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The pathway less traveled
November 2009
EDIT CONNECT
SHARING OPTIONS:
PHOENIX, Ariz.—Using computer modeling, researchers at the
Translational Genomics Research Institute (TGen) and Scottsdale Healthcare have
uncovered lung cancer "pathways" that ultimately could become targets for new
drugs.
According to Dr. Glen Weiss, director of thoracic oncology
at TGen Clinical Research Services at Scottsdale Healthcare, the study,
published in the Journal of Thoracic Oncology, showed the value of conducting computer modeling, or in
silico research.
"The focus is to mine the publicly available gene expression
microarray data sets for shared common pathways, looking at identifying new and
possibly unrealized targets for small-cell cancer and large-cell cancer
treatments," notes Weiss.
Scottsdale Healthcare and TGen have partnered on
groundbreaking cancer research since 2005. The partnership allows molecular and
genomic discoveries made by TGen and others around the world to reach the
patient bedside through Scottsdale Healthcare's Virginia G. Piper Cancer Center
as quickly as possible through clinical trials with agents directed at specific
targets in patients' tumors.
The researchers hope that over time, in silico research will help lower healthcare costs while
speeding up the process of turning scientific discoveries into treatments for
patients. Weiss notes that by using in silico research, investigators can design more focused
laboratory experiments, hopefully with more precision and efficiency.
"There are pathways that you can identify just from in
silico analysis. And we can use these types
of tools to explore treatments for patients, down the road," says Weiss, an
associate investigator in TGen's Cancer and Cell Biology division and the
senior author of the paper.
Weiss says the expectation is that in silico research will yield targets for further clinical and
laboratory research.
The study sought to identify metabolic pathways that could
be targeted by drugs in patients with both small-cell and large-cell lung
cancers. Small-cell lung cancer represents about 15 percent of all lung
cancers. The rest are classified as non-small cell lung cancer, of which
large-cell lung cancer represents about 10 percent. The study used publicly
available data sets, searching for connections that may have been previously
overlooked.
"By utilizing what is available, other investigators can
mine these datasets to lend support for their hypotheses or help focus
laboratory experiments," notes Weiss. "Because it may be costly and challenging
to assemble large databases of gene expression data in a particular cancer
type/situation, it is important to make these databases accessible to the
public."
Weiss says that within those datasets, there are common
pathways.
"We point out some examples that provide some
proof-of-principle from the in silico
search," adds Weiss, who was joined in his research by TGen's Dr. Chris
Kingsley and by Dr. Anoor Paripati of the Scottsdale Clinical Research
Institute at Scottsdale Healthcare.
As an example, the study cites one particular signaling
pathway, Wnt/ß-catenin, that could be targeted by two drugs, Vorinostat and
Dasatinib, both of which are under study in clinical trials.
"This is an exploration of the publicly available data sets
in an attempt to answer a new question. It shows that you can look at pathways
and identify targets," Weiss points out. "We did our validation by looking at
what's been tested, or what's available already."
In silico research,
which is far less costly than conducting genetic profiling analysis of cancer
tumors, is expected to become more common as the National Cancer Institute
ramps up its cancer Biomedical Informatics Grid, also known as caBIG. Such
research should lead to targets for further laboratory and clinical research,
and also should help clinicians provide more personalized treatment for
patients, Weiss says.
"There is going to be a wealth of profiling data out there
in the near future. You can then apply techniques like this, and hopefully
design smarter clinical trials to find the drugs that would work," Weiss notes.
"Like other clinical research conducted at Scottsdale Healthcare, this study
will be measured by clinically validated results."
Report heralds TGen's annual economic impact on Arizona
economy
PHOENIX—A report issued in late September by research firm
Tripp Umbach estimates that the Translational Genomics Research Institute
(TGen) provides Arizona with an annual total economic impact of $77.4 million.
The firm also estimates that including spin-off businesses and
commercialization of TGen-led research, TGen's total annual economic impact
will grow to $321.3 million by 2025.
With these results, TGen has outpaced all previous
performance marks and projections made in a December 2006 economic impact
report by Tripp Umbach.
The new report concludes that TGen operations in 2008 produced
$8.09 for every $1 invested by the state of Arizona, 461 full-time jobs
(directly and indirectly), $2.7 million in state taxes and a direct annual
economic impact of $44.5 million.
When the impact of TGen-generated business spin-offs and
commercialization are included, the study shows that TGen in 2008 produced
$14.07 for every $1 invested by the state, $5.7 million in taxes and $77.4
million in total annual economic impact.
By 2025, the report predicts, TGen operations will return
$30.20 for every $1 invested by the state, resulting in 2,332 jobs, $13.4
million in state taxes and an annual economic impact of $166.1 million.
Including projected business spin-offs and commercialization, the report says,
TGen would return $58.42 for every $1 invested by the state, create 4,116 jobs,
generate $27.4 million in taxes and produce a total annual economic impact of
$321.3 million.
"TGen has certainly kept its promise to the state of Arizona to be a
strong economic engine,'' said Paul Umbach, president of Pittsburgh-based Tripp
Umbach, in a statement. "Our updated analysis shows dramatic increases in
economic, employment, and government revenue impacts on Arizona's economy. As a
result of TGen's better-than-expected performance over the past two years, our
projected impact numbers for 2015 and 2025 are also significantly stronger. It
is clear from our updated analysis that commercial spin-off activities from
TGen are rapidly having a positive economic impact on the Arizona economy at
just a time when adding jobs is so important." Code: E110918 Back |
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