Evidence map›Paper›PMID 42653150›Full record

ArticleInternational journal of molecular sciences2026

Integrative Analysis of Gene and Protein Expression Data Reveals Novel Clusters for Ovarian Cancer Prognosis.

Jisup Kim, Seong Beom Cho

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. 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

2 authors.

Jisup KimDepartment of Pathology, Gil Medical Center, College of Medicine, Gachon University, Incheon 21565, Republic of Korea.ORCID 0000-0002-0742-5517
Seong Beom ChoDepartment of Biomedical Informatics, Gil Medical Center, College of Medicine, Gachon University, Incheon 21565, Republic of Korea.ORCID 0000-0002-5734-1645

Funding

Ministry of Science and ICT RS-2022-NR070832
6 · The paper itself

Abstract

Ovarian cancer exhibits clinical heterogeneity; reliable prognostic stratification remains challenging despite extensive biomarker research. We performed an integrative analysis of transcriptomic and proteomic data to identify prognostically distinct molecular clusters in ovarian cancer. Using The Cancer Genome Atlas dataset, RNA sequencing and reverse-phase protein array data from 146 overlapping samples were analyzed. Genes (

Indexed as

Biomarkers, TumorGene Expression Regulation, NeoplasticOvarian NeoplasmsActininCluster AnalysisClustering AlgorithmsFemaleGene Expression ProfilingHumansMultiomicsPrognosisProteomicsTranscriptomeActininACTN4 protein, humanBiomarkers, Tumorgene–protein co–expressionmulti–omics integrationovarian cancerprognostic clusteringsurvival analysis

Identifiers

PMID42653150
PMCPMC13513427

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.