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2009 AAAS Annual Meeting
Call for Symposium ProposalsDeadline: Monday, 28 April 2008
The theme calls to mind that 2009 is the 200th anniversary of Charles Darwin’s
birth and the 150th anniversary of the publication of his book On the Origin
of Species by Means of Natural Selection. Astronomy, physics, mathematics,
linguistics, neuroscience ... indeed every discipline can demonstrate its own
unique evolutionary path and speculate on where it may lead.
Call for Posters: AAAS Student CompetitionOpens: Monday, 14 July > Deadline: Thursday, 16 October
The competition is open to college undergraduate and graduate students
only. Winners receive a cash prize, a framed certi�cate, and a one-year AAAS
membership including a subscription to Science! The names of �rst-place
winners and honorable mention entrants will be published in Science.
Our Planet and Its Life: Origins and Futures
12–16 February • Chicago
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AAAS/Science Business Office Feature
“I want to
identify who are the
patients who will have true
clinical benefit, and include
them in my trial, and who will
be resistant, and exclude them
from the trial.”Look for these Upcoming ArticlesGenomics 1—April 4
RNAi — June 6
Proteomics 2—August 1
continued >
GENOMIC BIOMARKER DISCOVERY:BRINGING THE GENOME TO LIFE
Inclusion of companies in this article does not indicateendorsement by either AAAS or Science, nor is it meantto imply that their products or services are superior tothose of other companies.
Biomarkers
AAAS/Science Business Office FeatureCREDIT:©ISTOCKPHOTO.COM/YAKOBCHUK
A convergence of technological breakthroughs has taken genomic biomarker dis-
covery to a new level. Between advances in sequencing, evolving array designs,
and a more sophisticated understanding of genome architecture, simple tests for
glucose, cholesterol, and human chorionic gonadotropin could soon be competing for
pharmacy shelf space with gene expression– and epigenome-based diagnostics that prom-
ise to detect diseases earlier, stratify patients into treatment classes, and identify those
most likely to respond to therapies. First to benefit: cancer patients. The era of personal-
ized medicine is just around the corner. By Jeffrey M. Perkel
The US Food and Drug Administration approved the first gene expression
microarray–based test for use in the United States on February 6, 2007.
MammaPrint, from Amsterdam-based Agendia, is a breast cancer diagnostic
that uses the combined expression of 70 genes to predict whether a woman
is at high or low risk for her cancer to recur.
Based on Agilent Technologies’ 60-mer oligonucleotide microarrays and costing
about $4,200, MammaPrint helps doctors and their patients make more informed
decisions, says René Bernards, Agendia’s scientific director and professor of
molecular carcinogenesis at the Netherlands Cancer Institute (NCI).
Patients classified as having a high risk of metastasis have a 50 percent 10-year
survival, says Bernards, versus 96 percent for low-risk patients. A combination of
adjuvant chemotherapy and hormonal therapy, however, increases the high-risk pool’s
survival to about 70 percent.
“If you can increase your chances of survival from 50 percent to 70 percent, that is
fairly significant,” he says. At the same time, Bernards continues, “you can show that
the net benefit of adding chemotherapy to the hormonal therapy [for low-risk patients] is
essentially zero.”
Such prognostic clarity can pay both medical and economic dividends. About 90 percent
of US breast cancer patients currently receive chemotherapy, Bernards estimates. If that
number were reduced to 60 percent (the fraction of women whose tumors are labeled high
risk), the healthcare system could save millions. Meanwhile, patients who either do not
need, or cannot benefit from, chemotherapy avoid its unpleasant side effects.
It truly is individualized medicine. And MammaPrint is just the beginning. Researchers in
both academia and industry are scrambling to find new genomic biomarkers based on both
gene expression and epigenetic modifications, especially for cancer.
Serving Different NeedsGenomic biomarkers come in several flavors, includingdiseasedetection and classification,
treatment response prediction, treatment efficacy, and prognosis.
Their development follows a common theme. Typically, genomewide microarrays are
used in a preliminary screen on a relatively small set of cell lines or tissue biopsies. The
resulting biomarker candidates are then validated on an independent sample set, and
typically migrated to a different assay platform, such as quantitative real-time PCR, which
can better probe a small number of loci for a large number of samples.
