Evidence map›Paper›PMID 33291749›Full record

ReviewCells2020

Tolerant/Persister Cancer Cells and the Path to Resistance to Targeted Therapy.

Mirna Swayden, Houssein Chhouri, Youssef Anouar, Luca Grumolato

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

29 citing papers in PubMed, 40 citations in OpenAlex.

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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 at 1 institution in 1 country.

Mirna SwaydenLaboratoire Différenciation et Communication Neuronale et Neuroendocrine, UNIROUEN, INSERM, Normandie Université, 76183 Rouen, France.
Houssein ChhouriLaboratoire Différenciation et Communication Neuronale et Neuroendocrine, UNIROUEN, INSERM, Normandie Université, 76183 Rouen, France.
Youssef AnouarLaboratoire Différenciation et Communication Neuronale et Neuroendocrine, UNIROUEN, INSERM, Normandie Université, 76183 Rouen, France.
Luca GrumolatoLaboratoire Différenciation et Communication Neuronale et Neuroendocrine, UNIROUEN, INSERM, Normandie Université, 76183 Rouen, France.ORCID 0000-0001-8231-3032
Inserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The capacity of cancer to adapt to treatment and evolve is a major limitation for targeted therapies. While the role of new acquired mutations is well-established, recent findings indicate that resistance can also arise from subpopulations of tolerant/persister cells that survive in the presence of the treatment. Different processes contribute to the emergence of these cells, including pathway rebound through the release of negative feedback loops, transcriptional rewiring mediated by chromatin remodeling and autocrine/paracrine communication among tumor cells and within the tumor microenvironment. In this review, we discuss the non-genetic mechanisms that eventually result in cancer resistance to targeted therapies, with a special focus on those involving changes in gene expression.

Indexed as

Antineoplastic AgentsCell Line, TumorDisease ProgressionDrug Resistance, NeoplasmHumansLung NeoplasmsMelanomaNeoplasmsPhenotypeProtein Kinase InhibitorsProto-Oncogene Proteins B-rafSignal TransductionSkin NeoplasmsTranscriptomeTumor MicroenvironmentAntineoplastic AgentsBRAF protein, humanProtein Kinase InhibitorsProto-Oncogene Proteins B-rafBRAFcell signalingdrug resistanceEGFRintratumor heterogeneitylung cancermelanomatargeted therapytolerant and persister cells

Identifiers

PMID33291749
PMCPMC7761971
OpenAlexW3110514015

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.