Abstract 1761
Background
Patient-derived organoids (PDOs) are versatile experimental models for cancer research. At the Faculty of medicine Siriraj Hospital, we have recently established live biobank of over seventy PDO models from stage I-IV Thai colorectal cancer patients. Our biobank included at least 10 patients who underwent neoadjuvant chemotherapy. We aimed to apply this resource for N-of-1 co-clinical trials, for the discovery of novel therapeutic agents and for biomarker development. We report here our application of the developed PDO models for predicting clinical outcome of colorectal cancer patients.
Methods
Surgically resected colorectal specimens from both normal and cancerous tissue were digested and embedded in appropriate matrices to form PDO models. Subsequently, all successful PDO models were collected in Siriraj live biobank together with their clinical data. Herein, we characterized our derived PDO models by pathological and molecular techniques. Some models were profiled with panel sequencing to assess for the causal driver mutations. Drug sensitivity of each PDO model to standard-of-care drugs were generated and compared with clinical outcome in each patient.
Results
We successfully established PDO models from different colorectal sites, of different pathological grades and staging. We identified heterogeneous morphologies of PDO models which appear to be corresponding well with the pathological and genomic profiles of each specimen origin. Although the PDO models from different colorectal cancer patients exhibited variable response to 5-fluorouracil (5-Fu), Leucovorin and Oxaliplatin, the response patterns are consistent with the clinical outcome of the individual patients as determined by tumor regression grade or radiologic imaging for neoadjuvant cases. We are examining the use of drug sensitivity profiling of PDO models for prioritizing anti-cancer treatment choices in a prospective clinical study.
Conclusions
The Siriraj live biobank of PDO from colorectal cancer patients can serve as a useful resource for N-of-1 co-clinical trials, and for comparison of drug response among patients from different ethnic backgrounds.
Clinical trial identification
Editorial acknowledgement
This work is supported in part by The National Research Council of Thailand and Siriraj foundation.
Legal entity responsible for the study
Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand.
Funding
The National Research Council of Thailand and Siriraj foundation, Siriraj Hospital.
Disclosure
All authors have declared no conflicts of interest.
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