Evidence map›Paper›PMID 35551664›Full record

ReviewCancer treatment and research2022

The Single-Cell Level Perspective of the Tumor Microenvironment and Its Remodeling by CAR-T Cells.

Sanxing Gao, Ryohichi Sugimura

Abstract readReview
PubMed Publisher
In one paragraph

Review in Cancer treatment and research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.5field-weighted citation impact, top 13% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Sanxing GaoSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Ryohichi SugimuraSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong. Rios@hku.hk.
University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tumor microenvironment (TME) is a complex milieu consisting of lymphoid cells, myeloid cells, fibroblasts, and multiple molecules, which play a key role in tumor progression and immunotherapy. TME is characterized by immune-suppressive features, which release anti-inflammatory cytokines such as IL-4 and TGFβ to skew the T cells to a Th2 state as well to polarize tumor-associated macrophages (TAMs) to an anti-inflammatory phenotype to curb the immunotherapy. Considering the heterogeneity of the TME and its role in determining response to chimeric antigen receptor (CAR)-T cells, delineating TME at a single-cell level will provide useful information for cancer treatment. First, we discuss cellular and molecular features that curb the response to CAR-T cells, for example, high expression of immune checkpoint molecules (PD-1, LAG3) and anti-inflammatory cytokines (IL-4, TGFb) that block CAR-T cell function. Then, we summarize how newly invented single-cell technologies such as spatial multi-omics would benefit the understanding of cancer immunotherapy. Finally, we will further describe recent attempts of CAR-T to remodel TME by arming the CAR-T with anti-PD-1 single-chain variants or Th1 triggering cytokines (such as IL-7, IL-12) to remodel TME into a pro-inflammatory state. Herein, we review the single-cell-level signatures of TME and the strategies of CAR-T to remodel TME.

Indexed as

NeoplasmsReceptors, Chimeric AntigenHumansImmunotherapy, AdoptiveInterleukin-4T-LymphocytesTumor MicroenvironmentInterleukin-4Receptors, Chimeric Antigen

Identifiers

PMID35551664
OpenAlexW4285263024

What OpenQuestion holds

Textmetadata
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.