Chapter title |
Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic Analysis of Oncogenic Mutations.
|
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Chapter number | 8 |
Book title |
Proteogenomics
|
Published in |
Advances in experimental medicine and biology, September 2016
|
DOI | 10.1007/978-3-319-42316-6_8 |
Pubmed ID | |
Book ISBNs |
978-3-31-942314-2, 978-3-31-942316-6
|
Authors |
Toshihide Nishimura, Haruhiko Nakamura, Nishimura, Toshihide, Nakamura, Haruhiko |
Editors |
Ákos Végvári |
Abstract |
Molecular therapies targeting lung cancers with mutated epidermal growth factor receptor (EGFR) by EGFR-tyrosin kinase inhibitors (EGFR-TKIs), gefitinib and erlotinib, changed the treatment system of lung cancer. It was revealed that drug efficacy differs by race (e.g., Caucasians vs. Asians) due to oncogenic driver mutations specific to each race, exemplified by gefitinib / erlotinib. The molecular target drugs for lung cancer with anaplastic lymphoma kinase (ALK) gene translocation (the fusion gene, EML4-ALK) was approved, and those targeting lung cancers addicted ROS1, RET, and HER2 have been under development. Both identification and quantification of gatekeeper mutations need to be performed using lung cancer tissue specimens obtained from patients to improve the treatment for lung cancer patients: (1) identification and quantitation data of targeted mutated proteins, including investigation of mutation heterogeneity within a tissue; (2) exploratory mass spectrometry (MS)-based clinical proteogenomic analysis of mutated proteins; and also importantly (3) analysis of dynamic protein-protein interaction (PPI) networks of proteins significantly related to a subgroup of patients with lung cancer not only with good efficacy but also with acquired resistance. MS-based proteogenomics is a promising approach to directly capture mutated and fusion proteins expressed in a clinical sample. Technological developments are further expected, which will provide a powerful solution for the stratification of patients and drug discovery (Precision Medicine). |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 15 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 3 | 20% |
Student > Ph. D. Student | 2 | 13% |
Other | 1 | 7% |
Professor | 1 | 7% |
Student > Doctoral Student | 1 | 7% |
Other | 2 | 13% |
Unknown | 5 | 33% |
Readers by discipline | Count | As % |
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Computer Science | 3 | 20% |
Biochemistry, Genetics and Molecular Biology | 3 | 20% |
Medicine and Dentistry | 2 | 13% |
Economics, Econometrics and Finance | 1 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
Other | 0 | 0% |
Unknown | 5 | 33% |