Evidence map›Paper›PMID 29694896›Full record

ArticleCell reports2018

High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia.

Fanny A Pelissier Vatter, Denis Schapiro, Hang Chang, Alexander D Borowsky, Jonathan K Lee, Bahram Parvin, Martha R Stampfer, Mark A LaBarge, Bernd Bodenmiller, James B Lorens

Abstract read
In one paragraph

Article in Cell reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
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

44 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

10 authors.

Fanny A Pelissier VatterDepartment of Biomedicine, University of Bergen, Bergen 5009, Norway; Centre for Cancer Biomarkers (CCBIO), University of Bergen, Bergen 5009, Norway.
Denis SchapiroInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland.
Hang ChangBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Alexander D BorowskyDepartment of Pathology and Laboratory Medicine, Center for Comparative Medicine, University of California, Davis, School of Medicine, Sacramento, CA, USA.
Jonathan K LeeBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Bahram ParvinDepartment of Electrical and Biomedical Engineering, University of Nevada, Reno, NV, USA.
Martha R StampferInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland.
Mark A LaBargeCentre for Cancer Biomarkers (CCBIO), University of Bergen, Bergen 5009, Norway; Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA; Department of Population Sciences & Center for Cancer and Aging, City of Hope, Duarte, CA, USA. Electronic address: mlabarge@coh.org.
Bernd BodenmillerInstitute of Molecular Life Sciences, University of Zürich, 8057 Zürich, Switzerland. Electronic address: bernd.bodenmiller@imls.uzh.ch.
James B LorensDepartment of Biomedicine, University of Bergen, Bergen 5009, Norway; Centre for Cancer Biomarkers (CCBIO), University of Bergen, Bergen 5009, Norway. Electronic address: jim.lorens@uib.no.

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI STANLEY R. HAMILTON · 1985 to 2026
$86.3M
Single-Cell Analyses of Human Islets in T1D Using Highly Multiplexed ImagingUC4DK108132 · NIDDK · UNIVERSITY OF FLORIDA · PI ATKINSON, MARK A., BODENMILLER, BERND · 2015 to 2015
$3.6M
Age-related shifts in epithelial lineages and tissue homeostasis in mammary gland 5R01AG040081-05R01AG040081 · NIA · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI LABARGE, MARK A · 2011 to 2015
$2.3M
The role of microenvironment in aging-related phenotypes of breastR00AG033176 · NIA · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI LABARGE, MARK A · 2010 to 2012
$703k
European Research Council 336921NCI NIH HHS P30 CA033572NIA NIH HHS R00 AG033176NIA NIH HHS R01 AG040081NIDDK NIH HHS UC4 DK108132
6 · The paper itself

Abstract

Aging is associated with tissue-level changes in cellular composition that are correlated with increased susceptibility to disease. Aging human mammary tissue shows skewed progenitor cell potency, resulting in diminished tumor-suppressive cell types and the accumulation of defective epithelial progenitors. Quantitative characterization of these age-emergent human cell subpopulations is lacking, impeding our understanding of the relationship between age and cancer susceptibility. We conducted single-cell resolution proteomic phenotyping of healthy breast epithelia from 57 women, aged 16-91 years, using mass cytometry. Remarkable heterogeneity was quantified within the two mammary epithelial lineages. Population partitioning identified a subset of aberrant basal-like luminal cells that accumulate with age and originate from age-altered progenitors. Quantification of age-emergent phenotypes enabled robust classification of breast tissues by age in healthy women. This high-resolution mapping highlighted specific epithelial subpopulations that change with age in a manner consistent with increased susceptibility to breast cancer.

Indexed as

AdolescentAdultAgedAged, 80 and overAgingFemaleHumansMammary Glands, HumanMiddle Agedagingbreast cancerheterogeneityhuman mammary epitheliamass cytometrysingle-cell analysis

Identifiers

PMID29694896
PMCPMC5946804

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.