Evidence map›Paper›PMID 26747277›Full record

ArticleBreast cancer research : BCR2016

Increased peri-ductal collagen micro-organization may contribute to raised mammographic density.

James C McConnell, Oliver V O'Connell, Keith Brennan, Lisa Weiping, Miles Howe, Leena Joseph, David Knight, Ronan O'Cualain, Yit Lim, Angela Leek and 7 more

Open access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed
17.3field-weighted citation impact, top 1% 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

71 citing papers in PubMed, 113 citations in OpenAlex.

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  3. Understanding and targeting the tumour matrisome.Nature reviews. Clinical oncology · 2026
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11 more citing papers are in PubMed but not listed here.

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

17 authors at 4 institutions in 1 country.

James C McConnellCentre for Tissue Injury & Repair, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK. james.mcconnell@manchester.ac.uk.
Oliver V O'ConnellWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. oliver.oconnell@postgrad.manchester.ac.uk.
Keith BrennanWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. keith.brennan@manchester.ac.uk.
Lisa WeipingWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. weiping.li-2@manchester.ac.uk.
Miles HoweUniversity Hospital of South Manchester, Manchester, UK. miles.howe@uhsm.nhs.uk.
Leena JosephUniversity Hospital of South Manchester, Manchester, UK. leena.joseph@uhsm.nhs.uk.
David KnightWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. david.knight@manchester.ac.uk.
Ronan O'CualainWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. ronan.o'cualain@manchester.ac.uk.
Yit LimUniversity Hospital of South Manchester, Manchester, UK. yit.lim@uhsm.nhs.uk.
Angela LeekManchester Cancer Research Centre Tissue Biobank, University of Manchester, Manchester, UK. angela.leek@uhsm.nhs.uk.
Rachael WaddingtonManchester Cancer Research Centre Tissue Biobank, University of Manchester, Manchester, UK. rachael.waddington@uhsm.nhs.uk.
Jane RoganManchester Cancer Research Centre Tissue Biobank, University of Manchester, Manchester, UK. jane.rogan@christie.nhs.uk.
Susan M AstleyCentre for Imaging Sciences, Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK. sue.astley@manchester.ac.uk.
Ashu GandhiUniversity Hospital of South Manchester, Manchester, UK. ashu.gandhi@uhsm.nhs.uk.
Cliona C KirwanInstitute of Cancer Sciences, Manchester Academic Health Sciences Centre, University Hospital of South Manchester, University of Manchester, Manchester, UK. cliona.kirwan@manchester.ac.uk.
Michael J SherrattCentre for Tissue Injury & Repair, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK. michael.sherratt@manchester.ac.uk.
Charles H StreuliWellcome Trust Centre for Cell-Matrix Research and Manchester Breast Centre, Faculty of Life Sciences, University of Manchester, Manchester, UK. cstreuli@manchester.ac.uk.
University of Manchester · GBWellcome Centre for Cell-Matrix Research · GBCancer Research UK Manchester Institute · GBManchester Academic Health Science Centre · GB

Funding

Department of Health NIHR-CS-011-014Medical Research Council G1001398Wellcome TrustWellcome Trust 097820/Z/11/A
6 · The paper itself

Abstract

backgroundHigh mammographic density is a therapeutically modifiable risk factor for breast cancer. Although mammographic density is correlated with the relative abundance of collagen-rich fibroglandular tissue, the causative mechanisms, associated structural remodelling and mechanical consequences remain poorly defined. In this study we have developed a new collaborative bedside-to-bench workflow to determine the relationship between mammographic density, collagen abundance and alignment, tissue stiffness and the expression of extracellular matrix organising proteins.

methodsMammographic density was assessed in 22 post-menopausal women (aged 54-66 y). A radiologist and a pathologist identified and excised regions of elevated non-cancerous X-ray density prior to laboratory characterization. Collagen abundance was determined by both Masson's trichrome and Picrosirius red staining (which enhances collagen birefringence when viewed under polarised light). The structural specificity of these collagen visualisation methods was determined by comparing the relative birefringence and ultrastructure (visualised by atomic force microscopy) of unaligned collagen I fibrils in reconstituted gels with the highly aligned collagen fibrils in rat tail tendon. Localised collagen fibril organisation and stiffness was also evaluated in tissue sections by atomic force microscopy/spectroscopy and the abundance of key extracellular proteins was assessed using mass spectrometry.

resultsMammographic density was positively correlated with the abundance of aligned periductal fibrils rather than with the abundance of amorphous collagen. Compared with matched tissue resected from the breasts of low mammographic density patients, the highly birefringent tissue in mammographically dense breasts was both significantly stiffer and characterised by large (>80 μm long) fibrillar collagen bundles. Subsequent proteomic analyses not only confirmed the absence of collagen fibrosis in high mammographic density tissue, but additionally identified the up-regulation of periostin and collagen XVI (regulators of collagen fibril structure and architecture) as potential mediators of localised mechanical stiffness.

conclusionsThese preliminary data suggest that remodelling, and hence stiffening, of the existing stromal collagen microarchitecture promotes high mammographic density within the breast. In turn, this aberrant mechanical environment may trigger neoplasia-associated mechanotransduction pathways within the epithelial cell population.

Indexed as

ProteomicsAgedAnimalsBreast DensityBreast NeoplasmsCell Adhesion MoleculesCollagenExtracellular Matrix ProteinsFemaleHumansMammary Glands, HumanMammographyMicroscopy, Atomic ForceMiddle AgedRatsRisk FactorsCell Adhesion MoleculesCOL16A1 protein, humanCollagenExtracellular Matrix ProteinsPOSTN protein, human

Identifiers

PMID26747277
PMCPMC4706673
OpenAlexW2231580835

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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.