Center for Systematic Modeling of Cancer Development Section N1. Center Overview and Effort Integration Center for Systematic Modeling of Cancer Development (CSMCaD), i

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Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

152


Research Plan

Page



Figure 1.

The flowchart for the proposed research for the
C
enter for
S
ystematic
M
odeling of
Ca
ncer
D
evelopment
(CSMC
a
D)


Center for Systematic Modeling of Cancer Development


Section N1. Center Overview and Effort Integration

This section provides an overview of the proposed center,
C
enter for
S
ystematic
M
odeling of
Ca
ncer
D
evelopment
(CSMC
a
D)
,

i
ncluding scientific focus,
description
of
individual
components

and

their integration,
a
s well as

an estimated

timeline for the overall program. The synergies to be achieved through the

establishment
of multi
-
disciplinary teams and novel collaborations
are

fully described.

The Center will draw its strength from an

inter
-
disciplinary
, multi
-
institutional

team of experienced investigators

and a
rich
variety of

laboratory and
institutional

resources.

The Center PI (Dr. Stephen Wong)
and project lead investigators
(Dr. Michael Lewis, Dr.
Jeffr
e
y Rosen, Dr. Xiaobo Zhou,
and
Dr. Vittorio Cristini)
will be responsible for developing and managing
the
project such that we will have a representative
decision
-
making
process
and administrative structure that will
allow resources to be allocated
as needed

to meet the
scientific
go
als

in a timely

and cost
-
effective

fashion
.

N1.1. Overview of the scientif
ic focus of the proposed Center (Abstract)

Excluding cancers of the skin, b
reast cancer is the most common cancer

diagnosed in American women

(
1 in

8

women
;

about 13%
)

and is the second leading cause of ca
ncer deaths among women
.
Systemic therapies

such as chemo
-

or radiation therapy

are effective initially in controlling and reversing tumor growth. However,
residual cancers will invariably re
-
grow despite this initial response.
While there have been several

advances in
the
treatment of breast cance
r in
the last

two
decade
s
,
notably targeted therapy for breast cancers expressing
estrogen receptor (ER
+
) or the HER2 (ErbB2) oncogene,
breast cancer
survivorship has improved only
modestly. Unfortunately, for women with “triple negative” breast cancers (l
acking expression of ER,
progesterone receptor (PR)

and

HER2) we currently have no targeted therapies
.

Our recent
clinical
data, as well as experimental evidence

in both mouse mammary tumors and human
xenograft models,
support the existence of a subpopulation of cancer cells present in the original tumor that are
greatly enriched in residual cancers after conventional

systemic

therapies. These residual cancer cells are
characterized by
their intrinsic resistance to chemotherapy and relative

growth

quiescence
. However, a discreet
subset of these residual cells possesses

enhanced self
-
renewal
capacity
, as well as

the

ability to form tumors
upon transplantation.

These
residual
tumor
-
initiating cells (TIC) (a.k.a.
cancer stem cells (
CSC
)
)
, which
may be

located in certain tumor microenvironment (mE),

may
therefore
be responsible

for tumor
growth
, maintenance
,
resistance
to treatment
, and disease relapse
.
If th
e

hypothesis is correct, t
he failure of traditional

systemic

therapies, such as radiation and chemotherapy, to cure breast cancer may be
due to the fact that they

incorrectly

target

the
highly proliferative
cells
,

while
allowing survival of

treatment
-
refractory

tumor
-
initiating “
cancer stem

cells

.
T
hese findings
fundamentally
modify our conceptual approach
to

oncogenesis and
have dramatic

implications
for

breast cancer prev
ention, treatment
, and drug development.

I
n
this proposal, we seek to build upon
,

and
significantly
extend
,

ongoing
laboratory and clinical
studies and
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

153


Research Plan

Page

use newly developed experimental and imaging methodologies to identify, localize, purify
,

and characterize TIC

to a degree not possible before
. This will then allow us to identify and image TIC in vivo and to model TIC
behavior during tumor development mathematically with respect not only to spatial localization and movement,
but also to proliferation, apoptosis, and specific changes in gene exp
ression and cellular signaling. Combined
functional genomics and data mining strategies will allow us to characterize novel growth regulators.

Further
more
, our combined experimental and systems biology approach will allow us to evaluate responses to
exper
imental therapeutics that may inhibit or kill TIC specifically in a manner not possible before.
Aside from a
wealth of basic biological insight, extensions of this work may allow drug repositioning as well as development of
directed, mechanism
-
based and “s
tem cell”
-
centric drug screening and evaluation methods.


Figure 1

provides an overview of the CSMCaD and its scientific goals. The
upper
portion

illustrate
s a
flowchart of the four
Specific
Aims in
C
omponent 1

of the Center
. These
a
ims

focus

on the
goal o
f
understanding
the behavior of
TIC,

whose function is governed by the spatial and temporal ordering of multiple interacting
components at the molecular, cellular, and tissue levels.
The

experimental

d
ata will be used in Component 2,
depicted

in the lower

portion of the figure, to develop mathematical
and computational
models of TIC signaling
and behavior,

including the use of mathematical equations and relationships
as well as

computer simulations to
represent
and model
biological phenomena
,

such as
proliferation,
apoptosis, cell migration
, and treatment
response
.

These approaches serve two purposes. First, they provide a basic framework for the interrogation and
integration of data, often providing insight into the type and quality
of data
needed fo
r addressing a hypothesis or
experimental design. Second, these models or simulations should allow one to predict the biological
response of
TIC to an experimental therapeutic agent

under investigation

and to predict how TIC
-
related
process
es

will
behave
u
nder

different
circumstances.
The predictions generated in Component 2 can
in turn
be tested

explicitly

in experiments conducted within Component 1.

We
will
discuss the
synergy

of the Specific Aims between
Component 1 and
C
omponent 2

at the end of this Sec
tion.

Component 1

is guided by the
hypothesis

that TIC
represent

a unique sub
-
population of cells within a
tumor possessing properties of self
-
renewal and the ability to give rise to the characteristic cell types
present within a given tumor
. Because of
their unique abilities
, we hypothesize
further
that TIC are
localized and function within a spatially and molecularly
-
regulated microenvironment

(mE)

(
a.k.a.
niche).

To identify, localize, and functionally interrogate TIC in vivo in sufficient detail to al
low mathematical
modeling of their behavior
s

and responses to genetic and pharmacological manipulation

in Component 2
,

the

Specific Aims

of Component 1 are
:

Aim 1.
1
:

To i
dentify
tumor
-
initiating cells (
cancer stem cells
)

using newly developed lentiviral
fluorescent signaling reporters and to characterize their spatial distribution and behaviors during tumor
growth using in vivo imaging.

Based on our current knowledge of TIC regulation by signaling networks, including
Wnt, Notch
, and
Hedgehog
,
we propose t
o use a novel set of lentiviral fluorescent signaling reporter vectors to identify, localize, and purify
TIC from both mouse and human mammary tumors based on
activities
of these and other pathways in the TIC
cells themselves.
In addition to static histolo
gical preparations, individual stem cells can be tracked in live
animals using a combination of high
-
resolution confocal microscopy and two
-
photon video imaging methods.

Thus, the

location and movement of
TIC

can be monitored over time

at different phases of tumor development
.
These analyses should be informative about interactions between TIC and their local environment, including
proximity to blood vessels, ECM, and interactions with stromal cell types
,

such as macrophages, neutrophil
s, and
fibroblasts.
T
hese data will be used to develop and
validate

the
bio
-
mathematical model of TIC
mE
(
microenvironment
) model
that will be
discussed

in Specific Aim
2.
1 of Component 2.


Aim 1.
2
:

To identify candidate genes and pathways that may regulate TIC behaviors (e.g. self
-
renewal,
differentiation, and metastasis)

B
y
using

the new fluorescent signaling reporter vectors used

or
developed in Aim 1, as well as known

cell
surface
and enzymatic
m
arkers
(
e.g.
,

CD44, CD24,
and
ALDH1
), we will purify (or highly enrich) TIC populations away
from other non
-
tumorigenic cell types using Fluorescence Activated Cell Sorting

(FACS).

