Evidence map›Paper›PMID 25866791›Full record

ReviewBioMed research international2015

Insulin-like growth factor system in cancer: novel targeted therapies.

Varsha P Brahmkhatri, Chinmayi Prasanna, Hanudatta S Atreya

Open access · hybridAbstract readReview
In one paragraph

Review in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed, 4 pooled it
23.2field-weighted citation impact, top 1% 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

126 citing papers in PubMed, 4 syntheses or guidelines pooled it, 276 citations in OpenAlex.

  1. Pooled it
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  13. IGF Pathway Components as Potential Biomarkers in Gastric Cancer.International journal of molecular sciences · 2025
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66 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Varsha P BrahmkhatriNMR Research Centre, Indian Institute of Science, Bangalore 560012, India.
Chinmayi PrasannaNMR Research Centre, Indian Institute of Science, Bangalore 560012, India.
Hanudatta S AtreyaNMR Research Centre, Indian Institute of Science, Bangalore 560012, India ; Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore 560012, India.
Indian Institute of Science Bangalore · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin-like growth factors (IGFs) are essential for growth and survival that suppress apoptosis and promote cell cycle progression, angiogenesis, and metastatic activities in various cancers. The IGFs actions are mediated through the IGF-1 receptor that is involved in cell transformation induced by tumour. These effects depend on the bioavailability of IGFs, which is regulated by IGF binding proteins (IGFBPs). We describe here the role of the IGF system in cancer, proposing new strategies targeting this system. We have attempted to expand the general viewpoint on IGF-1R, its inhibitors, potential limitations of IGF-1R, antibodies and tyrosine kinase inhibitors, and IGFBP actions. This review discusses the emerging view that blocking IGF via IGFBP is a better option than blocking IGF receptors. This can lead to the development of novel cancer therapies.

Indexed as

Receptors, SomatomedinAnimalsAntineoplastic AgentsDrug Delivery SystemsHumansInsulin-Like Growth Factor Binding ProteinsNeoplasmsReceptor, IGF Type 1SomatomedinsAntineoplastic AgentsIGF1R protein, humanInsulin-Like Growth Factor Binding ProteinsReceptor, IGF Type 1Receptors, SomatomedinSomatomedins

Identifiers

PMID25866791
PMCPMC4383470
OpenAlexW1974502272

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.