Literature DB >> 29458007

A Genomically Characterized Collection of High-Grade Serous Ovarian Cancer Xenografts for Preclinical Testing.

Paulina Cybulska1, Jocelyn M Stewart2, Azin Sayad3, Carl Virtanen3, Patricia A Shaw4, Blaise Clarke4, Natalie Stickle3, Marcus Q Bernardini5, Benjamin G Neel6.   

Abstract

High-grade serous ovarian cancer (HGSC) is the leading cause of morbidity and mortality from gynecologic malignant tumors. Overall survival remains low because of the nearly ubiquitous emergence of platinum resistance and the paucity of effective next-line treatments. Current cell culture-based models show limited similarity to HGSC and are therefore unreliable predictive models for preclinical evaluation of investigational drugs. This deficiency could help explain the low overall rate of successful drug development and the decades of largely unchanged approaches to HGSC treatment. We used gene expression, copy number variation, and exome sequencing analyses to credential HGSC patient-derived xenografts (PDXs) as effective preclinical models that recapitulate the features of human HGSC. Mice bearing PDXs were also treated with standard-of-care carboplatin therapy. PDXs showed similar sensitivity to carboplatin as the patient's tumor at the time of sampling. PDXs also recapitulated the diversity of genomic alterations (copy number variation and mutation profiles) previously described in large data sets that profiled HGSC. Furthermore, mRNA profiling showed that the PDXs represent all HGSC subtypes with the exception of the immunoreactive group. Credentialing of PDX models of HGSC should aid progress in HGSC research by providing improved preclinical models of HGSC that can be used to test novel targets and more accurately evaluate their likelihood of success.
Copyright © 2018 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29458007     DOI: 10.1016/j.ajpath.2018.01.019

Source DB:  PubMed          Journal:  Am J Pathol        ISSN: 0002-9440            Impact factor:   4.307


  12 in total

1.  Short-term organoid culture for drug sensitivity testing of high-grade serous carcinoma.

Authors:  Hui Chen; Kristin Gotimer; Cristabelle De Souza; Clifford G Tepper; Anthony N Karnezis; Gary S Leiserowitz; Jeremy Chien; Lloyd H Smith
Journal:  Gynecol Oncol       Date:  2020-04-04       Impact factor: 5.482

2.  Noninvasive prediction of residual disease for advanced high-grade serous ovarian carcinoma by MRI-based radiomic-clinical nomogram.

Authors:  Haiming Li; Rui Zhang; Ruimin Li; Wei Xia; Xiaojun Chen; Jiayi Zhang; Songqi Cai; Yong'ai Li; Shuhui Zhao; Jinwei Qiang; Weijun Peng; Yajia Gu; Xin Gao
Journal:  Eur Radiol       Date:  2021-04-16       Impact factor: 5.315

3.  Genetically Defined, Syngeneic Organoid Platform for Developing Combination Therapies for Ovarian Cancer.

Authors:  Shuang Zhang; Sonia Iyer; Hao Ran; Igor Dolgalev; Shengqing Gu; Wei Wei; Connor J R Foster; Cynthia A Loomis; Narciso Olvera; Fanny Dao; Douglas A Levine; Robert A Weinberg; Benjamin G Neel
Journal:  Cancer Discov       Date:  2020-11-06       Impact factor: 39.397

4.  Patient-derived ovarian cancer organoids capture the genomic profiles of primary tumours applicable for drug sensitivity and resistance testing.

Authors:  Yoshiko Nanki; Tatsuyuki Chiyoda; Akira Hirasawa; Aki Ookubo; Manabu Itoh; Masaru Ueno; Tomoko Akahane; Kaori Kameyama; Wataru Yamagami; Fumio Kataoka; Daisuke Aoki
Journal:  Sci Rep       Date:  2020-07-28       Impact factor: 4.379

5.  Targeting HER2 in patient-derived xenograft ovarian cancer models sensitizes tumors to chemotherapy.

Authors:  Faye R Harris; Piyan Zhang; Lin Yang; Xiaonan Hou; Konstantinos Leventakos; Saravut J Weroha; George Vasmatzis; Irina V Kovtun
Journal:  Mol Oncol       Date:  2018-12-21       Impact factor: 6.603

Review 6.  Current Status of Patient-Derived Ovarian Cancer Models.

Authors:  Yoshiaki Maru; Yoshitaka Hippo
Journal:  Cells       Date:  2019-05-25       Impact factor: 6.600

7.  A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity.

Authors:  Louisa Nelson; Anthony Tighe; Anya Golder; Samantha Littler; Bjorn Bakker; Daniela Moralli; Syed Murtuza Baker; Ian J Donaldson; Diana C J Spierings; René Wardenaar; Bethanie Neale; George J Burghel; Brett Winter-Roach; Richard Edmondson; Andrew R Clamp; Gordon C Jayson; Sudha Desai; Catherine M Green; Andy Hayes; Floris Foijer; Robert D Morgan; Stephen S Taylor
Journal:  Nat Commun       Date:  2020-02-13       Impact factor: 14.919

8.  PIK3R1W624R Is an Actionable Mutation in High Grade Serous Ovarian Carcinoma.

Authors:  Concetta D'Ambrosio; Jessica Erriquez; Maddalena Arigoni; Sonia Capellero; Gloria Mittica; Eleonora Ghisoni; Fulvio Borella; Dionyssios Katsaros; Silvana Privitera; Marisa Ribotta; Elena Maldi; Giovanna Di Nardo; Enrico Berrino; Tiziana Venesio; Riccardo Ponzone; Marco Vaira; Douglas Hall; Mercedes Jimenez-Linan; Anna L Paterson; Raffaele A Calogero; James D Brenton; Giorgio Valabrega; Maria Flavia Di Renzo; Martina Olivero
Journal:  Cells       Date:  2020-02-14       Impact factor: 7.666

Review 9.  Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: pre-clinical updates.

Authors:  Magdalena Cybula; Magdalena Bieniasz
Journal:  Oncotarget       Date:  2022-03-24

Review 10.  Characteristics of in Vivo Model Systems for Ovarian Cancer Studies.

Authors:  Patrycja Tudrej; Katarzyna Aleksandra Kujawa; Alexander Jorge Cortez; Katarzyna Marta Lisowska
Journal:  Diagnostics (Basel)       Date:  2019-09-14
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