M
icroarray
(Affymetrix)
and proteomic (antibody arrays, high
-
throughput imm
unofluorescence imaging) analyses will then be used
to
obtain gene expression data for
each
different cell
population. Data will be analyzed using
advanced
b
ioinformatics methods
(Component 2) to discover molecular pathways active in TIC and niche cell typ
es.
These

data describ
ing the

relation
ship

between signal pathways and cellular
identities will be used

to refine the
TIC mE
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

154


Research Plan

Page

model

and predictive modes

of Aim
2.
1

and Aim 2.2

in Component 2
, respectively.

The genes identified

or
predicted will then be
tested functionally in Aim 3 of Component 1
.

Aim 1.
3
:

To conduct a “Directed Iterative Functional Genomic Screen” (DIFGS) to characterize genes
functionally that either
increase or
decrease tumor
-
initiating capacity.

Using a TIC gene expression signature
defined previously using the CD44 and CD24 cell surface markers on
human clinical samples, we recently completed an initial functional genomics screen of 1
,
290 lentiviral shRNA
constructs targeting ~500 genes. This screen identified
101

genes regulating mammosphere formation (a
surrogate in vitro assay for TIC and normal stem/progenitor cell function). A similar study is underway using a
gene expression signature derived from TIC in mouse p53
-
null tumor models. We propose to extend these

screens in a directed, iterative manner by
advanced
bioinformatic approaches (Component 2) to define a new
candidate target list using the
101

genes as input to identify known

or
suspected interacting proteins, immediate
upstream regulators, and downstrea
m targets.

Additional unknowns from microarray data will also be tested
whenever possible (up to about 500 genes can be screened at one time). These new candidates will be tested
functionally using mammosphere
-
formation assays to identify only those genes

regulating MSFE and the
process repeated for
five

iterations

per species (~2500 genes each species)
, or until all bioinformatics
-
defined
interactions are exhausted. Human and mouse gene lists can then be mined for overlapping and unique gene
sets and test
ed in vivo in
Specific
Aim
1.
4

described next
.

T
hese data will be analyzed through
advanced
bioinformatics methods described in
Specific
Aim
2.
3 of Component 2, and the results can be used for the
validation of
the
refined model
TIC mE
in Aim
2.
2.

Aim 1.
4
:

To define the cellular responses of TIC to genetic and pharmacological manipulation of genes
regulating TIC survival or function in vivo.

O
nce
key molecules are identified as functionally important in Aim
1.
3 of Component 1, and
the integrated
molecular

and cellular

model

is built
in Component 2
, the response
to genetic

and
pharmacological manipulation
of molecules in the model
will be
predicted, tested, and used to refine the model
.

Based on the premise that TIC
must be targeted specifically for
development of effective treatment or prevention of breast cancer,

discovery of
drugs that
kill TIC specifically,

or block the
ir

function
will be critically important
.
Our ongoing work investigating
inhibitors of

normal stem cell

self
-
renewal (including in
hibitors of Notch, Hedgehog, and the PI3K/Akt axis)

suggests that these agents function at the level of the TIC since they reduce the frequency of self
-
renewing cells,
but typically do not alter tumor volume significantly unless combined with cytotoxic sys
temic therapies
.
We
expect that a subset of the lentiviral shRNA constructs affecting TIC behavior in MS assays will have similar
activity against TIC function in vivo.

We will use
a novel collection of mouse mammary tumors and low passage transplantable h
uman xenografts
to
study

the effects of
genetic (constitutive or doxycyclin
-
inducible lentiviral shRNA expression vectors) and
candidate pharmacological TIC

inhibitors
(
currently in use or,
suggested from analyses
of

Component 2)
on
TIC
behavior and frequency in vivo.
Moreover, the
combinatorial

effects of
shRNA knockdown or experimental
therapeutics with conventional chemotherapies

will be examined
with the goal of

finding

more

effective cancer
treatment
s for individual breast cancer

subtypes
.

T
hese data will again be used for the development of
the
drug
-
integrated model and for the validation

for Aim
2.
4 in
C
omponent 2
.

Component 2

is guided by the
hypothesis

that TIC behavior during tumor development can be
simulated using
a robust,

multiparameter mathematical/computational model of TIC behavior during
breast cancer development. Further, that these models can be built to reflect not only the molecular,
cellular, and tissue
-
level dynamics, but also to allow prediction of the response
of TIC to experimental
therapeutics.

T
hus, t
he central goal of
Component 2

is
to build a mu
l
ti
-
scale model platform

of TIC mE for
investigating
TIC self
-
renewal, proliferation, localization, and other functions
within a spatially and
molecularly
-
regulated
microenvironment.

Based on the experimental data
obtained from Component 1
and
published

knowledge of TIC, we will model the TIC tissue microenvironment

(TIC mE
) from
the molecular and

cellular level up to
the
tissue level
.

The T
IC mE model

can further pre
dict and guide
the
pathway analysis, the
candidate gene selection,

genetic and pharmacological manipulation

in Component 1
.

Acco
r
dingly, t
he
Specific Aims of Component 2 are:

Aim 2.
1
:

To model the TIC tissue mE mathematically based on 2D and 3D microscopy
and image
analysis

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

155


Research Plan

Page

The microenvironment, including cellular and non
-
cellular components, is well
-
known to play an important role in
supporting and influencing the behavior of TIC.
Bio
-
imaging informatics models will be developed to quantify the
TIC tissue microenvironment images obtained from Component 1 and then TIC mE spatial distribution can be
modeled.
Based on
the quantified

data as well as from the literature

and online databases
,

we can
apply

ordinary
differential equations (ODEs) and more
sophisticated

differential equations to describe the relationship
among

TIC and molecules, enzymes, nutrients and other cell types in microenvironment (e.g. fibroblasts, vasculature,
immune cell
s) mathematically in an effort to model tumor development
in silico
.
T
his will be a model at
the
cellular

and tissue
level
s onto which

the
key
molecular level mechanisms

discovered in Aim 1.3 of Component 1

can be mapped in Aim 2.3. T
herefore,
further expe
riments will be carried out in Specific Aim
1.
2 of Component 1

based on feedback
from

the results obtained in
this aim
.

Aim
2
.2
:

To p
redict the
TIC

pathways or key genes related to specific cancer

subtypes
so to
refine

the

TIC
microenvironment model

B
ioinformatic a
nalysis of DNA microarray
and proteomic
data

generated in
Specific
Aim
1.
2

of Component 1
,
coupled with the genetic and pharmacologic manipulations of TIC function

in Aims 1.3 and 1.4
, will

enable us to
identify key candidate

components in the pathways
that

are related to cellular
behavior and survival
.

Subsequently
, we
will
map these signaling pathway factors to

specific tumor cell types

and further to specific
cellular
properties
by modeling them as functions of the factors
. For example,
,
where

are genes/factors, and
and
are the functions that model the relationship between symmetric
or asymmetric
self
-
renewal
rates and the genes in
TIC

pathways.

The TIC mE model will
,

in turn,
be refined
based on the newly infer
r
ed pathway and network information.

W
ith the network of genes integrated into the
bio
mathematical model, predictions can be made by changing the parameter values for the network components,
so that
a subset of key factors will be found.
These

prediction
s

will guide the
iterative functional genomics
experiments in Aim
1.
3 of Component 1 to
focus on
the most likely

gene candidates.

Aim 2.
3
:

To d
evelop
bio
i
maging
informatics models for
mapping

gene functional networks
within and
among TIC and niche cells
from
the directed iterative

shRNA

screen and further refine

the

TIC mE

model

We will d
evelop bioinformatics models for discovering gene functional networks by integrating gene function
annotation results
from
the
shRNA
genome

subset

screen
ing

in
Specific
Aim
1.
3

and publicly available
multi
-
modality genomic data.

