Discover how patient-derived organoids can revolutionize oncology research by enabling accurate modeling of tumor biology and predicting patient response to treatment.

We have come a long way in treating cancer. From surgeries, radiations, and injecting systemic drugs, to tailoring therapies that delicately disintegrate tumors. Despite advances in the field, there is still a considerable distance to go. The current statistics indicate that 95% of the anti-cancer agents that are developed in the preclinical phase falter as they progress toward clinical trials.

The complexity of cancer biology

Let’s be real. Cancer is an excruciatingly complex disease.

Recent advances in genomics have demonstrated layers of genetic, transcriptomic, epigenetic, and /or phenotypic evidence that could make a cell cancerous1. The stochastic nature of the disease manifests in the form of both inter- and intra-tumor heterogeneity2,3. Inter-tumor heterogeneity refers to the existence of distinct mutational patterns in different tumors originating from the same patient, while intra-tumor heterogeneity refers to the coexistence of multiple cancer cell clones within a single tumor mass. Tumor heterogeneity especially contributes as a challenge in the early phase of drug development, where preclinical models with little to no patient relevance are used to identify, validate, and develop clinical candidates3.

The lack of preclinical models that capture cancer biology

While pre-clinical studies in conventional models such as cell lines and xenografts are a useful tool to screen compounds and provide useful biological insights, they do not show a good correlation with efficacy in Phase II trials or survival advantage in Phase III trials4

While cell lines are fast and easy to establish, they are markedly deficient in representing original tumor biology. While patient-derived xenografts and explants are better representatives of patient tumor antigen expression, they do not recapitulate the stromal component of the tumor, leaving open-ended questions on how the drug might respond in the tumor microenvironment.

Mini tumors in the lab

HUB Organoids derived from patient-derived tumor samples or biopsies reflect crucial features in terms of tumor architecture, genetic makeup, and the composition of differentiated cell types. Tumor organoids show a remarkable representation of interpatient tumor heterogeneity5 and have shown promising data in predicting patient drug response in the lab6.

In a recent study7, HUB Organoids derived from colorectal cancer patients were used to develop the first bispecific against cancer stem cells in all solid tumor types. Remarkably, the bispecific was developed within five years, thanks to validating the therapeutic potential of the agent in a diverse panel of patient-derived organoids representative of the clinical setting.

Patient-derived organoids established from single cells in tumor-adjacent normal crypts also allow testing for off-target and off-tumor toxicities within the same patients, making it easier to cross out compounds with toxic effects early in the drug development pipeline.

Creating tumor organoid biobanks for personalized medicine

Through years of experience, the culture conditions have undergone optimization and expansion, facilitating the establishment of organoid biobanks of a diverse range of solid tumor types, including intestine, colon, bladder, lung, liver, ovary, pancreas, kidney, breast, and stomach.

Most biobanking studies confirm that patient-derived organoids (PDOs) reflect the characteristics of the primary tumor, at least at the level of bulk tumor DNA sequence8. Moreover, studies also show that the clonal drift over prolonged culture times for organoids is relatively small as compared to conventional models9,10sup>.

Retrospective studies have indicated that the response of PDO to therapies closely resembles the initial response of patients to the same treatments12. Beyond the empiric potential of PDOs to help choose therapies for individual patients, large panels of PDOs representing one type of cancer have been used to develop biomarkers predictive of drug response12.

The evolution of organoid modeling is happening at an unprecedented pace, and the potential for this cutting-edge approach to revolutionize oncology and advance clinical research is truly exciting.

Want to know how patient-derived organoids can help you de-risk your drug development program? Book a free consultation with an expert.

