Proteomic Characterization of the Gastric Cancer Response to Chemo- and Targeted therapies Reveals Axis of the Immune and Metabolic Pathways

Published: 25 November 2020| Version 2 | DOI: 10.17632/bsfcgp927h.2
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Description

Herein, we set out to investigate the responses to first-line therapies (DOS, XELOX, and anti-HER2-based therapies) for GC through a comprehensive proteomic analysis. We constructed a GC cohort that covered three clinical therapy subcohorts, including a DOS subcohort (44 patients treated with DOS therapy), an XELOX subcohort (70 patients treated with XELOX therapy) and a HER2 subcohort (71 patients who received anti-HER2-based therapy).

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Herein, we set out to investigate the responses to first-line therapies (DOS, XELOX, and anti-HER2-based therapies) for GC through a comprehensive proteomic analysis. We constructed a GC cohort that covered three clinical therapy subcohorts, including a DOS subcohort (44 patients treated with DOS therapy), an XELOX subcohort (70 patients treated with XELOX therapy) and a HER2 subcohort (71 patients who received anti-HER2-based therapy). Proteomic clustering resulted in four distinct subgroups that showed associations with the survival of patients, personalized treatment, and clinical outcomes. Furthermore, we conducted a differential proteomic analysis between the sensitive and non-sensitive groups in DOS, XELOX, and anti-HER2-based therapy subcohorts. Interestingly, we found that in the DOS subcohort, the overrepresented proteins in the sensitive group were enriched in immune pathways, whereas the overrepresented proteins in the non-sensitive group were enriched in metabolic pathways. Conversely, in the XELOX cohort, the overrepresented proteins in the sensitive group were enriched in metabolic pathways, whereas the overrepresented proteins in the non-sensitive group were enriched in immune pathways. Additionally, the combination of XELOX with the anti-HER2 treatment partially relieved the immune-related XELOX resistance, disclosing the mechanistic advantage of using this combination therapy over a single chemotherapeutic approach. Finally, independent risk factors among the proteins were screened by multivariable logistic regression analysis, and a corresponding, predictive model for the chemotherapy response was generated. Further, we confirmed the robustness of this prediction model on an independent BPRC DGC cohort. This study presents a comprehensive proteomic approach for the prediction of the response to chemo-/targeted therapy, and implicates its prognostic and therapeutic significance as well as the underlying regulatory mechanisms that may benefit clinical practice.

Institutions

Henan Normal University, Zhongshan Hospital Fudan University, Fudan University Shanghai Cancer Center, Fudan University

Categories

Proteomics, Chemotherapy, Stomach Cancer

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