Certain groups at Wyeth identify candidate patient-selection biomarkers using
Affymetrix’s U133 whole genome microarray and targeted signaling protein array analysis
of drug-resistant and drug-sensitive cell lines, says Christina Coughlin, associate director
of translational medicine efforts in the oncology pipeline at the company’s Collegeville,
Pennsylvania, facility. The 100 or 200most-promising hits are then culled via more focused
work using xenografts and genetically engineered mice.
“Iwant to identifywhoare thepatientswhowillhave trueclinicalbenefit,and include them
in my trial, and who will be resistant, and exclude them from the trial,” says Coughlin.
Other biomarkers, like those found on MammaPrint’s 70-gene panel, help
LIFE SCIENCE TECHNOLOGIES AAAS/Science Business Office Feature
1854 www.sciencemag.org/products
Biomarkers
guide treatment decisions. Similarly, Oncotype DX, from Redwood City,
California–based Genomic Health, uses the combined expression of
just 21 genes to predict both a patient’s breast cancer prognosis and
her likelihood of responding to chemotherapy.
Steve Shak, Genomic Health’s chief medical officer, explains that for
every 100 women diagnosed with node-negative, ER-positive breast
cancer, 85 “will survive without recurrence” with surgery and hormonal
therapy alone. Of the 15 who will recur, chemotherapy benefits four. In
other words, just 4 percent of breast cancer patients both need and can
benefit from cytotoxic chemotherapy.
“So because we don’t know who is more likely to recur, we ‘punish’
the many to benefit the few,” he says.
Oncotype DX uses quantitative RT-PCR to produce a “recurrence
score” between 0 and 100, with the likelihood of recurrence ranging
from 4 percent for a low score to 35 percent for a high one. As with
MammaPrint, its gene panel arose by retrospectively mining earlier
studies correlating outcome with gene expression in breast cancer.
But key to Oncotype’s development was a novel method to perform
RT-PCR on RNA in formalin-fixed tissues, says Shak—an advance that
took Genomic Health two years to pull off, but which opened up for
the company all those archived tissue blocks left over from 30 years of
clinical studies in the United States and abroad.
“The RNA was there, but it was fragmented. By optimizing the assay
to look at those fragments of RNA, we were able to reliably quantify
it,” he says.
Expect the UnexpectedThe success of Oncotype DX andMammaPrint highlights the continued
utility of archived cancer array datasets. But how to locate, integrate,
and analyze them all? Arul Chinnaiyan, professor of pathology and
urology at the University of Michigan School of Medicine, and former
graduate student Daniel Rhodes developed what has turned out
to be an unexpectedly fruitful resource for researchers looking to do
just that.
Oncomine (available through Compendia Bioscience), is an online
database of gene expression in cancer. Its 608 million datapoints
represent 342 studies on 40 different disease types —24,250 arrays
in total.
According to Chinnaiyan, the project arose out of “mundane”
necessity. “We were doing more gene expression analyses, and
were always asked by academics whether their favorite genes were
dysregulated in a specific cancer, and we had to mine the datasets to
find out.”
They developed Oncomine to “empower the average oncologist or
biologist to ask the question themselves.”
But Chinnaiyan quickly realized Oncomine was a useful hypothesis-
generating tool, as well. “It’s like a Google for high throughput gene
expression data in cancer,” he says.
His lab has plumbed Oncomine to discover several potential
biomarkers, including a novel chromosome translocation (typically
associated with “liquid cancers”) in prostate cancer, a solid tumor. The
translocation produces a gene fusion between TMPRSS2 and an Ets
transcription factor, empowering Ets with androgen responsiveness,
and represents a unique opportunity, he says.
“The identification of a gene fusion in prostate cancer makes it
a highly specific biomarker and a good therapeutic target,” he says,
just as the Bcr-Abl fusion is both a biomarker for chronic myelogenous
leukemia, and the target of its therapy, Gleevec.
So unexpected was the observation, Chinnaiyan recalls, he initially
thought it must be wrong. Now San Diego–based Gen-Probe is devel-
oping a urine-based detection diagnostic for prostate cancer based on
the discovery, he says.
Epigenetic BiomarkersNot all genomic biomarkers are based on gene expression. Researchers
have become increasingly aware recently of the critical role that
epigenetic changes—whether involving DNA methylation or histone
modifications—play in both development and disease.
Most epigenetic biomarker discovery focuses on DNA hyper-
methylation. One of the most common events in tumor formation, it
turns out, is silencing tumor suppressors and cell cycle control genes
by methylating their (otherwise unmethylated or partially methylated)
promoters.
