cells
• Highly mutated genome
• High level oxidative stress (may cause DNA damage)
Over expressed NADPH oxidase are
highly correlated with the oxidative
stress responsive genes and the
predicted immune cell proportions.
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Linking the micro-environmental alterations to
genomic mutations
• Gain or loss of functions led by a certain mutation
• Example:
CtBP-binding region
APC gene
Beta-Catenin-binding region
Cell Migration
Cell Adhesion
Control of
Proliferation
Chromosomal
segregation
• Collective effect of multiple mutations
It is critical to comprehensively infer the functions of each
mutation and their collective effect
A bi-clustering based data integration approach:
Genomics, Transcriptomics and Clinical Data
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Example: APC mutation in colon cancer
• A possible functional change due to APC mutations in the 14th
and 15th exons.
Other samples
with APC mutation
Samples
APC mutation
profile in
colon cancer
samples
In the bi-cluster
Exon and nucleotide positions
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Functional changes and prognosis of the
concurrent mutations
Gene Functions:
1. Innate immune
response
2. Tumor associated
macrophage
3. T cell activation
4. Interferon gamma
signaling
5. Steroid hormone
metabolism
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Applications on more cancer types
• We have
studied:
Acute
Myeloid
Leukemia
Dr.
Kapur
21Reuben
well studied
cancer
associated genes.
20 other frequently
mutated genes.
Colorectal
cancer
18 cancer
types.
Outcome
of chemotherapy
~40,000 significant biclusters have been
identified
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Future directions
Center for Computational
Biology and Bioinformatics
Cell line data:
Mutation
Gene expression
Dr. Lijun Chen
Drug response
Predict for possible drugs
Mutation:
Druggable target
on protein tertiary
structure
Dr. Samy Meroueh
Linking the results to
cancer microenvironment:
Elucidate how certain
mutations are selected
More data types
Dr. Chi Zhang
Mutations on a
certain exon:
Alternative splicing
A dysfunctioned
isoform
Development
of new
algorithm,
Machine
Learning
Dr. Lang Li
Dr. Yunlong Liu
Dr. Ning Xia
Clinical Trial
Outcome with
respect to
certain clinical
Dr. Yong Zang
features
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Thank you!
You are welcomed to do
rotation in my lab!
Chi Zhang
[email protected]
Suit 5000 (Room 5021), HITS Building
csbl.bmb.uga.edu/~zhangchi
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