Platforms

Inducible Models of Human Cancer

AVEO has built a pipeline of proprietary inducible in vivo cancer models for multiple applications. Each of these tissue-specific cancer models (e.g. lung, colon, breast, etc.) is engineered to contain signature genetic mutations (e.g., HER2, EGFR, etc.) that are present in human disease. Beyond these cancer-initiating, engineered mutations, the tumors which develop in these models acquire common and distinct spontaneous mutations during tumor progression, providing additional natural genetic variation akin to the range of genetic heterogeneity encountered across different primary human tumors. Further, tumors that arise in this model have a number of differing phenotypes, including significant variation in tissue architecture and angiogenic potential.

Target Identification

This proprietary platform provides the opportunity to identify and validate functionally relevant targets since the developing tumors retain critical tumor/stromal interactions.

To exploit the inducible tumor models for target identification, AVEO has developed proprietary functional genetic screens to identify novel tumor targets. These screens are able to identify, in an unbiased fashion, gene targets that can functionally drive the growth of tumors which have been engineered to contain genetic lesions relevant to human cancer. For a variety of reasons, including the preservation of critical tumor/stromal interactions, these models provide an excellent tool for identifying cell-surface targets and secreted targets that are amenable to targeting with antibodies and other biologics.

AVEO’s MaSS Screen: Identifying functionally relevant cancer targets

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Target Validation

Candidate genes identified in AVEO’s genetic screens go through extensive validation protocols. Key validation steps include:

• Assessment of tractability based on cell surface expression or secretion
• Oncogenic loss of function in an extensive set of human cancer cell lines using siRNA
• Determination of human relevance based on publicly available and proprietary human expression, mutation and amplification data
• Examine intellectual property landscape
• Generation, characterization and testing of proof of principle antibodies in human cancer xenografts and proprietary AVEO cancer models.

Drug discovery efforts are now underway at AVEO to identify proof of principle functional antibodies against our top 10 Ab target candidates. The lead candidate, AV-299, had a clinical candidate selected in 2006 with an IND to follow near the beginning of 2008.

Human Response Prediction^TM (HRP^TM) Platform

In addition to being characterized by different genetic and phenotypic properties, tumors arising in AVEO’s cancer models display variable responsiveness to drug treatment. As a consequence, this platform provides a unique preclinical setting in which to identify genetic signatures of responsive vs. non-responsive tumor populations. Once identified, such signatures can then be applied in clinical development to formulate and test hypotheses and to enrich trials for patient populations likely to be responsive to a given therapy.

While data are still emerging, ongoing treatment experiments with taxotere provide an early example of the type of data that can be generated in AVEO’s models. Experimentally, to ensure tumor heterogeneity, multiple primary tumors are grown in a selected AVEO cancer model. After carefully controlled expansion in secondary animals to ensure minimal changes in the primary tumors, cells from this set of genetically heterogeneous tumors are re-implanted in mice and resultant tumors are treated with taxotere. Unlike in the standard xenograft setting, we see a broad array of responsiveness to taxotere treatment.

Once treatment responsiveness is determined, archived tumor samples are submitted to microarray analysis and distinct signatures of responsiveness and non-responsiveness can clearly be identified. It is postulated that because tumors from the AVEO models recapitulate the genetics of human cancer, correlation to the human condition will be possible. Experiments are now underway to correlate these preclinically-derived signatures of responsiveness with human microarray data, with an eye toward the goal of ultimately predicting responsive patient populations and guiding clinical development.

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