Evidence map›Paper›PMID 42206767›Full record

ArticleInternational journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists2026

p53 Normal and p53 Abnormal Clear Cell Ovarian Carcinomas: Clinical Characteristics and Biomarker Profiles.

Piret Hellberg, Annukka Pasanen, Jonna Similä-Maarala, Ralf Bützow, Heini Lassus

Abstract read
In one paragraph

Article in International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

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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

5 authors.

Piret HellbergDepartment of Obstetrics and Gynecology, Gynecologic Oncology.ORCID 0000-0002-9119-1820
Annukka PasanenDepartment of Pathology.
Jonna Similä-MaaralaDepartment of Pathology.
Ralf BützowDepartment of Pathology.
Heini LassusDepartment of University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new concept of molecular classification for clear cell ovarian carcinoma (CCOC) has been proposed: TP53 wild-type and TP53 mutated. Our aim was to evaluate this classification at the immunohistochemical level in p53 normal and abnormal subgroups. Clinicopathologic factors and 12 immunohistochemical biomarkers (p53, PR, ER, β-catenin, vimentin, ARID1A, HNF1-β, E-cadherin, c-erb-B2, MIB-1, p16, and L1CAM) and patient prognosis were analyzed in 132 CCOCs. The p53 abnormal group presented with significantly worse disease-specific overall survival (DSS) and disease-free survival (DFS) than the p53 normal group, which was largely due to higher stage and a more frequent presence of residual tumor in the p53 abnormal group. Furthermore, higher stage and presence of residual tumor were markers of poor outcome within both p53 subgroups. Interestingly, the presence of ascites was related to shorter DSS only in p53 normal cases. The p53 normal group was also characterized by a higher frequency of ARID1A loss and HNF1-β positivity, whereas p16 overexpression and ER positivity were more common in p53 abnormal cases. Interestingly, ARID1A loss correlated with poor DSS in the p53 abnormal group. In the p53 normal tumors, ER positivity was associated with better DSS and p16 positivity with worse DFS. L1CAM positivity was associated with residual tumor only in the p53 normal group. Our findings support the existence of 2 distinct molecular subgroups of CCOC, p53 normal and p53 abnormal, with diverse characteristics and patient outcomes. Clinical and molecular differences were discovered within these subgroups.

Indexed as

Adenocarcinoma, Clear CellBiomarkers, TumorOvarian NeoplasmsTumor Suppressor Protein p53AdultAgedAged, 80 and overDisease-Free SurvivalDNA-Binding ProteinsFemaleHumansImmunohistochemistryMiddle AgedNuclear ProteinsPrognosisTranscription FactorsARID1A protein, humanBiomarkers, TumorDNA-Binding ProteinsNuclear ProteinsTP53 protein, humanTranscription FactorsTumor Suppressor Protein p53BiomarkersClear cell ovarian carcinomap53 abnormalp53 normalSurvival

Identifiers

PMID42206767
PMCPMC13460317

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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.