| Current
Molecular Medicine
ISSN: 1566-5240
Current Molecular Medicine
Volume 5, Number 1, February 2005
Contents
Transcriptome Analysis in Drug Development
Executive Editor: William V. Williams
Editorial
William V. Williams
[Full text
article]
The Transcriptome in Blood: Challenges and Solutions
for Robust Expression Profiling Pp.3-10
Hongtao Fan and Priti S. Hegde
[Abstract] [Full
text article]
Pathway and Ontology Analysis: Emerging Approaches
Connecting Transcriptome Data and Clinical Endpoints Pp.11-21
L. Yue and W.C. Reisdorf
[Abstract] [Full
text article]
Ethical and Legal Aspects of Applied Genomic Technologies:
Practical Solutions Pp.23-28
Penelope K. Manasco
[Abstract] [Full
text article]
From Traditional Biomarkers to Transcriptome Analysis
in Drug Development Pp.29-38
Yun-Fu Hu, June Kaplow and Yiwu He
[Abstract] [Full
text article]
The Agony and Ecstasy of “OMIC” Technologies
in Drug Development Pp.39-52
John A. Bilello
[Abstract] [Full
text article]
The Role of Transcriptome Analysis in Pre-Clinical
Toxicology Pp.53-64
George H. Searfoss, Timothy P. Ryan and Robert A. Jolly
[Abstract] [Full
text article]
Application of Transcriptome Analysis to Clinical
Pharmacology Studies Pp.65-82
Benjamin Hsu, Lisa Cass and William V. Williams
[Abstract] [Full
text article]
Clinical Pharmacogenomics and Transcriptional
Profiling in Early Phase Oncology Clinical Trials
Pp.83-102
Michael E. Burczynski, Judith L. Oestreicher, Monica J.
Cahilly, Deborah P. Mounts, Maryann Z. Whitley, Lisa A. Speicher
and William L. Trepicchio
[Abstract] [Full
text article]
Development of Oncology Drug Response Markers
Using Transcription Profiling Pp.103-110
Nicholas C. Dracopoli
[Abstract] [Full
text article]
DNA Microarrays in Clinical Cancer Research Pp.111-120
Raymond Wadlow and Sridhar Ramaswamy
[Abstract] [Full
text article]
Abstracts
[Back to top]
Editorial
William V. Williams
[Full text article]
What will drug development look like in 10, 20 or 40 years?
Opinions abound on this interesting question, ranging from
totally personalized development of medicines, (visions of
Scotty in Star Trek using his scanner to diagnose and treat
Captain Kirk on the spot!) to multifunctional drug targets
that can be used across a wide range of disease indications.
As the landscape in drug development is rapidly evolving,
there are heightened expectations that we should reap the
benefits of the genomic revolution, increased pressure for
better drug safety, and price pressure from generic medicines
and consumer demand. Within this rapidly evolving environment,
new technologies are being developed that will likely change
the face of drug discovery and development. Prominent among
these is the fledgling enterprise of transcriptome analysis.
Transcriptome analysis provides the opportunity to evaluate
global changes in gene transcript expression in a cell, tissue,
organ or whole organism. Within the past decade there has
been an exponential increase in publications on transcriptomics
(see the Figure), with several significant advances already
seen. This issue is dedicated to exploring how transcriptome
analysis is impacting drug discovery and development, and
to allow the reader to become familiar with the application
of this technology within this context.
Results from a search of Current Contents of transcriptome
or transcriptomic or transcriptomics on a yearly basis. The
data for 2004 are to week 49.
The issue is divided thematically into two groups of articles.
The first five articles discuss the technology, how it is
used, how to approach data analysis, and how this technology
fits into the larger picture of available and developing technologies.
