Evidence map›Paper›PMID 38983795›Full record

ReviewMedicine international

Myeloid‑derived suppressor cells as targets of emerging therapies and nanotherapies (Review).

Dileep Kumar, Victor Carlos Da Silva, Natalia Lemos Chaves

Abstract readReview
In one paragraph

Review in Medicine international. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
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.

Dileep KumarDepartment of Genetics and Morphology, Institutes of Biological Sciences, University of Brasilia, Brasilia, DF 70910-900, Brazil.
Victor Carlos Da SilvaMicroscopy and Microanalysis Laboratory, Institutes of Biological Sciences, University of Brasilia, Brasilia, DF 70910-900, Brazil.
Natalia Lemos ChavesDepartment of Genetics and Morphology, Institutes of Biological Sciences, University of Brasilia, Brasilia, DF 70910-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is the leading cause of cancer-related mortality among women worldwide. Immunotherapies are a promising approach in cancer treatment, particularly for aggressive forms of BC with high mortality rates. However, the current eligibility for immunotherapy remains limited to a limited fraction of patients with BC. Myeloid-derived suppressor cells (MDSCs), originating from myeloid cells, are known for their dual role in immunosuppression and tumor promotion, significantly affecting patient outcomes by fostering the formation of premetastatic niches. Consequently, targeting MDSCs has emerged as a promising avenue for further exploration in therapeutic interventions. Leveraging nanotechnology-based drug delivery systems, which excel in accumulating drugs within tumors via passive or active targeting mechanisms, are a promising strategy for the use of MDSCs in the treatment of BC. The present review discusses the immunosuppressive functions of MDSCs, their role in BC, and the diverse strategies for targeting them in cancer therapy. Additionally, the present review discusses future advancements in BC treatments focusing on MDSCs. Furthermore, it elucidates the mechanisms underlying MDSC activation, recruitment and differentiation in BC progression, highlighting the clinical characteristics that render MDSCs suitable candidates for the therapy and targeted nanotherapy of BC.

Indexed as

breast cancerimmunosuppressionimmunotherapymyeloid-derived suppressor cellsnanotherapytumor microenvironment

Identifiers

PMID38983795
PMCPMC11228699

What OpenQuestion holds

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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.