We will first develop an integrated image analysis system for shRNA screens and
scor
e

each gene based on the phenotypic information, then
we will
develop an
imag
e
-
based system
s

biology
approach to study the gene functional networks. Biological processes ar
e often an orchestra of groups of genes,
and the gene functional network studies are important to understand
and study
gene functions. Combining with
the prior knowledge, the gene functional annotation results from
the
shRNA
screen

will have the potential
to
identify known

or
suspected interacting proteins, immediate upstream regulators, and downstream targets.

N
ew
experimental data that
are
u
nanticipated

by the model can be used to further improve our mathematical TIC mE
model.

Aim 2.
4
:

To
model the
response of TIC and their microenvironment to genetic and pharmacologic
al

manipulations of TIC function
in vivo

Based on our ability to assay

the relationship between
exposure to signaling inhibitors a
nd gene expression

in
relatively pure cell populations
,

a
s well as

the
mathematical
model linking molecular level
data
to
the
cellular and
tissue level
s
, we can adjust the model to predict the response of TIC
to new

drug candidates
. Technologies will
be designed to elucidate, interrogate, and model the role of

physical forces on varying cellular functions,
including cellular
ligand
-
receptor interaction, cell proliferation, differentiation, cell cycle
evaluation
,
apoptosis

and
evolution of tumor phen
o
types
, or motility in order to facilitate an increased underst
anding of the role that
physical forces play in cancer pathology and metastasis. Under different conditions, e.g.
,

metastasis or
non
-
metastasis stage, increased

or
decreased motility, changes in intracellular mechanics and ability of cells to
interact with

the environment will
all
be included for modeling the distribution of
tumor
-
initiating

cells.

The
collaboration of the Aim
2.
4 and Aim
1.
4 will be in an iterative manner to better refine the mathematical model
in
order to derive more
robust
drug

candidates

for
inhibiting or managing
TIC
.


Coherence
and Synergy
of Specific Aims between Component 1 and
C
omponent 2

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

156


Research Plan

Page

In this section, we

provide
a summary of
the aforementioned
Specific Aims

and elucidate
the coherence

and
synergy

between

Component 1 and Component 2.

As proposed, Aim 1
.1

of

Component 1 will identify, localize
,

and purify TIC using newly developed
experimental bio
technologies and
will
also analyze the interactions between TIC and their
micro
environment.
Armed w
ith
such
info
rmation, in Aim
2.
1

of Component 2
, we propose to
construct

a
bio
mathematical model
describing the cellular behavior of TIC and
their

interactions with
other

cellular and non
-
cellular components
surrounding them.
F
urther experiments will be carried out in
Specific Aim
1.
2 of Component 1

based on the
feedback of the results obtained in Aim 2.1
.

N
ext, in Aim
1.
2

of Component 1
, we will identify candidate genes and pathways that may regulate TIC
behavior by using genomic and proteomic analysis.
C
orrespondingly, in Aim
2.
2, we will use
advanced
bioinformatics
algorithms

to identify key components
identified in

Aim
1.
2, which form a
pathway
or
network that
may regulate cellular behavior.

T
herefore, we can
investigate
models to describe the interactions in this network,
and then map
these

genes and proteins to specific cellular
properties
. In this way, we can refine our
mathematical
TIC mE
model
derived in earlier
Aim
2.1

by incorporating the function of gene networks.
Since the
initial pathway network can sometimes be very complex and large, we
will divide
the network

into several
sub
-
networks
according to

their functions

for better navigation

and manipulat
ion
.

W
ith the refined
TIC mE
model
in Aim
2.
2

of Component 2
, w
e can study the effects of all components in
these
pathway
sub
-
networks by
changing their values in the
mE
model, through which we can predict the outcomes of up
-
regulation or
down
-
regulation of certain genes.
T
hus, we can find the key components in each s
ub
-
network, which can be
seen as hypotheses for biological mechanisms underlying cellular behavior.

The genes in these sub
-
networks
will be also the candidate genes used for
directed iterative

shRNA screen in Aim
1.
3

of Component 1.

T
o validate the hypotheses, Aim
1.
3 will
evaluate

the functions of these found genes

in Aim 2.2

on TIC
properties

first

by using mammosphere
-
formation
cellular
assays
,

a surrogate assay for TIC and progenitor cell
function
.
C
orresponding
bioimaging
informat
ics
technique
s
for
analyzing
these data
are

proposed in Aim
2.
3.
I
n
this

way, new
experimental

data will be generated and analyzed to validate the predictions by the refined model
in Aim 2
.2
.
This can
also
further refine

our
TIC mE
model
, which

will be employed to guide the
definition of
cellular responses of TIC to genetic and pharmacologic manipulation as well as drug response prediction.

A
fter these Specific Aims
are
complete
d
, an integrated and
robust

bio
mathematical model will be establishe
d,
including interactions from
the
sub
-
cellular to
the
cellular and tissue level
s
.
S
imilarly, in Aim
2.
4, we will
first use
data from
previous finding
s
of the TIC mE model

to incorporate the effects of drug
s/shRNA

into our model

and

then predict the potential outcomes by modifying
treatment
-
related parameters. In Aim
1.
4, we will investigate
further the
effect of the
drugs (e.g. inhibitors of TIC)

experimentally, with the purpose of generating data for
validation and improvement of o
ur
TIC mE
model.


N1.2.
CSMC
a
D

Center Organization

The proposed
C
enter for
S
ystematic
M
odeling of
Ca
ncer
D
evelopment (CSMC
a
D)
is compo
sed of a
multi
-
disciplinary
team
of
investigators from several institutions

across Texas Medical Center, including
: The
Methodist Hospital
-
Weill Cornell Medical College,

Ba
ylor College of Medicine, and
the
University of Texas Health
Science Center
(UTHSC)
at Houston.

The Methodist
Hospital
,

Baylor College of Medicine, and
UT
HSC

at Houston

are located within walking
distance of each other
at
Texas Medical Center. This geographic proximity provides great convenience for the
synergy and interaction
among

the Methodist
-
Cornell
, Baylor
,

and
UTHSC

teams.
Many of the team members
have
been
collab
orati
ng

in a
number

of research projects on
bre
ast and other type of cancers
, including those

requiring new techniques

in
computational biology
,
bioimaging
, pathway inference
,

tumor invasion
microenvironment modeling,
and computational
modeling of
drug tre
atment

response
.

The
CSMC
a
D
will

be leaded by a group of established researchers with track records in managing larger
scale nationally allied projects, including the PI, Dr. Stephen Wong, and the other co
re
PIs at
the

partner
ing

sites,
Dr. M
ichael Lewis,

Dr. Jeffrey Rosen
, and Dr. Suzanne Fuqua at Baylor

College of Medicine
, Dr. Xiaobo Zhou at
Methodist, and Dr. Vittorio Cristini at UTHSC

The
PI
,

Dr. Stephen Wong
,

John S. Dunn Distinguished Endowed Chair of Biomedical Engineering and
Professor of
Bioengin
eering and Computer science in
Radiology at Weill Cornell Medical College,
is an
esta
blished scientist and seasoned
project manager. He has extensive experience in leading national
biomedical research networks. Before he moved to the Methodist Hospital i
n May 2007, Dr. Wong was the Co
-
PI
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

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Page


Figure 2.


The o
rganization
structure
of the
Center for Systematic Modeling of Cancer
Development (CSMCaD)


and management core PI of NAMIC (National Alliance of Medical Image Computing), a NIH National Center of
Biomedical Computing for the analysis and visualization of medical images.
Dr. Wong
wa
s also the informatics
Co
-
Chair for fBIRN
(functional Biomedical
Informatics Research
Network) and a member of
fBIRN steering committee.
fBIRN is the integral part of
BIRN, another NIH roadmap
funded initiative that fosters
distributed collaborations in
biomedical science by
uti
lizing information
technology innovations.

