targeted therapies in colorectal cancer---an integrative view by pppm在结直肠癌靶向治疗u2014u2014u2014u2014由pppm综合视图.pdfVIP

targeted therapies in colorectal cancer---an integrative view by pppm在结直肠癌靶向治疗u2014u2014u2014u2014由pppm综合视图.pdf

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targeted therapies in colorectal cancer---an integrative view by pppm在结直肠癌靶向治疗u2014u2014u2014u2014由pppm综合视图

Hagan et al. The EPMA Journal 2013, 4:3 /content/4/1/3 REVIEW Open Access Targeted therapies in colorectal cancer—an integrative view by PPPM Suzanne Hagan1*, Maria C M Orr2 and Brendan Doyle3 Abstract In developed countries, colorectal cancer (CRC) is the third most common malignancy, but it is the second most frequent cause of cancer-related death. Clinicians are still faced with numerous challenges in the treatment of this disease, and future approaches which target the molecular features of the disorder will be critical for success in this disease setting. Genetic analyses of many solid tumours have shown that up to 100 protein-encoding genes are mutated. Within CRC, numerous genetic alterations have been identified in a number of pathways. Therefore, understanding the molecular pathology of CRC may present information on potential routes for treatment and may also provide valuable prognostic information. This will be particularly pertinent for molecularly targeted treatments, such as anti-vascular endothelial growth factor therapies and anti-epidermal growth factor receptor (EGFR) monoclonal antibody therapy. KRAS and BRAF mutations have been shown to predict response to anti-EGFR therapy. As EGFR can also signal via the phosphatidylinositol 3-kinase (PI3K) kinase pathway, there is considerable interest in the potential roles of members of this pathway (such as PI3K and PTEN) in predicting treatment response. Therefore, a combined approach of new techniques that allow identification of these biomarkers alongside interdisciplinary approaches to the treatment of advanced CRC will aid in the treatment decision-making process and may also serve to guide future therapeutic approaches. Keywords: Clinical decision-making process, Molecularly targeted treatment, Therapy response, Prediction, Therapy

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