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Poster session 08

2258P - Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: Drug screen optimization and correlation with patient response

Date

21 Oct 2023

Session

Poster session 08

Topics

Cytotoxic Therapy;  Translational Research

Tumour Site

Colon and Rectal Cancer

Presenters

Lidwien Smabers

Citation

Annals of Oncology (2023) 34 (suppl_2): S1152-S1189. 10.1016/S0923-7534(23)01927-0

Authors

L.P. Smabers1, E. Wensink1, C.S. Verissimo2, E. Koedoot2, M. Doorn2, K. Pitsa2, M. Huismans3, C. Higuera Barón2, L. Valkenburg-van Iersel4, A. Brousali5, R. Overmeer2, M. Braat6, S. Elias7, R. Vries2, O. Kranenburg8, M. Koopman1, S. Boj2, J.M.L. Roodhart1

Author affiliations

  • 1 Medical Oncology Department, University Medical Center Utrecht, 3584 CX - Utrecht/NL
  • 2 Oncology, HUB Organoids, 3584 CM - Utrecht/NL
  • 3 Center For Molecular Medicine, University Medical Center Utrecht, 3584 CX - Utrecht/NL
  • 4 Medical Oncology Department, Maastricht University Medical Center, 6229 HX - Maastricht/NL
  • 5 Utrecht Platform For Organoid Technology (uport), University Medical Center Utrecht, 3584 CX - Utrecht/NL
  • 6 Radiology Department, University Medical Center Utrecht, 3584 CX - Utrecht/NL
  • 7 Julius Center For Health Sciences And Primary Care, University Medical Center Utrecht, 3584 CX - Utrecht/NL
  • 8 Surgical Oncology Department, University Medical Center Utrecht, 3584 CX - Utrecht/NL

Resources

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Abstract 2258P

Background

Currently, response to cancer treatment cannot be predicted upfront, hampering treatment efficacy. There is a need for effective biomarkers to select patients for optimal treatment. A promising predictive biomarker is response testing on patient-derived organoids (PDOs). For metastatic colorectal cancer (mCRC), it is unclear what drug screening method is optimal and if PDOs predict response for all treatment types.

Methods

Drug screens were performed by exposing 23 PDOs to a concentration range of systemic drugs for 5 days. The following standard mCRC treatments were evaluated: 5-fluorouracil (n = 6), oxaliplatin (n = 14) and irinotecan (n = 10). Drug sensitivity was measured by cell viability and quantified by calculating the area under the curve (AUC). We compared in vitro sensitivity to patient response, evaluated using progression-free survival (PFS) and % change in the size of target lesions on CT scans.

Results

Drug screen methods regarding medium composition (with/without N-acetylcysteine), combination treatment ratios and read-outs were optimized, as they impact the correlation with clinical response. Correlations were seen between PDO response (AUC) and patient response (% change) for all chemotherapies (Spearman r = 0.3-0.6, ns). PFS was evaluable for patients treated with oxaliplatin (n=14). Median PFS of patients with organoids classified as resistant to oxaliplatin-based treatment - based on AUC - was relevantly shorter than for organoids classified as sensitive (3.4 vs 10.1 months, log rank p = 0.07). PDOs from patients previously exposed to chemotherapy showed increased resistance to chemotherapy with a significantly higher AUC (median 0.9 vs 0.4, Mann-Whitney U p = 0.005).

Conclusions

After drug screen optimization, we show that PDO response correlates with patient response to commonly used systemic mCRC treatments. This suggests that PDOs can serve as a predictive biomarker and guide personalized cancer treatment. PDOs adequately reflect prior treatment effect, supporting their use for modeling mCRC. Our findings and optimized screening method will be validated in the ongoing OPTIC trial (NL61668.041.17), to facilitate implementation of PDOs in clinical treatment.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

University Medical Center Utrecht.

Funding

HUB Organoids.

Disclosure

L. Valkenburg-van Iersel: Financial Interests, Advisory Role, Also travel/accommodations paid or reimbursed: Servier, Pierre Fabre; Financial Interests, Advisory Role: Roche, Amgen. M. Koopman: Financial Interests, Institutional, Advisory Board, advisory board and speaker: Pierre Fabre; Financial Interests, Institutional, Advisory Board: MSD, Bayer; Financial Interests, Institutional, Advisory Board, Advisory Board, speaker: Servier; Financial Interests, Institutional, Invited Speaker: Merck, BMS; Financial Interests, Institutional, Trial Chair: Servier; Financial Interests, Institutional, Research Grant: Servier, Roche, Bayer, Bristol Myers Squibb, Merck, Personal Genomics Diagnostics, Sirtex, Pierre Fabre; Financial Interests, Institutional, Funding: Pierre Fabre, Amgen, Nordic Pharma, Novartis, Merck, Servier, BMS; Non-Financial Interests, Leadership Role, vice-chair of DCCG: Dutch Colorectal Cancer Group; Non-Financial Interests, Advisory Role, Member of KWF scientific board: KWF; Non-Financial Interests, Other, ESMO faculty member for the Gastro-Intestinal Tumours – colorectal cancer: ESMO; Non-Financial Interests, Advisory Role, expert member of committee “regie op registers dure geneesmiddelen” ZINNL; Non-Financial Interests, Advisory Role, CRC expert on Kanker.nl platform for answering online CRC questions of CRC (non) patients: Patient representative organisation (Kanker.nl); Non-Financial Interests, Leadership Role, chair of RWD & DH working group: ESMO; Other, PI of the Dutch Prospective Colorectal Cancer Cohort study: PLCRC project. J.M.L. Roodhart: Financial Interests, Institutional, Advisory Board: Bayer, BMS, Merck-Serono, Pierre Fabre, Servier, Amgen; Financial Interests, Institutional, Funding: HUB Organoids, Cleara Biotech, BMS, Pierre Fabre, Servier; Financial Interests, Institutional, Member of Board of Directors: Foundation Hubrecht Organoid Biobank. All other authors have declared no conflicts of interest.

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