Literature Information

DOI10.1038/s41467-018-05190-9
PMID30061675
JournalNature communications
Impact Factor15.7
JCR QuartileQ1
Publication Year2018
Times Cited190
KeywordsEsophageal adenocarcinoma, Organoid cultures, Clonal selection, Precision therapeutics, Polyclonality
Literature TypeJournal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov’t
ISSN2041-1723
Pages2983
Issue9(1)
AuthorsXiaodun Li, Hayley E Francies, Maria Secrier, Juliane Perner, Ahmad Miremadi, Núria Galeano-Dalmau, William J Barendt, Laura Letchford, Genevieve M Leyden, Emma K Goffin, Andrew Barthorpe, Howard Lightfoot, Elisabeth Chen, James Gilbert, Ayesha Noorani, Ginny Devonshire, Lawrence Bower, Amber Grantham, Shona MacRae, Nicola Grehan, David C Wedge, Rebecca C Fitzgerald, Mathew J Garnett

TL;DR

This study addresses the rising incidence of esophageal adenocarcinoma (EAC) and its low survival rates by developing clinically annotated organoid cultures that mimic the primary tumor’s genetic and morphological characteristics. These organoids not only reveal insights into clonal evolution but also present a promising pre-clinical platform for testing targeted therapies, particularly against receptor tyrosine kinases.

Search for more papers on MaltSci.com

Esophageal adenocarcinoma · Organoid cultures · Clonal selection · Precision therapeutics · Polyclonality

Abstract

Esophageal adenocarcinoma (EAC) incidence is increasing while 5-year survival rates remain less than 15%. A lack of experimental models has hampered progress. We have generated clinically annotated EAC organoid cultures that recapitulate the morphology, genomic, and transcriptomic landscape of the primary tumor including point mutations, copy number alterations, and mutational signatures. Karyotyping of organoid cultures has confirmed polyclonality reflecting the clonal architecture of the primary tumor. Furthermore, subclones underwent clonal selection associated with driver gene status. Medium throughput drug sensitivity testing demonstrates the potential of targeting receptor tyrosine kinases and downstream mediators. EAC organoid cultures provide a pre-clinical tool for studies of clonal evolution and precision therapeutics.

MaltSci.com AI Research Service

Intelligent ReadingAnswer any question about the paper and explain complex charts and formulas
Locate StatementsFind traces of a specific claim within the paper
Add to KBasePerform data extraction, report drafting, and advanced knowledge mining

Primary Questions Addressed

  1. How do organoid cultures enhance our understanding of the genetic diversity in esophageal adenocarcinoma?
  2. What specific mutations and alterations are most commonly observed in the organoid models of esophageal adenocarcinoma?
  3. In what ways can the findings from organoid cultures influence the development of targeted therapies for esophageal adenocarcinoma?
  4. How does the clonal architecture observed in organoid cultures compare to that of traditional tumor models?
  5. What are the implications of drug sensitivity testing in organoid cultures for future clinical trials in esophageal adenocarcinoma treatment?

Key Findings

Research Summary

Background and Purpose

Esophageal adenocarcinoma (EAC) is a rapidly increasing cancer type with a poor prognosis, characterized by low five-year survival rates of less than 15%. The lack of suitable experimental models has hindered advancements in understanding and treating this disease. This study aims to establish patient-derived organoid cultures that mimic the morphological, genomic, and transcriptomic features of primary EAC tumors. The objectives include creating a biobank of EAC organoids, characterizing their molecular profiles, evaluating their clonal evolution, and assessing their drug sensitivity for precision therapeutic strategies.

Main Methods/Materials/Experimental Design

The research employed a series of methodologies to establish and characterize EAC organoid cultures:

  1. Organoid Derivation: Freshly resected EAC tissues were processed to create organoid cultures. The tissue was minced, digested with collagenase, and then plated in a specialized matrix for growth.

    graph TD;
    A["Tissue Collection"] --> B["Minced and Digested"];
    B --> C["Cell Suspension"];
    C --> D["Plated in Matrix"];
    D --> E["Organoid Culture"];

  2. Characterization: The organoids were subjected to histopathological assessment, karyotyping, genomic profiling, and RNA sequencing to determine their fidelity to the original tumors.