Fan and Hedge explore the use of blood as a tissue for transcriptome
analysis, guiding the reader into the intricacies and potential
pitfalls that can be encountered. Yue and Residorf discuss
the various methods of data analysis that can be applied to
transcriptomic data, and which analysis tools are currently
available. Manasco discusses the ethical and legal implications
for the use of transcriptome and genomic data, with potential
solutions to various issues of confidentiality and consent
proposed. Hu, Kaplow and He describe the lessons we have learned
from use of traditional biomarkers and how this can be applied
to transcriptomics. To put the use of this technology into
a broader context, Bilello discusses how “OMIC”
technologies can complement each other, and how the parallel
fields of proteomics, metabonomics etc. are developing. These
papers should serve to orient the reader to understanding
in a general sense how transcriptomics can be applied in studying
drugs.
The papers that follow deal more specifically with the use
of transcriptome analysis in the various stages of drug development.
Searfoss, Ryan and Jolly describe use in pre-clinical toxicology
studies. In the clinical realm, Hsu, Cass and Williams discuss
the use of transcriptomics in clinical pharmacology, which
in general comprises the earliest stage of drug development.
This is followed by three papers that discuss what has been
to date the most widespread application of transcriptomics
in drug development, namely in oncology. Burczynski and his
collaborators discuss early phase oncology trials, while the
papers by Dracopoli and Wadlow & Ramaswamy discuss later
stage and additional uses in the oncology setting.
Overall, the reader should come away with a good understanding
of how transcriptomics is being used and its potential applications.
Clearly we are on the verge of a new era in drug discovery
and development. The papers within this issue set the stage
for the revolutionary impact transcriptomics will have on
every aspect of pharmaceutical research and development.
I would like to thank all the authors for their diligent
work on these manuscripts. It has been a pleasure and a privilege
to edit this special issue.
[Back to top]
The Transcriptome in Blood: Challenges and Solutions for Robust
Expression Profiling
Hongtao Fan and Priti S. Hegde
[Full text
article]
Peripheral blood may be the most feasible tissue source in
clinical assessment of differences in gene expression between
diseases and drug treatments due to accessibility. Yet, gene
expression profiling from blood remains a challenge. Blood
is a complicated biological system consisting of a variety
of cell types at different stages of development. In addition,
blood is also one of the most variable tissue types for gene
expression analysis. The success of a blood microarray study
depends on the choice of cell isolation method and preparation
technique. In this review, we give a brief overview of the
current status of using blood as a source for expression profiling
and discuss potential applications of this method in the practices
of clinical research.
[Back to top]
Pathway and Ontology Analysis: Emerging Approaches Connecting
Transcriptome Data and Clinical Endpoints
L. Yue and W.C. Reisdorf
[Full text
article]
The increasing use of gene expression profiling offers great
promise in clinical research into disease biology and its
treatment. Along with the ability to measure changing expression
levels in thousands of genes at once, comes the challenge
of analyzing and interpreting the vast sets of data generated.
Analysis tools are evolving rapidly to meet such challenges.
The next step is to interpret observed changes in terms of
the biological properties or relationships underlying them.
One powerful approach is to make associations between the
genes that are under investigation and well-known biochemical
or signaling pathways, and further to assess the significance
of such associations. Similarly, genes can be mapped to standardized
biological categories via an ontology resource. We
discuss these approaches and several web-based resources and
tools designed to facilitate such analyses. This information
can be used to facilitate understanding and to help design
more focused experiments for validating the relevance and
importance of these biological pathways and processes in human
disease and therapeutics.
[Back to top]
Ethical and Legal Aspects of Applied Genomic Technologies:
Practical Solutions
Penelope K. Manasco
[Full text
article]
Many ethical and legal issues surround genomic technologies,
some of which are present for other kinds of medical data,
but some of which are specific to genomic data. Specifically
the global nature of genomic data and the life-long implications
of genetic defects on the health of the individual subject
produce challenges in the ethical and legal handling of this
data. In general, data derived from transcriptome analysis,
which studies gene expression, as well as proteomics and metabolomics,
carry less ethically-charged information than measures of
the germ line genome. However, theoretical issues that have
been raised related to withholding therapy based on a specific
genotype which could also apply to a specific expression profile.
