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UCSC Team to Develop Data Sharing, Analysis Tools for Prostate Cancer Personalized Rx Project

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Researchers from the University of California, Santa Cruz, will analyze genomic data and develop a data-sharing platform for a project focused on overcoming treatment resistance in advanced prostate cancer cases.

UCSC is one of several institutions participating in a $10 million, three-year prostate cancer initiative — dubbed The Stand Up To Cancer Dream Team — that is funded by Stand Up to Cancer, the Prostate Cancer Foundation, and the American Association for Cancer Research.

The project will explore the idea that resistance in prostate cancer is the result of tumor cells using common cellular responses, called adaptive pathways, to beat current therapies. Thus, identifying and inhibiting these pathways should prevent treatment resistance in patients. The researchers will also develop an online platform, dubbed MedBook, which will apply social media concepts to oncology research and treatment information exchange.

The researchers will focus on identifying the causes of resistance from biopsies and blood samples collected from around 500 patients with advanced prostate cancer and tailoring therapies for them.

Besides UCSC, participants in the project include teams from UC San Francisco, UC Los Angeles, UC Davis, Oregon Health and Sciences University, and the University of British Columbia.

The project is expected to start later this fall, and the first clinical trials are scheduled to open at some point next year.

The UCSC bioinformatics team, led by Joshua Stuart, a professor of biomolecular engineering, will work on identifying genetic pathways in prostate cancer cells that are resistant to treatment as well as identifying potential drug targets within those networks of molecular interactions.

They will use a tool developed at UCSC called the Pathway Recognition Algorithm Using Data Integration of Genomic Models, or PARADIGM, which takes a pathway-centric approach to identify alterations in cellular circuitry that lead to cancer, Stuart told BioInform.

PARADIGM uses probabilistic inference to predict the degree to which a pathway’s activities are altered in a particular patient. The approach integrates different types of genomic measurements for a single patient — such as gene expression data, copy number data, and the like — in order to infer the activities of genes and products for a given pathway (BI 6/18/2012).

Stuart explained that the team will gather data on genetic pathways in prostate cancer from the public literature and combine this information into a “super pathway” that contains all the molecular interactions that occur in these tumors. The team will then use PARADIGM to explore data from patient samples in the context of this larger pathway, he said.

The UCSC bioinformatics team will also develop the MedBook application, which will connect patients, doctors, and researchers involved in the study and enable them to exchange information from their efforts and work collaboratively to discover new models of disease as well as match patients to more tailored treatments.

Inspired by social media tools like Facebook, MedBook will provide access to findings from the analysis of the collected tumor samples as well as deidentified clinical information from patients.

In addition, users will have the ability to create pages for tumor samples that will include information about things like pathway signatures, mutated genes, and properties about the cancer — such as whether it originated from a metastasis that occurred elsewhere in the body, Stuart told BioInform.

“The power of this is you can connect one sample to another … based on shared properties, so if two samples are evaluated to be molecularly similar, you can connect those together or put them in the same group” and then look for other commonalities between them, he explained.

Tools like MedBook are important for oncology, Stuart noted, because “cancer is still entrenched in these silos of research that are defined by the tissue of origin,” although at the molecular level, “some of these tumors look identical.”

Looking across the cancer spectrum, there are “themes that emerge … where we see clearly [that] 25 percent of patients with breast cancer have the same molecular fingerprint as these 30 percent we saw in ovarian cancer and they share a set of similarities with lung squamous patients,” for example. As such, therapies that have been shown to benefit one set of cancer patients might help others, he said. MedBook could be used to bring together those patient populations for clinical trials based on molecular- and pathway-level criteria.

“If you can get those communities to share results, then we might be able to borrow from each other's discoveries,” he said.

For now, MedBook will be restricted to researchers in the SU2C-PCF project, Stuart said. If it works as planned, he hopes it would be adopted and used on a larger scale within the oncology community.

“For now, what we are trying to do is come up with a pilot and build the research component of MedBook within Stand Up to Cancer,” he said. Then, that proof of concept will be put through its paces by the prostate cancer team and other teams involved in other oncology studies and then refined based on their feedback.

In addition to informatics, UCSC will handle RNA sequencing for the prostate cancer samples — an effort led by Nader Pourmand, a UCSC associate professor of biomolecular engineering.

This is UCSC’s second dream team project. It previously participated in a similar project focused on breast cancer that just wrapped up.

That project — which received around $16.5 million in funding — looked at three breast cancer subtypes — ER positive, HER2 positive, and triple negative — and focused on studying pathways of treatment resistance, building a database that integrates existing information about breast cancer, and developing less toxic treatments for the disease.

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