Evidence map›Paper›PMID 29100299›Full record

ArticleOncotarget2017

Coupling to a cancer-selective heparan-sulfate-targeted branched peptide can by-pass breast cancer cell resistance to methotrexate.

Lorenzo Depau, Jlenia Brunetti, Chiara Falciani, Silvia Scali, Giulia Riolo, Elisabetta Mandarini, Alessandro Pini, Luisa Bracci

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

13 citing papers in PubMed, 25 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

8 authors at 1 institution in 1 country.

Lorenzo DepauDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Jlenia BrunettiDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Chiara FalcianiDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Silvia ScaliDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Giulia RioloDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Elisabetta MandariniDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Alessandro PiniDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
Luisa BracciDepartment of Medical Biotechnologies, University of Siena, 53100 Siena, Italy.
University of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer-selective tetra-branched peptides, named NT4, can be coupled to different functional units for cancer cell imaging or therapy. NT4 peptides specifically bind to lipoprotein receptor-related proteins (LRP) receptors and to heparan sulfate chains on membrane proteoglycans and can be efficiently internalized by cancer cells expressing these membrane targets. Since binding and internalization of NT4 peptides is mediated by specific NT4 receptors on cancer cell membranes and this may allow drug resistance produced by drug membrane transporters to be by-passed, we tested the ability of drug-armed NT4 to by-pass drug resistance in cancer cell lines. We found that MTX-conjugated NT4 allows drug resistance to be by-passed in MTX-resistant human breast cancer cells lacking expression of folate reduced carrier. NT4 peptides appear to be extremely promising cancer-selective targeting agents that can be exploited as theranostics in personalized oncological applications.

Indexed as

drug-resistanceheparan sulfatemethotrexatepeptides

Identifiers

PMID29100299
PMCPMC5652693
OpenAlexW2733221249

What OpenQuestion holds

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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.