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Checkpoint inhibition in advanced gastroesophageal cancer: clinical trial data, molecular subtyping, predictive biomarkers, and the potential of combination therapies.

ABSTRACT: The development of checkpoint inhibitors has redefined the treatment paradigm for advanced gastroesophageal cancer. While recent developments have improved clinical outcomes, the prognosis for the disease remains meager. In this review, we discuss the rationale and detail the results from recent phase I-III trials supporting the activity of PD-1 inhibitors. Specifically, we highlight the seminal clinical trials leading to the FDA approval of pembrolizumab for advanced gastroesophageal cancer. Finally, we review the current understanding and future considerations of molecular subtyping and predictive biomarkers to help guide therapy and the promise of combination therapy to further improve the efficacy of checkpoint inhibitors.

SUBMITTER: Chuang J

PROVIDER: S-EPMC6737389 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Checkpoint inhibition in advanced gastroesophageal cancer: clinical trial data, molecular subtyping, predictive biomarkers, and the potential of combination therapies.

Chuang Jeremy J Chao Joseph J Hendifar Andrew A Klempner Samuel J SJ Gong Jun J

Translational gastroenterology and hepatology 20190827

The development of checkpoint inhibitors has redefined the treatment paradigm for advanced gastroesophageal cancer. While recent developments have improved clinical outcomes, the prognosis for the disease remains meager. In this review, we discuss the rationale and detail the results from recent phase I-III trials supporting the activity of PD-1 inhibitors. Specifically, we highlight the seminal clinical trials leading to the FDA approval of pembrolizumab for advanced gastroesophageal cancer. Fi ...[more]

PMID: 31559344

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Project description:BackgroundBased on molecular biomarkers, anti-angiogenic drugs in combination with programmed cell death protein 1 (PD-1) antibodies can screen the potentially beneficial populations with hepatocellular carcinoma (HCC) and predict the efficacy after treatment. Therefore, we aimed to study predictive molecular biomarkers to improve the effectiveness of immuno-targeted combination therapy for HCC.Patients and methodsBaseline clinical data, blood samples, and imaging data of the first evaluation after two cycles of treatment were collected for 40 patients with advanced HCC who underwent combination therapy, and then these data were compared according to the efficacy. Since 15 patients had complete hematology samples, we additionally tested the T lymphocyte subpopulations of these 15 patients and also compared them according to the efficacy. In addition, we also selected five patients who benefited the most from the combination therapy and five patients with the worst curative effect for gene detection based on survival time and efficacy evaluation. Finally, the relationship between certain clinical characteristics, laboratory indicators, specific T lymphocyte subpopulations, gene mutations and the response of immuno-targeted combination therapy for HCC was evaluated.ResultsThe high levels of CD3+CD4+CD279+, CD3+CD8+CD45RO+CD62L+T lymphocytes and tumor mutational burden (TMB) were associated with good efficacy of the combination therapy (P=0.03, P<0.01 and P=0.03). The high levels of CD3+CD4+CD28+ T lymphocytes were associated with poor efficacy of the combination therapy (P=0.02). The high mutation frequency of TP53 and ARID1A appeared in the non-response cohort. In addition, amplification mutation of 11q13-CCND1, FGF3, FGF4, and FGF19 was found in a patient with hyperprogression (HP).ConclusionsThe certain clinical characteristics, laboratory indicators, specific T lymphocyte subpopulations, and gene mutations established in this paper were potential predictive biomarkers for HCC patients treated with combination therapy.

Dataset Information

Checkpoint inhibition in advanced gastroesophageal cancer: clinical trial data, molecular subtyping, predictive biomarkers, and the potential of combination therapies.

Publications

Checkpoint inhibition in advanced gastroesophageal cancer: clinical trial data, molecular subtyping, predictive biomarkers, and the potential of combination therapies.

Similar Datasets

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