کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8225555 1533071 2012 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Molecular Profiling to Optimize Treatment in Non-Small Cell Lung Cancer: A Review of Potential Molecular Targets for Radiation Therapy by the Translational Research Program of the Radiation Therapy Oncology Group
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم تشعشع
پیش نمایش صفحه اول مقاله
Molecular Profiling to Optimize Treatment in Non-Small Cell Lung Cancer: A Review of Potential Molecular Targets for Radiation Therapy by the Translational Research Program of the Radiation Therapy Oncology Group
چکیده انگلیسی
Therapeutic decisions in non-small cell lung cancer (NSCLC) have been mainly based on disease stage, performance status, and co-morbidities, and rarely on histological or molecular classification. Rather than applying broad treatments to unselected patients that may result in survival increase of only weeks to months, research efforts should be, and are being, focused on identifying predictive markers for molecularly targeted therapy and determining genomic signatures that predict survival and response to specific therapies. The availability of such targeted biologics requires their use to be matched to tumors of corresponding molecular vulnerability for maximum efficacy. Molecular markers such as epidermal growth factor receptor (EGFR), K-ras, vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR), and anaplastic lymphoma kinase (ALK) represent potential parameters guide treatment decisions. Ultimately, identifying patients who will respond to specific therapies will allow optimal efficacy with minimal toxicity, which will result in more judicious and effective application of expensive targeted therapy as the new paradigm of personalized medicine develops.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Radiation Oncology*Biology*Physics - Volume 83, Issue 4, 15 July 2012, Pages e453-e464
نویسندگان
, , , , , , , , , , , , ,