  3. Clonality Analysis: Spectral karyotyping and Bayesian Dirichlet processes were used to analyze the clonal dynamics and heterogeneity of the organoid cultures over multiple passages.

  4. Drug Sensitivity Testing: The organoids were screened against a panel of 24 anti-cancer drugs to evaluate their therapeutic potential and identify effective treatment strategies.

Key Results and Findings

  • Establishment of Organoids: Organoids were successfully derived from 10 patients, with a 31% success rate. Most cultures could be passaged multiple times and maintained for over six months.
  • Histological and Genomic Fidelity: The organoids displayed histological characteristics consistent with EAC, including mutation patterns in key driver genes such as TP53 and PIK3CA. Six distinct mutational signatures were identified, reflecting the intra-tumor heterogeneity of EAC.
  • Clonal Dynamics: Analysis showed that organoids retained the polyclonal structure of the original tumors, with some subclones demonstrating selection during culture. Clonal evolution was observed, with certain mutations becoming dominant over time.
  • Drug Sensitivity: There was significant variability in drug responses among the organoid cultures. Some organoids exhibited resistance to standard chemotherapy, mirroring patient outcomes. Sensitivities were identified for targeted therapies, particularly against MEK and EGFR inhibitors.

Main Conclusions/Significance/Innovation

The study successfully developed EAC organoid cultures that recapitulate the complex biology of the disease, including its genomic landscape and clonal evolution. These organoids serve as valuable preclinical models for studying EAC, offering insights into tumor heterogeneity and therapeutic responses. This research paves the way for future investigations into personalized medicine approaches for EAC, potentially leading to improved treatment strategies.

Research Limitations and Future Directions

  • Limitations: The success rate for organoid derivation was relatively low, and the organoids did not fully capture all aspects of the tumor microenvironment. Differences in gene expression between organoids and primary tumors were noted, likely due to the artificial culture conditions.
  • Future Directions: Further studies are needed to enhance the organoid culture system, including incorporating stromal and immune components. Additionally, expanding the biobank with more patient samples could facilitate more comprehensive drug screening and the development of tailored therapies for EAC.

