Signaling pathways in breast cancer metastasis - novel insights from functional genomics.

Mario Andres Blanco; Yibin Kang

doi:10.1186/bcr2831

Signaling pathways in breast cancer metastasis - novel insights from functional genomics.

Mario Andres Blanco, Yibin Kang

Research output: Contribution to journal › Review article › peer-review

41 Scopus citations

Abstract

The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases.

Original language	English (US)
Pages (from-to)	206
Number of pages	1
Journal	Breast cancer research : BCR
Volume	13
Issue number	2
DOIs	https://doi.org/10.1186/bcr2831
State	Published - 2011

All Science Journal Classification (ASJC) codes

Oncology
Cancer Research

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10.1186/bcr2831

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title = "Signaling pathways in breast cancer metastasis - novel insights from functional genomics.",

abstract = "The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases.",

author = "Blanco, {Mario Andres} and Yibin Kang",

note = "Funding Information: We apologize to the authors of many excellent studies whose works we could not cite due to space limitations. Funding support of this work includes an NRSA pre-doctoral fellowship from the National Institutes of Health (to MAB) and grants from Champalimaud Foundation, Brewster Foundation, DOD (BC051647), and NIH (5R01CA134519 and 1R01CA141062) (to YK).",

year = "2011",

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T1 - Signaling pathways in breast cancer metastasis - novel insights from functional genomics.

AU - Blanco, Mario Andres

AU - Kang, Yibin

N1 - Funding Information: We apologize to the authors of many excellent studies whose works we could not cite due to space limitations. Funding support of this work includes an NRSA pre-doctoral fellowship from the National Institutes of Health (to MAB) and grants from Champalimaud Foundation, Brewster Foundation, DOD (BC051647), and NIH (5R01CA134519 and 1R01CA141062) (to YK).

PY - 2011

Y1 - 2011

N2 - The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases.

AB - The advent of genomic profiling technology has brought about revolutionary changes in our understanding of breast cancer metastasis. Gene expression analyses of primary tumors have been used to predict metastatic propensity with high accuracy. Animal models of metastasis additionally offer a platform to experimentally dissect components of the metastasis genetic program. Recent integrated studies have synergized clinical bioinformatic analyses with advanced experimental methodology and begun to uncover the identities and dynamics of signaling programs driving breast cancer metastasis. Such functional genomics studies hold great promise for understanding the genetic basis of metastasis and improving therapeutics for advanced diseases.

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Signaling pathways in breast cancer metastasis - novel insights from functional genomics.

Abstract

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