Oncotarget

Research Papers:

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

Laila Babar, Juliann E. Kosovec, Vida Jahangiri, Nobel Chowdhury, Ping Zheng, Ashten N. Omstead, Madison S. Salvitti, Matthew A. Smith, Ajay Goel, Ronan J. Kelly, Blair A. Jobe and Ali H. Zaidi

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Oncotarget. 2019; 10:4546-4555. https://doi.org/10.18632/oncotarget.27052

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Abstract

Laila Babar1, Juliann E. Kosovec1, Vida Jahangiri1, Nobel Chowdhury1, Ping Zheng1, Ashten N. Omstead1, Madison S. Salvitti1, Matthew A. Smith1, Ajay Goel2, Ronan J. Kelly3, Blair A. Jobe1 and Ali H. Zaidi1

1 Esophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA

2 Beckman Research Institute, City of Hope Comprehensive Cancer Center, Monrovia, CA, USA

3 Department of Hematology and Oncology, Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX, USA

Correspondence to:

Ali H. Zaidi,email: Ali.Zaidi@ahn.org

Keywords: esophageal adenocarcinoma; LAG3; IDO1; CXCL9; TIM3

Received: April 03, 2019     Accepted: June 14, 2019     Published: July 16, 2019

ABSTRACT

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.


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