Evidence map›Paper›PMID 42277572›Full record

ReviewJournal of cellular and molecular medicine2026

Immune Landscape and Tumour Heterogeneity in Ovarian Cancer: Insights From Single-Cell RNA Sequencing.

Sihan Chen, Ghada Moh Samir Elhessewi, Helen Cai, Wedad M Alawad, Manoj Kumar Mishra, Usamah Sayed

Abstract readReview
In one paragraph

Review in Journal of cellular and molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. International journal of molecular sciences · 2026
    Review
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

6 authors.

Sihan ChenENT Clinical Fellow, University Hospitals Bristol and Weston, Bristol Royal Infirmary, Bristol, UK.
Ghada Moh Samir ElhessewiDepartment of Health Sciences, College of Health and Rehabilitation Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Helen CaiMiddlesex Business School, Middlesex University, London, UK.
Wedad M AlawadDepartment of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia.
Manoj Kumar MishraSalale University, Fitche, Ethiopia.
Usamah SayedFaculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumour heterogeneity is a key factor in cancer progression, with immune responses within the tumour microenvironment (TME) contributing significantly to treatment resistance and immunotherapy outcomes. Recent advances in single-cell RNA sequencing (scRNA-seq) have provided unprecedented insights into the diverse immune cell populations infiltrating tumours, including both innate immune cells like dendritic cells, neutrophils, macrophages, and natural killer (NK) cells, as well as adaptive immune cells such as T lymphocytes. The immune landscape of tumours is complex and dynamic, characterised by a mixture of activated and suppressed immune states that evolve over time. The degree of immune cell infiltration varies among tumour types and disease stages, influencing tumour response to therapies. For example, ovarian cancer typically exhibits weaker immune infiltration compared to cancers like melanoma and non-small cell lung cancer. Increased CD8+ T cell infiltration is generally associated with favourable prognosis, while elevated regulatory T cells (Tregs) can suppress anti-tumour immune responses. The use of scRNA-seq has enabled detailed profiling of immune cells, revealing the roles of exhausted T cells and immunosuppressive macrophages in the TME. This high resolution approach facilitates the identification of distinct immune cell subsets and their functional states, providing a platform for developing more targeted, personalised immunotherapies. The findings offer promising avenues for improving clinical outcomes in ovarian cancer and other malignancies through refined immune profiling.

Indexed as

Ovarian NeoplasmsSequence Analysis, RNASingle-Cell Gene Expression AnalysisTumor MicroenvironmentAnimalsFemaleGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingT-Cell ExhaustionBioinformaticsimmune heterogeneityimmunotherapyovarian cancersingle‐cell RNA sequencingtumour microenvironment

Identifiers

PMID42277572
PMCPMC13259974

What OpenQuestion holds

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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.