Prognostic immune markers for recurrence and survival in locally advanced esophageal adenocarcinoma.

Journal Article (Journal Article)

Treatment options and risk stratification for esophageal adenocarcinomas (EAC) currently rely on pathological criteria such as tumor staging. However, with advancement in immune modulated treatments, there is a need for accurate predictive biomarkers that will help identify high-risk patients and provide novel therapeutic targets. Hence, we analyzed as prognostic classifiers a host of histopathological parameters in conjunction with novel immune biomarkers. Specifically, gene expression levels for CXCL9, IDO1, LAG3, and TIM3 were established in treatment naïve samples. Additionally, PD-L1 and CD8 positivity was determined by immunohistochemical staining. Based on our finding, a Cox model consisting of pathological complete response (CR), LAG3, and CXCL9 provided improved predictability for disease-free survival (DFS) compared to CR alone, and it demonstrated statistical significance for predictability of recurrence (p=0.0001). Likewise, for overall survival (OS), a Cox model constituted of TIM3, CR, and IDO1 performed better than CR alone, and it demonstrated statistical significance for predictability of survival (p = 0.0004). TIM3 was identified as the best predictor for OS (HR=4.43, p=0.0023). In conclusion, given the paucity of treatment options for EAC, evaluation of these biomarkers early in the disease course will lead to better risk stratification of patients and much needed alternatives for improved therapy.

Full Text

Duke Authors

Cited Authors

  • Babar, L; Kosovec, JE; Jahangiri, V; Chowdhury, N; Zheng, P; Omstead, AN; Salvitti, MS; Smith, MA; Goel, A; Kelly, RJ; Jobe, BA; Zaidi, AH

Published Date

  • July 16, 2019

Published In

Volume / Issue

  • 10 / 44

Start / End Page

  • 4546 - 4555

PubMed ID

  • 31360303

Pubmed Central ID

  • PMC6642049

Electronic International Standard Serial Number (EISSN)

  • 1949-2553

International Standard Serial Number (ISSN)

  • 1949-2553

Digital Object Identifier (DOI)

  • 10.18632/oncotarget.27052

Language

  • eng