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Reversing the Tumor Target: Establishment of a Tumor Trap

Authors: Mathie Najberg; Mathie Najberg; Muhammad Haji Mansor; Muhammad Haji Mansor; Frank Boury; Carmen Alvarez-Lorenzo; Emmanuel Garcion;

Reversing the Tumor Target: Establishment of a Tumor Trap

Abstract

Despite the tremendous progress made in the field of cancer therapy in recent years, certain solid tumors still cannot be successfully treated. Alongside classical treatments in the form of chemotherapy and/or radiotherapy, targeted treatments such as immunotherapy that cause fewer side effects emerge as new options in the clinics. However, these alternative treatments may not be useful for treating all types of cancers, especially for killing infiltrative and circulating tumor cells (CTCs). Recent advances pursue the trapping of these cancer cells within a confined area to facilitate their removal for therapeutic and diagnostic purposes. A good understanding of the mechanisms behind tumor cell migration may drive the design of traps that mimic natural tumor niches and guide the movement of the cancer cells. To bring this trapping idea into reality, strong efforts are being made to create structured materials that imitate myelinated fibers, blood vessels, or pre-metastatic niches and incorporate chemical cues such as chemoattractants or adhesive proteins. In this review, the different strategies used (or could be used) to trap tumor cells are described, and relevant examples of their performance are analyzed.

Countries
Spain, France
Keywords

Pharmacology, Cancer therapy, [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer, Tumor cell migration, RM1-950, Biomimetic trap, tumor cell migration, Premetastatic niche recruitment, Tumor trap, tumor trap, cancer therapy, [SDV.IB]Life Sciences [q-bio]/Bioengineering, biomimetic trap, Therapeutics. Pharmacology, premetastatic niche recruitment

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Average
Top 10%
Green
gold
Related to Research communities
Cancer Research