Cancer Research and Treatment

Original Articles

Genetic Profiles Associated with Chemoresistance in Patient-Derived Xenograft Models of Ovarian Cancer: Lan Ying Li, Hee Jung Kim, Sun Ae Park, So Hyun Lee, Lee Kyung Kim, Jung Yun Lee, Sunghoon Kim, Young Tae Kim, Sang Wun Kim, Eun Ji Nam; Cancer Res Treat. 2019;51(3):1117-1127. Published online November 6, 2018; DOI: https://doi.org/10.4143/crt.2018.405

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Purpose
Recurrence and chemoresistance (CR) are the leading causes of death in patients with high-grade serous carcinoma (HGSC) of the ovary. The aim of this study was to identify genetic changes associated with CR mechanisms using a patient-derived xenograft (PDX) mouse model and genetic sequencing.
Materials and Methods
To generate a CR HGSC PDX tumor, mice bearing subcutaneously implanted HGSC PDX tumors were treated with paclitaxel and carboplatin. We compared gene expression and mutations between chemosensitive (CS) and CR PDX tumors with whole exome and RNA sequencing and selected candidate genes. Correlations between candidate gene expression and clinicopathological variables were explored using the Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (THPA).
Results
Three CR and four CS HGSC PDX tumor models were successfully established. RNA sequencing analysis of the PDX tumors revealed that 146 genes were significantly up-regulated and 54 genes down-regulated in the CR group compared with the CS group. Whole exome sequencing analysis showed 39 mutation sites were identified which only occurred in CR group. Differential expression of SAP25, HLA-DPA1, AKT3, and PIK3R5 genes and mutation of TMEM205 and POLR2A may have important functions in the progression of ovarian cancer chemoresistance. According to TCGA data analysis, patients with high HLA-DPA1 expression were more resistant to initial chemotherapy (p=0.030; odds ratio, 1.845).
Conclusion
We successfully established CR ovarian cancer PDX mouse models. PDX-based genetic profiling study could be used to select some candidate genes that could be targeted to overcome chemoresistance of ovarian cancer.

