Background: Treatment options and risk stratification for esophageal adenocarcinomas (EAC) primarily rely on clinical and pathological criteria, such as tumor stage and pathological response (PR) evaluation. However, with immunotherapy showing hints of activity in EAC there is an emerging need to develop new predictive biomarkers that will not only identify high-risk patients but also unlock novel therapeutic strategies. The aim of this study was to evaluate if LAG3, TIM3, IDO and CXCL9 gene expression along with pathological classifiers correlate with recurrence and/or death in EAC. Methods: Clinical and histopathology data on 49 resectable EAC patients was captured. Mean age at diagnosis was 64.2 years with a median follow up of 21.2 months. Laser capture microdissection followed by qRT-PCR was performed on pretreatment FFPE samples to quantify LAG3, TIM3, IDO and CXCL9 gene levels. Statistical tools established individual biomarker cutoffs and these were correlated with clinical outcomes. Results: For disease free survival, a best fit Cox model was generated consisting of PR (HR=9.54, 95% CI = 2.13 ~ 42.62, p = .003), LAG3 (HR = 2.86, 95% CI = 1.03 ~ 7.94, p = .044), and CXCL9 (HR = 0.40, 95% CI = 0.16 ~ 0.99, p = .049). Moreover, the classification performance of the 3 predictor Cox model was deemed superior to PR alone; P = 0.0001 (Likelihood Ratio Test (LRT)) indicated strong significance in predictability with the recurrence model. For overall survival, a best fit Cox model was generated consisting of TIM3 (HR = 4.43, 95% CI= 1.70 ~ 11.5, p = .002) PR (HR = 3.09, 95% CI= 1.00 ~ 9.56, p = .051) and IDO (HR = 0.31, 95% CI = 0.11 ~ 0.82, p = .019). Likewise, the classification performance of the 3 predictor Cox model was deemed superior to PR alone; P = 0.0004 (LRT) indicated strong significance in predictability with the survival model. Conclusions: LAG3, TIM3, IDO and CXCL9 expression in conjunction with PR to neoadjuvant therapy provide superior tools to predict recurrence and death in locally advanced EAC patients. Additionally, given the paucity of treatment options for esophageal cancer we must check for these markers early on in the disease course to better risk stratify patients and provide newer targets for novel treatments.