Loss of

Jacob Haagsma, Yudith Ramos Valdes, Xuejin Ou, Rasheduzzaman Rashu, S M Mansour Haeryfar, Jim Petrik, Trevor G Shepherd

Abstract read

In one paragraph

Article in Oncotarget, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Jacob HaagsmaThe Mary and John Knight Translational Ovarian Cancer Research Unit, Verspeeten Family Cancer Centre, London, ON, Canada.

Yudith Ramos ValdesThe Mary and John Knight Translational Ovarian Cancer Research Unit, Verspeeten Family Cancer Centre, London, ON, Canada.

Xuejin OuDepartment of Microbiology and Immunology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.

Rasheduzzaman RashuDepartment of Microbiology and Immunology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.

S M Mansour HaeryfarDepartment of Microbiology and Immunology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.

Jim PetrikDepartment of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.

Trevor G ShepherdThe Mary and John Knight Translational Ovarian Cancer Research Unit, Verspeeten Family Cancer Centre, London, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian high-grade serous carcinoma (HGSC) is an aggressive disease with an urgent need for improved therapies. Immunotherapies have proved useful for some cancers but have failed to provide benefits for HGSC. Improving our understanding of the mechanisms regulating the HGSC tumor microenvironment will facilitate the discovery of novel immunotherapies and help predict patient response. To this end, the development of syngeneic models is imperative to recapitulate immune responses observed in patients with HGSC. Yet, few syngeneic HGSC mouse models exist that accurately reflect the initiation and disease progression of human disease. In this study, we developed a syngeneic model reflecting both the site of origin and the genotype of early HGSC disease by deleting

Indexed as

Cystadenocarcinoma, SerousOvarian NeoplasmsT-LymphocytesTumor Suppressor Protein p53AnimalsCell Line, TumorDisease Models, AnimalFemaleHumansMiceMice, Inbred C57BLMice, KnockoutPhenotypeSignal TransductionTumor MicroenvironmentTrp53 protein, mouseTumor Suppressor Protein p53high-grade serous ovarian carcinomainflammationmicroenvironmentorthotopic models

Identifiers

PMID40982347

DOI10.18632/oncotarget.28768

PMCPMC12453223

What Socratic holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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 Socratic graph.