Elise Nassif

Objective: The vast majority of gastrointestinal stromal tumors (GISTs) are driven by activating mutations in KIT, PDGFRA, or components of the succinate dehydrogenase (SDH) complex (SDHA, SDHB, SDHC, and SDHD genes). A small fraction of GISTs lack alterations in KIT, PDGFRA, and SDH. We aimed to further characterize the clinical and genomic characteristics of these so-called “triple-negative” GISTs. Methods: We extracted clinical and genomic data from patients seen at MD Anderson Cancer Center with a diagnosis of GIST and available clinical next generation sequencing data to identify “triple-negative” patients. Results: Of the 20 patients identified, 11 (55.0%) had gastric, 8 (40.0%) had small intestinal, and 1 (5.0%) had rectal primary sites. In total, 18 patients (90.0%) eventually developed recurrent or metastatic disease, and 8 of these presented with de novo metastatic disease. For the 13 patients with evaluable response to imatinib (e.g., neoadjuvant treatment or for recurrent/metastatic disease), the median PFS with imatinib was 4.4 months (range 0.5–191.8 months). Outcomes varied widely, as some patients rapidly developed progressive disease while others had more indolent disease. Regarding potential genomic drivers, four patients were found to have alterations in the RAS/RAF/MAPK pathway: two with a BRAF V600E mutation and two with NF1 loss-of-function (LOF) mutations (one deletion and one splice site mutation). In addition, we identified two with TP53 LOF mutations, one with NTRK3 fusion (ETV6-NTRK3), one with PTEN deletion, one with FGFR1 gain-of-function (GOF) mutation (K654E), one with CHEK2 LOF mutation (T367fs*), one with Aurora kinase A fusion (AURKA-CSTF1), and one with FANCA deletion. Patients had better responses with molecularly targeted therapies than with imatinib. Conclusions: Triple-negative GISTs comprise a diverse cohort with different driver mutations. Compared to KIT/PDGFRA-mutant GIST, limited benefit was observed with imatinib in triple-negative GIST. In depth molecular profiling can be helpful in identifying driver mutations and guiding therapy.