Kenneth Nephew, Professor of Cellular and Integrative Physiology at
IndianaUniversity School ofMedicine,who studies epigenetic changes
as indicators of breast and ovarian cancer, says such changes represent
good disease biomarkers for three reasons: they are stable, common,
and involve a gain of signal.
They also are easily detected: As tumor cells die they shed their DNA
into the circulation. So, researchers are looking for ways to diagnose
diseases earlier using the methylated DNA they find in blood, urine,
feces, and sputum.
Theprocess is essentially the samearray-basedmethodaswith single
nucleotide polymorphism and gene-expression biomarker discovery,
says Art Petronis, of the Centre for Addiction and Mental Health in
Toronto. “The difference is we have to use tiling arrays.”
Rather than focusing on protein-coding or polymorphic DNA
loci, tiling arrays cover the entire genome (or a large fraction of it).
Petronis uses two in his search for epigenetic hallmarks of complex
non-Mendelian disorders: a homemade array of some 12,000 CpG
islands, and Affymetrix’s higher density GeneChip Human Tiling
2.0R Array Set, which spans the entire human genome with
35-bp spacing on seven arrays.
The other difference, Petronis adds, “is we have to enrich the fraction
that contains a high density or low density of methylcytosine, and then
interrogate that fraction.”
There are basically two ways to perform those steps, one based
on differential restriction enzyme sensitivity of methylated DNA, the
other on bisulfite conversion of methylcytosines to uracil.
Peter Laird, director of the University of Southern California
Epigenome Center, uses two bisulfite conversion strategies in
his search for colorectal cancer classification and ovarian cancer
detection biomarkers. Laird starts with Illumina’s Infinium assay,
an array-based method that probes 27,000 CpG islands in a 12-
sample format. He then validates those hits using a more sensitive
technique called MethyLight, which is based on Applied Biosystems’
TaqMan quantitative PCR chemistry and the ability of primers to
distinguish minute sequence variations.
“With MethyLight we can detect 0.1 percent methylated versus 99.9
percent unmethylated DNA,” he says. “With a profiling technology [like
an array] you couldn’t detect that.”
“The identification of a gene fusion
in prostate cancer makes it a highly
specific biomarker and a
good therapeutic target.”
CREDIT:©ISTOCKPHOTO.COM/M
EVANS
LIFE SCIENCE TECHNOLOGIESAAAS/Science Business Office Feature
www.sciencemag.org/products 1855
Biomarkers
According to Victor Levenson, research associate professor at
Northwestern University, the discovery of bisulfite conversion
chemistry was a “breakthrough” in epigenetic research. “Before that,
it was extremely difficult to identify sequence-specific epigenetic
modifications,” he says.
“But the breakthrough came at a cost,” he adds. First, the conversion
usually destroys 85 percent to 95 percent of input DNA, creating
potential bias. And PCR on the surviving DNA is difficult, both because
the two strands are no longer complementary, and because the
sequence has degenerated from a tetranucleotide alphabet to one with
only three bases.
Instead, Levenson uses a restriction enzyme–based approach for
biomarker discovery. So does biomarker firm Epigenomics, says Achim
Plum, vice president of corporate communications. Epigenomics’
process, called differential methylation hybridization (DMH), involves
fragmenting genomic DNA, attaching primers to all fragment ends,
and then digesting them with a methylation-sensitive enzyme. While
methylated DNA will survive the treatment, he explains, unmethylated
DNA will not. Thus, it is excluded from subsequent steps, in which
the fragments are amplified and used to probe a custom Affymetrix
array covering some 50,000 genomic fragments—mostly promoters
and CpG islands.
“The beauty of the array is we put all our knowledge of what regions
to look at on the array,” says Plum. “So the fragments covered by probes
are highly selected based on our knowledge and experience.”
Plum says the company has used DMH to drive internal efforts to
develop a lung cancer detection diagnostic. The process took less than
a year, he says, from discovery to clinical proof-of-concept with a set
of markers that could detect lung cancer with 69 percent sensitivity
and 91 percent specificity in blood. Epigenomics’ most advanced
diagnostic, in development with Abbott Molecular, is a colorectal
cancer–screening test using methylated Septin-9 DNA in blood as
a biomarker.
