| Chapter title |
Modelling Intestinal Carcinogenesis Using In Vitro Organoid Cultures
|
|---|---|
| Chapter number | 4 |
| Book title |
Inflammation and Cancer
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7568-6_4 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7567-9, 978-1-4939-7568-6
|
| Authors |
Thierry Jardé, Genevieve Kerr, Reyhan Akhtar, Helen E. Abud |
| Abstract |
Mouse models of intestinal carcinogenesis are very powerful for studying the impact of specific mutations on tumour initiation and progression. Mutations can be studied both singularly and in combination using conditional alleles that can be induced in a temporal manner. The steps in intestinal carcinogenesis are complex and can be challenging to image in live animals at a cellular level. The ability to culture intestinal epithelial tissue in three-dimensional organoids in vitro provides an accessible system that can be genetically manipulated and easily visualised to assess specific biological impacts in living tissue. Here, we describe methodology for conditional mutation of genes in organoids from genetically modified mice via induction of Cre recombinase induced by tamoxifen or by transient exposure to TAT-Cre protein. This methodology provides a rapid platform for assessing the cellular changes induced by specific mutations in intestinal tissue. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 18% |
| Student > Bachelor | 4 | 18% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Doctoral Student | 2 | 9% |
| Student > Master | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 7 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Nursing and Health Professions | 1 | 5% |
| Unspecified | 1 | 5% |
| Immunology and Microbiology | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 7 | 32% |