Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response

Author:

Smabers Lidwien Paula1,Wensink Emerens1,Verissimo Carla S.2,Koedoot Esmee2,Pitsa Katharina-Chara3,Huismans Maarten Age1,Barón Celia Higuera2,Doorn Mayke2,Iersel Liselot B. Valkenburg-van4,Cirkel Geert Anne5,Brousali Anneta1,Overmeer René2,Koopman Miriam1,Braat Manon N.1,de Vries Bas Penning6,Elias Sjoerd G.6,Vries Robert G.2,Kranenburg Onno1,Boj Sylvia F.2,Roodhart Jeanine M.1

Affiliation:

1. UMC Utrecht: Universitair Medisch Centrum Utrecht

2. HUB Organoids B.V.

3. HUB Organoids

4. Maastricht UMC+: Maastricht Universitair Medisch Centrum+

5. Meander MC: Stichting Meander Medisch Centrum

6. Julius Center for Health Sciences and Primary Care: Julius Centrum voor Gezondheidswetenschappen en Eerstelijns Geneeskunde

Abstract

Abstract Background The inability to predict treatment response of colorectal cancer patients results in unnecessary toxicity, decreased efficacy and survival. Response testing on patient-derived organoids (PDOs) is a promising biomarker for treatment efficacy. The aim of this study is to optimize PDO drug screening methods for correlation with patient response and explore the potential to predict responses to standard chemotherapies.Methods We optimized drug screen methods on 5–11 PDOs per condition of the complete set of 23 PDOs from patients treated for metastatic colorectal cancer (mCRC). PDOs were exposed to 5-fluorouracil (5-FU), irinotecan- and oxaliplatin-based chemotherapy. We compared medium with and without N-acetylcysteine (NAC), different read-outs and different combination treatment layouts to capture the strongest association with patient response. We expanded the screens using the optimized methods for all PDOs. Organoid sensitivity was correlated to the patient’s response, determined by % change in the size of target lesions. We assessed organoid sensitivity in relation to prior exposure to chemotherapy, mutational status and sidedness.Results Drug screen optimization involved excluding N-acetylcysteine from the medium and biphasic curve fitting for 5-FU & oxaliplatin combination screens. CellTiter-Glo measurements were comparable with CyQUANT and did not affect the correlation with patient response. Furthermore, the correlation improved with application of growth rate metrics, when 5-FU & oxaliplatin was screened in a ratio, and 5-FU & SN-38 using a fixed dose of SN-38. Area under the curve was the most robust drug response curve metric. After optimization, organoid and patient response showed a correlation coefficient of 0.58 for 5-FU (n = 6, 95% CI -0,44-0.95), 0.61 for irinotecan- (n = 10, 95% CI − .03-0.90) and 0.60 for oxaliplatin-based chemotherapy (n = 11, 95% CI -0.01-0.88). Median progression-free survival of patients with resistant PDOs to oxaliplatin-based chemotherapy was significantly shorter than sensitive PDOs (3.3 vs 10.9 months, p = 0.007). Increased resistance to 5-FU in patients with prior exposure to 5-FU/capecitabine was adequately reflected in PDOs (p = 0.005).Conclusions Our study emphasizes the critical impact of the screening methods for determining correlation between PDO drug screens and mCRC patient outcomes. Our 5-step optimization strategy provides a basis for future research on the clinical utility of PDO screens.

Publisher

Research Square Platform LLC

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