Citations

Citations to this article as recorded by

Creation and Validation of Patient-Derived Cancer Model Using Peritoneal and Pleural Effusion in Patients with Advanced Ovarian Cancer: An Early Experience
Ruri Nishie, Tomohito Tanaka, Kensuke Hirosuna, Shunsuke Miyamoto, Hikaru Murakami, Hiromitsu Tsuchihashi, Akihiko Toji, Shoko Ueda, Natsuko Morita, Sousuke Hashida, Atsushi Daimon, Shinichi Terada, Hiroshi Maruoka, Hiromi Konishi, Yuhei Kogata, Kohei Tan
Journal of Clinical Medicine.2024; 13(9): 2718. CrossRef
Uncovering miRNA–mRNA Regulatory Networks Related to Olaparib Resistance and Resensitization of BRCA2MUT Ovarian Cancer PEO1-OR Cells with the ATR/CHK1 Pathway Inhibitors
Łukasz Biegała, Damian Kołat, Arkadiusz Gajek, Elżbieta Płuciennik, Agnieszka Marczak, Agnieszka Śliwińska, Michał Mikula, Aneta Rogalska
Cells.2024; 13(10): 867. CrossRef
Patient-derived xenograft models in cancer therapy: technologies and applications
Yihan Liu, Wantao Wu, Changjing Cai, Hao Zhang, Hong Shen, Ying Han
Signal Transduction and Targeted Therapy.2023;[Epub] CrossRef
Deregulations of RNA Pol II Subunits in Cancer
Martina Muste Sadurni, Marco Saponaro
Applied Biosciences.2023; 2(3): 459. CrossRef
Transcriptome and Metabolome Analyses Reveal the Mechanism of Corpus Luteum Cyst Formation in Pigs
Jiage Dai, Jiabao Cai, Taipeng Zhang, Mingyue Pang, Xiaoling Xu, Jiahua Bai, Yan Liu, Yusheng Qin
Genes.2023; 14(10): 1848. CrossRef
Prediction of Chemoresistance—How Preclinical Data Could Help to Modify Therapeutic Strategy in High-Grade Serous Ovarian Cancer
Jacek Wilczyński, Edyta Paradowska, Justyna Wilczyńska, Miłosz Wilczyński
Current Oncology.2023; 31(1): 229. CrossRef
Personalization of Therapy in High-Grade Serous Tubo-Ovarian Cancer—The Possibility or the Necessity?
Jacek Wilczyński, Edyta Paradowska, Miłosz Wilczyński
Journal of Personalized Medicine.2023; 14(1): 49. CrossRef
PIK3R5 genetic predictors of hypertension induced by VEGF-pathway inhibitors
Julia C. F. Quintanilha, Alessandro Racioppi, Jin Wang, Amy S. Etheridge, Stefanie Denning, Carol E. Peña, Andrew D. Skol, Daniel J. Crona, Danyu Lin, Federico Innocenti
The Pharmacogenomics Journal.2022; 22(1): 82. CrossRef
AKT Isoforms Interplay in High-Grade Serous Ovarian Cancer Prognosis and Characterization
Eros Azzalini, Domenico Tierno, Michele Bartoletti, Renzo Barbazza, Giorgio Giorda, Fabio Puglisi, Sabrina Chiara Cecere, Nunzia Simona Losito, Daniela Russo, Giorgio Stanta, Vincenzo Canzonieri, Serena Bonin
Cancers.2022; 14(2): 304. CrossRef
Comparative analysis of cancer gene mutations using targeted sequencing in matched primary and recurrent gastric cancers after chemotherapy
Yeon-Ju Huh, Sung-Yup Cho, Min-Sun Cho, Kyoung-Eun Lee, Joo-Ho Lee
Genes & Genomics.2022; 44(11): 1425. CrossRef
Validation of a Patient-Derived Xenograft Model for Cervical Cancer Based on Genomic and Phenotypic Characterization
Shunsuke Miyamoto, Tomohito Tanaka, Kensuke Hirosuna, Ruri Nishie, Shoko Ueda, Sousuke Hashida, Shinichi Terada, Hiromi Konishi, Yuhei Kogata, Kohei Taniguchi, Kazumasa Komura, Masahide Ohmichi
Cancers.2022; 14(12): 2969. CrossRef
HCP5, as the sponge of miR-1291, facilitates AML cell proliferation and restrains apoptosis via increasing PIK3R5 expression
Yan Liu, Xue-Bing Jing, Zhen-Cheng Wang, Qing-Kun Han
Human Genomics.2021;[Epub] CrossRef
Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer
Sandra Muñoz-Galván, Amancio Carnero
Cancers.2021; 13(16): 4029. CrossRef
CD83, a Novel MAPK Signaling Pathway Interactor, Determines Ovarian Cancer Cell Fate
Aalia Batool, Hao Liu, Yi-Xun Liu, Su-Ren Chen
Cancers.2020; 12(8): 2269. CrossRef
A recombinant platform to characterize the role of transmembrane protein hTMEM205 in Pt(ii)-drug resistance and extrusion
Marc J Gallenito, Tahir S Qasim, Jasmine N Tutol, Ved Prakash, Sheel C Dodani, Gabriele Meloni
Metallomics.2020; 12(10): 1542. CrossRef
Function, Regulation and Biological Roles of PI3Kγ Variants
Bernd Nürnberg, Sandra Beer-Hammer
Biomolecules.2019; 9(9): 427. CrossRef

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Comparison of Clinical Features and Outcomes in Epithelial Ovarian Cancer according to Tumorigenicity in Patient-Derived Xenograft Models: Kyung Jin Eoh, Young Shin Chung, So Hyun Lee, Sun-Ae Park, Hee Jung Kim, Wookyeom Yang, In Ok Lee, Jung-Yun Lee, Hanbyoul Cho, Doo Byung Chay, Sunghoon Kim, Sang Wun Kim, Jae-Hoon Kim, Young Tae Kim, Eun Ji Nam; Cancer Res Treat. 2018;50(3):956-963. Published online October 17, 2017; DOI: https://doi.org/10.4143/crt.2017.181

