Open AccessPolyisocyanide Hydrogels as a Tunable Platform for Mammary Gland Organoid Formation
Author(s) -
Zhang Ying,
Tang Chunling,
Span Paul N.,
Rowan Alan E.,
Aalders Tilly W.,
Schalken Jack A.,
Adema Gosse J.,
Kouwer Paul H. J.,
Zegers Mirjam M. P.,
Ansems Marleen
Publication year - 2020
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202001797
Subject(s) - organoid , self healing hydrogels , extracellular matrix , regenerative medicine , matrix (chemical analysis) , mammary gland , progenitor cell , microbiology and biotechnology , spheroid , chemistry , in vitro , nanotechnology , biology , materials science , stem cell , biochemistry , genetics , cancer , breast cancer , organic chemistry , chromatography
In the last decade, organoid technology has developed as a primary research tool in basic biological and clinical research. The reliance on poorly defined animal‐derived extracellular matrix, however, severely limits its application in regenerative and translational medicine. Here, a well‐defined, synthetic biomimetic matrix based on polyisocyanide (PIC) hydrogels that support efficient and reproducible formation of mammary gland organoids (MGOs) in vitro is presented. Only decorated with the adhesive peptide RGD for cell binding, PIC hydrogels allow MGO formation from mammary fragments or from purified single mammary epithelial cells. The cystic organoids maintain their capacity to branch for over two months, which is a fundamental and complex feature during mammary gland development. It is found that small variations in the 3D matrix give rise to large changes in the MGO: the ratio of the main cell types in the MGO is controlled by the cell–gel interactions via the cell binding peptide density, whereas gel stiffness controls colony formation efficiency, which is indicative of the progenitor density. Simple hydrogel modifications will allow for future introduction and customization of new biophysical and biochemical parameters, making the PIC platform an ideal matrix for in depth studies into organ development and for application in disease models.