Literature DB >> 32579167

Establishing metastatic patient-derived xenograft model for colorectal cancer.

Yanmei Zhang1, Sau Har Lee2, Cheng Wang3, Yunhe Gao4, Jiyang Li4, Wei Xu5,6.   

Abstract

BACKGROUND: Patient-derived xenograft model is a powerful and promising tool for drug discovery and cancer biology studies. The application of previous metastatic colorectal cancer models has been greatly limited by its low success rate and long time to develop metastasis. Therefore, in this study, we aim to describe an optimized protocol for faster establishment of colorectal cancer metastatic patient-derived xenograft mouse models.
METHODS: Smaller micro tissues (˂150 μm in diameter) mixed with Matrigel were engrafted subcutaneously into NSG mice to generate the passage 1 (P1) patient-derived xenograft. The micro tumours from P1 patient-derived xenograft were then excised and orthotopically xenografted into another batch of NSG mice to generate a metastatic colorectal cancer patient-derived xenograft, P2. Haematoxylin and eosin and immunohistochemistry staining were performed to compare the characters between patient-derived xenograft tumours and primary tumours.
RESULTS: About 16 out of 18 P1 xenograft models successfully grew a tumour for 50.8 ± 5.1 days (success rate 89.9%). Six out of eight P1 xenograft models originating from metastatic patients successfully grew tumours in the colon and metastasized to liver or lung in the NSG recipients for 60.9 ± 4.5 days (success rate 75%). Histological examination of both P1 and P2 xenografts closely resembled the histological architecture of the original patients' tumours. Immunohistochemical analysis revealed similar biomarker expression levels, including CDH17, Ki-67, active β-catenin, Ki-67 and α smooth muscle actin when compared with the original patients' tumours. The stromal components that support the growth of patient-derived xenograft tumours were of murine origin.
CONCLUSIONS: Metastatic patient-derived xenograft mouse model could be established with shorter time and higher success rate. Although the patient-derived xenograft tumours were supported by the stromal cells of murine origin, they retained the dominant characters of the original patient tumours.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  PDX; colorectal cancer; metastasis; orthotopic xenograft

Year:  2020        PMID: 32579167     DOI: 10.1093/jjco/hyaa089

Source DB:  PubMed          Journal:  Jpn J Clin Oncol        ISSN: 0368-2811            Impact factor:   3.019


  5 in total

1.  An Orthotopic Patient-Derived Xenograft (PDX) Model Allows the Analysis of Metastasis-Associated Features in Colorectal Cancer.

Authors:  Maria Laura De Angelis; Federica Francescangeli; Chiara Nicolazzo; Eljona Xhelili; Filippo La Torre; Lidia Colace; Alessandro Bruselles; Daniele Macchia; Sara Vitale; Paola Gazzaniga; Marta Baiocchi; Ann Zeuner
Journal:  Front Oncol       Date:  2022-06-28       Impact factor: 5.738

Review 2.  Patient-derived xenograft (PDX) models, applications and challenges in cancer research.

Authors:  Shahrokh Abdolahi; Zeinab Ghazvinian; Samad Muhammadnejad; Mahshid Saleh; Hamid Asadzadeh Aghdaei; Kaveh Baghaei
Journal:  J Transl Med       Date:  2022-05-10       Impact factor: 8.440

3.  Monitoring of tumor growth and vascularization with repetitive ultrasonography in the chicken chorioallantoic-membrane-assay.

Authors:  Jonas Eckrich; Philipp Kugler; Christoph Raphael Buhr; Benjamin Philipp Ernst; Simone Mendler; Jan Baumgart; Juergen Brieger; Nadine Wiesmann
Journal:  Sci Rep       Date:  2020-10-29       Impact factor: 4.379

Review 4.  Patient-derived tumor models: a more suitable tool for pre-clinical studies in colorectal cancer.

Authors:  Giulia Rizzo; Andrea Bertotti; Simonetta Maria Leto; Stefania Vetrano
Journal:  J Exp Clin Cancer Res       Date:  2021-06-01

Review 5.  Biomarkers and cell-based models to predict the outcome of neoadjuvant therapy for rectal cancer patients.

Authors:  Aylin Alkan; Tobias Hofving; Eva Angenete; Ulf Yrlid
Journal:  Biomark Res       Date:  2021-07-28
  5 in total

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