References

  1. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. - Charlotte Soneson;Michael I Love;Mark D Robinson - F1000Research (2015)
  2. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. - Peter Eirew;Adi Steif;Jaswinder Khattra;Gavin Ha;Damian Yap;Hossein Farahani;Karen Gelmon;Stephen Chia;Colin Mar;Adrian Wan;Emma Laks;Justina Biele;Karey Shumansky;Jamie Rosner;Andrew McPherson;Cydney Nielsen;Andrew J L Roth;Calvin Lefebvre;Ali Bashashati;Camila de Souza;Celia Siu;Radhouane Aniba;Jazmine Brimhall;Arusha Oloumi;Tomo Osako;Alejandra Bruna;Jose L Sandoval;Teresa Algara;Wendy Greenwood;Kaston Leung;Hongwei Cheng;Hui Xue;Yuzhuo Wang;Dong Lin;Andrew J Mungall;Richard Moore;Yongjun Zhao;Julie Lorette;Long Nguyen;David Huntsman;Connie J Eaves;Carl Hansen;Marco A Marra;Carlos Caldas;Sohrab P Shah;Samuel Aparicio - Nature (2015)
  3. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. - Niccolo Bolli;Hervé Avet-Loiseau;David C Wedge;Peter Van Loo;Ludmil B Alexandrov;Inigo Martincorena;Kevin J Dawson;Francesco Iorio;Serena Nik-Zainal;Graham R Bignell;Jonathan W Hinton;Yilong Li;Jose M C Tubio;Stuart McLaren;Sarah O’ Meara;Adam P Butler;Jon W Teague;Laura Mudie;Elizabeth Anderson;Naim Rashid;Yu-Tzu Tai;Masood A Shammas;Adam S Sperling;Mariateresa Fulciniti;Paul G Richardson;Giovanni Parmigiani;Florence Magrangeas;Stephane Minvielle;Philippe Moreau;Michel Attal;Thierry Facon;P Andrew Futreal;Kenneth C Anderson;Peter J Campbell;Nikhil C Munshi - Nature communications (2014)
  4. Signatures of mutational processes in human cancer. - Ludmil B Alexandrov;Serena Nik-Zainal;David C Wedge;Samuel A J R Aparicio;Sam Behjati;Andrew V Biankin;Graham R Bignell;Niccolò Bolli;Ake Borg;Anne-Lise Børresen-Dale;Sandrine Boyault;Birgit Burkhardt;Adam P Butler;Carlos Caldas;Helen R Davies;Christine Desmedt;Roland Eils;Jórunn Erla Eyfjörd;John A Foekens;Mel Greaves;Fumie Hosoda;Barbara Hutter;Tomislav Ilicic;Sandrine Imbeaud;Marcin Imielinski;Marcin Imielinsk;Natalie Jäger;David T W Jones;David Jones;Stian Knappskog;Marcel Kool;Sunil R Lakhani;Carlos López-Otín;Sancha Martin;Nikhil C Munshi;Hiromi Nakamura;Paul A Northcott;Marina Pajic;Elli Papaemmanuil;Angelo Paradiso;John V Pearson;Xose S Puente;Keiran Raine;Manasa Ramakrishna;Andrea L Richardson;Julia Richter;Philip Rosenstiel;Matthias Schlesner;Ton N Schumacher;Paul N Span;Jon W Teague;Yasushi Totoki;Andrew N J Tutt;Rafael Valdés-Mas;Marit M van Buuren;Laura van ’t Veer;Anne Vincent-Salomon;Nicola Waddell;Lucy R Yates; ; ; ; ;Jessica Zucman-Rossi;P Andrew Futreal;Ultan McDermott;Peter Lichter;Matthew Meyerson;Sean M Grimmond;Reiner Siebert;Elías Campo;Tatsuhiro Shibata;Stefan M Pfister;Peter J Campbell;Michael R Stratton - Nature (2013)
  5. Lgr5(+ve) stem cells drive self-renewal in the stomach and build long-lived gastric units in vitro. - Nick Barker;Meritxell Huch;Pekka Kujala;Marc van de Wetering;Hugo J Snippert;Johan H van Es;Toshiro Sato;Daniel E Stange;Harry Begthel;Maaike van den Born;Esther Danenberg;Stieneke van den Brink;Jeroen Korving;Arie Abo;Peter J Peters;Nick Wright;Richard Poulsom;Hans Clevers - Cell stem cell (2010)
  6. Organoid cultures derived from patients with advanced prostate cancer. - Dong Gao;Ian Vela;Andrea Sboner;Phillip J Iaquinta;Wouter R Karthaus;Anuradha Gopalan;Catherine Dowling;Jackline N Wanjala;Eva A Undvall;Vivek K Arora;John Wongvipat;Myriam Kossai;Sinan Ramazanoglu;Luendreo P Barboza;Wei Di;Zhen Cao;Qi Fan Zhang;Inna Sirota;Leili Ran;Theresa Y MacDonald;Himisha Beltran;Juan-Miguel Mosquera;Karim A Touijer;Peter T Scardino;Vincent P Laudone;Kristen R Curtis;Dana E Rathkopf;Michael J Morris;Daniel C Danila;Susan F Slovin;Stephen B Solomon;James A Eastham;Ping Chi;Brett Carver;Mark A Rubin;Howard I Scher;Hans Clevers;Charles L Sawyers;Yu Chen - Cell (2014)
  7. Fast and accurate short read alignment with Burrows-Wheeler transform. - Heng Li;Richard Durbin - Bioinformatics (Oxford, England) (2009)
  8. Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity. - Austin M Dulak;Petar Stojanov;Shouyong Peng;Michael S Lawrence;Cameron Fox;Chip Stewart;Santhoshi Bandla;Yu Imamura;Steven E Schumacher;Erica Shefler;Aaron McKenna;Scott L Carter;Kristian Cibulskis;Andrey Sivachenko;Gordon Saksena;Douglas Voet;Alex H Ramos;Daniel Auclair;Kristin Thompson;Carrie Sougnez;Robert C Onofrio;Candace Guiducci;Rameen Beroukhim;Zhongren Zhou;Lin Lin;Jules Lin;Rishindra Reddy;Andrew Chang;Rodney Landrenau;Arjun Pennathur;Shuji Ogino;James D Luketich;Todd R Golub;Stacey B Gabriel;Eric S Lander;David G Beer;Tony E Godfrey;Gad Getz;Adam J Bass - Nature genetics (2013)
  9. Whole-genome sequencing of nine esophageal adenocarcinoma cell lines. - Gianmarco Contino;Matthew D Eldridge;Maria Secrier;Lawrence Bower;Rachael Fels Elliott;Jamie Weaver;Andy G Lynch;Paul A W Edwards;Rebecca C Fitzgerald - F1000Research (2016)
  10. Endothelial RSPO3 Controls Vascular Stability and Pruning through Non-canonical WNT/Ca(2+)/NFAT Signaling. - Beate Scholz;Claudia Korn;Jessica Wojtarowicz;Carolin Mogler;Iris Augustin;Michael Boutros;Christof Niehrs;Hellmut G Augustin - Developmental cell (2016)

