Patient-derived organoids (PDOs) generated from adult stem cells present in tissues are invaluable tools for translational cancer research (Drost, Clevers, Nat Rev Cancer 18(7):407-418, 2018). The generation of this 3D cultures is not trivial and requires dedicated procedures. Despite the rapid increase in the use of organoids in cancer research, it is noteworthy that published procedures regarding their generation often lack critical information and standardized protocols remain elusive. Addressing these limitations, the protocol described in this chapter offers an in-depth and comprehensive guide to establishing, expanding, and freezing gastrointestinal PDOs obtained from normal and tumor tissue biopsies. Notably, it also provides valuable insights in the form of tips and tricks to guide and overcome potential challenges that may arise during the procedure.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/978-1-0716-3730-2_9 | DOI Listing |
Background: Although invasiveness is one of the major determinants of the poor glioblastoma (GBM) outcome, the mechanisms of GBM invasion are only partially understood. Among the intrinsic and environmental processes promoting cell-to-cell interaction processes, eventually driving GBM invasion, we focused on the pro-invasive role played by Extracellular Vesicles (EVs), a heterogeneous group of cell-released membranous structures containing various bioactive cargoes, which can be transferred from donor to recipient cells.
Methods: EVs isolated from patient-derived GBM cell lines and surgical aspirates were assessed for their pro-migratory competence by spheroid migration assays, calcium imaging, and PYK-2/FAK phosphorylation.
Clin Cancer Res
January 2025
ACTREC, Tata Memorial Centre, Navi Mumbai, Maharashtra, India.
Purpose: Identifying therapeutic targets for Signet Ring Cell Carcinoma (SRCC) of the colon and rectum is a clinical challenge due to the lack of Patient-Derived Organoids (PDO) or Xenografts (PDX). We present a robust method to establish PDO and PDX models to answer address this unmet need. We demonstrate that these models identify novel therapeutic strategies targeting therapy resistance and peritoneal metastasis.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved a novel machine learning-based method to computationally screen, in a high-throughput manner, the effects of enzyme perturbations predicted by a computational model of CRC metabolism.
View Article and Find Full Text PDFMol Cancer Ther
January 2025
University of Michigan-Ann Arbor, Ann Arbor, MI, United States.
Up to 90% of high-grade serous ovarian cancer (HGSC) patients will develop resistance to platinum-based chemotherapy, posing substantial therapeutic challenges due to a lack of universally druggable targets. Leveraging BenevolentAI's AI-driven approach to target discovery, we screened potential AI-predicted therapeutic targets mapped to unapproved tool compounds in patient-derived 3D models. This identified TNIK, which is modulated by NCB-0846, as a novel target for platinum-resistant HGSC.
View Article and Find Full Text PDFBio Protoc
January 2025
Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Recurrent hormone receptor-positive (HR+) breast cancer is a leading cause of cancer mortality in women. Recurrence and resistance to targeted therapies have been difficult to study due to the long clinical course of the disease, the complex nature of resistance, and the lack of clinically relevant model systems. Existing models are limited to a few HR+ cell lines, organoid models, and patient-derived xenograft models, all lacking components of the human tumor microenvironment.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!