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At Network Bio Conference, Speakers Highlight Role of Molecular Methods in Unraveling Cancer's Complexity

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By Vivien Marx

CAMBRIDGE, Mass. — Cancer is a notoriously complex disease, but molecular methods and new approaches such as network modeling are helping to tease apart the mechanisms of the disease, according to speakers at a conference held here this week

At the Network Biology 2.0 conference, speakers underscored the degree to which the understanding of cancer is being empowered by molecular characterization projects and is accompanied by desire to select the right populations for clinical trials.

For example, William Sellers, vice president and global head of oncology research at Novartis Institutes for Biomedical Research, cited the use of molecular methods to enable the "rapid development" of Gleevec, and said that model is "one we hope to achieve over and over again."

He noted that the lack of robust methods to develop pre-clinical hypotheses has hampered drug discovery. In response, he and his colleagues are creating a "systematic collection of cancer models" that can be annotated in respect to various datasets, such as expression data, copy number variation, and other mutation data in order to align the models with the type of cancer being studied.

In addition, NIBR, the Broad Institute, and the Genomics Institute of the Novartis Research Foundation have launched the Cancer Cell Line Encyclopedia Project, which aims to molecularly characterize and perform compound profiling on 1,000 cell lines.

The goal is to profile these cell lines in an automated fashion and to develop informatics methods to build predictive algorithms, Sellers said.

The encyclopedia will be made public in late April or early May, he said. The publicly available version will not include any Novartis compound data, but will include information on 28 compounds in the public domain, as well as all the mutation data, SNP array data, mutation data, and expression data.

In another discussion, researchers highlighted the role that molecular tools have played in enabling increased granularity and segmentation in clinical trials.

W. Michael Korn, co-director of the Center for Molecular Oncology at the Helen Diller Family Comprehensive Cancer Center at the University of California, San Francisco, said that at this point most doctors are only aware of "driver mutations in a few subtypes of cancers." He added that network models should help elucidate how pathways function and should help identify subgroups.

Korn said the mathematical approach might help scientists "find a shortcut" to a drug with a higher probability of response, but he and other speakers pointed out that pathways are not "like a linear diagram," but rather there is "pathway cross talk and feedback loops," all of which can have a "profound" impact on a targeted therapy.

Korn told BioInform that pharmaceutical firms are realizing the value of -omics data, and have an increased willingness to go after smaller patient populations.

Sandra Silberman, vice president of oncology and drug development partnerships and innovation at contract research organization Quintiles, agreed that industry is shifting its approach to drug development in order to integrate more -omics knowledge, but she noted that the application of network biology might have more success outside of pharmaceutical firms.

Pharma is now more "open minded" about network biology approaches, but financial concerns have been a barrier, she said.

She believes a firm like Quintiles can "take the risk" more readily than pharma can by forging partnerships with vendors and validating technologies such as network modeling.

The Network Biology 2.0 conference was sponsored by the Broad Institute, Boston Area Systems and Synthetic Biology, and Gene Network Sciences.

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