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The pathway less traveled
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."