Evidence map›Paper›PMID 35012638›Full record

ArticleGenome medicine2022

Patient-derived xenograft models capture genomic heterogeneity in endometrial cancer.

Vanessa F Bonazzi, Olga Kondrashova, Deborah Smith, Katia Nones, Asmerom T Sengal, Robert Ju, Leisl M Packer, Lambros T Koufariotis, Stephen H Kazakoff, Aimee L Davidson and 13 more

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
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  5. Antitumor activity of rucaparib plus PLX038A in serous endometrial carcinoma.Journal of experimental & clinical cancer research : CR · 2025
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  17. Strategies for modelling endometrial diseases.Nature reviews. Endocrinology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors at 6 institutions in 1 country.

Vanessa F Bonazzi *School of Biomedical Sciences, Queensland University of Technology located at the Translational Research Institute, Brisbane, QLD, Australia.
Olga Kondrashova *Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Deborah SmithMater Health Services, South Brisbane, QLD, Australia.
Katia NonesDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Asmerom T SengalSchool of Biomedical Sciences, Queensland University of Technology located at the Translational Research Institute, Brisbane, QLD, Australia.
Robert JuSchool of Biomedical Sciences, Queensland University of Technology located at the Translational Research Institute, Brisbane, QLD, Australia.
Leisl M PackerSchool of Biomedical Sciences, Queensland University of Technology located at the Translational Research Institute, Brisbane, QLD, Australia.
Lambros T KoufariotisDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Stephen H KazakoffDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Aimee L DavidsonDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Priya Ramarao-MilneDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Vanessa LakisDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Felicity NewellDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Rebecca RogersMater Pathology, Mater Research, Brisbane, QLD, Australia.
Claire DaviesMater Pathology, Mater Research, Brisbane, QLD, Australia.
James NicklinThe Wesley Hospital, Auchenflower, QLD, Australia.
Andrea GarrettThe Wesley Hospital, Auchenflower, QLD, Australia.
Naven ChettyMater Health Services, South Brisbane, QLD, Australia.
Lewis PerrinMater Health Services, South Brisbane, QLD, Australia.
John V PearsonDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Ann-Marie PatchDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Nicola WaddellDepartment of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Pamela M PollockSchool of Biomedical Sciences, Queensland University of Technology located at the Translational Research Institute, Brisbane, QLD, Australia. pamela.pollock@qut.edu.au.ORCID 0000-0001-8420-1026
QIMR Berghofer Medical Research Institute · AUTranslational Research Institute · AUThe University of Queensland · AUMater Health Services · AUMater Research · AUWesley Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprises four molecular subtypes with differing etiology, prognoses, and responses to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. As pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models.

methodsHere, we report whole exome or whole genome sequencing of 11 PDX models and their matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC.

resultsPDX models were successfully generated from grade 2/3 tumors, including three uterine carcinosarcomas. The models showed similar histomorphology to the primary tumors and represented all four molecular subtypes of EC, including five mismatch-repair deficient models. The different PDX lineages showed a wide range of inter-tumor and intra-tumor heterogeneity. However, for most PDX models, one arm recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease; however, all lacked the HR deficiency genomic signature.

conclusionsEC PDX models represent the four molecular subtypes of disease and can capture intra-tumor heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi; however, deeper and more durable responses will likely require combination of PARPi with other agents.

Indexed as

Antineoplastic AgentsEndometrial NeoplasmsFemaleGenomicsHeterograftsHumansPoly(ADP-ribose) Polymerase InhibitorsXenograft Model Antitumor AssaysAntineoplastic AgentsPoly(ADP-ribose) Polymerase InhibitorsEndometrial cancerGenomic characterizationGenomic scarringHomologous recombinationMutational signaturesPARP inhibitorsPatient-derived xenograftsTumor heterogeneity

Identifiers

PMID35012638
PMCPMC8751371
OpenAlexW4205684046

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.