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Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors

Nature Cancer volume 3, pages 418–436 (2022)Cite this article

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Abstract

Patient-derived organoids (PDOs) recapitulate tumor architecture, contain cancer stem cells and have predictive value supporting personalized medicine. Here we describe a large-scale functional screen of dual-targeting bispecific antibodies (bAbs) on a heterogeneous colorectal cancer PDO biobank and paired healthy colonic mucosa samples. More than 500 therapeutic bAbs generated against Wingless-related integration site (WNT) and receptor tyrosine kinase (RTK) targets were functionally evaluated by high-content imaging to capture the complexity of PDO responses. Our drug discovery strategy resulted in the generation of MCLA-158, a bAb that specifically triggers epidermal growth factor receptor degradation in leucine-rich repeat-containing G-protein-coupled receptor 5-positive (LGR5+) cancer stem cells but shows minimal toxicity toward healthy LGR5+ colon stem cells. MCLA-158 exhibits therapeutic properties such as growth inhibition of KRAS-mutant colorectal cancers, blockade of metastasis initiation and suppression of tumor outgrowth in preclinical models for several epithelial cancer types.

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Fig. 1: bAb generation, PDO biobank and EGF dependency.
Fig. 2: Functional bAb screening on PDOs.
Fig. 3: Characterization of MCLA-158.
Fig. 4: Targeting of LGR5+ cells by MCLA-158.
Fig. 5: Therapeutic effects of MCLA-158 compared to cetuximab.
Fig. 6: Transcriptional changes in PDOs treated with either MCLA-158 or cetuximab.
Fig. 7: Internalization and degradation of EGFR by MCLA-158 treatment.

Data availability

Organoid exome sequencing data have been deposited at European Genome–Phenome Archive (study no. EGAS00001004584). RNA-sequencing data of P18T and C55T organoids treated with antibodies are deposited at Gene Expression Omnibus (GSE186531). Microarray data of Fab072+ versus Fab072− tumor cells are deposited at Gene Expression Omnibus (GSE190543). Further information and requests for resources and reagents should be directed to the corresponding authors. All requests for raw and analyzed data and materials will be reviewed promptly by the corresponding author to verify whether the request is subject to any intellectual property or confidentiality obligations. Any data and materials that can be shared will be released via a material transfer agreement. Source data are provided with this paper.

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Acknowledgements

We thank all patients for donating materials to the organoid biobank and all employees of U-PORT UMC Utrecht, as well as O. Kranenburg at UMC Utrecht and E. Wink van Gestel and N. van Scharrenburg at Meander Medisch Centrum for their assistance with patient inclusion and tissue acquisition. We thank J. Blokker, R. Korporaal and T. Mehraban for their contributions to building the CRC organoid biobank. We also thank R. Fong from Integral Molecular for performing the alanine scanning; L. Kaldenberg for graphically displaying the structural models; H. van der Maaden and W. Bartelink for technical assistance; M. Sevillano, A. Berenguer and staff at IRB facilities for excellent support with flow cytometry, functional genomics and histopathology. This study was funded by the European Union under the Seventh Framework Programme (FP7-HEALTH-2013-INNOVATION-2, SUPPRESSTEM, grant agreement no. 601876). IRB Barcelona is the recipient of a Severo Ochoa Award of Excellence from the Spanish Ministry of Economy and Competitiveness and E.B. received support from AGAUR 2017-SGR-698 (Generalitat de Catalunya). A.V. was supported by grant from the Spanish Ministry of Economy and Competitiveness, Instituto de Salud Carlos III FEDER (PI19/01320). A.C.-S. held an FPU predoctoral fellowship from the Spanish Ministry of Economy and Competitiveness.

Author information

Authors and Affiliations

  1. OcellO BV, Leiden, The Netherlands

    Bram Herpers, Jara García Mateos, Kuan Yan, Lucia Salinaro & Leo S. Price

  2. Crown Bioscience Netherlands BV, Leiden, The Netherlands

    Bram Herpers, Jara García Mateos, Kuan Yan & Leo S. Price

  3. Merus NV, Utrecht, The Netherlands

    Berina Eppink, Rob C. Roovers, Carina Bartelink-Clements, Vanessa Zondag-van der Zande, Abdul Basmeleh, Szabolcs Fatrai, David Maussang, Jeroen J. Lammerts van Bueren, John de Kruif, Ton Logtenberg & Mark Throsby

  4. Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain

    Mark I. James, Carme Cortina, Adrià Cañellas-Socias, Xavier Hernando-Momblona, Camille Stephan-Otto Attolini, Elena Sancho & Eduard Batlle

  5. CIBERONC, Madrid, Spain

    Carme Cortina, Adrià Cañellas-Socias, Xavier Hernando-Momblona, Elena Sancho, Hector G. Palmer, Josep Tabernero & Eduard Batlle