Dr.
Wong brings to the
CSMC
a
D

with more than two decades
of experience in building
and
modeling
large scale
systems and managing
scientific

and product
development for leading
institutions in academia and
industry, including HP, AT&T
Bell Labs, Japanese Fifth
Generation Computer
Systems project, Philips Medical Systems, Charles Schwab, UCSF, and Harvard. He was a key member of the
pioneering
UCSF PACS

(picture archiving and communication system)

program,
head
ed

scientific
industrial
labs at Philips
Research

and
product development departments of Philips Medical Systems, managed

the

technology division of Charles Schwab, and created several re
search labs and centers

during his tenure
at
Harvard, including HCNR Center for Bioinformatics at Harvard Medical School, as well as

the

Functional and
Molecular Imaging Center, Optical Imaging Laboratory, and Conjugate and Medicinal Chemistry Laboratory a
t
Brigham and Women’s Hospital. He directed interdisciplinary teams of over
4
00
scientists, researchers, and
engineers

globally while in industry. Dr. Wong received his executive education from MIT Sloan School, Stanford
University Graduate School of Busin
ess and Columbia University Graduate School of Business.

The core leadership team of the
CSMC
a
D

is

composed

by a group of
established scientist and
researchers
from multiple disciplines including
computational biology, imag
ing

bioinformatics,
molecular biology,
cancer
biology,
imaging chemistry,
bio
engineering,
bio
physics and instrumentation, and
clinical oncology
, as well as

staff members in administrative and other supporting cores.

N1.3.
Management

The PI, Dr. Stephen Wong, will direct and manage the daily operation and coordinat
ion across sub
-
teams of
the CSMC
a
D

projects. The site Co
re
PIs at
Baylor College of Medicine

will
take the responsibility
for

C
omponent
1
:

E
xperimental system
s

biology

and the Core PIs at Metho
d
ist
-
Cornell and UT Health

Science Center

will
be
responsible for C
omponent 2
:

Computational
biology and modeling predictive medicine.
The PI

will also wor
k
with the core PI at Baylor
,

Dr. Lewis
,

on the
Component
3 of the education and training
, and
,

meanwhile
,

man
a
ge
the pilot projects

together with the co
-
PI
and project manager
of the Administrative Core, Dr. Fei Cao of
Methodist
-
Cornell
. The PI and Core
PIs will have regular meetings and ad
-
hoc conversations
on project
progression
. The PI will assume the ultimate responsibility for ensuring smooth execution of this project, with the
I
nternal
A
dvisory
C
ommittee

(IAC)

to assist in conflict resolution. The
members of the internal advisory
committee w
ill include Dr. Wong and the core
PIs of the three
partnering
sites
, Dr. Michael Lewis, Dr. Jeffr
e
y
Rosen, Dr. Xiaobo Zhou,
and
Dr. Vittorio Cristini
.

The center will

also
form an External Advisory Panel (EAP)
to include three to five experts in the areas
of
cancer cell

biology and computational biology
. This panel is primarily designed to provide feedback and
suggestions
and

will

visit and
interact with the center

at least

once a year.
The EAP
will also act as

a counsel for
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

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158


Research Plan

Page

the investigators
in

the management of resources
,
resolving potential administrative issues arise
,

and ensur
ing

the

smooth

integration of the Methodist
-
Baylor
-
UTHSC
partnershi
p.

The selection of the EAP is to be made by
the PIs with consent from the NCI program officer. The applicants
will

identify the desirable profiles of
prospective EAP members.

We also invite a strong consultant team
composed of well
-
known experts in the can
cer biology, stem cell
biology, system
s

biology,
bioinformatics
, cancer microenvironment modeling, and in
-
vivo stem cell labeling
,

includ
ing

Professor
Norbert Perrimon

at Harvard Medical School,
P
rofessor
Dihua Yu
at UT MD Anderson
Cancer center,
Professor
s

Margaret Goodell

and
Daniel Medina

at Baylor College of Medicine
,
P
rofessor
Michael Zhang at Cold Spring
Ha
r
bor
Lab
oratory
,
P
rofessor Muhammad Zaman at UT

Austin, and
Professor
Charles Lin

at
Massachu
setts General Hospital (
MGH
)
, Harvard Medical School
.

They will
contribute their
experience to guide the
proposed
project.

T
o ensure effective management, a relatively s
mall leadership team (PI and Core
PIs) will be
formed to

coordinat
e

primary project
s
, task
-
specific
-
projects and supporting core activities.

This team will also bring many
facets of knowledge to bear upon the decision
-
making process, enabling faster, more effective decisions to be
made about shaping the direction of the scientific research

of the CSMC
a
D
.

This will be especially important in
vi
ew of the demands of working with research groups across multiple
disciplines and multiple
institutions. The
small yet representative nature of the team will minimize the cost of overhead and ensure swifter
communications. Additional input to the decision
-
making process will come from the core leaders.

N1.4
.
Interdisciplinary Research Team

The proposed
CSMC
a
D

is composed of a multi
-
disciplinary team of investigators across
three major

institutions at Texas Medical Center, i.e., The Methodist Hospital

Research Institute
, Baylor College of Medicine,
and the
University of Texas Health Science Center
. The expertise ranges from basic science such as cell biology
and cancer genetics to applied technology such as computational systems biology
,
i
n
s
il
i
co

cancer cell
-
matrix,
cell microenvironment modeling,
and software development; as well as clinical disciplines
, such as clinical
pathology

and oncology
.

The PI, Dr. Wong and the core PIs, Drs. Lewis, Rosen, Zhou, Cristini, each brings complementary skills
and
capabilities to the proposed Center for cancer system biology at Texas Medical Center. Dr. Wong is a
world
-
renown
ed

leader in biomedical informatics and
image computing
while Drs. Lewis and Rosen have
expertise

in the field
s

of
breast development and
function, as well as
in
breast cancer research



particularly in
the area of normal and malignant stem cell biology
.
Dr. Zhou has extensive research experience in
b
ioinformatics and imag
e

bio
informatics. Dr. Cristini has rich experience in tumor invas
ion

m
odeling and drug
responsive simulation.
Working together, the

team

will be responsible for the overall direction of the
CSMC
a
D
,
and the planning, management, coordination, and integration of all contract activities. They will also be
responsible for the sc
ientific and technical

leadership of
CSMC
a
D
, its implementation, interfacing with
ICBP

staffs and subcontractors, and ensuring that deliverables and milestones are achieved according to established
timetables. Furthermore, the comprehensive expertise and e
xperience of the investigator team is
evidence that
this team is
well
-
qualified to carry out the proposed project.


Stephen TC Wong, PhD (PI)
,
please see description of the qualification and experience of the PI in Section
N1.2.

Fei Cao, PhD,
(Project M
anager),
Director of Clinical Research Informatics Lab, Bioinformatics
&
Biomedical Engineering
Program, TMHRI and Assistant Professor of Bioinformatics in Radiology, WCMC, will
serve as a

project manager to coordinate the management of the
proposed
center

by w
orking closely with Dr.
Wong

and the co
-
PIs
.
Dr. Cao has over fifteen years of biomedical informatics
and
scientific project
management
experience
.

Michael Lewis, Ph.D. (C
ore PI)
, Assistant Professor of Molecular and Cellular Biology in the Lester an
d Sue
Smith Breast Center at Baylor College of Medicine. Dr. Lewis is trained in normal mammary gland development
and breast cancer. His main research focus is in the role of hedgehog signaling in the regulation of mammary
stem cells and functional differe
ntiation at lactation.
His m
ore recent collaborative work with Drs.
Jenny
Chang
and
Jeff
Rosen has been in the area of identification of tumor initiating cells and characterization of their intrinsic
chemo
-
resistance phenotypes in clinical samples after tr
eatment with conventional therapeutics. In addition, Dr.
Lewis has expertise in
in vivo

analysis of experimental therapeutics and the effect of experimental therapeutics
on the tumor
-
initiating population. Dr. Lewis has long
-
standing collaborations with Dr
s. Chang, Rosen,
Hilsenbeck, and Edwards
, and has collaborated with Dr. Wong and his group
s

over the
p
ast
few

year
s
.

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

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159


Research Plan

Page

Dr
. Lewis will also serve as the C
ore
co
-
PI for the educational component in collaboration with Dr. Suzanne
Fuqua
. Dr. Lewis has extensive teaching experience at the undergraduate and graduate level,
as well as
training
experience at the graduate and postdoctoral levels.