Reference

  1. Roychowdhury S, Chinnaiyan AM. Translating cancer genomes and transcriptomes for precision oncology. CA Cancer J Clin. 2016 Jan-Feb;66(1):75-88. doi: 10.3322/caac.21329
  2. Yancovitz M, Litterman A, Yoon J, Ng E, Shapiro RL, Berman RS, Pavlick AC, Darvishian F, Christos P, Mazumdar M, Osman I, Polsky D. Intra- and inter-tumor heterogeneity of BRAF(V600E))mutations in primary and metastatic melanoma. PLoS One. 2012;7(1):e29336. doi: 10.1371/journal.pone.0029336
  3. Liu J, Dang H, Wang XW. The significance of intertumor and intratumor heterogeneity in liver cancer. Exp Mol Med. 2018 Jan 5;50(1):e416. doi: 10.1038/emm.2017.165. PMID: 29303512; PMCID: PMC5992990
  4. Johnson JI, Decker S, Zaharevitz D. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br J Cancer 2001;84(10):1424-31
  5. Yang H, Zhang N, Liu YC. An organoids biobank for recapitulating tumor heterogeneity and personalized medicine. Chin J Cancer Res. 2020 Jun;32(3):408-413. doi: 10.21147/j.issn.1000-9604.2020.03.12. PMID: 32694905; PMCID: PMC7369175
  6. https://resources.huborganoids.nl/elrig-2022-poster-patient-derived-organoids-predict-clinical-response
  7. Herpers, B., Eppink, B., James, M. I., Cortina, C., Cañellas-Socias, A., Boj, S. F., . Throsby, M. (2022). Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors. Nature Cancer, 3(4), 418-436. doi:10.1038/s43018-022-00359-0
  8. Weeber F, van de Wetering M, Hoogstraat M, Dijkstra KK, Krijgsman O, Kuilman T, Gadellaa-van Hooijdonk CG, van der Velden DL, Peeper DS, Cuppen EP, Vries RG, Clevers H, Voest EE. Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases. Proc Natl Acad Sci U S A. 2015 Oct 27;112(43):13308-11. doi: 10.1073/pnas.1516689112. Epub 2015 Oct 12. PMID: 26460009; PMCID: PMC4629330
  9. Fujii M, Shimokawa M, Date S, Takano A, Matano M, Nanki K, Ohta Y, Toshimitsu K, Nakazato Y, Kawasaki K, Uraoka T, Watanabe T, Kanai T, Sato T. A Colorectal Tumor Organoid Library Demonstrates Progressive Loss of Niche Factor Requirements during Tumorigenesis. Cell Stem Cell. 2016 Jun 2;18(6):827-838. doi: 10.1016/j.stem.2016.04.003. Epub 2016 May 19. PMID: 27212702
  10. Kopper O, de Witte CJ, Lõhmussaar K, Valle-Inclan JE, Hami N, Kester L, Balgobind AV, Korving J, Proost N, Begthel H, van Wijk LM, Revilla SA, Theeuwsen R, van de Ven M, van Roosmalen MJ, Ponsioen B, Ho VWH, Neel BG, Bosse T, Gaarenstroom KN, Vrieling H, Vreeswijk MPG, van Diest PJ, Witteveen PO, Jonges T, Bos JL, van Oudenaarden A, Zweemer RP, Snippert HJG, Kloosterman WP, Clevers H. An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity. Nat Med. 2019 May;25(5):838-849. doi: 10.1038/s41591-019-0422-6. Epub 2019 Apr 22. PMID: 31011202
  11. Hill SJ, Decker B, Roberts EA, Horowitz NS, Muto MG, Worley MJ Jr, Feltmate CM, Nucci MR, Swisher EM, Nguyen H, Yang C, Morizane R, Kochupurakkal BS, Do KT, Konstantinopoulos PA, Liu JF, Bonventre JV, Matulonis UA, Shapiro GI, Berkowitz RS, Crum CP, D’Andrea AD. Prediction of DNA Repair Inhibitor Response in Short-Term Patient-Derived Ovarian Cancer Organoids. Cancer Discov. 2018 Nov;8(11):1404-1421. doi: 10.1158/2159-8290.CD-18-0474. Epub 2018 Sep 13. PMID: 30213835; PMCID: PMC6365285
  12. Lee SH, Hu W, Matulay JT, Silva MV, Owczarek TB, Kim K, Chua CW, Barlow LJ, Kandoth C, Williams AB, Bergren SK, Pietzak EJ, Anderson CB, Benson MC, Coleman JA, Taylor BS, Abate-Shen C, McKiernan JM, Al-Ahmadie H, Solit DB, Shen MM. Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer. Cell. 2018 Apr 5;173(2):515-528.e17. doi: 10.1016/j.cell.2018.03.017. PMID: 29625057; PMCID: PMC5890941.
X

Have any questions?

contact us