Potential solutions for these challenges are discussed, such
as maintaining a connection with research participants through
a trusted third party, using electronic means to manage that
contact and reconsent subjects. A flexible, secure information
technology infrastructure is proposed to manage and search
consent forms, provide the ability to collect additional data
and consent while maintaining participant confidentiality.
[Back to top]
From Traditional Biomarkers to Transcriptome Analysis
in Drug Development
Yun-Fu Hu, June Kaplow and Yiwu He
[Full text
article]
Traditional biomarkers have played an important role in drug
development as well as patient care. A single traditional
biomarker or surrogate endpoint is unlikely to either characterize
the complete pathophysiology of a complex disease or capture
all the therapeutic benefits or potential adverse effects
that a drug will have in a diverse patient population. Transciptome
analysis, on the other hand, can provide a large-scale survey
of gene expression associated with the etiology of a human
disease or pharmacological responses to a therapeutic intervention.
The quantitative and qualitative readouts can provide increased
power to identify novel drug targets or biomarkers indicative
of drug safety or efficacy. Transcriptomics has positively
impacted drug development and will continue to improve the
medicines of the future. Here, we describe the increasingly
important roles that traditional biomarkers and transcriptome
analysis have played in various phases of drug discovery and
development as well as the opportunities and challenges that
they present to the pharmaceutical industry.
[Back to top]
The Agony and Ecstasy of “OMIC” Technologies
in Drug Development
John A. Bilello
[Full text
article]
Over the last decade we have witnessed a fundamental change
in how biomedical research is carried out and we can now assess
the impact of the Human Genome Project on drug discovery and
development. Advances in “omics” technologies
(genomics, transcriptomics, proteomics and metabonomics) were
touted as having the potential to revolutionise our approach
to disease diagnosis, prognostication and development of novel
therapeutics. However, the promise of rapid advances in medicine
“from the lab bench to the bedside” has not manifested
as of yet. Indeed it appears that the translational applications
of genomic-based research have preceded the development of
both (i) a conceptual framework
for disease understanding and (ii)
effective tools that can exploit the vast amounts of data
derived from these efforts. In reality great progress has
been made, however understanding processes such as disease
progression (or drug response) requires systematic insight
into dynamic (and temporal) differences in gene regulation,
interaction and function. This review will discuss “omic”
technologies with the emphasis upon advances in our understanding
of the human genome derived transcriptome (RNA), and its proteome
(proteins), while focusing upon the translation of this information
into the drug development paradigm.
[Back to top]
The Role of Transcriptome Analysis in Pre-Clinical Toxicology
George H. Searfoss, Timothy P. Ryan and Robert
A. Jolly
[Full text
article]
A major benefit of the genomics revolution in biomedical
research has been the establishment of transcriptome analysis
as an enabling technology in the drug development process.
Nowhere in the realm of drug development has the expectation
of the impact of transcriptome analysis been greater than
in the area of pre-clinical toxicology. Transcriptome analysis,
along with other new high-content data generating technologies,
has the potential to radically improve the drug safety assessment
process by allowing drug development teams to identify potential
toxicity liabilities earlier, and thus proceed only with those
molecules that have both efficacy at the target and a low
potential for toxicity in the human population. In this review
we will briefly describe the major ways in which transcriptome
analysis is being applied in the pre-clinical safety assessment
process, focusing primarily on four areas where transcriptome
analysis has already begun to have impact. These include using
transcriptome analysis to: 1) understand mechanisms of toxicity:
2) predict toxicity: 3), develop in vivo and in
vitro surrogate models and screens; and, 4) develop toxicity
biomarkers. We will close by briefly addressing future trends
and needs in the application of transcriptome analysis to
drug safety assessment.
