A narrative review of the evolving role of immunotherapy in the management of esophageal and gastric cancer.

J Gastrointest Oncol

Division of Medical Oncology, Department of Internal Medicine, Duke University Medical Center, Durham, NC, USA.

Published: August 2022

Background And Objective: Despite recent advances in the multidisciplinary management of esophagogastric cancer, overall prognosis remains poor. There is a need for improved treatment options, along with predictive biomarkers that improve therapeutic decision-making.

Methods: We conducted an extensive review of immunotherapy articles in the PubMed database between December 2013 and October 2021. Articles in English were included. We included phase 1, 2, and 3 clinical trials for immunotherapy review, and prospective, retrospective, and meta-analyses for biomarker review.

Key Content And Findings: Initial studies of immunotherapy were performed in patients with relapsed refractory metastatic disease and demonstrated a modest survival benefit. Subsequent studies have evaluated the use of these agents in combination with first line chemotherapy for metastatic disease. Finally, recent data indicates that immunotherapy in the adjuvant setting after concurrent chemoradiation and surgery improves disease free survival. Both microsatellite instability high (MSI-H) status and Epstein-Barr virus (EBV) positivity predict response to immunotherapy, but many patients without these biomarkers still benefit. The predictive impact of programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB) have been variable, and the optimal cutoff point for these biomarkers remains poorly defined.

Conclusions: While immunotherapy agents have demonstrated clinical benefit and are now incorporated into the current standard of care, novel immunotherapy approaches such as dual immunotherapy combinations, chimeric antigen receptor (CAR) T cells, and tumor vaccines need to be further investigated. As the era of precision medicine beckons, refined biomarkers to predict benefit are needed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459175PMC
http://dx.doi.org/10.21037/jgo-22-55DOI Listing

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