title: Personalized medicine and proteomics: lessons from non-small cell lung cancer.
abstract: Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.
authors.affiliation: Respiratory Biological Sciences, AstraZeneca R&D Lund, SE-221 87 Lund, Sweden.
authors.forename: György
authors.initials: G
authors.lastname: Marko-Varga
authors.forename: Atsushi
authors.initials: A
authors.lastname: Ogiwara
authors.forename: Toshihide
authors.initials: T
authors.lastname: Nishimura
authors.forename: Takeshi
authors.initials: T
authors.lastname: Kawamura
authors.forename: Kiyonaga
authors.initials: K
authors.lastname: Fujii
authors.forename: Takao
authors.initials: T
authors.lastname: Kawakami
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Kyono
authors.forename: Hsiao-Kun
authors.initials: HK
authors.lastname: Tu
authors.forename: Hisae
authors.initials: H
authors.lastname: Anyoji
authors.forename: Mitsuhiro
authors.initials: M
authors.lastname: Kanazawa
authors.forename: Shingo
authors.initials: S
authors.lastname: Akimoto
authors.forename: Takashi
authors.initials: T
authors.lastname: Hirano
authors.forename: Masahiro
authors.initials: M
authors.lastname: Tsuboi
authors.forename: Kazuto
authors.initials: K
authors.lastname: Nishio
authors.forename: Shuji
authors.initials: S
authors.lastname: Hada
authors.forename: Haiyi
authors.initials: H
authors.lastname: Jiang
authors.forename: Masahiro
authors.initials: M
authors.lastname: Fukuoka
authors.forename: Kouichiro
authors.initials: K
authors.lastname: Nakata
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Nishiwaki
authors.forename: Hideo
authors.initials: H
authors.lastname: Kunito
authors.forename: Ian S
authors.initials: IS
authors.lastname: Peers
authors.forename: Chris G
authors.initials: CG
authors.lastname: Harbron
authors.forename: Marie C
authors.initials: MC
authors.lastname: South
authors.forename: Tim
authors.initials: T
authors.lastname: Higenbottam
authors.forename: Fredrik
authors.initials: F
authors.lastname: Nyberg
authors.forename: Shoji
authors.initials: S
authors.lastname: Kudoh
authors.forename: Harubumi
authors.initials: H
authors.lastname: Kato
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000378:metabolism*; D002289:Carcinoma, Non-Small-Cell Lung / Q000188:drug therapy / Q000378:metabolism*; D000077156:Gefitinib; D020869:Gene Expression Profiling; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy / Q000378:metabolism*; D009363:Neoplasm Proteins / Q000032:analysis*; D040901:Proteomics / Q000295:instrumentation / Q000379:methods*; D011799:Quinazolines / Q000627:therapeutic use; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D011799:Quinazolines; D000077156:Gefitinib