Evidence map›Paper›PMID 36568144›Full record

ArticleFrontiers in oncology2022

Breast tumor IGF1R regulates cell adhesion and metastasis: alignment of mouse single cell and human breast cancer transcriptomics.

Alison E Obr, Joseph J Bulatowicz, Yun-Juan Chang, Virginia Ciliento, Alexander Lemenze, Krystopher Maingrette, Quan Shang, Emily J Gallagher, Derek LeRoith, Teresa L Wood

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

10 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. ActivationFrontiers in endocrinology · 2022
    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

10 authors at 2 institutions in 1 country.

Alison E ObrDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Joseph J BulatowiczDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Yun-Juan ChangOffice of Advance Research Computing, Rutgers University, Piscataway, NJ, United States.
Virginia CilientoDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Alexander LemenzeDepartment of Pathology, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Krystopher MaingretteDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Quan ShangDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Emily J GallagherDivision of Endocrinology, Diabetes and Bone Diseases, The Samuel Bronfman Department of Medicine, Icahn Sinai School of Medicine at Mt. Sinai, New York, NY, United States.
Derek LeRoithDivision of Endocrinology, Diabetes and Bone Diseases, The Samuel Bronfman Department of Medicine, Icahn Sinai School of Medicine at Mt. Sinai, New York, NY, United States.
Teresa L WoodDepartment of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, United States.
Rutgers, The State University of New Jersey · USIcahn School of Medicine at Mount Sinai · US

Funding

Pathways that regulate basal and metastatic phenotypes in triple negative breast cancersR01CA204312 · NCI · RBHS-NEW JERSEY MEDICAL SCHOOL · PI WOOD, TERESA L · 2017 to 2021
$2.7M
NCI NIH HHS R01 CA204312
6 · The paper itself

Abstract

Introduction: The acquisition of a metastatic phenotype is the critical event that determines patient survival from breast cancer. Several receptor tyrosine kinases have functions both in promoting and inhibiting metastasis in breast tumors. Although the insulin-like growth factor 1 receptor (IGF1R) has been considered a target for inhibition in breast cancer, low levels of IGF1R expression are associated with worse overall patient survival. Methods: To determine how reduced IGF1R impacts tumor phenotype in human breast cancers, we used weighted gene co-expression network analysis (WGCNA) of Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) patient data to identify gene modules associated with low IGF1R expression. We then compared these modules to single cell gene expression analyses and phenotypes of mouse mammary tumors with reduced IGF1R signaling or expression in a tumor model of triple negative breast cancer. Results: WGCNA from METABRIC data revealed gene modules specific to cell cycle, adhesion, and immune cell signaling that were inversely correlated with IGF1R expression in human breast cancers. Integration of human patient data with single cell sequencing data from mouse tumors revealed similar pathways necessary for promoting metastasis in basal-like mammary tumors with reduced signaling or expression of IGF1R. Functional analyses revealed the basis for the enhanced metastatic phenotype including alterations in E- and P-cadherins. Discussion: Human breast and mouse mammary tumors with reduced IGF1R are associated with upregulation of several pathways necessary for promoting metastasis supporting the conclusion that IGF1R normally helps maintain a metastasis suppressive tumor microenvironment. We further found that reduced IGF1R signaling in tumor epithelial cells dysregulates cadherin expression resulting in reduced cell adhesion.

Indexed as

adhesionbreast cancercadherininsulin-like growth factor receptormetastasis

Identifiers

PMID36568144
PMCPMC9769962
OpenAlexW4311816672

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.