Evidence map›Paper›PMID 29594035›Full record

ReviewFrontiers in oncology2018

Targeting Macrophages in Cancer: From Bench to Bedside.

Ashleigh R Poh, Matthias Ernst

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 314 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
314citing papers in PubMed, 1 pooled it
–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

314 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Prognostic Role of CD68British journal of biomedical science · 2023
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  17. Sonodynamic biomimetic-nanomedicine fight cancers.Journal of nanobiotechnology · 2025
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254 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

2 authors.

Ashleigh R PohOlivia Newton-John Cancer Research Institute, and La Trobe University School of Cancer Medicine, Heidelberg, VIC, Australia.
Matthias ErnstOlivia Newton-John Cancer Research Institute, and La Trobe University School of Cancer Medicine, Heidelberg, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macrophages are a major component of the tumor microenvironment and orchestrate various aspects of immunity. Within tumors, macrophages can reversibly alter their endotype in response to environmental cues, including hypoxia and stimuli derived from other immune cells, as well as the extracellular matrix. Depending on their activation status, macrophages can exert dual influences on tumorigenesis by either antagonizing the cytotoxic activity immune cells or by enhancing antitumor responses. In most solid cancers, increased infiltration with tumor-associated macrophages (TAMs) has long been associated with poor patient prognosis, highlighting their value as potential diagnostic and prognostic biomarkers in cancer. A number of macrophage-centered approaches to anticancer therapy have been investigated, and include strategies to block their tumor-promoting activities or exploit their antitumor effector functions. Integrating therapeutic strategies to target TAMs to complement conventional therapies has yielded promising results in preclinical trials and warrants further investigation to determine its translational benefit in human cancer patients. In this review, we discuss the molecular mechanisms underlying the pro-tumorigenic programming of macrophages and provide a comprehensive update of macrophage-targeted therapies for the treatment of solid cancers.

Indexed as

cancerimmunotherapyinflammationmacrophage polarizationmacrophages

Identifiers

PMID29594035
PMCPMC5858529

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.