Evidence map›Paper›PMID 34000441›Full record

ReviewGenomics, proteomics & bioinformatics2021

Single-cell Analysis Technologies for Immuno-oncology Research: from Mechanistic Delineation to Biomarker Discovery.

Zhiliang Bai, Graham Su, Rong Fan

Open access · goldAbstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.6field-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

11 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. The metastasis landscape ofFrontiers in immunology · 2026
    Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
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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 at 3 institutions in 2 countries.

Zhiliang BaiDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511, USA; State Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China.
Graham SuDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511, USA.
Rong FanDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511, USA; Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT 06511, USA; Human and Translational Immunology, Yale School of Medicine, New Haven, CT 06511, USA. Electronic address: rong.fan@yale.edu.
Tianjin University · CNYale Cancer Center · USYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The successes with immune checkpoint blockade (ICB) and chimeric antigen receptor (CAR)-T-cell therapy in treating multiple cancer types have established immunotherapy as a powerful curative option for patients with advanced cancers. Unfortunately, many patients do not derive benefit or long-term responses, highlighting a pressing need to perform complete investigation of the underlying mechanisms and the immunotherapy-induced tumor regression or rejection. In recent years, a large number of single-cell technologies have leveraged advances in characterizing immune system, profiling tumor microenvironment, and identifying cellular heterogeneity, which establish the foundations for lifting the veil on the comprehensive crosstalk between cancer and immune system during immunotherapies. In this review, we introduce the applications of the most widely used single-cell technologies in furthering our understanding of immunotherapies in terms of underlying mechanisms and their association with therapeutic outcomes. We also discuss how single-cell analyses help to deliver new insights into biomarker discovery to predict patient response rate, monitor acquired resistance, and support prophylactic strategy development for toxicity management. Finally, we provide an overview of applying cutting-edge single-cell spatial-omics to point out the heterogeneity of tumor-immune interactions at higher level that can ultimately guide to the rational design of next-generation immunotherapies.

Indexed as

NeoplasmsSingle-Cell AnalysisBiomarkersHumansImmunotherapyTumor MicroenvironmentBiomarkersBiomarker discoveryCAR-TCheckpoint blockadeImmunotherapySingle-cell analysis

Identifiers

PMID34000441
PMCPMC8602396
OpenAlexW3159997702

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.