Evidence map›Paper›PMID 26861122›Full record

ArticleBMC systems biology2016

Quantitative analysis of insulin-like growth factor 2 receptor and insulin-like growth factor binding proteins to identify control mechanisms for insulin-like growth factor 1 receptor phosphorylation.

Dan Tian, Isaiah Mitchell, Pamela K Kreeger

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. The Many Microenvironments of Ovarian Cancer.Advances in experimental medicine and biology · 2020
    Review
  4. Article
  5. Article
  6. Article
  7. Article
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.

Dan TianDepartment of Biomedical Engineering, 4553 WI Institute Medical Research, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI, 53705, USA. dtian@wisc.edu.
Isaiah MitchellDepartment of Biomedical Engineering, 4553 WI Institute Medical Research, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI, 53705, USA. imitchell@wisc.edu.
Pamela K KreegerDepartment of Biomedical Engineering, 4553 WI Institute Medical Research, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI, 53705, USA. kreeger@wisc.edu.
University of Wisconsin–Madison · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI AMY TRENTHAM-DIETZ · 1985 to 2026
$142.6M
Analysis of how quantitative cellular network variation impacts tumor progressionDP2CA195766 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI KREEGER, PAMELA K · 2014 to 2014
$2.3M
NCI NIH HHS 1DP2CA195766-01NCI NIH HHS DP2 CA195766NCI NIH HHS P30 CA014520
6 · The paper itself

Abstract

backgroundThe insulin-like growth factor (IGF) system impacts cellular development by regulating proliferation, differentiation, and apoptosis, and is an attractive therapeutic target in cancer. The IGF system is complex, with two ligands (IGF1, IGF2), two receptors (IGF1R, IGF2R), and at least six high affinity IGF-binding proteins (IGFBPs) that regulate IGF ligand bioavailability. While the individual components of the IGF system are well studied, the question of how these different components integrate as a system to regulate cell behavior is less clear.

resultsTo analyze the relative importance of different mechanisms that control IGF network activity, we developed a mass-action kinetic model incorporating cell surface binding, phosphorylation, and intracellular trafficking events. The model was calibrated and validated using experimental data collected from OVCAR5, an immortalized ovarian cancer cell line. We then performed model analysis to examine the ability of IGF2R or IGFBPs to counteract phosphorylation of IGF1R, a critical step for IGF network activation. This analysis suggested that IGF2R levels would need to be 320-fold greater than IGF1R in order to decrease pIGF1R by 25 %, while IGFBP levels would need to be 390-fold greater. Analysis of The Cancer Genome Atlas (TCGA) data set suggested that this level of overexpression is unlikely for IGF2R in ovarian, breast, and colon cancer. In contrast, IGFBPs can likely reach these levels, suggesting that IGFBPs are the more critical regulator of IGF1R network activity. Levels of phosphorylated IGF1R were insensitive to changes in parameters regulating the IGF2R arm of the network.

conclusionsUsing a mass-action kinetic model, we determined that IGF2R plays a minor role in regulating the activity of IGF1R under a variety of conditions and that due to their high expression levels, IGFBPs are the dominant mechanism to regulating IGF network activation.

Indexed as

Models, BiologicalCell Line, TumorHumansInsulin-Like Growth Factor Binding ProteinsInsulin-Like Growth Factor IIIntracellular SpacePhosphorylationProtein ConformationProtein TransportReceptor, IGF Type 2IGF2 protein, humanInsulin-Like Growth Factor Binding ProteinsInsulin-Like Growth Factor IIReceptor, IGF Type 2

Identifiers

PMID26861122
PMCPMC4746774
OpenAlexW2261735598

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.