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Engineered matrices reveal stiffness-mediated chemoresistance in patient-derived pancreatic cancer organoids

Nature Materials volume 23, pages 1138–1149 (2024)Cite this article

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Abstract

Pancreatic ductal adenocarcinoma (PDAC) is characterized by its fibrotic and stiff extracellular matrix. However, how the altered cell/extracellular-matrix signalling contributes to the PDAC tumour phenotype has been difficult to dissect. Here we design and engineer matrices that recapitulate the key hallmarks of the PDAC tumour extracellular matrix to address this knowledge gap. We show that patient-derived PDAC organoids from three patients develop resistance to several clinically relevant chemotherapies when cultured within high-stiffness matrices mechanically matched to in vivo tumours. Using genetic barcoding, we find that while matrix-specific clonal selection occurs, cellular heterogeneity is not the main driver of chemoresistance. Instead, matrix-induced chemoresistance occurs within a stiff environment due to the increased expression of drug efflux transporters mediated by CD44 receptor interactions with hyaluronan. Moreover, PDAC chemoresistance is reversible following transfer from high- to low-stiffness matrices, suggesting that targeting the fibrotic extracellular matrix may sensitize chemoresistant tumours. Overall, our findings support the potential of engineered matrices and patient-derived organoids for elucidating extracellular matrix contributions to human disease pathophysiology.

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Fig. 1: ECM stiffness drives PDAC chemoresistance.
Fig. 2: Long-term culture in stiff matrices drives PDAC chemoresistance.
Fig. 3: Drug efflux transporter expression and activity mediates PDAC organoid chemoresistance.
Fig. 4: Influence of HA on PDAC chemoresistance.
Fig. 5: HA-mediated CD44 signalling mediates PDAC organoid chemoresistance.
Fig. 6: Stiffness-mediated PDAC chemoresistance is reversible.

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Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Raw data related to this paper are uploaded to the Stanford Digital Repository, which can be accessed through the persistent URL (https://purl.stanford.edu/nw595bg6402) and the DOI (https://doi.org/10.25740/nw595bg6402). RNA-seq data from the TCGA and GTEx databases were accessed and plotted using the GEPIA online tool (http://gepia.cancer-pku.cn). Source data are provided with this paper.

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Acknowledgements

We thank T. Lozanoski, E. Rankin, S. Natarajan and J. Roth for insightful conversations and editing of the paper. We are grateful to the patients who donated tissue samples used for this research. We thank the Stanford Tissue Bank for their assistance in procuring patient tissue samples. We thank Z. Ma for help with barcode DNA sequencing. We thank P. Chu at the Stanford Human Pathology/Histology Service Center for assistance with tissue and organoid paraffin embedding and sectioning. B.L.L. acknowledges financial support from the Siebel Scholars Program and Stanford Bio-X Bowes Graduate Fellowship. D.Z. acknowledges financial support from the Stanford Graduate Fellowship and the National Science Foundation Graduate Research Fellowship Program. C.H.-L. acknowledges financial support from Fundación Alfonso Martín Escudero. B.A.K. acknowledges financial support from the Stanford Bio-X Bowes Graduate Fellowship. K. Karlsson acknowledges financial support from the Swedish Research Council (2018-00454). K.C.K. acknowledges financial support from the National Science Foundation Graduate Research Fellowship Program. M.S.H. acknowledges financial support from the National Institutes of Health F31 Pre-Doctoral Fellowship (NS132505), the Stanford ChEM-H O’Leary-Thiry Graduate Fellowship and the Gerald J. Lieberman Fellowship. This work was supported by funding from the National Institutes of Health (R01 EB027171 to S.C.H.; R01CA2515143, U01CA217851 and U54CA224081 to C.J.K.; U01CA217851 and DP1CA238296 to C.C.), Stand Up to Cancer and Cancer Research UK (C.J.K.), and the National Science Foundation (CBET 2033302 to S.C.H.). Flow cytometry data were collected on BD FACSymphony A5 in the Shared FACS Facility, obtained using a NIH S10 Shared Instrument Grant (1S10OD026831-01). Part of this work was performed at the Stanford Nano Shared Facilities (SNSF), supported by the National Science Foundation under award ECCS-2026822.

