Evidence map›Paper›PMID 42332817›Full record

ReviewJournal of ovarian research2026

Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.

Usamah Sayed, Shaker Al-Hasnaawei, Hayjaa Mohaisen-Mousa, Renuka Jyothi-S, Priya Priyadarshini-Nayak, Bethanney Janney-J, Gurjant Singh, Ashish Singh-Chauhan, Manoj Kumar-Mishra

Abstract readReview
In one paragraph

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.

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

9 authors.

Usamah SayedFaculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.
Shaker Al-HasnaaweiCollege of pharmacy, the Islamic University, Najaf, Iraq.
Hayjaa Mohaisen-MousaDepartment of Medicinal chemistry, Al-Turath University, Al Mansour, Baghdad, 10013, Iraq.
Renuka Jyothi-SDepartment of Biotechnology and Genetics, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Priya Priyadarshini-NayakDepartment of Medical Oncology, IMS and SUM Hospital, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, 751003, Odisha, India.ORCID http://orcid.org/0009-0001-8421-3630
Bethanney Janney-JDepartment of Biomedical, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India.
Gurjant SinghDepartment of Physiotherapy, University Institute of Allied Health Sciences, Chandigarh University, Chandigarh, Punjab, India.
Ashish Singh-ChauhanDivision of research and innovation, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India.
Manoj Kumar-MishraSalale University, Fitche, Ethiopia. biopolymer714@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Ovarian NeoplasmsPrecision MedicineSequence Analysis, RNASingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorFemaleHumansMultiomicsSingle-Cell Gene Expression AnalysisBiomarkers, TumorOvarian cancerPrecision oncologySingle-cell RNA sequencingStromal cellsTumor microenvironment

Identifiers

PMID42332817
PMCPMC13543436

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.