Jeffrey Rosen, Ph.D. (C
ore PI),
C.C. Bell Professor of Molecular and Cellular Biology,
BCM

Dr. Ro
sen
is an
internationally recognized leader in the area of hormonal regulation

of mammary gland development
, stem cells
and the molecular biology of mammary gland gene expression.

Dr. Rosen’s laboratory, in collaboration with Dr.
Peggy Goodell at Baylor C
ollege of Medicine, was the first to identify functional stem/progenitor cells marke
rs in
the normal mammary gland
. His laboratory has extended these studies to the characterization of tumor initiating
cells

(TICs) in a p53 null mouse model of breast can
cer, and using microarray and functional assays have
identified intrinsic differences in cell cycle checkpoints and DNA repair pathways in TICs. In collaboration, with
Dr. Charles Perou’s laboratory Drs. Rosen, Jenny Chang
,

and Michael Lewis at BCM have
shown that
tumor
-
initiating

cells

(TICs) often termed “cancer stem” cells (
TIC
s) defined in human breast cancers share many
common genomic patterns with a new molecular subtype called the “claudin
-
low” subtype, which was identified
by comparative mouse
-
hum
an oncogenomics. A tumorigenic signature derived from the
TIC
s was present as a
small population in all breast cancer subtypes revealed by the analysis of residual tumor cells post
-
therapy. This
collaborative study is currently in press in the Proceeding
s of the National Academy of

Sciences.

Xiaobo Zhou, Ph.D.

(Core PI)
,
Associate Professor of Bioinformatics in Radiology,
Weill Cornell Medical
College
and Chief of Bioinformatics and Bio
-
image Computing Laboratory, Bioinformatics
and Biomedical
Engineering

Program, TMHRI, will
serve as a core PI of the
C
omponent 2
of
CSMC
a
D
. He is an expert of
applying advanced mathematics, pattern recognition, computer vision, signal processing, and data mining
techniques in analyzing and modeling biological data and images, particularly those generated from high
throughput biotechnology su
ch as genomics, proteomics, tissue arrays, and high content screening. He and Dr.
Wong
pioneered the
field of image

bio
informatics and image
-
based system biology. They
lead the development
of a family of new image bioinformatics packages fo
r cell biology a
nd neurobiology studies.
They have recently
co
-
authored one of the first books in Compu
tational Systems Bioinformatics.

Vittorio Cristini, Ph.D.

(Core PI),

Associate Professor
,
the School of Health Information Sciences at
UTHSC at Houston, will serve as a

core PI of the
C
omponent 2
.
Dr. Cristini is also affiliated with
the
Bioengineering
Departments
at
UT Austin and UT MD Anderson Cancer Center.
His group

seek
s

to integrate
experimental and computational methods in an effort to investigate tumor biology. C
urrently,
he

focus
es

on
examining the role of tumor micro
-
environmental spatial and temporal heterogeneity in promoting invasive and
eventually metastatic cancer phenotypes
. His group

develop
s

and app
lies

multi
-
scale, predictive, computational
cancer model
s
based on

well
-
established principles of physics, mathematics, and cancer biology that utilize
state
-
of
-
the
-
art numerical techniques. This integrative framework allows us to form and test hypotheses that
drive experimental investigation, which in turn pro
vides data to refine our
bio
mathematical models.

Suzanne A.W. Fuqua, Ph.D

(Core PI)
.

Professor of Medicine, The Lester and Sue Smith Breast Center. Dr.
Fuqua is
a co
-
PI for the Breast Center training grant,
the
course director for the Translational and
Clinical Breast
Cancer course, and is an internationally recognized leader in the areas of estrogen receptor function in breast
cancer, hormone therapy resistance, and metastasis. Dr. Fuqua has extensive training experience at the
graduate and postdoctoral

levels. She will be an invaluable resource for multiple aspects of the project,
particularly the educational component, which she and Dr. Lewis will oversee jointly.

Mary Dickinson, Ph.D.
, Associate Professor, BCM, will serve as a co
-
inves
t
igator to guide

in
-
vivo imaging.
Her
laboratory

uses a multi
-
disciplinary approach
, including microscopy, molecular biology, and fluid mechanics,

to study the role of fluid
-
derived mechanical forces in vascular remodeling and heart morphogenesis in early
vertebrate embry
os
;
her lab

has

developed methods for time
-
lapse, confocal imaging of rapid blood flow and
heart mechanics using vital fluorescent protein reporters.
Her
lab
is a part of the Molecular Physiology and
Biophysics Department at
BCM

Jenny Chang, M.D.,
Medical
Director of the Lester and Sue Smith Breast Center
and Professor of Medicine
of the
Baylor College of Medicine

and Chief of Breast Medical Oncology, Ben Taub General Hospital

will serve as
a co
-
investigator to guide clinical aspect of the CSMC
a
D project.
D
r. Chang has extensive clinical and laboratory
experience in the area of therapy resistance,

gene expression analysis for the prediction of treatment response,
and evaluation of experimental therapeutics
,
both pre
-
clinically and clinically.

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

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160


Research Plan

Page

Thomas
Westbroo
k
, Ph.D.,

Assistant Professor of Biochemistry and Molecular Biology at
BCM
. Dr.
Westbrook was recently

recruited to Baylor from Dr. Steven Elledge’s laboratory
at
Harvard University

and brings
with him extensive expertise in the use of lentivirally
-
delivered shRNA
. Dr. Westbrook is the Director of the
Cell
Based Assay Screening Service (C
-
BASS
) shRNA

core facility and has conducted genome
-
wide shRNA
screens similar to the Directed It
erative Functional Genomics Screen proposed.

Dr. Westbrook has also
spearheaded the development of novel inducible lentiviral shRNA vectors for use specifically in mammary
epithelium, vectors that will be used extensively in Component 1, Aim
1.
4.

Susan G.
Hilsenbeck, Ph
.
D,

Professor of Medicine and Director of Biostatistics and Bioinformatics in the
Lester and Sue Smith Breast Center at
BCM
, will serve as a co
-
investigator to guide the statistic analysis.

Dr.
Hilsenbeck is an internationally recognized bio
statistician with extensive experience in clinical trial design,
microarray analysis, and preclinical study design. Dr. Hilsenbeck will work extensively with Dr. Shaw, and both
will serve as intellectual

and communication

bridges between the laboratory bas
ed component 1 and the
mathematical

and
computational

modeling based Component 2 of this proposal.

Chad Shaw Ph
.
D
.
,

Assistant
Professor of Genetics at
BCM
, will serve as a co
-
investigator to be responsible
for

the

initial

genomics
and proteomics
data analy
sis

generated in Component 1
.
His

research interests are
systems biology and the analysis of large scale genomic data.
His
group

analyzes

primary microarray data sets
from all array platforms including expression arrays, genome content arrays (aCGH), micro
RNA arrays, and
chromatin arrays with an expertise in data pre
-
processing and normalization.

Dean P. Edwards Ph.D.,

Professor of Molecular and Cellular Biology,
BCM
, will sever as a co
-
investigator to
be responsible for the statistic analysis Dr. Edwards is an internationally recognized expert in hormonal
regulation of breast cancer and gene expression. He has extensive experience in development of monoclonal
antibod
ies, protein biochemistry, and more recently high
-
throughput proteomics analyses. Dr. Edwards is the
director of the Proteomics Shared Resource of the Dan L. Duncan Cancer Center at Baylor College of Medicine.
He will work closely with Drs. Huang and Engle
r for the proteomic analyses proposed herein.

Shixia Huang, Ph.D.
,

Assistant Professor of Molecular and Cellular Biology, is an expert in proteomic
analyses, particularly using protein and antibody microarrays. In addition, she has extensive knowledge of i
ssues
related to breast cancer and mammary gland development. She will work closely with Dr. Edwards and Dr.
Engler for the proteomic analyses proposed.