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Author notes

  1. These authors contributed equally: Daiyao Zhang, Carla Huerta-López, Aidan E. Gilchrist.

Authors and Affiliations

  1. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Bauer L. LeSavage & Christopher M. Madl

  2. Department of Chemical Engineering, Stanford University, Stanford, CA, USA

    Daiyao Zhang, Brad A. Krajina & Michelle S. Huang

  3. Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA

    Carla Huerta-López, Aidan E. Gilchrist, Christopher Long & Sarah C. Heilshorn

  4. Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, USA

    Kasper Karlsson & Christina Curtis

  5. Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    Kasper Karlsson & Christina Curtis

  6. Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

    Kasper Karlsson, Kremena Karagyozova & Christina Curtis

  7. Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, CA, USA

    Amber R. Smith & Calvin J. Kuo

  8. Institute for Stem Cell Biology & Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Katarina C. Klett

  9. Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Gernot Kaber & Paul L. Bollyky

  10. Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA, USA

    Christopher M. Madl

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Contributions

B.L.L., D.Z., C.H.-L., A.E.G., B.A.K., A.R.S. and S.C.H. designed the research. B.L.L., D.Z., C.H.-L., A.E.G., B.A.K., K. Karagyozova, K.C.K., M.S.H., C.L., G.K. and C.M.M. conducted experiments. B.L.L., D.Z., C.H.-L., A.E.G., K. Karlsson, C.L., G.K. and C.M.M. analysed data. K. Karlsson, A.R.S., C.C. and C.J.K. provided organoids and reagents. B.L.L., D.Z., C.H.-L. and A.E.G. wrote the paper. B.L.L., D.Z., C.H.-L., A.E.G., B.A.K., K. Karlsson, A.R.S., K. Karagyozova, K.C.K., M.S.H., C.L., G.K., C.M.M., P.L.B., C.C., C.J.K. and S.C.H. edited and approved the final paper.

Corresponding author

Correspondence to Sarah C. Heilshorn.

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Competing interests

S.C.H. has a patent application pending related to the hydrogel formulations used in this paper, as described in an international patent application PCT/US/2021/057925 with an international filing date of 3 November 2021. This application has been submitted to the U.S. Patent Office and published on 16 November 2023 as US 2023-0365940 A1, and this same application has entered the national phase in China (publication number 116829126), Singapore (application number 11202303493U), Europe (publication number 4240327), Japan (serial number 2023-526661), Canada (serial number 3,196,621), Israel (serial number 302453), South Korea (serial number 10-2023-7018686) and Australia (serial number 2021376143). The named inventors are S. Heilshorn, R. Suhar and D. Hunt, and the named applicant is the Board of Trustees of the Leland Stanford Junior University. C.C. is an advisor and holds equity in Grail, Ravel and Deepcell, and is an advisor to Genentech and NanoString. C.J.K. is an advisor and holds equity in Surrozen, Mozart and NextVivo. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Matrix stiffness mediates PDAC organoid clonal heterogeneity.

a, Schematic summarizing the protocol and potential outcomes of genetically barcoded PDAC organoid expansion within Cultrex and HELP matrices. b, Number of barcodes present within PDAC organoid populations expanded within Cultrex and HELP matrices for one to three passages (N = 3 independent biological replicates per matrix type, mean ± 95% confidence interval, center line represents linear fit for each matrix over three passages, shaded region represents 95% confidence interval of linear fit). Statistical analysis was performed using an ordinary one-way ANOVA with Tukey multiple comparisons correction between data points at passage three (****P < 0.0001 for comparison between HELP High and Cultrex/HELP Low, comparison between HELP Low and Cultrex was not significantly different). The initial Parent population was the same for all matrices (N = 1). c, Slope of linear fit from b for each matrix (N = 3 independent biological replicates per matrix type, mean ± 95% confidence interval, ordinary one-way ANOVA with Tukey multiple comparisons correction, ****P < 0.0001, NS, not significant). d, Frequencies of barcodes present in the indicated matrix at passage three. Barcodes are listed in rank order and colored bars correspond to barcodes unique to only the indicated matrix. The number of these unique barcodes and their cumulative frequency are reported for each matrix. e, Venn diagram of barcodes at passage three across indicated matrices. f, Correlation plots comparing barcode frequencies across Cultrex and HELP at passage three. Pearson r values are reported for each pairing. Dashed line represents perfect correlation. In d-f, only barcodes with a frequency >0.01% across all three biological replicates at passage three were included.

