Towards novel systemic treatment approaches in esophagogastric cancer

Open Access
Authors
  • S. Schokker
Supervisors
  • H.W.M. van Laarhoven
Cosupervisors
  • M.F. Bijlsma
Award date 12-03-2021
ISBN
  • 9789464211924
Number of pages 246
Organisations
  • Faculty of Medicine (AMC-UvA)
Abstract
The aim of this thesis was to explore novel systemic treatment approaches in esophagogastric cancer that could improve treatment outcome. For this purpose we investigated the addition of dual HER2 blockade through trastuzumab and pertuzumab to neoadjuvant chemoradiotherapy for resectable HER2+ esophageal adenocarcinoma and concluded that this treatment is both feasible and promising. The hybrid LC-MS/MS method we developed for quantifying co-administered trastuzumab and pertuzumab can be used in further studies where these two (or other) mAbs are administered and can reduce the required sampling volume. Furthermore, since currently patients do not receive further treatment after surgery, adjuvant therapy could improve survival. However, we showed that, unfortunately, six cycles of SOX after neoadjuvant chemoradiation and esophagectomy in esophageal adenocarcinoma patients is not feasible and appears to lack efficacy in unselected patients. In the curative treatment of esophageal cancer, research should be directed towards optimization of neoadjuvant treatment.
Since a substantial number of patients present with synchronous metastases, and unfortunately most curatively treated patients eventually develop disease recurrence, more effective palliative treatment is urgently needed. Despite our finding that the addition of nab-paclitaxel to first-line palliative treatment with CapOx caused more toxicity and apparent improvement of survival was modest, this study did provide valuable information on the potential prognostic serum biomarker ADAM12. Other prognostic factors we identified in our systematic review can be used for future trial design, and aid in the development of survival nomograms. The identified predictive factors can be used to increasingly personalize treatment decisions.
Document type PhD thesis
Note Please note that the acknowledgements section is not included in the thesis downloads.
Language English
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