Ching Tung
, Ph.D.,
Professor of
Radiology
, WCMC and Directo
r of Diagnostic and Imaging Probes Lab
,
TMHRI, will serve as
a co
-
investigator
to
guide
the
in
-
vivo

TIC cell labeling in mouse model

and
assist
Dr. Wong
(PI) to manage the pilot projects
.
Dr. Tung’s research focuses on creating molecular probes to detect biomarkers
in various types of disease
s. Dr. Tung has pioneered the field of optical molecular probes for in vivo imaging.
Over the past few years, he has applied the development of novel multi
-
functional molecules to molecular
sensing, in vivo molecular imaging, therapy, and drug delivery.

Je
ff (Chung
-
Che) Chang, M.D., Ph.D.,
Professor of Pathology & Laborat
ory Medicine, WCMC and Director
of

Hemopathology, TMHRI, will serve as a
co
-
investigator,
participate the TIC mE modeling, pathway inference,
and

data analysis. Dr. Chang is a hematopatholo
gist wit
h research interest in myeloma,
diffuse large B
-
cell
lymphoma, and myedysplastic syndromes. Dr. Chang focuses on clinical and translational focusing on
identifying markers and signaling pathways that are important for diagnosis, prognosis and treat
ment of
hematological malignancies. Dr. Chang has a rich experience in DNA/cDNA/tissue microarray analysis, flow
cytometry, meloma stem cells, and molecular diagnostic techniques. He will guide the data analysis and
algorithmic development.

John Baxter, M.
D.
, Professor of Medicine, WCMC, Director of Genomic Core and Co
-
Director of the
Diabetes Center, TMHRI; and Chief of Endocrinology, the Department of Medicine, TMH, will serve as an
investigator. He was Chief of the Division of Endocrinology and Director

of Metabolic Research Unit at UCSF.
He also co
-
founded several startup companies in biotechnology. Dr. Baxter will provide guide for the software
development and data analysis.

David Engler, Ph.D.

Director of the Proteomics Core at TMHRI will serve as a
n investigator. He will be
responsible for guiding protein
-
level quantification and verification work necessary to validate or confirm the
genomics
-
level data that the
CSMCD

will be analyzing. The Proteomics Core will also provide assistance in
protein
-
level pathway analysis stemming from systems
-
level biological data directly correlated to, or inferred
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

161


Research Plan

Page

from many of the genomic, epigenomic, or transcriptomic changes observed

in the cancers studied by the

CSMC
a
D
.

Paul Macklin, Ph.D.
, Assistant P
rofessor of
H
ealth
I
nformatics at the School of Health Information Sciences
at the University
of

Texas Health Science Center


Houston
, will serve as a co
-
investigator to work on cancer

mE
modeling
.
He
work
s

at the intersection between biology, medicine, mathematics, and computer science to
develop and validate sophistica
ted computer models of cancer. He

work
s under Vittorio Cristini
on several
research projects in the field of computati
onal and predictive oncology.

Xiaofeng Xia, Ph.D
,
Instructor
,
Medical Systems Biology Lab
,
The Methodist Hospital Research Institute
,
will serve as a co
-
investigator in
the
C
omponent
2
to guide the TIC mE modeling. H
e
completed
his postdoc in
University o
f Wisconsin


Madison

working in stem cell research and subsequent spending three years as a
research
scientist in
WiCell working
under

Dr. James Thomson
.

He has worked in a number of areas including
bioinformatics, neurotransmitter releasing and neuronal differentiation of stem cells.

N1.4
. Consultants

In addition,
we
have assembled a team of leading experts in bioinformatics, cancer biology, computationa
l
biology, computational genomics,
stem cell biology
and systems biology as consultants to this project. These
consultants will serve as “thought leaders” for their respective expertise and for the
CSMC
a
D

as a whole to guide
the development of biologically
-
related pathway analysis and data analysis. They will also be called upon to beta
test new software

and
provide feedback on the current
CSMC
a
D

performance
.
The consultants include



Dr. Margaret Goodell, Professor and Director of STaR Center, Baylor Colleg
e of Medicine,
a leader
scientist in the basic biology of hematopoietic stem cells
,
the behavior
study
of stem cells in vivo and in
vitro using mouse stem cells as a model
;




Dr. Daniel Medina, Professor of Molecular and Celllular Biology, Baylor College of

Medicine
Dr.
Medina is an internationally recognized leader in mammary gland development and preneoplastic breast
disease
;




Dihua Yu, MD, PhD
,
Nylene Eckles Distinguished

Professor and Vice Chair of Molecular and
Cellular Oncology and Director of Cancer
Biology Program at M.D. Anderson Cancer Center
, a
leader in understanding breast cancer initiation, metastasis, therapeutic resistance, apoptosis, cell cycle
control, signal transduction, cancer stem cell
-
like properties, microRNA deregulation, cancer
dere
gulation of cellular metabolism, and cancer molecular imaging of breast cancer;



Michael Zhang, PhD, Professor of Computational Biology and Bioinformatics at Cold Spring
Harbor Laboratory
, a well
-
known expert in building a comprehensive network of the gene
s involved in
the regulation of growth and homeostasis which can provide a "system level" understanding of gene and
pathways;



Norbert Perrimon, PhD, Professor of Genetics at Harvard Medical School
, a leader in
whole
-
genome RNA interference (RNAi) and othe
r chemical genetics screens using our high
-
throughput
screening and pathway analysis;



Dr.
Charles

Lin
,
Associate
Professor of
Wellman Center for Photomedicine & Center for Systems
Biology
,
Massachusetts General Hospital & Harvard Medical School
,

a leader
in
cancer stem
labeling in in
-
vivo animal model,
In
-
vivo monitoring of cell trafficking in circulation,
i
maging of vasculature
and microenvironment in tissue,
i
nteraction of cells with microenvironment
;




Dr. Muhammad H. Zaman, Assistant Professor of Depart
ment of Biomedical Engineering, The
University of Texas at Austin,
a leading scientist in modeling cancer cell
microenvironment
to
understand how

cancer cells interact with the extra cellular matrices in native environments

by
employ
ing

computational and experimental tools of biophysics, cell biology, mechanics and chemistry to study
cancer related problems.

N1.5
. Timeline for the overall program

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

162


Research Plan

Page

The outline of defining how novel analytical tools will be developed and applied to
ICBP

dat
a will be generated
and submitted to the NCI within the first three months of the project. We request
five

years to
complete
the
proposed project. The timeline of this project is listed in the next Table

1
.

Table

1
: The estimated timeline of th
e CSMC
a
D

project.

Tasks

Year 1

Year 2

Year 3

Year 4

Year 5

TIC identification, labeling & distribution study
,
TIC mE image
analysis and
TIC mE modeling






TIC distribution
study, TIC mE modeling, genomics,
proteomics
& mechanism study in regulating TIC
, TIC
Pathway inference, and TIC mE remode
l
ing






TIC mE modeling, mechanism study in regulating TIC via
pathway analysis, shRNA interference screening, target
discovery for regulating TIC






shRNA interference screening, bioimaging informatics for
candidate target discovery,
and TIC mE refining






Integration study based on in
-
vitro/in
-
vivo information; TIC mE
modeling and prediction for drug treatment response







Section
N.2.
Administrative Core

T
he specific aim of the administrati
ve core i
s to provide a flexible yet effective administrative structure to
support the infrastructural and scientific aims, in view of the many faceted interactions that must necessarily
occur among the
CSMC
a
D

teams
. To accomplish this aim, we will develop and exec
ute a management plan
based on a balanced management strategy that supports an environment of shared decision
-
making and mutual
responsibility among the core PIs, while providing the oversight and leadership necessary to produce quality
biomedical imaging
work. We will manage the overall
CSMCaD

project using sound basics, including phased
delivery, quick and concrete feedback, clear articulation of the project needs, project tracking and oversight,
effective governance, and inter
-
group coordination.

The o
verall organization and administrative structure of this
CSMCaD

project is shown in Figure
2
. The PI,
Dr. Stephen Wong

and the project manager (PM) Dr. Fei Cao
,
along with Ms Sample and Ms. Roberts
will direct
and manage the daily operation and coordinati
on across subteams of the project. The four specialized cores
including the administration core,
experimental system biology core, computational biology core, and education
& training core,
will
provide the infrastructure to execute and support the propos
ed research projects.
The PI
,
PM,

and Core
PIs will have regular meetings to interact with each other. The PI will assume the ultimate
responsibility for ensuring smooth execution of this project, with the internal advisory committee to assist in
conflict

resolutio
n. The members of the
advisory committee
and the management are described in Section N1.3.


