Modeling Cancer as a Stem-Cell Disease: Clinical and Biological Applications of the 'Cancer Stem Cell' Theory

12:00pm-1:00pm PT
Broad CIRM Center Seminar Room, 1425 San Pablo St.

"Modeling Cancer as a Stem-Cell Disease: Clinical and Biological Applications of the 'Cancer Stem Cell' Theory"

presented by

Piero Dalerba, M.D., S

tanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford University

Tuesday, February 5
12 noon

Broad CIRM Center Seminar Room
Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC
1425 San Pablo Street

Hosted by Henry Sucov, Ph.D.

According to the "cancer stem cell" model, tumors can be envisioned as “pathological organs”, whose architecture and cell composition often mirror, though in a distorted way, that of their corresponding normal counterparts. Indeed, increasing experimental evidence indicates that epithelial cancer tissues can be organized according to a hierarchical structure akin to a stem cell system, where: a) cancer cells retain the capacity to diversify according to a multi-lineage differentiation process; and b) long-term tissue growth is sustained by a pathological population of stem-like cells (i.e. the “cancer stem cells”). To explore these concepts, and discover novel markers of both normal stem cells and "cancer stem cells", we developed a novel analytical platform based on single-cell gene-expression PCR (SINCE-PCR), which allows to take, in a single experiment, a “panoramic snapshot” of the cell composition of a tissue, and to rapidly identify minority populations with special gene-expression properties, such as stem cells. Analysis by SINCE-PCR of cell composition in colon and breast epithelial tissues, both normal and neoplastic, led to the discovery of novel epithelial populations and of novel markers to differentially label them, and provided formal proof of multi-lineage differentiation as a source of cellular diversity in cancer. Most remarkably, using SINCE-PCR results as guide, we identified novel powerful prognostic and predictive bio-markers for breast and colon cancer patients, able to predict differential patient responses to several anti-tumor therapies. 

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