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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
3
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pubmed:dateCreated |
2010-8-5
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pubmed:abstractText |
The recently developed ability to interrogate genome-wide data arrays has provided invaluable insights into the molecular pathogenesis of lung cancer. These data have also provided information for developing targeted therapy in lung cancer patients based on the identification of cancer-specific vulnerabilities and set the stage for molecular biomarkers that provide information on clinical outcome and response to treatment. In addition, there are now large panels of lung cancer cell lines, both non-small-cell lung cancer and small-cell lung cancer, that have distinct chemotherapy and radiation response phenotypes. We anticipate that the integration of molecular data with therapy response data will allow for the generation of biomarker signatures that predict response to therapy. These signatures will need to be validated in clinical studies, at first retrospective analyses and then prospective clinical trials, to show that the use of these biomarkers can aid in predicting patient outcomes (eg, in the case of radiation therapy for local control and survival). This review highlights recent advances in molecular profiling of tumor responses to radiotherapy and identifies challenges and opportunities in developing molecular biomarker signatures for predicting radiation response for individual patients with lung cancer.
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pubmed:grant |
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-10700174,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-11358816,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-12509763,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-15057290,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-16103067,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-17339364,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-17409807,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-17905465,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-18440087,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-18579254,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-19706816,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-19735874,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-19825801,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-2539297,
http://linkedlifedata.com/resource/pubmed/commentcorrection/20685577-6303568
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:chemical |
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pubmed:status |
MEDLINE
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pubmed:month |
Jul
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pubmed:issn |
1532-9461
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pubmed:author |
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pubmed:copyrightInfo |
Copyright 2010 Elsevier Inc. All rights reserved.
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pubmed:issnType |
Electronic
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pubmed:volume |
20
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
149-55
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pubmed:dateRevised |
2011-9-26
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pubmed:meshHeading |
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pubmed:year |
2010
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pubmed:articleTitle |
Radiogenomics predicting tumor responses to radiotherapy in lung cancer.
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pubmed:affiliation |
The University of Texas Southwestern Medical Center, The Hamon Center for Therapeutic Oncology Research, Dallas, TX 75390-8593, USA. amit.das@utsouthwestern.edu
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Review,
Research Support, N.I.H., Extramural
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