TY - JOUR
T1 - Towards elucidation of functional molecular signatures of the adhesive-migratory phenotype of malignant cells
AU - Geiger, Tamar
AU - Geiger, Benjamin
N1 - Funding Information:
The authors’ work was partially supported by a grant from the Israel Science Foundation, by a Weizmann Institute of Science – Mario Negri Institute grant, and by the Yad Abraham Center for Cancer Diagnostics and Therapy. T.G. is supported by a fellowship from the Humboldt Foundation. B.G. is the incumbent of the Erwin Neter Professorial Chair in Cell and Tumor Biology. The authors wish to thank Barbara Morgenstern for editorial assistance.
PY - 2010/6
Y1 - 2010/6
N2 - Over the years, malignant transformation has been investigated on multiple levels, ranging from clinical pathology to the underlying molecular mechanisms. In "zooming in" on this process, cancer biologists have focused their attention on the molecular and cellular manifestations of the "transformed phenotype", including the genomic instability of cancer cells, their deregulated transcriptional activity, their aberrant morphology and dynamics, and the altered signaling networks activated in them. Attempts to elucidate the mechanisms underlying malignant and metastatic transformation are primarily motivated by the desire to identify specific molecules and signaling pathways that can serve as targets for novel therapies. In recent years, such studies were reinforced by major technological and conceptual developments: novel and powerful tools for genomic and proteomic analysis have been developed, and advanced computational approaches offer "systems-level" integration of rich and complex biological datasets into meaningful functional networks. In this article, we consider the current and potential impact of these new experimental approaches and, in particular, the recent progress made in quantitative proteomics, to elucidate the mechanisms underlying the "transformed phenotype" We will primarily focus on the adhesion and migration of cancer cells, and their relationships to the deregulated growth, metastatic dissemination, and anchorage independence associated with malignant transformation.
AB - Over the years, malignant transformation has been investigated on multiple levels, ranging from clinical pathology to the underlying molecular mechanisms. In "zooming in" on this process, cancer biologists have focused their attention on the molecular and cellular manifestations of the "transformed phenotype", including the genomic instability of cancer cells, their deregulated transcriptional activity, their aberrant morphology and dynamics, and the altered signaling networks activated in them. Attempts to elucidate the mechanisms underlying malignant and metastatic transformation are primarily motivated by the desire to identify specific molecules and signaling pathways that can serve as targets for novel therapies. In recent years, such studies were reinforced by major technological and conceptual developments: novel and powerful tools for genomic and proteomic analysis have been developed, and advanced computational approaches offer "systems-level" integration of rich and complex biological datasets into meaningful functional networks. In this article, we consider the current and potential impact of these new experimental approaches and, in particular, the recent progress made in quantitative proteomics, to elucidate the mechanisms underlying the "transformed phenotype" We will primarily focus on the adhesion and migration of cancer cells, and their relationships to the deregulated growth, metastatic dissemination, and anchorage independence associated with malignant transformation.
KW - Cell adhesion
KW - Cell migration
KW - Functional proteomics
KW - Genomic analysis
KW - Transformed phenotype
UR - http://www.scopus.com/inward/record.url?scp=77956615361&partnerID=8YFLogxK
U2 - 10.1016/j.semcancer.2010.05.004
DO - 10.1016/j.semcancer.2010.05.004
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C2 - 20493263
AN - SCOPUS:77956615361
SN - 1044-579X
VL - 20
SP - 146
EP - 152
JO - Seminars in Cancer Biology
JF - Seminars in Cancer Biology
IS - 3
ER -