Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy
The NGS method successfully maps the mutational landscape of GC, providing a practical TCGA classification surrogate to optimize patient-specific treatment strategies.
Authors
- Matthew R. Strickland (ORCID: https://orcid.org/0000-0001-7845-0712)
- Bei Zhang (ORCID: https://orcid.org/0000-0003-1852-5844)
- Peng-Da Guo
- Fabrício Freire de Melo (ORCID: https://orcid.org/0000-0002-5680-2753)
- Min Huang (ORCID: https://orcid.org/0000-0003-1960-4552)
- Jinping Cai
- Yang Yang (ORCID: https://orcid.org/0000-0002-1090-3065)
- Biao Liu (ORCID: https://orcid.org/0000-0001-8310-7732)
- Yu Zhang (ORCID: https://orcid.org/0009-0009-4844-3867)
- Lu Wang (ORCID: https://orcid.org/0000-0003-1535-8411)
Institutions
- Universidade Federal da Bahia (BR)
- Harvard University (US)
- Massachusetts General Hospital (US)
- Suzhou Municipal Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Journal of Gastrointestinal Oncology
- Published
- 2024-09-23
- DOI
- https://doi.org/10.21037/jgo-24-345
- Citations
- 4
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 1.68