Current status of clinical proteogenomics in lung cancer. (2nd September 2019)

• Record Type: Journal Article
• Authors: Nishimura, Toshihide; Nakamura, Haruhiko; Végvári, Ákos; Marko-Varga, György; Furuya, Naoki; Saji, Hisashi
• Is Part Of: Expert review of proteomics. Volume 16:Number 9(2019)
• Page Start: 761
• Page End: 772
• Publication Date: 2019-09-02
• Subjects: Lung cancer -- clinical proteogenomics -- next generation sequencing -- proteomics⋅mass -- spectrometry -- mutant identification -- network-based bioinformatics; Proteins -- Biotechnology -- Periodicals; Proteomics -- Periodicals; 572.6
• DOI: 10.1080/14789450.2019.1654861
• Languages: English
• ISSNs: 1478-9450

Abstract

ABSTRACT: Introduction : Lung cancer is the leading cause of cancer death worldwide. Proteogenomics, a way to integrate genomics, transcriptomics, and proteomics, have emerged as a way to understand molecular causes in cancer tumorigenesis. This understanding will help identify therapeutic targets that are urgently needed to improve individual patient outcomes. Areas covered : To explore underlying molecular mechanisms of lung cancer subtypes, several efforts have used proteogenomic approaches that integrate next generation sequencing (NGS) and mass spectrometry (MS)-based technologies. Expert opinion : A large-scale, MS-based, proteomic analysis, together with both NGS-based genomic data and clinicopathological information, will facilitate establishing extensive databases for lung cancer subtypes that can be used for further proteogenomic analyzes. Proteogenomic strategies will further be understanding of how major driver mutations affect downstream molecular networks, resulting in lung cancer progression and malignancy, and how therapy-resistant cancers resistant are molecularly structured. These strategies require advanced bioinformatics based on a dynamic theory of network systems, rather than statistics, to accurately identify mutant proteins and their affected key networks.