Evidence map›Paper›PMID 32272497›Full record

ReviewJournal of leukocyte biology2020

Unravelling the heterogeneity and dynamic relationships of tumor-infiltrating T cells by single-cell RNA sequencing analysis.

Xin Yu, Lei Zhang, Ashutosh Chaudhry, Aaron S Rapaport, Wenjun Ouyang

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of leukocyte biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

21 citing papers in PubMed, 28 citations in OpenAlex.

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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

5 authors at 2 institutions in 2 countries.

Xin YuDepartment of Inflammation and Oncology, Amgen Research, Amgen Inc., South San Francisco, California, USA.
Lei ZhangBeijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
Ashutosh ChaudhryDepartment of Inflammation and Oncology, Amgen Research, Amgen Inc., South San Francisco, California, USA.
Aaron S RapaportDepartment of Inflammation and Oncology, Amgen Research, Amgen Inc., South San Francisco, California, USA.
Wenjun OuyangDepartment of Inflammation and Oncology, Amgen Research, Amgen Inc., South San Francisco, California, USA.
Amgen (United States) · USPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

T cells are crucial for the success of immune-based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor-infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor-infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single-cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single-cell RNA sequencing technology and current strategies to uncover heterogeneous tumor-infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)-based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential.

Indexed as

TranscriptomeCell CommunicationGene ExpressionGenetic HeterogeneityHumansLymphocyte ActivationLymphocytes, Tumor-InfiltratingNeoplasmsReceptors, Antigen, T-CellRNA, NeoplasmSequence Analysis, RNASingle-Cell AnalysisT-Lymphocyte SubsetsTumor MicroenvironmentReceptors, Antigen, T-CellRNA, Neoplasmcancer microenvironmentexhausted T cellsmemory T cellsregulatory T cellssingle-cell RNA sequencingTCR-based lineage tracingtumor-infiltrating T cells

Identifiers

PMID32272497
PMCPMC7317876
OpenAlexW3015367336

What OpenQuestion holds

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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.