Evidence map›Paper›PMID 28769933›Full record

ReviewFrontiers in immunology2017

Reprogramming of Tumor-Associated Macrophages with Anticancer Therapies: Radiotherapy versus Chemo- and Immunotherapies.

Géraldine Genard, Stéphane Lucas, Carine Michiels

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 224 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
224citing papers in PubMed, 1 pooled it
17.1field-weighted citation impact, top 1% 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

224 citing papers in PubMed, 1 synthesis or guideline pooled it, 410 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review

164 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

3 authors at 1 institution in 1 country.

Géraldine GenardURBC - NARILIS, University of Namur, Namur, Belgium.
Stéphane LucasLaboratory of Analysis by Nuclear Reaction (LARN/PMR) - NARILIS, University of Namur, Namur, Belgium.
Carine MichielsURBC - NARILIS, University of Namur, Namur, Belgium.
University of Namur · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor-associated macrophages (TAMs) play a central role in tumor progression, metastasis, and recurrence after treatment. Macrophage plasticity and diversity allow their classification along a M1-M2 polarization axis. Tumor-associated macrophages usually display a M2-like phenotype, associated with pro-tumoral features whereas M1 macrophages exert antitumor functions. Targeting the reprogramming of TAMs toward M1-like macrophages would thus be an efficient way to promote tumor regression. This can be achieved through therapies including chemotherapy, immunotherapy, and radiotherapy (RT). In this review, we first describe how chemo- and immunotherapies can target TAMs and, second, we detail how RT modifies macrophage phenotype and present the molecular pathways that may be involved. The identification of irradiation dose inducing macrophage reprogramming and of the underlying mechanisms could lead to the design of novel therapeutic strategies and improve synergy in combined treatments.

Indexed as

chemotherapynuclear factor kappa Bpolarization immunotherapyradiotherapyreactive oxygen speciesreprogrammingtumor-associated macrophages

Identifiers

PMID28769933
PMCPMC5509958
OpenAlexW2735818385

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.