Axel Bengtsson1, Roland Andersson1, Jonas Rahm1, Karthik Ganganna1, Bodil Andersson1, Daniel Ansari2. 1. Department of Surgery, Clinical Sciences Lund, Skåne University Hospital, Lund University, Skåne University Hospital, Lund, SE-221 85, Lund, Sweden. 2. Department of Surgery, Clinical Sciences Lund, Skåne University Hospital, Lund University, Skåne University Hospital, Lund, SE-221 85, Lund, Sweden. daniel.ansari@med.lu.se.
Abstract
BACKGROUND: Pancreatic ductal adenocarcinoma has the lowest survival rate among all major cancers and is the third leading cause of cancer-related mortality. The stagnant survival statistics and dismal response rates to current therapeutics highlight the need for more efficient preclinical models. Patient-derived organoids (PDOs) offer new possibilities as powerful preclinical models able to account for interpatient variability. Organoid development can be divided into four different key phases: establishment, propagation, drug screening and response prediction. Establishment entails tailored tissue extraction and growth protocols, propagation requires consistent multiplication and passaging, while drug screening and response prediction will benefit from shorter and more precise assays, and clear decision-making tools. CONCLUSIONS: This review attempts to outline the most important challenges that remain in exploiting organoid platforms for drug discovery and clinical applications. Some of these challenges may be overcome by novel methods that are under investigation, such as 3D bioprinting systems, microfluidic systems, optical metabolic imaging and liquid handling robotics. We also propose an optimized organoid workflow inspired by all technical solutions we have presented.
BACKGROUND:Pancreatic ductal adenocarcinoma has the lowest survival rate among all major cancers and is the third leading cause of cancer-related mortality. The stagnant survival statistics and dismal response rates to current therapeutics highlight the need for more efficient preclinical models. Patient-derived organoids (PDOs) offer new possibilities as powerful preclinical models able to account for interpatient variability. Organoid development can be divided into four different key phases: establishment, propagation, drug screening and response prediction. Establishment entails tailored tissue extraction and growth protocols, propagation requires consistent multiplication and passaging, while drug screening and response prediction will benefit from shorter and more precise assays, and clear decision-making tools. CONCLUSIONS: This review attempts to outline the most important challenges that remain in exploiting organoid platforms for drug discovery and clinical applications. Some of these challenges may be overcome by novel methods that are under investigation, such as 3D bioprinting systems, microfluidic systems, optical metabolic imaging and liquid handling robotics. We also propose an optimized organoid workflow inspired by all technical solutions we have presented.
Entities:
Keywords:
Drug screening; Organoids; Pancreatic cancer; Personalized medicine
Authors: Valerie M Weaver; Sophie Lelièvre; Johnathon N Lakins; Micah A Chrenek; Jonathan C R Jones; Filippo Giancotti; Zena Werb; Mina J Bissell Journal: Cancer Cell Date: 2002-09 Impact factor: 31.743
Authors: Lola Rahib; Benjamin D Smith; Rhonda Aizenberg; Allison B Rosenzweig; Julie M Fleshman; Lynn M Matrisian Journal: Cancer Res Date: 2014-06-01 Impact factor: 12.701
Authors: Xingnan Li; Lincoln Nadauld; Akifumi Ootani; David C Corney; Reetesh K Pai; Olivier Gevaert; Michael A Cantrell; Paul G Rack; James T Neal; Carol W-M Chan; Trevor Yeung; Xue Gong; Jenny Yuan; Julie Wilhelmy; Sylvie Robine; Laura D Attardi; Sylvia K Plevritis; Kenneth E Hung; Chang-Zheng Chen; Hanlee P Ji; Calvin J Kuo Journal: Nat Med Date: 2014-05-25 Impact factor: 87.241
Authors: Željka P Kačarević; Patrick M Rider; Said Alkildani; Sujith Retnasingh; Ralf Smeets; Ole Jung; Zrinka Ivanišević; Mike Barbeck Journal: Materials (Basel) Date: 2018-11-06 Impact factor: 3.623
Authors: Benjamin Bian; Natalia Anahi Juiz; Odile Gayet; Martin Bigonnet; Nicolas Brandone; Julie Roques; Jérôme Cros; Nenghui Wang; Nelson Dusetti; Juan Iovanna Journal: Front Oncol Date: 2019-06-05 Impact factor: 6.244
Authors: John Kokkinos; Anya Jensen; George Sharbeen; Joshua A McCarroll; David Goldstein; Koroush S Haghighi; Phoebe A Phillips Journal: Cancers (Basel) Date: 2021-05-17 Impact factor: 6.639