  6. Hubrecht Organoid Technology (HUB), Utrecht, the Netherlands

    Sylvia F. Boj & Robert G. J. Vries

  7. Wellcome Sanger Institute, Hinxton, UK

    Dominik Glodzik & Michael R. Stratton

  8. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Dominik Glodzik

  9. Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands

    Marc van de Wetering & Hans Clevers

  10. Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences (KNAW) and University Medical Center Utrecht, Utrecht, the Netherlands

    Marc van de Wetering & Hans Clevers

  11. Oncode Institute, Hubrecht Institute, Utrecht, the Netherlands

    Marc van de Wetering & Hans Clevers

  12. Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain

    Irene Chicote, Garazi Serna, Laia Cabellos, Lorena Ramírez, Paolo Nuciforo, Hector G. Palmer & Josep Tabernero

  13. Medical Oncology Department, Vall d’Hebron University Hospital (HUVH), Barcelona, Spain

    Laia Cabellos, Lorena Ramírez, Hector G. Palmer & Josep Tabernero

  14. Department of Medical Oncology, Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL)-CIBERONC, L’Hospitalet de Llobregat, Barcelona, Spain

    Ramon Salazar & Cristina Santos

  15. Chemoresistance and Predictive Factors Group, Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet del Llobregat, Barcelona, Spain

    Alberto Villanueva

  16. Xenopat SL, Parc Cientific de Barcelona (PCB), Barcelona, Spain

    Alberto Villanueva

  17. Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain

    Eduard Batlle

Authors
  1. Bram Herpers
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Contributions

M.T., E.B., T.L., H.C. and R.G.J.V. conceived and designed the study. B.H., J.G.M., K.Y., L.S. and L.S.P. performed antibody screens and characterized mechanisms of action. B.E., C.B.-C., V.Z.-v.d.Z., R.C.R., A.B., D.M., J.d.K., T.L. and M.T. generated the bispecific antibody panel. M.I.J., A.C.-S., C.C., S.F., J.J.L.v.B., X.H.-M., E.S. and E.B. characterized the MCLA-158 mode of action and performed xenograft experiments. D.G. and M.R.S. performed genomic analyses of PDOs. C.S.-O.A. performed statistical analysis. L.C., L.R. and P.N. performed in situ hybridization for LGR5. S.F.B., M.v.d.W., R.G.J.V. and H.C. generated the organoid biobank. H.G.P., J.T., I.C., G.S., R.S., C.S. and A.V. performed and analyzed antibody effects on orthotopic PDXs. E.B. and M.T. coordinated the study and wrote the manuscript.

Corresponding authors

Correspondence to Eduard Batlle or Mark Throsby.

Ethics declarations

Competing interests

S.F.B. and R.G.J.V. are employed by the Foundation Hubrecht Organoid Technology, which holds the exclusive license to the Organoid Technology. R.G.J.V. and H.C. are inventors on patents for Organoid Technology. B.E., R.C.R., C.B.-C., V.Z.-v.d.Z., A.B., S.F., J.J.L.v.B., J.d.K., T.L. and M.T. are employees of Merus NV. B.H., J.G.M., K.Y. and L.S.P. are employees of Crown Bioscience Netherlands BV. M.T., J.d.K., T.L., H.C., R.G.J.V., E.B. and B.H. are inventors on intellectual property related to this work. J.T. is paid advisor and H.C. has been paid advisor to Merus NV. H.C. is non-executive Board of Directors-member of Roche, Basel. The other authors declare no competing interests.

Peer review

Peer review information

Nature Cancer thanks Byoung Chul Cho, Livio Trusolino and Ömer Yilmaz for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Genomic alteration of PDOs.

a. Frequency of mutations in common driver genes among the PDO biobank and the TCGA CRC dataset9. b. Graphs indicate % of PDOs in the biobank with amplifications, deletions and loss of heterozygosity segments across chromosome regions. Upper side of the graphs correspond to PDO biobank and bottom part to the TCGA CRC dataset9. c. Number of single base substitutions in each PDO. d. Number of small indels in each PDO. e. Frequencies of mutational signatures25 in each PDO.