[Back to top]
Application of Transcriptome Analysis to Clinical Pharmacology
Studies
Benjamin Hsu, Lisa Cass and William V. Williams
[Full
text article]
Clinical pharmacology is the investigation of drug effects
in humans. This review discusses the basic tenets of clinical
pharmacology research, including pharmacokinetic and pharmacodynamic
analysis, therapeutic window, and clinical trial design, and
the issues that may arise in the application of transcriptome
analysis to clinical pharmacology studies. Examples of how
transcriptome analysis can be applied to clinical pharmacology
research are described, including a model system of endotoxin
challenge (in vitro and in vivo), and an
example of a cross-over drug study in normal volunteers. Various
data display and analysis methods are also illustrated, including
principal component analysis, hierarchical cluster analysis,
and pathways analysis.
[Back to top]
Clinical Pharmacogenomics and Transcriptional Profiling in
Early Phase Oncology Clinical Trials
Michael E. Burczynski, Judith L. Oestreicher,
Monica J. Cahilly, Deborah P. Mounts, Maryann Z. Whitley,
Lisa A. Speicher and William L. Trepicchio
[Full text
article]
Microarray-based expression profiling studies in the field
of oncology have demonstrated encouraging correlations between
tumor transcriptional profiles and eventual patient outcomes.
These findings have fueled great interest in the application
of transcriptional profiling to samples available from real-time
clinical trials, and clinical pharmacogenomic objectives utilizing
transcriptional profiling strategies are becoming increasingly
incorporated into clinical trial study designs. Over the last
few years several retrospective studies based on the profiling
of archival tumor tissues suggest that transcriptional analysis
of oncology samples may provide general prognosis measures,
and in some cases may even predict response to specific therapies.
Recently the FDA released a voluntary genomic data guidance
meant to assist both regulatory agencies and pharmaceutical
companies alike in evaluating the potential benefit of implementing
expression profiling studies during the preclinical and clinical
phases of drug development. Despite the great promise afforded
by this technology, the ultimate benefit of applying transcriptional
profiling in prospective clinical trials has yet to be realized
because a number of practical impediments to this process
exist. The multi-fold purpose of the current review is to
highlight the increasing evidence from studies that have identified
transcriptional signatures in archived tumors prognostic of
patient outcome, to describe some of the drivers for the implementation
of transcriptional profiling strategies in real-time drug
development, to discuss the use of transcriptional profiling
in the context of increasingly complex translational medicine
strategies, and to highlight the practical issues and potential
approaches involved in the successful application of clinical
pharmacogenomic objectives during real-time clinical trials.
Strategic implementation of transcriptional profiling in early
oncology clinical trials can provide an opportunity to identify
predictive markers of clinical response and eventually provide
a substantial step forward towards the era of personalized
medicine.
[Back to top]
Development of Oncology Drug Response Markers Using Transcription
Profiling
Nicholas C. Dracopoli
[Full text
article]
Transcriptional profiling of a tumor’s entire genomic
complement has become a key tool in the analysis of human
cancers and identification of novel markers to predict disease
state, outcome, and response to therapy. At present, this
technology provides the most comprehensive approach for the
analysis of somatic changes altering critical pathways during
transformation of stable diploid cells into unstable tumor
cells. Such analyses are impacting the development of novel
anti-cancer drugs through the early detection of cancer, development
of targeted therapies, identification of optimal dose and
regimens for new drugs, and segmentation of patients to enrich
response rates and reduce risk of adverse events.
[Back to top]
DNA Microarrays in Clinical Cancer Research
Raymond Wadlow and Sridhar Ramaswamy
[Full text
article]
The recent sequencing of the human genome, coupled with advances
in biotechnology, is enabling the comprehensive molecular
"profiling” of human tissues. In particular, DNA
microarrays are powerful tools for obtaining global views
of human tumor gene expression. Complex information from tumor
"expression profiling” studies can, in turn, be
used to create novel molecular cancer diagnostics. We discuss
the utility of DNA microarray-based tumor profiling in clinical
cancer research, highlight some important recent studies,
and identify future avenues of research in this evolving field.
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