Evidence map›Paper›PMID 29530981›Full record

ArticleThe Journal of biological chemistry2018

The proximity-labeling technique BioID identifies sorting nexin 6 as a member of the insulin-like growth factor 1 (IGF1)-IGF1 receptor pathway.

Akshay Bareja, Conrad P Hodgkinson, Erik Soderblom, Greg Waitt, Victor J Dzau

Open access · hybridAbstract read
In one paragraph

Article in The Journal of biological chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. The NamBio · 2025
    Article
  3. MappingmBio · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Proximity-dependent labeling methods for proteomic profiling in living cells: An update.Wiley interdisciplinary reviews. Developmental biology · 2021
    Review
  10. Article
  11. Review
  12. The emerging role of sorting nexins in cardiovascular diseases.Clinical science (London, England : 1979) · 2019
    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

5 authors at 1 institution in 1 country.

Akshay BarejaFrom the Duke Cardiovascular Research Center, the Mandel Center for Hypertension and Atherosclerosis Research, and akshay.bareja@duke.edu.
Conrad P HodgkinsonFrom the Duke Cardiovascular Research Center, the Mandel Center for Hypertension and Atherosclerosis Research, and.
Erik Soderblomthe Duke Center for Genomic and Computational Biology, Duke University, Durham, North Carolina 27710.
Greg Waittthe Duke Center for Genomic and Computational Biology, Duke University, Durham, North Carolina 27710.
Victor J DzauFrom the Duke Cardiovascular Research Center, the Mandel Center for Hypertension and Atherosclerosis Research, and victor.dzau@duke.edu.
Duke University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The insulin-like growth factor 1 receptor (IGF1R) is a receptor tyrosine kinase with critical roles in various biological processes. Recent results from clinical trials targeting IGF1R indicate that IGF1R signaling pathways are more complex than previously thought. Moreover, it has become increasingly clear that the function of many proteins can be understood only in the context of a network of interactions. To that end, we sought to profile IGF1R-protein interactions with the proximity-labeling technique BioID. We applied BioID by generating a HEK293A cell line that stably expressed the BirA* biotin ligase fused to the IGF1R. Following stimulation by IGF1, biotinylated proteins were analyzed by MS. This screen identified both known and previously unknown interactors of IGF1R. One of the novel interactors was sorting nexin 6 (SNX6), a protein that forms part of the retromer complex, which is involved in intracellular protein sorting. Using co-immunoprecipitation, we confirmed that IGF1R and SNX6 physically interact. SNX6 knockdown resulted in a dramatic diminution of IGF1-mediated ERK1/2 phosphorylation, but did not affect IGF1R internalization. Bioluminescence resonance energy transfer experiments indicated that the SNX6 knockdown perturbed the association between IGF1R and the key adaptor proteins insulin receptor substrate 1 (IRS1) and SHC adaptor protein 1 (SHC1). Intriguingly, even in the absence of stimuli, SNX6 overexpression significantly increased Akt phosphorylation. Our study confirms the utility of proximity-labeling methods, such as BioID, to screen for interactors of cell-surface receptors and has uncovered a role of one of these interactors, SNX6, in the IGF1R signaling cascade.

Indexed as

MAP Kinase Signaling SystemCarbon-Nitrogen LigasesEscherichia coli ProteinsGene Knockdown TechniquesHEK293 CellsHumansInsulin-Like Growth Factor IInsulin Receptor Substrate ProteinsMitogen-Activated Protein Kinase 1Mitogen-Activated Protein Kinase 3PhosphorylationProto-Oncogene Proteins c-aktReceptor, IGF Type 1Receptors, SomatomedinRepressor ProteinsSorting NexinsbirA protein, E coliCarbon-Nitrogen LigasesEscherichia coli ProteinsIGF1 protein, humanIGF1R protein, humanInsulin-Like Growth Factor IInsulin Receptor Substrate ProteinsIRS1 protein, humanMAPK1 protein, humanMitogen-Activated Protein Kinase 1Mitogen-Activated Protein Kinase 3Proto-Oncogene Proteins c-aktReceptor, IGF Type 1Receptors, SomatomedinRepressor ProteinsSHC1 protein, humanSNX6 protein, humanSorting NexinsSrc Homology 2 Domain-Containing, Transforming Protein 1Akt PKBBioIDcell signalingextracellular-signal-regulated kinase (ERK)growth factorIGF1Rinsulin-like growth factor (IGF)retromerSNX6

Identifiers

PMID29530981
PMCPMC5925803
OpenAlexW2792320820

What OpenQuestion holds

Textmetadata
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.