Evidence map›Paper›PMID 37578622›Full record

ArticleHandbook of experimental pharmacology2024

Nanomedicine - Immune System Interactions: Limitations and Opportunities for the Treatment of Cancer.

Sara Elsafy, Josbert Metselaar, Twan Lammers

Abstract read
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In one paragraph

Article in Handbook of experimental pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Article
  3. 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 at 1 institution in 1 country.

Sara ElsafyDepartment of Nanomedicine and Theranostics, Institute for Experimental Molecular Imaging (ExMI), Center for Biohybrid Medical Systems (CBMS), University Hospital RWTH Aachen, Aachen, Germany.
Josbert MetselaarDepartment of Nanomedicine and Theranostics, Institute for Experimental Molecular Imaging (ExMI), Center for Biohybrid Medical Systems (CBMS), University Hospital RWTH Aachen, Aachen, Germany.
Twan LammersDepartment of Nanomedicine and Theranostics, Institute for Experimental Molecular Imaging (ExMI), Center for Biohybrid Medical Systems (CBMS), University Hospital RWTH Aachen, Aachen, Germany. tlammers@ukaachen.de.
RWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanoparticles interact with immune cells in many different ways. These interactions are crucially important for determining nanoparticles' ability to be used for cancer therapy. Traditionally, strategies such as PEGylation have been employed to reduce (the kinetics of) nanoparticle uptake by immune cells, to endow them with long circulation properties, and to enable them to exploit the Enhanced Permeability and Retention (EPR) effect to accumulate in tumors. More recently, with immunotherapy becoming an increasingly important cornerstone in the clinical management of cancer, ever more research efforts in academia and industry are focusing on specifically targeting immune cells with nanoparticles. In this chapter, we describe the barriers and opportunities of immune cell targeting with nanoparticles, and we discuss how nanoparticle-based drug delivery to specific immune cell populations in tumors as well as in secondary myeloid and lymphoid organs (such as bone marrow, lymph nodes, and spleen) can be leveraged to boost the efficacy of cancer immunotherapy.

Indexed as

NanomedicineNeoplasmsDrug Delivery SystemsHumansImmune SystemImmunotherapyCancerImmune cellsImmunotherapyMacrophageNanoparticle

Identifiers

PMID37578622
OpenAlexW4385799344

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.