Source Data

Extended Data Fig. 2 Long-term drug efflux inhibitor treatment exacerbates PDAC organoid chemoresistance.

a, PDAC viability following treatment with DMSO (control, normalized to 1), 66 nM gemcitabine (Gem), or 66 nM gemcitabine + 20 μM Ko143 (N = 4-5 independent experimental replicate hydrogels, mean ± s.d.). b, PDAC toxicity following treatment with DMSO (control, normalized to 0), 100 nM gemcitabine, 100 nM gemcitabine + 20 μM Ko143, or 3,333 nM gemcitabine (positive control, normalized to 1) (N = 4-5 independent experimental replicate hydrogels, mean ± s.d.). In a and b, PDAC organoids were expanded for four passages in HELP Low (left) or HELP High (right) prior to gemcitabine (+ Ko143) treatment for six days on single cells during log-phase growth (a) or for three days following formation of ~75-μm diameter multicellular organoids (b). Statistical analysis comparing experimental gemcitabine treatment and gemcitabine + Ko143 treatment was performed using an unpaired two-tailed t-test (*P < 0.05, ****P < 0.0001), and the fold change between these two conditions is reported for each comparison. c, Illustrated summary of results from a and b. d,e, qPCR (d) and Western blot (e) quantification of mRNA and protein-level ABC-family drug efflux transporter expression in PDAC organoids expanded within HELP Low or HELP High for four passages and treated with either DMSO or 20 μM Ko143 (N = 4 independent experimental replicates, qPCR: mean ± 95% confidence interval, Western: mean ± s.d.). Statistical analysis comparing DMSO vs. Ko143 treatment for each matrix was performed using an unpaired two-tailed t-test (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). qPCR data are normalized to GAPDH gene expression and respective marker expression of Cultrex DMSO samples. Western data are normalized to β-actin expression and DMSO samples for each marker and matrix. PDAC cells were treated with Ko143 throughout single-cell log-phase growth for six days. f, Illustrated summary of results from d and e.

Source Data

Extended Data Fig. 3 Influence of RGD ligand on PDAC organoid chemoresistance.

a, Schematic of recombinant elastin-like protein (ELP) component of HELP, which can be engineered to display a non-interactive, scrambled RDG sequence, resulting in a HELP matrix without RGD, but with identical mechanical properties and HA concentration. b, Stiffness measurements of HELP RDG matrices stiffness-matched to HELP Low and HELP High (N = 3 independent experimental replicate hydrogels, mean ± s.d., unpaired two-tailed t-test, ****P < 0.0001). c, Representative bright-field images of PDAC organoids expanded within HELP RDG Low (top) or HELP RDG High (bottom) for four passages. Scale bar, 250 μm. d, qPCR quantification of mRNA-level ABCG2 expression in PDAC organoids expanded within HELP RDG Low or High for four passages (N = 4 independent experimental replicate hydrogels, mean ± 95% confidence interval). Statistical analysis comparing marker expression in Low vs. High matrices was performed using an unpaired two-tailed t-test (**P < 0.01). All data are normalized to GAPDH gene expression and respective marker expression in the PDAC organoid parent population cultured within Cultrex prior to expansion in HELP RDG (that is, Cultrex P0). e, Single-cell-level (left) and organoid-level (right) gemcitabine dose-response curves for PDAC organoids expanded within HELP RDG Low or High for four passages. Each data point represents the mean ± s.e.m. (N = 4 independent experimental replicate hydrogels, solid center line is nonlinear least squares regression of data; shaded region represents 95% confidence bands of nonlinear fit; data are normalized to positive controls (DMSO for single cells, 3,333 nM gemcitabine for organoids). f, Gemcitabine IC50 values calculated from nonlinear fit of dose-response curves shown in e for single-cell (left) and organoid (right) drug treatment in HELP RDG compared to HELP containing RGD. Each bar represents the mean ± s.e.m. (N = 4 independent experimental replicate hydrogels, unpaired two-tailed t-test between Low and High for each matrix variation, **P < 0.01, ***P < 0.001, ****P < 0.0001).

Source Data

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Western blots.

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LeSavage, B.L., Zhang, D., Huerta-López, C. et al. Engineered matrices reveal stiffness-mediated chemoresistance in patient-derived pancreatic cancer organoids. Nat. Mater. 23, 1138–1149 (2024). https://doi.org/10.1038/s41563-024-01908-x

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