Personalized targeted therapy for esophageal squamous cell carcinoma

World J Gastroenterol. 2015 Jul 7;21(25):7648-58. doi: 10.3748/wjg.v21.i25.7648.

Abstract

Esophageal squamous cell carcinoma continues to heavily burden clinicians worldwide. Researchers have discovered the genomic landscape of esophageal squamous cell carcinoma, which holds promise for an era of personalized oncology care. One of the most pressing problems facing this issue is to improve the understanding of the newly available genomic data, and identify the driver-gene mutations, pathways, and networks. The emergence of a legion of novel targeted agents has generated much hope and hype regarding more potent treatment regimens, but the accuracy of drug selection is still arguable. Other problems, such as cancer heterogeneity, drug resistance, exceptional responders, and side effects, have to be surmounted. Evolving topics in personalized oncology, such as interpretation of genomics data, issues in targeted therapy, research approaches for targeted therapy, and future perspectives, will be discussed in this editorial.

Keywords: Cancer heterogeneity; Cultured tumor cells; Driver mutation; Drug side effects; Esophageal squamous cell carcinoma; Exceptional responder; High-throughput nucleotide sequencing; Neoplasm drug resistance; Personalized medicine; Xenograft model.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Antineoplastic Agents / therapeutic use*
  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Carcinoma, Squamous Cell / drug therapy*
  • Carcinoma, Squamous Cell / genetics
  • Carcinoma, Squamous Cell / metabolism
  • Esophageal Neoplasms / drug therapy*
  • Esophageal Neoplasms / genetics
  • Esophageal Neoplasms / metabolism
  • Esophageal Squamous Cell Carcinoma
  • Genetic Predisposition to Disease
  • Genomics
  • Humans
  • Molecular Diagnostic Techniques
  • Molecular Targeted Therapy*
  • Phenotype
  • Precision Medicine*
  • Predictive Value of Tests
  • Risk Factors
  • Signal Transduction / drug effects
  • Treatment Outcome

Substances

  • Antineoplastic Agents
  • Biomarkers, Tumor