Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-13925
Lin, W M; Baker, A C; Beroukhim, R; Winckler, W; Feng, W; Marmion, J M; Laine, E; Greulich, H; Tseng, H; Gates, C; Hodi, F S; Dranoff, G; Sellers, W R; Thomas, R K; Meyerson, M; Golub, T R; Dummer, R; Herlyn, M; Getz, G; Garraway, L A (2008). Modeling genomic diversity and tumor dependency in malignant melanoma. Cancer Research, 68(3):664-673.
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The classification of human tumors based on molecular criteria offers tremendous clinical potential; however, discerning critical and "druggable" effectors on a large scale will also require robust experimental models reflective of tumor genomic diversity. Here, we describe a comprehensive genomic analysis of 101 melanoma short-term cultures and cell lines. Using an analytic approach designed to enrich for putative "driver" events, we show that cultured melanoma cells encompass the spectrum of significant genomic alterations present in primary tumors. When annotated according to these lesions, melanomas cluster into subgroups suggestive of distinct oncogenic mechanisms. Integrating gene expression data suggests novel candidate effector genes linked to recurrent copy gains and losses, including both phosphatase and tensin homologue (PTEN)-dependent and PTEN-independent tumor suppressor mechanisms associated with chromosome 10 deletions. Finally, sample-matched pharmacologic data show that FGFR1 mutations and extracellular signal-regulated kinase (ERK) activation may modulate sensitivity to mitogen-activated protein kinase/ERK kinase inhibitors. Genetically defined cell culture collections therefore offer a rich framework for systematic functional studies in melanoma and other tumors.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||04 Faculty of Medicine > University Hospital Zurich > Dermatology Clinic|
|DDC:||610 Medicine & health|
|Deposited On:||18 Feb 2009 16:09|
|Last Modified:||27 Nov 2013 16:41|
|Publisher:||American Association for Cancer Research|
|Citations:||Web of Science®. Times Cited: 131|
Scopus®. Citation Count: 133
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