Abstract
Recent advances in our understanding of cancer biology have led to the development of therapies targeting specific signaling pathways. Molecular targeting promises to improve our ability to predict who will respond by assessing the state of these targeted pathways in patients. However, a single pathway can be deregulated by multiple mechanisms, and for some pathways it may be difficult to assess activation state by analyzing a single oncogene or tumor suppressor. Therefore, developing gene expression signatures of pathway activation status using model systems or human tumor samples may enable a more reliable measurement of pathway activity. This review discusses recent advances in the identification of gene expression-based signatures of pathway deregulation and how this information may lead to improved therapeutic response prediction.
MeSH terms
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Animals
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Antineoplastic Agents / pharmacology
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Breast Neoplasms / metabolism
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Cluster Analysis
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Drug Evaluation, Preclinical
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Female
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Gene Expression Profiling*
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Humans
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Lung Neoplasms / metabolism
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Mice
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Neoplasms / diagnosis
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Neoplasms / drug therapy
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Neoplasms / metabolism*
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Neoplasms, Experimental / drug therapy
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Neoplasms, Experimental / metabolism
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Prognosis
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Proto-Oncogene Proteins / biosynthesis
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Proto-Oncogene Proteins / genetics
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Proto-Oncogene Proteins p21(ras) / biosynthesis
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Proto-Oncogene Proteins p21(ras) / genetics
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Signal Transduction*
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Tumor Cells, Cultured
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Tumor Suppressor Protein p53 / genetics
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Tumor Suppressor Protein p53 / physiology
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ras Proteins
Substances
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Antineoplastic Agents
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KRAS protein, human
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Proto-Oncogene Proteins
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TP53 protein, human
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Tumor Suppressor Protein p53
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Hras protein, mouse
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Proto-Oncogene Proteins p21(ras)
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ras Proteins