Evidence map›Paper›PMID 40062730›Full record

ReviewCancer medicine2025

Analyze the Diversity and Function of Immune Cells in the Tumor Microenvironment From the Perspective of Single-Cell RNA Sequencing.

Lujuan Ma, Yu Luan, Lin Lu

Abstract readReview
In one paragraph

Review in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

3 authors.

Lujuan MaDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
Yu LuanDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0000-7802-7092
Lin LuDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0001-6000-0895

Funding

Guangzhou Planned Project of Science and Technology 2023A03J0966The Natural Science Foundation of Guangdong Province, China 2021A1515011113
6 · The paper itself

Abstract

backgroundCancer development is closely associated with complex alterations in the tumor microenvironment (TME). Among these, immune cells within the TME play a huge role in personalized tumor diagnosis and treatment.

objectivesThis review aims to summarize the diversity of immune cells in the TME, their impact on patient prognosis and treatment response, and the contributions of single-cell RNA sequencing (scRNA-seq) in understanding their functional heterogeneity.

methodsWe analyzed recent studies utilizing scRNA-seq to investigate immune cell populations in the TME, focusing on their interactions and regulatory mechanisms.

resultsScRNA-seq reveals the functional heterogeneity of immune cells, enhances our understanding of their role in tumor antibody responses, and facilitates the construction of immune cell interaction networks. These insights provide guidance for the development of cancer immunotherapies and personalized treatment approaches.

conclusionApplying scRNA-seq to immune cell analysis in the TME offers a novel pathway for personalized cancer treatment. Despite its promise, several challenges remain, highlighting the need for further advancements to fully integrate scRNA-seq into clinical applications.

Indexed as

NeoplasmsSingle-Cell AnalysisTumor MicroenvironmentAnimalsHumansPrecision MedicinePrognosisSequence Analysis, RNAcancerimmune cellssingle‐cell sequencingtumor microenvironment

Identifiers

PMID40062730
PMCPMC11891933

What Socratic 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 Socratic graph.