Multiregion Genomic Analysis of Serially Transplanted Patient-derived Xenograft Tumors

Overview

Journal Cancer Genomics Proteomics

Specialties Biochemistry
Genetics
Oncology

Date 2018 Dec 28

PMID 30587497

Citations 5

Authors

Kuniaki Sato

Atsushi Niida

Takaaki Masuda

Dai Shimizu

Taro Tobo

Yousuke Kuroda

Hidetoshi Eguchi

Takashi Nakagawa

Yutaka Suzuki

Koshi Mimori

Affiliations

Soon will be listed here.

Abstract

Background: Intratumoral heterogeneity (ITH) is a major cause underlying therapeutic difficulty of cancer. Although an understanding of ITH is critically important in order to develop novel therapeutic strategies, experimental models that enable the examination of ITH in a time series are lacking.

Materials And Methods: We developed an experimental approach based on patient-derived xenograft (PDX) mice and a multiregional sequencing approach (MRA). The multiple regions of primary colorectal cancer (CRC) and serially transplanted PDX tumors were analyzed via whole-exome sequencing and bioinformatic analyses.

Results: Our PDX-MRA of CRC indicated the spatiotemporal genetic transition of ITH. It was found that the subclonal architecture of CRC dynamically changes during serial transplantation. Furthermore, our data suggest that environmental selective pressures drive the development of minor pre-existing subclones in PDX-MRA.

Conclusion: PDX-MRA is a useful tool for understanding the spatiotemporal dynamics of ITH.

Citing Articles

Patient-derived xenograft models in cancer therapy: technologies and applications.

Liu Y, Wu W, Cai C, Zhang H, Shen H, Han Y Signal Transduct Target Ther. 2023; 8(1):160.

PMID: 37045827 PMC: 10097874. DOI: 10.1038/s41392-023-01419-2.

Patient-Derived Xenografts Are a Reliable Preclinical Model for the Personalized Treatment of Epithelial Ovarian Cancer.

Chen J, Jin Y, Li S, Qiao C, Peng X, Li Y Front Oncol. 2021; 11:744256.

PMID: 34671560 PMC: 8522495. DOI: 10.3389/fonc.2021.744256.

Deciphering Tumor Heterogeneity in Hepatocellular Carcinoma (HCC)-Multi-Omic and Singulomic Approaches.

Dhanasekaran R Semin Liver Dis. 2021; 41(1):9-18.

PMID: 33764481 PMC: 8136683. DOI: 10.1055/s-0040-1722261.

A unified simulation model for understanding the diversity of cancer evolution.

Niida A, Hasegawa T, Innan H, Shibata T, Mimori K, Miyano S PeerJ. 2020; 8:e8842.

PMID: 32296600 PMC: 7150545. DOI: 10.7717/peerj.8842.

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies.

Oshi M, Okano M, Maiti A, Rashid O, Saito K, Kono K Cancers (Basel). 2020; 12(2).

PMID: 32074948 PMC: 7072242. DOI: 10.3390/cancers12020444.

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