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Extended Data Fig. 2 Molecular characterization of MCLA-158.

a. Examples of KRAS mutant PDOs cultured without EGF or with EGF (5 ng/mL) from the experiment shown in Fig. 1d. DNA is labeled in blue using Hoechst, and actin in red using phalloidin. The pictures are taken from day 7 cultures. Scale bars are 200 μm. b. Examples of KRAS wild-type PDOs cultured without EGF or with EGF (5 ng/mL) from the experiment in Fig. 1e. Scale bars are 200 μm. c. Alanine scanning epitope mapping of MCLA-158 on EGFR. For each clone, the mean binding value with Ab MCLA-158 is plotted as a function of the clone’s mean EGFR expression value (gray circles). Critical residues contributing to the binding of MCLA-158 to EGFR are depicted in blue. d. Alanine scanning epitope mapping of MCLA-158 on LGR5. For each clone, the mean binding value with Ab MCLA-158 is plotted as a function of the clone’s mean LGR5 expression value (gray circles). Critical residues contributing to the binding of MCLA-158 to LGR5 are depicted in blue. e. Flow cytometry histograms of representative P18T PDOs stained with Fab072 bivalent antibody or control TT antibody. Gates used to isolate Fab072+ and Fab072- cells for subsequent experiments are indicated. f. LGR5 mRNA levels by RT-qPCR on FACS-purified cell populations. Mean of n=3 technical replicates of one representative PDO +/- SD. g. Flow cytometry analysis of PDO biobank samples using Fab072 or Fab266 (irrelevant TT control) antibodies. Mean fluorescent intensity (MFI) values are shown.

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Extended Data Fig. 3 Effects of MCLA-158 on PDOs.

a. Representative Ki67 IHC staining of the quantifications shown in Fig.4b. Lower panels are magnifications. Bar in upper panel is 10 μm and in lower panels is 30 μm. b. Representative cell cycle plots of P18T PDOs treated with the indicated antibodies at a concentration of 2 μg ml-1. % of cells in each cell cycle phase are indicated. c. Nucleus size in PDO P18T cultures treated with indicated antibodies. Each dot indicates average nucleus area (pixels) of all organoids in an independent section (n=2 for cetuximab, n=7 for MCLA-158, 4 for EGFRxTT and 5 for TTxTT). Line labels the mean. Two-tailed Wald test of a linear model. d. P18T cultures were treated with the indicated antibodies for 4 days at a concentration of 20 μg ml-1 and then antibodies were washed away (arrow). Organoid size was monitored and y-axis shows growth relative to the day the treatment started. Each data point is mean +/- standard error (n=3 independent wells). Two-tailed unpaired t-test. e. MCLA-158+ cell distributions analyzed by flow cytometry in parental non-infected, shControl and shLGR5 P18T PDO culture. As a negative control we stained with TT-TT Ab. Cell frequencies were normalized to the mode of every sample.

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Extended Data Fig. 4 Effects of MCLA-158 in PDX and orthotopic xenografts.

a. Kaplan-Meier plot displaying mice survival for the experiment shown in Fig. 4j. Long-rank P value between MCLA-158 and cetuximab using Log-rank Mantel-Cox test. b. Volume of individual P18T xenografts in experiment shown in Fig. 4j. c. Mice bearing PDO C31M-derived subcutaneous xenografts were treated with indicated antibodies or PBS. Tumor volumes relative to day 1 of treatment are shown. Each data point is mean of tumor volumes +/- SEM. n=21 tumors for CET; n=21 for MCLA-158 and n=17 for vehicle at day=0. Two-tailed unpaired t-test. d-f. Organ-specific metastases for the experiment shown in Fig. 5j,k. g. LGR5 mRNA (density) analyzed in tissue sections by RNAscope on peritoneal metastases found in M005 model.

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Extended Data Fig. 5 Subcutaneous CRC PDX growth corresponding to experiment in Fig. 5e.

Panels show growth of individual mice. Two-tailed unpaired t-test was used to calculate p values.

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Extended Data Fig. 6 Localization of MCLA-158 in normal colon mucosa and CRC-derived organoids.

a. Representative confocal images of P18T and C0M PDOs treated with MCLA-158, or with EGFR (Fab232) or LGR5 (Fab072) combined with a control TT arm. PDOs were treated for 24 hours. Antibody localization was detected by immunofluorescence. Arrows indicate localization of antibodies (green) at basolateral membranes. Arrowheads indicate localization of antibodies in the cytoplasm. Red staining is actin labeled with phalloidin. Nuclei (blue) are stained with Hoechst. Scale bar is 50 μm. b. Representative confocal images of normal colon mucosa (C82N and C110N) and CRC (C55T and C47T) PDOs treated with MCLA-158 for 24 hours. Antibodies were added at 1μg ml-1. MCLA-158 (red) and EGFR (green) localization was detected by immunofluorescence. Arrows indicate localization of MCLA-158 at basolateral membranes. Arrowheads indicate localization of MCLA-158 in intracellular structures in the cytoplasm. Scale bar is 100 μm. c. Virtual image of a capillary western blot measuring EGFR levels on P18T, C55T or C82N (normal mucosa PDO) protein extracts. Antibodies were added at 1 μg ml-1 for the indicated time points.

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Herpers, B., Eppink, B., James, M.I. et al. Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors. Nat Cancer 3, 418–436 (2022). https://doi.org/10.1038/s43018-022-00359-0

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