Evidence map›Paper›PMID 32365498›Full record

ReviewCells2020

Targeting the IGF-Axis for Cancer Therapy: Development and Validation of an IGF-Trap as a Potential Drug.

Yinhsuan Michely Chen, Shu Qi, Stephanie Perrino, Masakazu Hashimoto, Pnina Brodt

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
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 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

20 citing papers in PubMed, 33 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

5 authors at 2 institutions in 1 country.

Yinhsuan Michely ChenDepartment of Medicine, Division of Experimental Medicine, McGill University, Montreal, QC H3A 0G4, Canada.
Shu QiThe Research Institute of the McGill University Health Center, Montreal, QC H4A 3J1, Canada.
Stephanie PerrinoThe Research Institute of the McGill University Health Center, Montreal, QC H4A 3J1, Canada.
Masakazu HashimotoThe Research Institute of the McGill University Health Center, Montreal, QC H4A 3J1, Canada.
Pnina BrodtDepartment of Medicine, Division of Experimental Medicine, McGill University, Montreal, QC H3A 0G4, Canada.
McGill University Health Centre · CAMcGill University · CA

Funding

CIHR MOP-77677CIHR PP2-141724
6 · The paper itself

Abstract

The insulin-like growth factor (IGF)-axis was implicated in cancer progression and identified as a clinically important therapeutic target. Several IGF-I receptor (IGF-IR) targeting drugs including humanized monoclonal antibodies have advanced to phase II/III clinical trials, but to date, have not progressed to clinical use, due, at least in part, to interference with insulin receptor signaling and compensatory signaling by the insulin receptor (IR) isoform A that can bind IGF-II and initiate mitogenic signaling. Here we briefly review the current state of IGF-targeting biologicals, discuss some factors that may be responsible for their poor performance in the clinic and outline the stepwise bioengineering and validation of an IGF-Trap-a novel anti-cancer therapeutic that could bypass these limitations. The IGF-Trap is a heterotetramer, consisting of the entire extracellular domain of the IGF-IR fused to the Fc portion of human IgG

Indexed as

Antibodies, MonoclonalHumansInsulin-Like Growth Factor IPharmaceutical PreparationsReceptor, IGF Type 1Receptor, InsulinSignal TransductionAntibodies, MonoclonalIGF1 protein, humanIGF1R protein, humanInsulin-Like Growth Factor IPharmaceutical PreparationsReceptor, IGF Type 1Receptor, InsulinIGF-I receptorIGF-Trapsignalingtargeted therapeutics

Identifiers

PMID32365498
PMCPMC7290707
OpenAlexW3023623960

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.