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PDX-derived organoids model in vivo drug response and secrete biomarkers. ​

Literature Information ​

PMID32990680
JournalJCI insight
Impact Factor6.1
JCR QuartileQ1
Publication Year2020
Times Cited67
KeywordsCancer, Glycobiology, Oncology
Literature TypeJournal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't
ISSN2379-3708
Issue5(21)
AuthorsLing Huang, Bruno Bockorny, Indranil Paul, Dipikaa Akshinthala, Pierre-Oliver Frappart, Omar Gandarilla, Arindam Bose, Veronica Sanchez-Gonzalez, Emily E Rouse, Sylvain D Lehoux, Nicole Pandell, Christine M Lim, John G Clohessy, Joseph Grossman, Raul Gonzalez, Sofia Perea Del Pino, George Daaboul, Mandeep S Sawhney, Steven D Freedman, Alexander Kleger, Richard D Cummings, Andrew Emili, Lakshmi B Muthuswamy, Manuel Hidalgo, Senthil K Muthuswamy

TL;DR ​

This study investigates patient-derived organoid models for pancreatic ductal adenocarcinoma (PDAC), revealing a significant correlation between organoid drug response and in vivo tumor growth, along with the successful replication of the in vivo glycan landscape by PDX-derived organoids. Furthermore, the research identifies potential circulating biomarkers for PDAC through extracellular vesicle protein analysis, highlighting the organoid model's utility in both drug response modeling and biomarker discovery for clinical applications.

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Cancer · Glycobiology · Oncology

Abstract ​

Patient-derived organoid models are proving to be a powerful platform for both basic and translational studies. Here we conduct a methodical analysis of pancreatic ductal adenocarcinoma (PDAC) tumor organoid drug response in paired patient-derived xenograft (PDX) and PDX-derived organoid (PXO) models grown under WNT-free culture conditions. We report a specific relationship between area under the curve value of organoid drug dose response and in vivo tumor growth, irrespective of the drug treatment. In addition, we analyzed the glycome of PDX and PXO models and demonstrate that PXOs recapitulate the in vivo glycan landscape. In addition, we identify a core set of 57 N-glycans detected in all 10 models that represent 50%-94% of the relative abundance of all N-glycans detected in each of the models. Last, we developed a secreted biomarker discovery pipeline using media supernatant of organoid cultures and identified potentially new extracellular vesicle (EV) protein markers. We validated our findings using plasma samples from patients with PDAC, benign gastrointestinal diseases, and chronic pancreatitis and discovered that 4 EV proteins are potential circulating biomarkers for PDAC. Thus, we demonstrate the utility of organoid cultures to not only model in vivo drug responses but also serve as a powerful platform for discovering clinically actionable serologic biomarkers.

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Primary Questions Addressed ​

  1. How do the drug response profiles of PDX-derived organoids compare to traditional cell line models in pancreatic cancer research?
  2. What specific mechanisms underlie the relationship between organoid drug dose response and in vivo tumor growth observed in this study?
  3. Can the identified extracellular vesicle protein markers serve as predictive indicators for treatment efficacy in patients with PDAC?
  4. How does the glycomic analysis of PDX and PXO models enhance our understanding of tumor biology and treatment resistance in pancreatic cancer?
  5. What are the potential implications of using organoid cultures for personalized medicine approaches in the treatment of pancreatic ductal adenocarcinoma?

Key Findings ​

Research Background and Objectives ​

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor prognosis and limited treatment options. Patient-derived xenograft (PDX) models have been effective in modeling therapeutic responses, but their high cost and lengthy preparation times hinder their widespread use. This study aimed to develop a cost-effective patient-derived organoid (PDO) model to predict drug responses and discover biomarkers for PDAC.

Main Methods/Materials/Experimental Design ​

The researchers created PDX-derived organoids (PXOs) using a WNT-free culture medium, allowing for rapid generation and maintenance of organoids that closely resemble the original tumors. The study involved the following key steps:

Mermaid diagram
  1. Generation of PDX Models: Tumor fragments were implanted into immunocompromised mice to create PDX models.
  2. Establishment of PXOs: Tumor fragments from PDX models were cultured in a WNT-free medium to generate organoids.
  3. Drug Treatment Assays: The organoids were treated with various chemotherapeutic agents, and cell viability was measured to determine drug responses.
  4. Glycomic Analysis: N-glycan profiles of PXOs were analyzed to assess glycosylation changes associated with PDAC.
  5. Extracellular Vesicle (EV) Protein Discovery: Proteins secreted by organoids were analyzed to identify potential biomarkers for PDAC.

Key Results and Findings ​

  • Drug Response Correlation: The area under the curve (AUC) values from organoid drug response assays correlated well with in vivo responses observed in PDX models, demonstrating that PXOs can effectively predict drug efficacy.
  • Glycomic Landscape: A total of 284 N-glycan masses were identified, with 188 shared between PDX and PXO models. A core set of 57 N-glycans was consistently found across all models, suggesting a shared glycan signature in PDAC.
  • Biomarker Discovery: Five EV proteins were identified as potential biomarkers for PDAC, with validation in patient plasma samples showing significant enrichment in patients with PDAC compared to benign gastrointestinal diseases.

