Unified framework for patient-derived, tumor-organoid-based predictive testing of standard-of-care therapies in metastatic colorectal cancer

Tao Tan; Dmitri Mouradov; Margaret Lee; Grace Gard; Yumiko Hirokawa; Shan Li; Cong Lin; Fuqiang Li; Huijuan Luo; Kui Wu; Michelle Palmieri; Evelyn Leong; Jordan Clarke; Anuratha Sakthianandeswaren; Helen Brasier; Jeanne Tie; Niall C Tebbutt; Azim Jalali; Rachel Wong; Antony W Burgess; Peter Gibbs; Oliver M Sieber

doi:10.1016/j.xcrm.2023.101335

Unified framework for patient-derived, tumor-organoid-based predictive testing of standard-of-care therapies in metastatic colorectal cancer

Cell Rep Med. 2023 Dec 19;4(12):101335. doi: 10.1016/j.xcrm.2023.101335.

Authors

Tao Tan¹, Dmitri Mouradov¹, Margaret Lee², Grace Gard³, Yumiko Hirokawa⁴, Shan Li⁴, Cong Lin⁵, Fuqiang Li⁵, Huijuan Luo⁵, Kui Wu⁵, Michelle Palmieri¹, Evelyn Leong⁴, Jordan Clarke⁴, Anuratha Sakthianandeswaren¹, Helen Brasier⁴, Jeanne Tie⁶, Niall C Tebbutt⁷, Azim Jalali⁸, Rachel Wong⁹, Antony W Burgess¹⁰, Peter Gibbs⁶, Oliver M Sieber¹¹

Affiliations

¹ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia.
² Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia; Department of Medical Oncology, Eastern Health, Box Hill, VIC 3128, Australia; Eastern Health Clinical School, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Box Hill, VIC 3128, Australia.
³ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia.
⁴ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia.
⁵ HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, BGI Research, Hangzhou 310000, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China.
⁶ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia.
⁷ Department of Medical Oncology, Olivia Newton-John Cancer Wellness & Research Centre, Austin Health, Heidelberg, VIC 3084, Australia.
⁸ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia; Department of Cancer Services, Latrobe Regional Hospital, Traralogon, VIC 3844, Australia; Department of Medical Oncology, The Northern Hospital, Epping, VIC 3076, Australia.
⁹ Department of Medical Oncology, Eastern Health, Box Hill, VIC 3128, Australia; Eastern Health Clinical School, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Box Hill, VIC 3128, Australia.
¹⁰ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Surgery, The University of Melbourne, Parkville, VIC 3050, Australia.
¹¹ Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Surgery, The University of Melbourne, Parkville, VIC 3050, Australia; Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia. Electronic address: sieber.o@wehi.edu.au.

Abstract

Predictive drug testing of patient-derived tumor organoids (PDTOs) holds promise for personalizing treatment of metastatic colorectal cancer (mCRC), but prospective data are limited to chemotherapy regimens with conflicting results. We describe a unified framework for PDTO-based predictive testing across standard-of-care chemotherapy and biologic and targeted therapy options. In an Australian community cohort, PDTO predictions based on treatment-naive patients (n = 56) and response rates from first-line mCRC clinical trials achieve 83% accuracy for forecasting responses in patients receiving palliative treatments (18 patients, 29 treatments). Similar assay accuracy is achieved in a prospective study of third-line or later mCRC treatment, AGITG FORECAST-1 (n = 30 patients). "Resistant" predictions are associated with inferior progression-free survival; misclassification rates are similar by regimen. Liver metastases are the optimal site for sampling, with testing achievable within 7 weeks for 68.8% cases. Our findings indicate that PDTO drug panel testing can provide predictive information for multifarious standard-of-care therapies for mCRC.

Keywords: colorectal cancer; patient-derived tumor organoid; precision medicine; predictive drug testing.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Antineoplastic Agents* / therapeutic use
Australia
Colonic Neoplasms* / drug therapy
Colorectal Neoplasms* / diagnosis
Colorectal Neoplasms* / drug therapy
Humans
Prospective Studies

Substances

Antineoplastic Agents