Identifying Secondary Mutations in Chinese Patients with Imatinib-Resistant Gastrointestinal Stromal Tumors (GISTs) by Next Generation Sequencing (NGS)

The aim of this study was to characterize secondary kinase mutations in Chinese patients with imatinib-resistant gastrointestinal stromal tumors (GISTs). Mutations in receptor tyrosine kinase (KIT; exons 9, 11, 13, 14, 17, and 18) and platelet-derived growth factor-alpha (PDGFRA; exons 12, 14, and 18) were analyzed by direct sequencing. After imatinib treatment, 425 cancer-related target genes were analyzed by next generation sequencing (NGS) in imatinib-resistant patients. Correlation of sequencing results with clinicopathologic features were analyzed. We identified 320 patients with secondary acquired resistance. We determined that 65.63% (210/320) of resistant patients had secondary KIT mutations in exon 13 (n = 134), exon 14 (n = 10), or exon 17 (n = 66), and 4.38% (14/320) had additional PDGFRA mutations in exon 14 (n = 3) or exon 18 (n = 11). All secondary KIT mutations were missense mutations and were mostly located in kinase domains. Ninety-six imatinib-resistant GIST patients did not have secondary KIT or PDGFRA mutations. Common independent mutation events were found in retinoblastoma protein 1 (RB1) (18/96 cases), SWI/SNF-related matrix associated actin-dependent regulator of chromatin subfamily B member 1 (SMARCB1) (16/96 cases), and myc-associated factor X (MAX) (10/96 cases). RB1 or SMARCB1 mutations coexisted with activation of other oncogenes in 6 or 15 cases, respectively. Multiple mutations were also seen in cases with MAX mutations. These mutations are frequently associated with clinicopathological factors. Secondary mutations of KIT/PDGFRA were the most important contributors in GISTs developing resistance to imatinib treatment. Additional genetic events including RB1, SMARCB1, and MAX except secondary KIT/PDGFRA mutations are the most common for GISTs to evolve into resistant disease. Clinical assessment of the effect of these mutations may benefit existing risk assessment models and selection of adjuvant therapies in GIST patients.