N
.2.
1

Management Plan

The management plan encompasses two balanced goals: Effective Management and Oversight of Quality
Research Work.

Effective manageme
nt
:
The goal for effective management includes the creation of a relatively small

leadership team (PI and Core
PIs), which will be responsible for coordinating primary project,
task
-
specific
-
projects and supporting core activities. This team will also
bring many facets of knowledge to bear
upon the decision
-
making process, enabling faster, more effective decisions to be made about shaping the
direction of the scientific research. This will be especially important in view of the demands of working with
r
esearch groups across multiple collaborative institutions. The small yet representative nature of the team will
minimize the cost of overhead and ensure swifter communications. Additional input to the decision
-
making
process will come from the core directo
rs.

Oversight of quality research work
:
Each of the cores will set its own goals and competencies that will

dovetail with the overall
CSMCaD

objectives. To a great extent, various research projects will run themselves. It
will be the role of the leadership

team of
CSMCaD

to shape the overall scientific direction and to bring projects
back in line when they go off course, as sometimes occurs in a multidisciplinary, multi
-
institutional
research
setting
.

Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

163


Research Plan

Page

The management strategy tha
t emerges for the proposed
CSMCaD

is one of decentralized decision
-
making
rather than centralized control. The mission of the leadership team is to make the entire
multi
-
disciplinary
project
a success. To that end, the tactics derived from the balanced goals of the management strate
gy include (1)
providing a relatively horizontal organizational structure as opposed to the vertical hierarchy that typifies most
corporate organizations; (2) implementing project management, quality controls, and service controls; (3)
enabling autonomous
units; (4) emphasizing flexibility and responsiveness; (5) collecting performance metrics to
ensure that metrics are reviewed by those whose work is being measured; (6) embracing changes when
necessary; and (7) intervening occasionally in situations that c
annot be resolved from a distance. These are the
characteristics of organizations that succeed over time. Accordingly, the specific aim of the leadership team of
CSMCaD

will be accomplished by:

(1)
e
stablishing
an effective management structure
; (2)
d
epl
oying
project
tracking and oversight mechanisms
; (3)
a
dministrating
overall center budgets and fiscal matters
; (4)
d
ocumenting
progress reports and accomplishments
; (5)
o
rganizing
and scheduling meetings, including annual
all
-
hands meetings; regular commit
tee meetings; regular core meetings and teleconferences; and ad hoc
meetings among investigators
of different projects and cores; (6)
p
roviding
and reinforcing guidelines and
policies regarding human subject protection, inclusion of women, minorities, and
children in research, care and
use of vertebrate animals in research, software licensing, intellectual property, and publication of
peer
-
reviewed
scientific papers; (7)
r
einforcing
the NIH data
-
sharing policies
; and (8)
c
oordinating
and interfacing with the
ICBP

steering committee and other
ICBP

centers.

N.2.2
. Organizational Roles of
Cores

Administration core
:
A highly effective administrative resource is critically important in the succes
sful
establishment of this
CSMCaD
. This core

will be the administrative center of the Methodist
-
Baylor
-
UT
HSC team
.
The administrative
core
resource

will consist of the PI, the Core
PIs, a Research Project Coordinator and an
Admi
nistrative Assistant. The
CSMCaD

advisory committee will communicate dir
ectly with this resource in terms
of monitoring progress, providing evaluation and counseling the PI in issues arising during the administration of
the Center.

The administrative core resource will coordinate

the administration of the
CSMCaD
, organize the

steering
and advisory committee meetings, and track milestones and project progress. Retreats, symposia, seminars,
and meetings will be coordinated and organized through this resource. Monitoring and reconciliation of the
various budgets, and facilitatio
n of the purchase of supplies will be also be provided by this resource.

T
he
CSMCaD

project team consists of seventeen investigators spread over three institutions. Efficient
communication and a high level of interaction will be achieved through the admini
strative resource which will
include the maintenance of an interactive Wiki project web site and annual all
-
hands meetings. Furthermore,
email listings where daily postings on day
-
to
-
day activities and information will be provided.

The administration core will
also
have support from TMHRI administration resources. Under the direction of
Edward Jones, M.B.A., Vice
-
President in charge of administration, TMHRI has a fully developed and staffed
research administration and support infrast
ructure. Among its innovations is web
-
based management of the
document flow for the Institutional Review Board and other research administration functions. TMHRI is fully
compliant with all NIH Grants Policies and OHRP policies regarding human research sub
jects.

The administration core will
ensure
s
ynergies
and resource sharing
of Component 1 & Component 2
.

The

weekly meeting between these two components will take place as usual. The core will also make sure
m
anagement of component 3

-
the Education & Train
ing

is

goi
ng well, see details in Section N5.

N.2.3.
Management
of

the

Research
Workshop

Annual Interdisciplinary Symposium: The

Methodist
,

Baylor
, and UT

teams

will host an annual 2
-
day
symposium a
t Texas Medical Center

featuring keynote speakers that will include local, national, and international
leaders in relevant
system
s and cancer biology

research, as well as leaders from the other
ICBP centers

and

members of external advisory panel
. We will feature live demonstrat
ions of the site, port
al, and analysis tools
,
and hands
-
on tutorial workshop training sessions. Annotation jamborees also will be scheduled during this event
to establish community consensus and standardization of terms

or
nomenclature. Scholarships will b
e available
to assist young investigators (students and post
-
doctoral fellows) with travel, lodging, and registration expenses
related to the event.

Houston presents as an ideal location for such an event for several reasons: 1) it is the hub for Continen
tal
Airlines, one of the nation’s largest, which means that investigators can easily travel here via nonstop flights from
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

164


Research Plan

Page

most cities, including
many
major foreign cities; 2) Houston’s central location in the country allows attendees to
avoid long, transco
ntinental flights; and 3) hotels in Houston are more reasonably priced than those in most other
major American cities.

N.2.4

Management of Pilot projects

The TMHRI will actively solicit opportunities to collaborate with the scientific community on biologic
al studies
of
cancer stem cell microenvironment
that involves the application of high
-
throughput technologies
, modeling,
and bioinformatics techniques. The
Pilot Projects or the
Driving Biological Projects (DBP) funding mechanism
will fund projects that ha
ve the potential to significantly contribute to the field of
cancer stem cell
microenvironment
and enhance the capabilities and usefulness of the
CSMCaD
. TMHRI will seek to fund
transformative projects whose outcomes will have implications for a broad arra
y of
can
c
er system
s

biology
. For
example, these projects could include the
in
-
vivo cancer stem cell and other cell labeling,
drug combination
prediction, development of new modeling of tumor metastatic tissue,
development of new analytical tools for
next
g
eneration sequences
, the deep characterization of drug resistan
ce
, and novel software to integrate in vivo
imaging data with other data modalities, such as
optical
microscopy
data. The
CSMCaD

plan
s

fund four

projects
in the year 1 and year 2, 3 proposals
in year 3 and 4, and 2 proposals in year 5

and totally
16

one
-
year
projects
over the 5
-
year period
.

T
he fi
rst four projects will start in August

of 2010.

We will
post an
announcement
open to
all

experimental laboratories in the United States
once t
he
CSMCa
D

is funded. I
nterested investigator
s

will be
invited to submit

their proposal
s
. The review panel will consist of the PI, Core PIs and the member
s

of external
advisory panel.
We anticipate that the TMHRI
Bioinformatics
and Biomedical Engineering Program

wi
ll provide
necessary
bioinformatics support to the
awardees.

