BACR 20: Individual Patient Oesophageal Cancer Models for Tailored Treatment
1University of Nottingham, Nottingham, UK,2Nottingham University Hospitals, Nottingham, UK
The response to neo-adjuvant chemotherapy in oesophago-gastric (OG) cancer is only 45%, so over half of these patients progress and also suffer toxic chemotherapy side-effects. A model to predict chemotherapy response would provide a marked clinical benefit, by enabling personalised treatment of OG cancer.
OG tumour was obtained endoscopically from individual patients who were about to undergo standard neo-adjuvant chemotherapy at Nottingham University Hospital NHS Trust. Following chemotherapy, patients underwent tumour resection and assessment of the histological tumour regression grade (TRG), which is a marker of chemotherapy response and directly relates to prognosis. Cells from the endoscopic biopsies were expanded, using an in-vitro feeder layer system and supplemented medium. To model the human tumour micro-environment (TME), a 3D-tumour growth assay (3D-TGA) was developed, where the individual patient's primary tumour cells were embedded within a basement membrane extract with stromal support. The 3D-TGA was then used to quantify the response of individual patient tumours to standard chemotherapy. This was then compared with the actual clinical response, as measured by TRG.
The individual patient tumours can be grown from primary endoscopic biopsy tissue within a clinically applicable timescale of 2-4 weeks. There is correlation between the 3D-TGA predicted chemosensitivity and actual clinical response for the 8 patients so far evaluated. As well as predicting potential chemosensitivity for individual patients, the 3D-TGA allows individual and novel drugs to be evaluated, trends in chemosensitivity between patients to be appraised, and demonstrates a change in chemosensitivity when cancer cells are grown in a humanized TME with supporting human stromal cells.
This research has direct clinical application: if this assay proves to be predictive across a wider patient population, then following clinical trials, it could potentially be used to routinely guide individual patient therapy in the clinic, with administration of personalised chemotherapy for individual patient benefit.