Main Conclusions/Significance/Innovation ​

This study highlights the utility of PXOs as a powerful platform for modeling PDAC drug responses and discovering clinically relevant biomarkers. The findings suggest that organoid cultures can replicate the complex biology of tumors, including glycosylation changes and drug response patterns, offering a promising tool for personalized medicine in cancer treatment.

Research Limitations and Future Directions ​

  • Limitations: The study was limited by the small number of patient samples and the need for further validation of identified biomarkers in larger cohorts.
  • Future Directions: Future research should focus on expanding the biomarker validation studies and exploring the functional implications of glycosylation changes in PDAC. Additionally, optimizing organoid culture conditions and drug screening methods could enhance the predictive power of this model for broader applications in cancer research.

References ​

  1. Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors. - E Izumchenko;K Paz;D Ciznadija;I Sloma;A Katz;D Vasquez-Dunddel;I Ben-Zvi;J Stebbing;W McGuire;W Harris;R Maki;A Gaya;A Bedi;S Zacharoulis;R Ravi;L H Wexler;M O Hoque;C Rodriguez-Galindo;H Pass;N Peled;A Davies;R Morris;M Hidalgo;D Sidransky - Annals of oncology : official journal of the European Society for Medical Oncology (2017)
  2. Estimation of rat mammary tumor volume using caliper and ultrasonography measurements. - Ana Faustino-Rocha;Paula A Oliveira;Jacinta Pinho-Oliveira;Catarina Teixeira-Guedes;Ruben Soares-Maia;Rui Gil da Costa;Bruno Colaço;Maria João Pires;Jorge Colaço;Rita Ferreira;Mário Ginja - Lab animal (2013)
  3. Discovery of sialyl Lewis A and Lewis X modified protein cancer biomarkers using high density antibody arrays. - Jung-hyun Rho;Judson R Mead;W Shea Wright;Dean E Brenner;James W Stave;Jeffrey C Gildersleeve;Paul D Lampe - Journal of proteomics (2014)
  4. Whole genomes redefine the mutational landscape of pancreatic cancer. - Nicola Waddell;Marina Pajic;Ann-Marie Patch;David K Chang;Karin S Kassahn;Peter Bailey;Amber L Johns;David Miller;Katia Nones;Kelly Quek;Michael C J Quinn;Alan J Robertson;Muhammad Z H Fadlullah;Tim J C Bruxner;Angelika N Christ;Ivon Harliwong;Senel Idrisoglu;Suzanne Manning;Craig Nourse;Ehsan Nourbakhsh;Shivangi Wani;Peter J Wilson;Emma Markham;Nicole Cloonan;Matthew J Anderson;J Lynn Fink;Oliver Holmes;Stephen H Kazakoff;Conrad Leonard;Felicity Newell;Barsha Poudel;Sarah Song;Darrin Taylor;Nick Waddell;Scott Wood;Qinying Xu;Jianmin Wu;Mark Pinese;Mark J Cowley;Hong C Lee;Marc D Jones;Adnan M Nagrial;Jeremy Humphris;Lorraine A Chantrill;Venessa Chin;Angela M Steinmann;Amanda Mawson;Emily S Humphrey;Emily K Colvin;Angela Chou;Christopher J Scarlett;Andreia V Pinho;Marc Giry-Laterriere;Ilse Rooman;Jaswinder S Samra;James G Kench;Jessica A Pettitt;Neil D Merrett;Christopher Toon;Krishna Epari;Nam Q Nguyen;Andrew Barbour;Nikolajs Zeps;Nigel B Jamieson;Janet S Graham;Simone P Niclou;Rolf Bjerkvig;Robert Grützmann;Daniela Aust;Ralph H Hruban;Anirban Maitra;Christine A Iacobuzio-Donahue;Christopher L Wolfgang;Richard A Morgan;Rita T Lawlor;Vincenzo Corbo;Claudio Bassi;Massimo Falconi;Giuseppe Zamboni;Giampaolo Tortora;Margaret A Tempero; ;Anthony J Gill;James R Eshleman;Christian Pilarsky;Aldo Scarpa;Elizabeth A Musgrove;John V Pearson;Andrew V Biankin;Sean M Grimmond - Nature (2015)
  5. Discovery of Pancreatic Ductal Adenocarcinoma-Related Aberrant Glycosylations: A Multilateral Approach of Lectin Microarray-Based Tissue Glycomic Profiling With Public Transcriptomic Datasets. - Takanori Wagatsuma;Chiaki Nagai-Okatani;Atsushi Matsuda;Yohei Masugi;Masako Imaoka;Ken Yamazaki;Michiie Sakamoto;Atsushi Kuno - Frontiers in oncology (2020)
  6. Optical Imaging of Drug-Induced Metabolism Changes in Murine and Human Pancreatic Cancer Organoids Reveals Heterogeneous Drug Response. - Alex J Walsh;Jason A Castellanos;Nagaraj S Nagathihalli;Nipun B Merchant;Melissa C Skala - Pancreas (2016)
  7. Annexin A11 in disease. - Jiasheng Wang;Chunmei Guo;Shuqing Liu;Houbao Qi;Yuling Yin;Rui Liang;Ming-Zhong Sun;Frederick T Greenaway - Clinica chimica acta; international journal of clinical chemistry (2014)
  8. Expression of blood group-related antigens ABH, Lewis A, Lewis B, Lewis X, Lewis Y, and CA 19-9 in pancreatic cancer cells in comparison with the patient's blood group type. - P M Pour;M M Tempero;H Takasaki;E Uchida;Y Takiyama;D A Burnett;Z Steplewski - Cancer research (1988)
  9. Xenograft and organoid model systems in cancer research. - Margit Bleijs;Marc van de Wetering;Hans Clevers;Jarno Drost - The EMBO journal (2019)
  10. Isolation of Extracellular Vesicles for Cancer Diagnosis and Functional Studies. - Alex W Brenner;Gloria H Su;Fatemeh Momen-Heravi - Methods in molecular biology (Clifton, N.J.) (2019)