Abstract PDF Supplementary Material PubReader ePub

Purpose
Although the use of xenograft models is increasing, few studies have compared the clinical features or outcomes of epithelial ovarian cancer (EOC) patients according to the tumorigenicity of engrafted specimens. The purpose of this study was to evaluate whether tumorigenicity was associated with the clinical features and outcomes of EOC patients.
Materials and Methods
Eighty-eight EOC patients who underwent primary or interval debulking surgery from June 2014 to December 2015 were included. Fresh tumor specimens were implanted subcutaneously on each flank of immunodeficient mice. Patient characteristics, progression-free survival (PFS), and germline mutation spectra were compared according to tumorigenicity.
Results
Xenografts were established successfully from 49 of 88 specimens. Tumorigenicity was associated with lymphovascular invasion and there was a propensity to engraft successfully with high-grade tumors. Tumors from patientswho underwent non-optimal (residual disease ≥ 1 cm) primary orinterval debulking surgery had a significantly greater propensity to achieve tumorigenicity than those who received optimal surgery. In addition, patients whose tumors became engrafted seemed to have a shorter PFS and more frequent germline mutations than patients whose tumors failed to engraft. Tumorigenicity was a significant factor for predicting PFS with advanced International Federation of Gynecology and Obstetrics stage and high-grade cancers.
Conclusions
Tumorigenicity in a xenograft model was a strong prognostic factor and was associated with more aggressive tumors in EOC patients. Xenograft models can be useful as a preclinical tool to predict prognosis and could be applied to further pharmacologic and genomic studies on personalized treatments.

Citations

Citations to this article as recorded by

TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer
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JCO Precision Oncology.2024;[Epub] CrossRef
Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice
Mingtang Zeng, Zijing Ruan, Jiaxi Tang, Maozhu Liu, Chengji Hu, Ping Fan, Xinhua Dai
Cancer Cell International.2023;[Epub] CrossRef
Cancer “Avatars”: Patient-Derived Xenograft Growth Correlation with Postoperative Recurrence and Survival in Pancreaticobiliary Cancer
Isaac T Lynch, Amro M Abdelrahman, Roberto Alva-Ruiz, Alessandro Fogliati, Rondell P Graham, Rory Smoot, Mark J Truty
Journal of the American College of Surgeons.2023; 237(3): 483. CrossRef
Identification of Prognostic Markers of Gynecologic Cancers Utilizing Patient-Derived Xenograft Mouse Models
Ha-Yeon Shin, Eun-ju Lee, Wookyeom Yang, Hyo Sun Kim, Dawn Chung, Hanbyoul Cho, Jae-Hoon Kim
Cancers.2022; 14(3): 829. CrossRef
Experimental models for ovarian cancer research
Sum In Tsang, Ayon A. Hassan, Sally K.Y. To, Alice S.T. Wong
Experimental Cell Research.2022; 416(1): 113150. CrossRef
Preclinical models of epithelial ovarian cancer: practical considerations and challenges for a meaningful application
Alessandra Ciucci, Marianna Buttarelli, Anna Fagotti, Giovanni Scambia, Daniela Gallo
Cellular and Molecular Life Sciences.2022;[Epub] CrossRef
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Tianyu Qin, Junpeng Fan, Funian Lu, Li Zhang, Chen Liu, Qiyue Xiong, Yang Zhao, Gang Chen, Chaoyang Sun
Journal of Experimental & Clinical Cancer Research.2022;[Epub] CrossRef
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The Journal of Pathology: Clinical Research.2021; 7(4): 338. CrossRef
Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review
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JHEP Reports.2020; 2(2): 100068. CrossRef
Patient-derived xenograft model engraftment predicts poor prognosis after surgery in patients with pancreatic cancer
Qi Chen, Tao Wei, Jianxin Wang, Qi Zhang, Jin Li, Jingying Zhang, Lei Ni, Yi Wang, Xueli Bai, Tingbo Liang
Pancreatology.2020; 20(3): 485. CrossRef
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Suad M. Abdirahman, Michael Christie, Adele Preaudet, Marie C. U. Burstroem, Dmitri Mouradov, Belinda Lee, Oliver M. Sieber, Tracy L. Putoczki
Cancers.2020; 12(9): 2340. CrossRef
High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints
Michael-Antony Lisio, Lili Fu, Alicia Goyeneche, Zu-hua Gao, Carlos Telleria
International Journal of Molecular Sciences.2019; 20(4): 952. CrossRef
Efficient use of patient-derived organoids as a preclinical model for gynecologic tumors
Yoshiaki Maru, Naotake Tanaka, Makiko Itami, Yoshitaka Hippo
Gynecologic Oncology.2019; 154(1): 189. CrossRef
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Cells.2019; 8(5): 505. CrossRef
Establishment of patient‐derived xenograft model in ovarian cancer and its influence factors analysis
Jianfa Wu, Yunxi Zheng, Qi Tian, Ming Yao, Xiaofang Yi
Journal of Obstetrics and Gynaecology Research.2019; 45(10): 2062. CrossRef
Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells
Ugo Testa, Eleonora Petrucci, Luca Pasquini, Germana Castelli, Elvira Pelosi
Medicines.2018; 5(1): 16. CrossRef

8,760 View
238 Download
18 Web of Science
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