Differential immune profiles distinguish the mutational subtypes of gastrointestinal stromal tumor
Gerardo A. Vitiello, … , Shan Zeng, Ronald P. DeMatteo
Gerardo A. Vitiello, … , Shan Zeng, Ronald P. DeMatteo
Published February 14, 2019
Citation Information: J Clin Invest. 2019;129(5):1863-1877. https://doi.org/10.1172/JCI124108.
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Research Article Immunology Oncology

Differential immune profiles distinguish the mutational subtypes of gastrointestinal stromal tumor

Abstract

Gastrointestinal stromal tumor (GIST) is the most common human sarcoma, frequently characterized by an oncogenic mutation in the KIT or PDGFRA gene. We performed RNA sequencing of 75 human GIST tumors from 75 patients, comprising what we believe to be the largest cohort of GISTs sequenced to date, in order to discover differences in the immune infiltrates of KIT- and PDGFRA-mutant GIST. Through bioinformatics, immunohistochemistry, and flow cytometry, we found that in PDGFRA-mutant GISTs, immune cells were more numerous and had higher cytolytic activity than in KIT-mutant GISTs. PDGFRA-mutant GISTs expressed many chemokines, such as CXCL14, at a significantly higher level when compared with KIT-mutant GISTs and exhibited more diverse driver-derived neoepitope:HLA binding, both of which may contribute to PDGFRA-mutant GIST immunogenicity. Through machine learning, we generated gene expression–based immune profiles capable of differentiating KIT- and PDGFRA-mutant GISTs, and identified additional immune features of high–PD-1– and –PD-L1–expressing tumors across all GIST mutational subtypes, which may provide insight into immunotherapeutic opportunities and limitations in GIST.

Authors

Gerardo A. Vitiello, Timothy G. Bowler, Mengyuan Liu, Benjamin D. Medina, Jennifer Q. Zhang, Nesteene J. Param, Jennifer K. Loo, Rachel L. Goldfeder, Frederic Chibon, Ferdinand Rossi, Shan Zeng, Ronald P. DeMatteo

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Figure 5

PDGFRA mutation produces multiple HLA-diverse, strong binding neoepitopes.

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PDGFRA mutation produces multiple HLA-diverse, strong binding neoepitop...
(A) Pearson’s correlation of ESTIMATE (top) and CYT (bottom) scores with total neoepitope burden (left), number of high-affinity neoepitopes (middle), and number of very high-affinity neoepitopes (right) among all GIST samples (n = 75). (B) Left: Percentage of patients with the indicated mutation whose mutation produced a predicted high-affinity neoepitope. Right: Number of potential neoepitope:HLA binding events produced by mutation type, averaged over the number of mutations per group. (C) Heatmap of the binding affinities of KIT and PDGFRA mutation–specific neoepitopes to all validated NetMHCPan 3.0 HLA types. Clinicopathologic characteristics of the GIST specimens are shown in Supplemental Table 3. Additional details regarding mutations, neoepitopes, and HLA types used to create this heatmap are shown in Supplemental Tables 6 and 7.