ArticleCancer medicine2025
Transcriptome Concordance Between Borderline Tumors and Endometrioid Carcinoma: An Integrative Genomic Analysis.
Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Misdiagnosis of Endometrioid Borderline Ovarian Tumors by Intraoperative Frozen Section Pathology: A Case Report and Review of the Literature.The American journal of case reports · 2026Review
- Clinicopathological Diagnosis and Prognosis of Endometrioid Borderline Ovarian Tumors: Dual Case Reports and Literature Review.Cancer reports (Hoboken, N.J.) · 2025Review
- Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundBorderline ovarian tumors (BOTs) differ from ovarian carcinomas in their clinical presentation and behavior, yet their molecular characteristics remain poorly understood. This study aims to address this gap by integrating whole-exome sequencing (WES) and RNA sequencing (RNA-seq) to compare BOTs with high-grade serous carcinoma (HGSC), endometrioid carcinoma (EC), and clear-cell carcinoma (CCC).
objectiveTo elucidate the molecular features of BOTs and evaluate their similarities and differences in comparison to HGSC, EC, and CCC.
methodsThe study analyzed 44 ovarian tumor samples, employing WES to identify genomic alterations and RNA-seq to examine transcriptomic profiles. Comparative analyses were conducted to investigate the molecular relationships among the tumor types.
resultsThe genomic analysis revealed that BOTs share significant similarities with EC. Furthermore, the transcriptomic data highlighted a novel and substantial similarity between BOTs and EC, suggesting deeper biological linkages, including potentially shared oncogenic pathways or tumor microenvironmental factors. These findings challenge traditional classifications and suggest a closer molecular alignment of BOTs with EC than previously understood.
conclusionsThis study provides new insights into the molecular characteristics of BOTs, demonstrating their significant resemblance to EC at both the genomic and transcriptomic levels. These results underscore the potential need to reconsider the molecular classification of ovarian tumors and open new avenues for research into the pathogenesis and treatment strategies for BOTs.
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