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Predicting the Response of Neoadjuvant Therapy for Patients with Esophageal Carcinoma: an In-depth Literature Review

Currently, the most promising strategy to improve the prognosis of advanced esophageal cancer is neoadjuvant chemoradiation (CRT) followed by surgery. However, patients who achieved pathological complete response can experience more survival benefit. Therefore, it is critical to identify the respond...

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Detalles Bibliográficos
Autores principales: Tao, Chang-Juan, Lin, Gang, Xu, Ya-Ping, Mao, Wei-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615355/
https://www.ncbi.nlm.nih.gov/pubmed/26516367
http://dx.doi.org/10.7150/jca.12346
Descripción
Sumario:Currently, the most promising strategy to improve the prognosis of advanced esophageal cancer is neoadjuvant chemoradiation (CRT) followed by surgery. However, patients who achieved pathological complete response can experience more survival benefit. Therefore, it is critical to identify the responders early in the course of treatment. Published data demonstrate that clinic-histopathological factors, molecular biomarkers, and functional imaging are predictive of neoadjuvant therapy. The existing biomarkers, including epidermal growth factor receptors, angiogenetic factors, transcription factors, tumor suppressor genes, cell cycle regulators, nucleotide excision repair pathway, cytokines, and chemotherapy associated genes, need to be validated and novel biomarkers warrant further exploration. Positron emission tomography (PET) is useful for differentiating the responders of neoadjuvant CRT. The most valuable parameters and the time point of performing PET in the course of treatment remains to be elucidated. Furthermore, predictive models incorporating the multiple categories of factors need to be established with a large, prospective, and homogeneous patient cohort in the future. Standardization of staging, biomarker detection method, and image acquisition protocol will be critical for the generalization of this model. Prospective, multi-center controlled trials, which stratified patients according to these predictive factors, will help guide individualized treatment strategies for patients with esophageal cancer.