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Mutations and Tumorigenesis Pathways Driving Personalized Treatment in Non-Small Cell Lung Cancer
- Source :
- Journal of Clinical & Experimental Pathology.
- Publication Year :
- 2012
- Publisher :
- OMICS Publishing Group, 2012.
-
Abstract
- There has not been a more exciting time in lung pathology than now. Because of new developments in tumor biology research and molecular pathology, the entire treatment algorithm of non small cell lung cancer has completely changed. Not too long ago, we still considered “carcinoma compatible with non small cell lung cancer” as a valid histopathologic diagnosis, good enough to start a patient on chemotherapy. Advances in pathology such as immunohistochemistry, gene expression profile, and the implementation of laboratory techniques like polymerase chain reaction, fluorescent in situ hybridization, and others have moved forward this field not only to identify a more accurate classification of this disease but also to identify new tumorigenesis pathways or active mutations which could serve as biomarkers with predictive and/or prognostic power to tailor our therapeutic agents. The fact that pathologists can accurately determine tumor histology as an adenocarcinoma or squamous cell carcinoma has a tremendous impact in the treatment selection. To date, the histologic subtype of non small cell lung cancer is the first step in customization of lung cancer therapy allowing us to choose among several chemotherapeutic agents. However, tumor biology has shown to be a stronger tool to personalized medicine, and pathology plays a crucial role in developing and improving these novel techniques. In this article, we will review the well established and most promising gene abnormalities as well as upregulated pathways recently found in lung cancer patients with the goal to use them to better classify these tumors and to identify new treatments for this disease.
Details
- ISSN :
- 21610681
- Database :
- OpenAIRE
- Journal :
- Journal of Clinical & Experimental Pathology
- Accession number :
- edsair.doi...........dd6902a6f5051d534bd0a100b498c45a
- Full Text :
- https://doi.org/10.4172/2161-0681.s5-002