Evidence map›Paper›PMID 36830713›Full record

ReviewBiomolecules2023

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment.

Jiayi Zhao, Yiwei Shi, Guangwen Cao

Abstract readReview
In one paragraph

Review in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. CCL24 recruits CCR3International journal of biological sciences · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Single-cell RNA sequencing: new insights for pulmonary endothelial cells.Frontiers in cell and developmental biology · 2025
    Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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.

Jiayi ZhaoDepartment of Epidemiology, Second Military Medical University, Shanghai 200433, China.
Yiwei ShiDepartment of Epidemiology, Second Military Medical University, Shanghai 200433, China.
Guangwen CaoDepartment of Epidemiology, Second Military Medical University, Shanghai 200433, China.ORCID 0000-0002-8094-1278

Funding

3-year public health program of Shanghai Health Commission GWV-10.1-XK17973 Program of China 2015CB554000National Natural Science Foundation of China 81520108021National Natural Science Foundation of China 81673250National Natural Science Foundation of China 91529305
6 · The paper itself

Abstract

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.

Indexed as

CognitionTumor MicroenvironmentHumansImmunotherapyInflammationSequence Analysis, RNAimmunologyinflammatory tumor microenvironmentscRNA-seq

Identifiers

PMID36830713
PMCPMC9953711

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.