Predicting response to treatment in gastroesophageal junction adenocarcinomas: combining clinical, imaging, and molecular biomarkers

Gillian H Bain, Russell David Petty

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


The incidence of adenocarcinomas of the gastroesophageal junction (GEJ) is rapidly rising, and even in early-stage locoregional confined disease the 5-year survival rate rarely exceeds 25%-35%. Randomized trials and meta-analyses have demonstrated a benefit with neoadjuvant or perioperative chemotherapy and with neoadjuvant chemoradiotherapy. However, the optimal approach in individual patients is not clear and remains controversial. A consistent finding is that patients who have a histopathological response to neoadjuvant therapy are more likely to receive a survival benefit. These clinical data provide a strong argument for the urgent development of methods to predict histopathological response to neoadjuvant therapies for GEJ adenocarcinoma. Published data demonstrate that clinicopathological features (tumor location), imaging (fluorodeoxyglucose-positron emission tomography "metabolic response"), and tissue/molecular biomarkers may all have a predictive value for neoadjuvant therapies. However, it is uncertain from published data whether or not they will be useful for clinical decision making in individual patients. Existing candidate biomarkers need to be properly qualified and validated and novel biomarkers are required; and an optimal approach should involve the combination and integration of clinical, imaging, and molecular biomarkers. This review presents the evidence base and discusses novel experimental approaches for the combination of biomarker modalities to allow optimization of an individualized treatment approach in GEJ adenocarcinoma patients that may be relevant to other tumor types as well.

Original languageEnglish
Pages (from-to)270-84
Number of pages15
Issue number3
Publication statusPublished - Mar 2010


  • gastroesophageal junction
  • adenocarcinoma
  • response
  • positron emission tomography
  • biomarkers


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