Evidence map›Paper›PMID 41588777›Full record

ArticleBiotechnology and applied biochemistry2026

Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late-Stage, Recurrent, and Metastatic Tumors.

Vandana Yadav, Aruna Sivaram, Renu Vyas

Abstract read
In one paragraph

Article in Biotechnology and applied biochemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Vandana YadavMIT ADTU School of Bioengineering Sciences & Research, MIT Art Design and Technology University, Pune, Maharashtra, India.
Aruna SivaramMIT ADTU School of Bioengineering Sciences & Research, MIT Art Design and Technology University, Pune, Maharashtra, India.ORCID https://orcid.org/0000-0003-4942-4114
Renu VyasMIT ADTU School of Bioengineering Sciences & Research, MIT Art Design and Technology University, Pune, Maharashtra, India.

Funding

CSIR HRDG for awarding a PhD research fellowshipCSIR SRF for the first authorMIT ADT UniversityMIT School of Bioengineering Sciences & Research, MIT Art Design and Technology University, for infrastructure support
6 · The paper itself

Abstract

Ovarian Cancer is a leading cause of mortality among women globally, primarily due to lack of specific and sensitive early-stage diagnostic tools. This study aims to identify hub genes associated with recurrent, late-stage, and metastatic tumors as potential prognostic biomarkers and drug targets. Gene expression data from eight National Center for Biotechnology Information (NCBI)-Gene Expression Omnibus (GEO) datasets were categorized by recurrence, tumor-stage, and metastasis. Differential gene expression and enrichment analyses were performed. Hub genes were identified by protein-protein interaction networks and validated by the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), GEPIA2, pROC, and Kaplan-Meier plotter databases. Genetic alterations, immune cell infiltration, miRNA prediction, and drug-gene interactions were assessed using cBioPortal, CIBERSORTx, Encyclopedia of RNA Interactomes (ENCORI), and Drug-Gene Interaction Database (DGIdb), respectively. Eight hub genes (FN1, COL1A1, COL1A2, COL3A1, POSTN, LUM, IGF1, and CXCL8) were identified, with COL1A2 common across all tumor categories. Note that 19.6% of cases showed mutations in these genes, primarily COL3A1. Overexpression of most hub genes and reduced expression of CXCL8 correlated with worse survival outcomes. COL1A1 and FN1 showed strong diagnostic ability. Late-stage tumors showed elevated M2 macrophages and neutrophils. hsa-miR-29a-3p, hsa-miR-29b-3p, and hsa-miR-29c-3p were identified as the most interactive miRNAs. Ocriplasmin and pamidronate were identified as potential therapeutics. Our findings highlight the therapeutic relevance of these hub genes and identify them as potential drug targets and prognostic biomarkers in ovarian cancer.

Indexed as

Biomarkers, TumorNeoplasm Recurrence, LocalOvarian NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsNeoplasm MetastasisNeoplasm StagingPrognosisBiomarkers, TumorMicroRNAsbiomarkerdifferential gene expressiondrug targetimmune cell infiltrationmetastatic tumormicroarraymiRNAovarian cancerrecurrent tumorsurvival analysis

Identifiers

PMID41588777
PMCPMC13446421

What OpenQuestion holds

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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.