Orion Genomics uses a similar strategy. Developed by Cold Spring
Harbor Laboratory’s Robert Martienssen, Orion’s MethylScope assay
involves shearing genomic DNA to approximately 1-kb fragments
(which enables complete genome coverage), splitting that pool into
two fractions, digesting one with the methylation-dependent enzyme
McrBC, size-fractionating theproducts to select for theuncut fragments,
and hybridizing the two pools to a 2.1-million oligonucleotide array
from Nimblegen.
With the right marker, even a single region can be informative, says
Orion CEO Nathan Lakey. “We found even single-locus epigenetic
changes that can discriminate breast cancer tumors from nontumor
tissue with 90 percent sensitivity and 96 percent specificity.”
Who Needs Arrays?Bradley Bernstein, of the Broad Institute of Harvard and MIT, has
developed a genomewide screening approach for histonemodifications
that eliminates DNA arrays.
“ChIP-Seq” combines chromatin immunoprecipitation (ChIP) and
Illumina’s next-generation sequencing technology, acquired from
Solexa. Like ChIP-on-chip, which reads ChIP data using whole-genome
microarrays, ChIP-Seq provides a genomewide view of chromatin
changes. The difference, says Bernstein, is that ChIP-on-chip measures
fluorescence intensity, while ChIP-Seq counts the absolute number of
times a particular genomic fragment is detected.
“ChIP-on-chip is an analog readout, whereas sequencing is a digital
readout,” he explains.
This past August, Bernstein coauthored a study that used ChIP-Seq
to map several histone modifications across the genome in mouse
embryonic stem cells, neural progenitors, and embryonic fibroblasts.
The data shed light on the cells’ transcriptional past, present, and
future, Bernstein said.
“It is a way to really precisely characterize the state of the cell,” he
explains. “The patterns tell you about what the cell is doing, and what
it can become later.”
A study, published February 17 in Nature, describes a similar method
for probing methylated DNA with single-base resolution. Called
BS-Seq, the technique combines Solexa sequencing technology with
bisulfite conversion; it was used to scan some 93 percent of all possible
methylation sites in the Arabidopsis genome.
Such data will be invaluable as the National Institutes of Health’s
$190 million Epigenome Project, part of the so-called “Roadmap
Initiative,” kicks off.
“The idea is to collect genomewide maps for some defined number
of primary cell types and models, in order to understand the normal
epigenome,” Bernstein says. “Once you do that, you can begin to look
at diseased epigenomes.”
Yet Bernstein admits DNA methylation will likely be more valuable
for biomarker development than histone modifications, because
while tumors release DNA into the circulation, they do not shed
intact chromatin. Thus, histone marks can only be assayed in intact
cells and tissues.
“The information content in the histones and chromatin is much
richer, but it’s more difficult to assay,” he says.
However these and other tests play out, says Stephen Baylin of the
Sidney Kimmel Comprehensive Cancer Center in Baltimore, Maryland,
the result will be a more individualized medical experience.
Take colon cancer, for instance. “Right now you do a blood test in
the stool to screen for blood,” he says. “That is suggestive, but not
indicative of colon cancer. But if you can get the DNA, it will be much
more diagnostic.” After all, why have a colonoscopy if you don’t
need it?
Abbott Molecularwww.abbottmolecular.com
Affymetrixwww.affymetrix.com
Agendiawww.agendia.com
Agilent Technologieswww.agilent.com
Applied Biosystemswww.appliedbiosystems.com
Broad Institute of Harvard and MITwww.broad.mit.edu
Centre for Addictionand Mental Healthwww.camh.net
Cold Spring Harbor Laboratorywww.cshl.edu
Compendia Biosciencewww.compendiabio.com
Epigenomicswww.epigenomics.com
Genomic Healthwww.genomichealth.com
Gen-Probewww.gen-probe.com
Featured Participants
Jeffrey Perkel is a freelance writer based in Pocatello, Idaho.
DOI: 10.1126/science.opms.p0800024
Illuminawww.illumina.com
Indiana University Schoolof Medicinewww.medicine.iu.edu
Netherlands Cancer Institutewww.onderzoekinformatie.nl/en/oi/
Nimblegenwww.nimblegen.com
Northwestern Universitywww.northwestern.edu
Oncominewww.oncomine.org
Orion Genomicswww.oriongenomics.com
Sidney Kimmel ComprehensiveCancer Centerwww.hopkinskimmelcancercenter.org
University of MichiganSchool of Medicinewww.med.umich.edu/medschool
University of Southern Californiawww.usc.edu
Wyethwww.wyeth.com
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