Background: Gastroesophageal adenocarcinoma (GEC) is a significant global health problem. KEYNOTE-012 demonstrated a 22% objective response rate in patients with PD-L1 expressing GEC that received pembrolizumab. A subset of patients (pts) tumors express a T cell “inflamed” (TCI) phenotype, which can be measured using an IFN-γ-based immune signature and may prove more predictive of clinical benefit. Using a 160 gene RNA-Seq immune expression profile, we sought to characterize the molecular environments of TCI versus non-TCI GEC patients in The Cancer Genome Atlas (TCGA). Methods: 395 GEC pts with primary tumors in TCGA were clustered into TCI, non-TCI, and intermediate subtypes using both unsupervised hierarchical and K-means clustering (k = 3). Molecular characteristics were categorized using data acquired via CbioPortal and the UCSC Xena repository. Only non-silent somatic mutations and copy number variations (CNVs) reaching GISTIC2 -2 or +2 thresholds were considered. Statistical comparisons were performed using chi-square, ANOVA, and t-test. Results: The TCI subtype contained patients from all TCGA-defined subtypes - EBV-associated (56%), MSI-high (16%), chromosomal unstable (6%), and genomically stable (27%). No significant differences were seen between TCI and non-TCI for tumor site or stage. Mutations in PTEN, PIK3CA, CDH1, and RHOA were more frequent in TCI patients. ERBB2, CCNE1, and KRAS CNVs were infrequent in TCI patients as were PDE4D deletions (p< 0.05). TCI tumors had higher expression of both co-inhibitory (PD-1, PD-L1/L2, CD28/80, BTLA, LAG3) and co-stimulatory (CD137/40/27, OX40, GITR, ICOS) checkpoint molecules (p< 10^-7). Total mutation burden was no different between TCI and non-TCI pts when excluding MSI-high pts nor when assessing MSI-high alone. Conclusions: The IFN immune phenotype encompassed GEC patients from all TCGA subsets. Correlation of clinical outcome with checkpoint blockade is necessary to confirm these molecular associations and the independent predictive utility of this immune-profile stratification.