Evidence map›Paper›PMID 34681023›Full record

ReviewGenes2021

High-Dimensional Single-Cell Transcriptomics in Melanoma and Cancer Immunotherapy.

Camelia Quek, Xinyu Bai, Georgina V Long, Richard A Scolyer, James S Wilmott

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Role of CD4Journal of translational medicine · 2025
    Review
  3. Article
  4. CD39Frontiers in oncology · 2025
    Review
  5. Review
  6. Review
  7. Article
  8. 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

5 authors at 1 institution in 1 country.

Camelia QuekMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2006, Australia.
Xinyu BaiMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2006, Australia.ORCID 0000-0003-4212-1938
Georgina V LongMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2006, Australia.
Richard A ScolyerMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2006, Australia.ORCID 0000-0002-8991-0013
James S WilmottMelanoma Institute Australia, The University of Sydney, Sydney, NSW 2006, Australia.
The University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in single-cell transcriptomics have greatly improved knowledge of complex transcriptional programs, rapidly expanding our knowledge of cellular phenotypes and functions within the tumour microenvironment and immune system. Several new single-cell technologies have been developed over recent years that have enabled expanded understanding of the mechanistic cells and biological pathways targeted by immunotherapies such as immune checkpoint inhibitors, which are now routinely used in patient management with high-risk early-stage or advanced melanoma. These technologies have method-specific strengths, weaknesses and capabilities which need to be considered when utilising them to answer translational research questions. Here, we provide guidance for the implementation of single-cell transcriptomic analysis platforms by reviewing the currently available experimental and analysis workflows. We then highlight the use of these technologies to dissect the tumour microenvironment in the context of cancer patients treated with immunotherapy. The strategic use of single-cell analytics in clinical settings are discussed and potential future opportunities are explored with a focus on their use to rationalise the design of novel immunotherapeutic drug therapies that will ultimately lead to improved cancer patient outcomes.

Indexed as

ImmunotherapyHumansMelanomaSingle-Cell AnalysisTranscriptomeTumor Microenvironmentcancerdiagnosisimmunotherapymelanomasequencingsingle-cellspatialtranscriptomicstreatment

Identifiers

PMID34681023
PMCPMC8535767
OpenAlexW3205349475

What OpenQuestion 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 OpenQuestion graph.