Literatures Citing This Work

  1. Genomic evolution of cancer models: perils and opportunities. - Uri Ben-David;Rameen Beroukhim;Todd R Golub - Nature reviews. Cancer (2019)
  2. The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic. - Alexander M Frankell;SriGanesh Jammula;Xiaodun Li;Gianmarco Contino;Sarah Killcoyne;Sujath Abbas;Juliane Perner;Lawrence Bower;Ginny Devonshire;Emma Ococks;Nicola Grehan;James Mok;Maria O’Donovan;Shona MacRae;Matthew D Eldridge;Simon Tavaré; ;Rebecca C Fitzgerald - Nature genetics (2019)
  3. Current Status of Patient-Derived Ovarian Cancer Models. - Yoshiaki Maru;Yoshitaka Hippo - Cells (2019)
  4. Preclinical Modelling of PDA: Is Organoid the New Black? - Sabrina D’Agosto;Silvia Andreani;Aldo Scarpa;Vincenzo Corbo - International journal of molecular sciences (2019)
  5. Establishment and characterization of patient-derived organoids from a young patient with cervical clear cell carcinoma. - Yoshiaki Maru;Naotake Tanaka;Keiko Ebisawa;Akiko Odaka;Takahiro Sugiyama;Makiko Itami;Yoshitaka Hippo - Cancer science (2019)
  6. Xenograft and organoid model systems in cancer research. - Margit Bleijs;Marc van de Wetering;Hans Clevers;Jarno Drost - The EMBO journal (2019)
  7. Disease modelling in human organoids. - Madeline A Lancaster;Meritxell Huch - Disease models & mechanisms (2019)
  8. Biological Significance of Tumor Heterogeneity in Esophageal Squamous Cell Carcinoma. - Lehang Lin;De-Chen Lin - Cancers (2019)
  9. In Silico Drug Prescription for Targeting Cancer Patient Heterogeneity and Prediction of Clinical Outcome. - Elena Piñeiro-Yáñez;María José Jiménez-Santos;Gonzalo Gómez-López;Fátima Al-Shahrour - Cancers (2019)
  10. Context is everything: aneuploidy in cancer. - Uri Ben-David;Angelika Amon - Nature reviews. Genetics (2020)

… (180 more literatures)

© 2025 MaltSci - We reshape scientific research with AI technology