Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/85264
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDuong, Hong Quan-
dc.date.accessioned2023-02-10T01:17:15Z-
dc.date.available2023-02-10T01:17:15Z-
dc.date.issued2020-
dc.identifier.issn2615-9023-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/85264-
dc.description.abstractLung cancer is the most common cause of cancer death worldwide, with most deaths having distant metastases. It has become increasingly complex to get effective treatment for lung cancer patients. While generalized medicine with traditional therapy resulted in comparatively poor response, personalized medicine has been well known to be an important strategy for effective treatment of lung cancer, with current focus on significant detection of clinical oncogenic drivers responsible for tumor initiation and maintenance and development of drug resistance. In lung cancer, especially in non-small-cell lung cancer (NSCLC), EGFR, ALK,RET, ROS1, BRAF,KRAS, NRAS, PIK3CA, DDR2, MET, ERBB2 have been reported to be key oncogenic drivers, which are targeted in the development and application of targeted therapeutic drugs. Personalized medicine based on these oncogenic drivers is highly recommended for treatment of advanced NSCLC patients. In this article, the significant application of personalized medicine based on the key oncogenic drivers for effective treatment of NSCLC with targeted therapeutic drugs is reviewed.vi_VN
dc.language.isoenvi_VN
dc.relation.ispartofseriesAcademia journal of biology;Vol.42, No.03 .- P.119-133-
dc.subjectPersonalized medicinevi_VN
dc.subjectTargeted therapyvi_VN
dc.subjectNon-small-cell lung cancervi_VN
dc.subjectTreatmentvi_VN
dc.titlePersonalized medicine for effective treatment of non-small-cell lung cancer with targeted therapiesvi_VN
dc.typeArticlevi_VN
Appears in Collections:Academia journal of biology

Files in This Item:
File Description SizeFormat 
_file_
  Restricted Access
3.63 MBAdobe PDF
Your IP: 18.222.161.57


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.