Solicitation and Review of Proposals
: The strategy that we will use for solicitation and review of proposals
is analogous to one that TMHRI
and Baylor
currently use successfully to manage several

internal seed funding
proposal programs. White paper proposals will be solicited from the scientific community through
annou
ncements posted on the
CSMCaD

website, and other outreach activities including ads in scientific journals
and flyers and posters d
istributed and posted at scientific meetings. The
Pilot Projects or
DBP Program will
especially be advertised to all
cancer and related
investigators in USA
. The DBP white page
guidelines

will also
be included in the solicitation. The proposals will be sub
mitted electronically via the streamlined
Methodist Online
Research Technology Initiative (MORTI)

system
of TMHRI
that forwards the applications to the
Research Project
Coordinator
, then to reviewers, grants and staff
s

for budget review
.

TMHRI investigators currently use this facile
electronic system extensively. Award notification and grant management are also managed by the MORTI
system.

We
will first review the proposals for responsiveness to the solicitation. Proposals deemed respons
ive to the
solicitation will then be sent out to external expert reviewers selected by the management committee. We will use
an NIH
-
style peer
-
review panel process to rank order the proposals. Reviewers will assign priority scores to the
proposals and retu
rn them to the Project

Manager within
one
month. The four

applications with the
best
priority
scores will then be forwarded on to the
ICBP

Project Officers for their review and approval. The
Research Project
Coordinator
, with input from the management comm
ittee, will address any questions or concerns the officers
may have regarding the projects and their management in her Final DBP Project Plan to be submitted to the
officers within 2 weeks of officer approval of the projects. Her plan will include monitori
ng procedures for the
projects

and will establish metrics and milestones. The monitoring procedures will likely emulate a U
-
series
reporting structure and include semi
-
annual reports to be submitted to the Project
Coordinator one

month prior to
the due dat
e of the BRC semi
-
annual progress report. Upon receipt of written approval of the Final DBP Project
Plan from
the PI

and ICBP
officers, funds will be dispersed to grantees.

N2.5. Existing Supporting
Cores

(
Environments and Resources
)


Resources of The
Methodist Hospital Research Institute
. A complete account of available resources for
this proposal
is
provided

in
the
resource pages of
this proposal
.
Briefly,
TMH
RI

Cores participating in the

ICBP

Project include Bioinformatics
and Biomedical Engineering
Programmatic
Core

(Stephen Wong, Director

and

PI
on this project and Xiaobo Zhou, Lab Chief and
a
core PI)
,
Cellular and Tissue Microscopy Core (Stephen Wong,
Director and PI on this project), Animal Imaging Core (Stephen Wong, co
-
Director and PI),
Genomic
s Core

(John
Baxter and Paul Webb, Director and co
-
Director a
s well as

co
-
investigators on this project)
, and Proteomics Core

(David Engler, Director and co
-
investigator on this project)
.

The
se

specialized cores

at TMHRI

provide the
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

165


Research Plan

Page

infrastructure to execu
te and support t
he proposed research projects.
Resources of the UT Health Science
Center

are

provide
d in the resource pages.

Resources of the Baylor College of Medicine

A detailed list is

also

provide
d in the resource pages.
Briefly, the institutional cor
e facilities available to support this center are the Gene Expression Core
(microarray/qPCR), Proteomics Core (Dean Edwards, Director and co
-
investigator on this project), C
-
BASS
Core (Thomas Westbrook, Director and co
-
investigator on this project), Cytome
try and Cell Sorting Core, Vector
and Virus Production Core, Integrated Microscopy Core, the Genome Sequencing Center, and the Genetically
Engineered Mouse Core. In addition to these institutional core
facilities
, the Lester and Sue Smith Breast Center,
in which Dr. Michael Lewis is a faculty member, has an Animal Handling and Imaging Core (Michael Lewis,
Director

and core PI on this project
), Microarray Core, qPCR Core, Pathology Core, and a
Bioinformatics/Biostatistics division (Susan Hilsenbeck, Direct
or and co
-
investigator on this project). Thus,
several of the institutional and center
-
based core directors are active participants in this project.

In addition,
Baylor College of Medicine

has an interinstitutional agreement with the MD Anderson Cancer C
enter which
allows full use of MD Anderson Core facilities by faculty at Baylor at subsidized prices.

The site
or core
PIs

will assume the oversight responsibilities for
individual core

resources

in their institutions
.
The
CSMCaD

PI will assume the ultimat
e responsibility for ensuring smooth and streamlined operating of the
core resources. The
supporting

core direct
ors will work closely with
CSMCaD

members to ensure access to the
core resources.

The PI and the core directors will also have regular meeting
s to interact with each other.


N
.2.6
.

Interaction with other
ICBP

centers

Our
ICBP

working group
is headed by the PI
,

Dr
. Wong. It facilitates interactions and collaborations
in order

to foster learning and improvements among the Centers which could then be also applied to the
other data

generated by other
groups
.
The
CSMCaD

will work under the guidance of the
ICBP

Steering Committee on the
development, harmonization, and standardizatio
n of methods for data collection and analysis across the different
platforms to be
developed by centers in the ICBP
network.


The
CSMCaD

will work closely with other
ICBP
centers

to identify and test methods suitable for performance validation of
multi
-
sca
le data acquisition and
multimodal imaging, leading to multi
-
center, multi
-
platform clinical studies i
nvolving all centers in the ICBP

network.
T
he
PI
and the
CSMCaD

research group leaders will participate in the
ICBP

working groups for the
purpose of comm
unicating information across the network centers relevant to joint activities and creation and
maintenance of network
-
wide resources.

N2.
7
.
Compatibility with caBIG

The software tools and da
ta models developed in the CSMCD

will be made compatible to the NCI caBIG
infrastructure, according to the caBIG Compatibility Guidelines. The
interoperab
ility betwe
en the
CSMCaD

tools
and caBIG software would be planned to be at least at the silver level

such that
the barrier to use
CS
MCaD

software by a third party will be significantly reduced.

N2.
8
.
Plan for Sharing Research Data, Resources, and Intellectual Property


Plan for Sharing Research Data, Resources, and Intellectual Property:
All primary
data, datasets,
algorithms, and pr
otocols generated
will be conducted at the PI’s labs (
Bioinformatics and Biomedical
Engineering Program,

including Laboratory for Medical Systems Biology and Laboratory for Bioinformatics and
Bio
-
image Computing) at TMHRI and Core PIs’ labs at Baylor and
UT
HSC
. All data pertaining to this project will
be deposited into the
CSMC
A
D

database. Data generated as part of this research project will be made freely
available after publication. Our
labs have an
excellent track record of sharing reagents with the com
munity.


As in previous stud
ies
, we will present and disseminate our research results, software package, and related
publications and documentation on the public
CSMC
A
D

website hosted by the PI’s lab. We will post step
-
by
-
step
instruction including screen
shots and test images for users to download and run by themselves. On the
CSMC
A
D

website, we set up a “Contact Us” for users to send us questions and comments.

Users may choose to
register with us online by just using their email addresses (
r
egistration is

not required to download the software).
We will notify registered users by email about new release and upgrade, in addition to post the messages online.

A
ll research data and analysis tools generated under this award will be made publicly available to the

research community
.

This includes all data generated through the driving biological projects and all software and
analysis tools developed for pathway analysis, data integration from different sources,
and so on
. All data will be
released once
they are

ve
rified. Any software algorithms and programs developed by the center and
our
collaborators will be made publicly available in a manner consistent with the goals of NIH for software
dissemination, and unique biological information (DNA sequences, etc.) will

be submitted to caBIG for wide
Program Director/Principal In
vestigator (Last, First, Middle
):
Wong, Stephen, T.C., Ph.D., P.E.

PHS 398/2590 (Rev. 11
/07)

Page

166


Research Plan

Page



Figure 3.

The 92 gene taxotere sensitivity predictor (Left) did not
predict AC response (Right)

The expression levels are shown in red
(expression levels above the median for the gene) and blue
(expression levels below the median for the gene).



dissemination to the research community. Research tools (including analysis tools, algorithms, software
interfaces, source codes and other
software technologies) developed or
enhanced with contract support will be
made avail
able in caBIG and the
CSMCaD

web portal after they have been
appropriately tested both internally and by
our cadre of expert consultants. The
CSMCaD

is a collaborative program, and
TMHRI and its
Baylor/UTHSC partners

will
work within the guidelines
established by
the NIH and with other funded sites to