Evidence map›Paper›PMID 38330741›Full record

ArticleBiomaterials2024

Aged breast matrix bound vesicles promote breast cancer invasiveness.

Jun Yang, Gokhan Bahcecioglu, George Ronan, Pinar Zorlutuna

Open access · greenAbstract read
In one paragraph

Article in Biomaterials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Macrophages and the Extracellular Matrix.Results and problems in cell differentiation · 2024
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Jun YangDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA. Electronic address: jyang26@nd.edu.
Gokhan BahceciogluDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Harper Cancer Research Institute, University of Notre Dame, Notre Dame, 46556, USA. Electronic address: gbahceci@nd.edu.
George RonanDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN, 46556, USA. Electronic address: gronan@nd.edu.
Pinar ZorlutunaDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA; Harper Cancer Research Institute, University of Notre Dame, Notre Dame, 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN, 46556, USA. Electronic address: pzorlutu@nd.edu.
University of Notre Dame · US

Funding

Engineered hybrid aging model for disease progressionR01CA275423 · NCI · UNIVERSITY OF NOTRE DAME · PI Pinar Zorlutuna · 2023 to 2026
$1.8M
An Engineered Tissue Model of Aged Mammary MicroenvironmentR01EB027660 · NIBIB · UNIVERSITY OF NOTRE DAME · PI ZORLUTUNA, PINAR · 2019 to 2022
$1.6M
NCI NIH HHS R01 CA275423NIBIB NIH HHS R01 EB027660
6 · The paper itself

Abstract

Aging is one of the inherent risk factors for breast cancer. Although the influence of age-related cellular alterations on breast cancer development has been extensively explored, little is known about the alterations in the aging breast tissue microenvironment, specifically the extracellular matrix (ECM). Here, for the first time in literature, we have identified tissue resident matrix bound vesicles (MBVs) within the healthy mouse breast ECM, investigated and compared their characteristics in young and aged healthy breast tissues, and studied the effects of these MBVs on normal (KTB21) and cancerous (MDA-MB-231) human mammary epithelial cells with respect to the tissue age that they are extracted from. Using vesicle labeling technology, we were able to visualize cellular uptake of the MBVs directly from the native decellularized tissue sections, showing that these MBVs have regulatory roles in the tissue microenvironment. We mimicked the ECM by embedding the MBVs in collagen gels, and showed that MBVs could be taken up by the cells. The miRNA and cytokine profiling showed that MBVs shifted towards a more tumorigenic and invasive phenotype with age, as evidenced by the more pronounced presence of cancer-associated cytokines, and higher expression levels of oncomiRs miR-10b, miR-30e, and miR-210 in MBVs isolated from aged mice. When treated with MBVs or these upregulated factors, KTB21 and MDA-MB-231 cells showed significantly higher motility and invasion compared to untreated controls. Treatment of cells with a cocktail of miRNAs (miR-10b, miR-30e, and miR-210) or with the agonist of adiponectin (AdipoRon), which both were enriched in the aged MBVs, recapitulated the effect of aged MBVs on cells. This study shows for the first time that the MBVs have a regulatory role in the tissue microenvironment and that the MBV contents change towards cancer-promoting upon aging. Studying the effects of MBVs and their cargos on cellular behavior could lead to a better understanding of the critical roles of MBVs played in breast cancer progression and metastasis.

Indexed as

Breast NeoplasmsMicroRNAsAgedAnimalsCell Line, TumorEpithelial CellsExtracellular MatrixFemaleHumansMiceNeoplasm InvasivenessTumor MicroenvironmentMicroRNAsAgingBreast cancerDecellularized extracellular matrix (dECM)InvasionMatrix bound vesicles (MBVs)Motility

Identifiers

PMID38330741
PMCPMC11202350
OpenAlexW4391520113

What OpenQuestion holds

Textmetadata
LicenceTDM
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.