Evidence map›Paper›PMID 41169094›Full record

ReviewClinical and translational medicine2025

Clinical application of single-cell RNA sequencing in disease and therapy.

Aisha Shigna Nadukkandy, Sowmiya Kalaiselvan, Lin Lin, Yonglun Luo

Abstract readReview
In one paragraph

Review in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Emerging technologies and current challenges in intratumoral microbiota research.Frontiers in cellular and infection microbiology · 2025
    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

4 authors.

Aisha Shigna NadukkandyDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.
Sowmiya KalaiselvanDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.
Lin LinDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.
Yonglun LuoDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.ORCID 0000-0002-0007-7759

Funding

Innovationsfonden 9355 PIECRISCIInnovative Health Initiative Joint Undertaking 101165643Lundbeck Foundation R396-2022-350Novo Nordisk Fonden NNF21OC0068988Novo Nordisk Fonden NNF21OC0072031
6 · The paper itself

Abstract

backgroundThe emergence of single-cell RNA sequencing (scRNA-seq) technology has revolutionized our capacity to study cell functions in complex tissue microenvironments. Traditional transcriptomic approaches, such as microarrays and bulk RNA sequencing, lacked the resolution to distinguish signals from heterogeneous cell populations or rare cell types, limiting their clinical utility. Since 2009, scRNA-seq has evolved as a new and powerful tool for revisiting somatic evolution and functions under physiological or pathological conditions. MAIN TOPICS COVERED: This review focus on elaborating on the clinical applications of scRNA-seq technology, with a particular emphasis on the application of scRNA-seq methods in revisiting the somatic cell evolution in human diseases. We further provide a snapshot of the scRNA-seq applications in biomarker discovery and drug development, current challenges associated with the technology, and future directions.

conclusionsWith the recent progresses in single cell and spatial transcriptome technologies, scRNA-seq enables a deeper understanding of the complexity of human diseases. The integration of AI and machine learning algorithms into big data analysis offers hope for overcoming these hurdles, potentially allowing scRNA-seq and multi-omics approaches to bridge the gap in our understanding of complex biological systems and advances the development of precision medicine. HIGHLIGHTS: This review provides a systematic overview of the application of scRNA-seq technology in understanding of disease mechanisms. We cover applications in respiratory diseases, metabolic disorders, cardiovascular diseases, cancers, autoimmune and auto-inflammatory diseases, neurodegenerative diseases, and infectious diseases. This review also explores promises and challenges for the emerging application of scRNA-seq in drug discovery.

Indexed as

Sequence Analysis, RNASingle-Cell AnalysisHumanssingle‐cell RNA sequencingthe dawn of a new genome medicine era

Identifiers

PMID41169094
PMCPMC12576031

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.