Literatures Citing This Work ​

  1. Drug Inhibition of SARS-CoV-2 Replication in Human Pluripotent Stem Cell-Derived Intestinal Organoids. - Jana Krüger;Rüdiger Groß;Carina Conzelmann;Janis A Müller;Lennart Koepke;Konstantin M J Sparrer;Tatjana Weil;Desiree Schütz;Thomas Seufferlein;Thomas F E Barth;Steffen Stenger;Sandra Heller;Jan Münch;Alexander Kleger - Cellular and molecular gastroenterology and hepatology (2021)
  2. Organotypic Modeling of the Tumor Landscape. - Maria M Haykal;Clara Nahmias;Christine Varon;Océane C B Martin - Frontiers in cell and developmental biology (2020)
  3. Exploring the Potential of Drug Response Assays for Precision Medicine in Ovarian Cancer. - Tanya Singh;Adam S Neal;Neda A Moatamed;Sanaz Memarzadeh - International journal of molecular sciences (2020)
  4. 3D Cell Cultures as Prospective Models to Study Extracellular Vesicles in Cancer. - Guillermo Bordanaba-Florit;Iratxe Madarieta;Beatriz Olalde;Juan M Falcón-Pérez;Félix Royo - Cancers (2021)
  5. A Prospective Feasibility Trial to Challenge Patient-Derived Pancreatic Cancer Organoids in Predicting Treatment Response. - Alica K Beutel;Lena Schütte;Jeanette Scheible;Elodie Roger;Martin Müller;Lukas Perkhofer;Annika M T U Kestler;Johann M Kraus;Hans A Kestler;Thomas F E Barth;Johannes Lemke;Marko Kornmann;Thomas J Ettrich;Johann Gout;Thomas Seufferlein;Alexander Kleger - Cancers (2021)
  6. Exploring the Complementarity of Pancreatic Ductal Adenocarcinoma Preclinical Models. - Owen Hoare;Nicolas Fraunhoffer;Abdessamad Elkaoutari;Odile Gayet;Martin Bigonnet;Julie Roques;Rémy Nicolle;Colin McGuckin;Nico Forraz;Emilie Sohier;Laurie Tonon;Pauline Wajda;Sandrine Boyault;Valéry Attignon;Séverine Tabone-Eglinger;Sandrine Barbier;Caroline Mignard;Olivier Duchamp;Juan Iovanna;Nelson J Dusetti - Cancers (2021)
  7. Three-Dimensional Culture Models to Study Innate Anti-Tumor Immune Response: Advantages and Disadvantages. - Alessandro Poggi;Federico Villa;Jordi Leonardo Castrillo Fernadez;Delfina Costa;Maria Raffaella Zocchi;Roberto Benelli - Cancers (2021)
  8. Dynamic Stromal Alterations Influence Tumor-Stroma Crosstalk to Promote Pancreatic Cancer and Treatment Resistance. - Kendelle J Murphy;Cecilia R Chambers;David Herrmann;Paul Timpson;Brooke A Pereira - Cancers (2021)
  9. The somatic molecular evolution of cancer: Mutation, selection, and epistasis. - Krishna Dasari;Jason A Somarelli;Sudhir Kumar;Jeffrey P Townsend - Progress in biophysics and molecular biology (2021)
  10. Novel 3D µtissues Mimicking the Fibrotic Stroma in Pancreatic Cancer to Study Cellular Interactions and Stroma-Modulating Therapeutics. - Kunal P Pednekar;Marcel A Heinrich;Joop van Baarlen;Jai Prakash - Cancers (2021)

... (57 more literatures)

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