A comparative study of tumour-on-chip models with patient-derived xenografts for predicting chemotherapy efficacy in colorectal cancer patients
Ong, Louis Jun Ye, Chia, Shumei, Wong, Stephen Qi Rong, Zhang, Xiaoqian, Chua, Huiwen, Loo, Jia Min, Chua, Wei Yong, Chua, Clarinda, Tan, Emile, Hentze, Hannes, Tan, Iain Beehuat, DasGupta, Ramanuj, & Toh, Yi Chin (2022) A comparative study of tumour-on-chip models with patient-derived xenografts for predicting chemotherapy efficacy in colorectal cancer patients. Frontiers in Bioengineering and Biotechnology, 10, Article number: 952726.
|
Published Version
(PDF 2MB)
115362219. Available under License Creative Commons Attribution 4.0. |
Open access copy at publisher website
Description
Inter-patient and intra-tumour heterogeneity (ITH) have prompted the need for a more personalised approach to cancer therapy. Although patient-derived xenograft (PDX) models can generate drug response specific to patients, they are not sustainable in terms of cost and time and have limited scalability. Tumour Organ-on-Chip (OoC) models are in vitro alternatives that can recapitulate some aspects of the 3D tumour microenvironment and can be scaled up for drug screening. While many tumour OoC systems have been developed to date, there have been limited validation studies to ascertain whether drug responses obtained from tumour OoCs are comparable to those predicted from patient-derived xenograft (PDX) models. In this study, we established a multiplexed tumour OoC device, that consists of an 8 × 4 array (32-plex) of culture chamber coupled to a concentration gradient generator. The device enabled perfusion culture of primary PDX-derived tumour spheroids to obtain dose-dependent response of 5 distinct standard-of-care (SOC) chemotherapeutic drugs for 3 colorectal cancer (CRC) patients. The in vitro efficacies of the chemotherapeutic drugs were rank-ordered for individual patients and compared to the in vivo efficacy obtained from matched PDX models. We show that quantitative correlation analysis between the drug efficacies predicted via the microfluidic perfusion culture is predictive of response in animal PDX models. This is a first study showing a comparative framework to quantitatively correlate the drug response predictions made by a microfluidic tumour organ-on-chip (OoC) model with that of PDX animal models.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
| ID Code: | 235213 | ||
|---|---|---|---|
| Item Type: | Contribution to Journal (Journal Article) | ||
| Refereed: | Yes | ||
| ORCID iD: |
|
||
| Additional Information: | Funding: This project is supported by Ministry of Education (R-397-000-298-114); Singapore-MIT Alliance for Research and Technology (SMART) (ING-000534 BIO) and Australian Research Council (FT180100157 and DP200101658) awarded to Y-CT; Biomedical Research Council (BMRC) (SPF 2015/002); Agency for Science, Technology and Research; National Medical Research Council (NMRC) (CIRG/1439/2015) awarded to IT. | ||
| Measurements or Duration: | 14 pages | ||
| Keywords: | 3D culture, dose response, in vitro, in vivo, microfluidic lab-on-a-chip, organ-on-chip (OoC), PDX (patient derived xenograft) | ||
| DOI: | 10.3389/fbioe.2022.952726 | ||
| ISSN: | 2296-4185 | ||
| Pure ID: | 115362219 | ||
| Divisions: | Current > Research Centres > Centre for Biomedical Technologies Current > Research Centres > Centre for Microbiome Research Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Mechanical, Medical & Process Engineering Current > QUT Faculties and Divisions > Faculty of Health |
||
| Funding Information: | This project is supported by Ministry of Education (R-397-000-298-114); Singapore-MIT Alliance for Research and Technology (SMART) (ING-000534 BIO) and Australian Research Council (FT180100157 and DP200101658) awarded to Y-CT; Biomedical Research Council (BMRC) (SPF 2015/002); Agency for Science, Technology and Research; National Medical Research Council (NMRC) (CIRG/1439/2015) awarded to IT. | ||
| Funding: | |||
| Copyright Owner: | 2022 The Authors | ||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||
| Deposited On: | 13 Sep 2022 14:44 | ||
| Last Modified: | 23 Jun 2026 06:55 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page