Evidence map›Paper›PMID 41033072›Full record

ReviewTranslational oncology2025

Selective antitumor activity of Tumor Treating Fields (TTFields) involving molecular factors in cancer cells and tumor microenvironment.

Ilaria Fuso Nerini, Rosy Amodeo, Maurizio D'Incalci, Monica Lupi

Abstract readReview
In one paragraph

Review in Translational oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Ilaria Fuso NeriniLaboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
Rosy AmodeoLaboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Maurizio D'IncalciLaboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Monica LupiLaboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy. Electronic address: monica.lupi@humanitasresearch.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The local application of low-intensity electric fields at intermediate frequencies (Tumor Treating Fields - TTFields) has emerged as an effective anticancer treatment in conjunction with chemotherapy and immunotherapy for several solid tumors. Despite this progress, the phenotypic and genetic determinants underlying tumor sensitivity to TTFields remain largely unexplored, representing a critical gap in our understanding. This review provides a comprehensive analysis of preclinical and translational studies describing the cellular factors that influence the anticancer properties of TTFields. An overview of recent omics studies on the complex cellular and molecular processes initiated by TTFields has revealed important mechanisms of action that warrant further investigation for their therapeutic potential. The goal is to identify effects that can be leveraged to develop rational, synergistic co-treatments with anticancer agents that have complementary modes of action. In particular, the ability of TTFields to modulate the tumor microenvironment and reverse the local and systemic immunosuppression could represent a promising strategy to enhance the efficacy of immunotherapy across different tumor types.

Indexed as

Anticancer therapyPreclinical studiesSolid tumorsTumor microenvironmentTumor Treating Fields (TTFields)

Identifiers

PMID41033072
PMCPMC12517075

What OpenQuestion holds

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Registered trials

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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.