Evidence map›Paper›PMID 33473192›Full record

ReviewCellular & molecular immunology2021

Tumor-associated myeloid cells: diversity and therapeutic targeting.

Alberto Mantovani, Federica Marchesi, Sebastien Jaillon, Cecilia Garlanda, Paola Allavena

Abstract readReview
In one paragraph

Review in Cellular & molecular immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers.

0numbers the graph read from it
0cells of the map it votes in
131citing 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

131 citing papers in PubMed.

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  12. The double-positive cells in the tumor microenvironment.Journal of translational internal medicine · 2026
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71 more citing papers are in PubMed but not listed here.

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.

Alberto MantovaniDepartment of Immunology and Inflammation, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy. Alberto.mantovani@humanitasresearch.it.
Federica MarchesiDepartment of Immunology and Inflammation, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy.
Sebastien JaillonDepartment of Immunology and Inflammation, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy.
Cecilia GarlandaDepartment of Immunology and Inflammation, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy.ORCID http://orcid.org/0000-0002-1510-7703
Paola AllavenaDepartment of Immunology and Inflammation, Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myeloid cells in tumor tissues constitute a dynamic immune population characterized by a non-uniform phenotype and diverse functional activities. Both tumor-associated macrophages (TAMs), which are more abundantly represented, and tumor-associated neutrophils (TANs) are known to sustain tumor cell growth and invasion, support neoangiogenesis and suppress anticancer adaptive immune responses. In recent decades, several therapeutic approaches have been implemented in preclinical cancer models to neutralize the tumor-promoting roles of both TAMs and TANs. Some of the most successful strategies have now reached the clinic and are being investigated in clinical trials. In this review, we provide an overview of the recent literature on the ever-growing complexity of the biology of TAMs and TANs and the development of the most promising approaches to target these populations therapeutically in cancer patients.

Indexed as

AnimalsHumansImmunotherapyMyeloid CellsNeoplasmsNeutrophilsTumor-Associated Macrophagesmacrophage targetingtumor-associated macrophagestumor microenvironment

Identifiers

PMID33473192
PMCPMC8027665

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.