ReviewJournal of ovarian research2026
Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.
Review in Journal of ovarian research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OC) remains a leading cause of mortality among gynecological malignancies, largely due to profound inter- and intra-tumoral heterogeneity and the critical influence of the tumor microenvironment (TME). Comprising immune, stromal, endothelial, and extracellular matrix components, the TME orchestrates tumor progression, metastasis, and therapeutic resistance. Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of OC by providing high-resolution insights into rare cellular subpopulations, dynamic transcriptional programs, and intercellular communication networks. These advances have facilitated the discovery of prognostic biomarkers, immune signatures, and novel therapeutic targets. Moreover, integration of scRNA-seq with spatial transcriptomics, multi-omics platforms, and artificial intelligence has expanded its potential to capture cellular complexity and refine patient stratification. Despite current challenges, including underrepresentation of specific cell types, technical variability, and high cost, scRNA-seq continues to drive progress in precision oncology. This review highlights recent applications of single-cell technologies in ovarian cancer, underscores their role in decoding TME biology, and explores future directions toward clinical translation and personalized therapeutic strategies.
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Registered trials
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.