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Abstract P4-04-14: High mammographic density is associated with deposition of organised fibrillar collagen and increased stiffness in periductal breast stroma

2015· article· en· W1566186431 on OpenAlexaff
Ashu Gandhi, Cliona Kirwan, J. C. McConnell, Oliver V. O’Connell, Michael J. Sherratt, Charles Streuli

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsCollagen fibrilStromaBreast tissueTrichromeStromal cellBreast cancerConnective tissuePathologyMaterials scienceHard tissueMedicineAnatomyChemistryStainingCancerH&E stainImmunohistochemistryInternal medicineDentistry

Abstract

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Abstract Introduction High mammographic density (MD) in women is strongly associated with breast cancer risk. However the structural and compositional differences between dense and non-dense breast tissues are not well defined. We determined the relationship between MD, collagen deposition and fibril alignment, and tissue micro-stiffness, in similarly aged individuals without adjacent cancer. Methods Fresh tissue samples were collected from post-menopausal women undergoing breast screening. Collagen deposition and fibril organisation were analysed using light microscopy of wax-sections stained with H&E, Trichrome or Picrosirius Red (with polarising light), and quantified using ImageJ. Local tissue stiffness was measured using atomic force microscopy (AFM) of hydrated tissue. For AFM, 3 x 25 µm2 areas of each sample were indented at 400 equally spaced points with a 1 µm diameter spherical probe at a loading rate of 1 Hz (Reduced Modulus; YM). Results Volumetric MD (VolparaTM) was determined in 22 women (54-66y) undergoing risk-reducing surgery or mastectomy. Localised regions of elevated density, determined from digital mammograms, were isolated from patients of low and high overall MD, using a new collaborative workflow linking radiologist, surgeon, pathologist, and tissue biobank. All elevated-density regions contained considerable amounts of stromal connective tissue. However, there were significant differences in these regions from women with low vs high overall MD. Picrosirius Red staining of the localised areas of density revealed that the percentage organised fibrillar collagen content, particularly in the periductal breast stroma, strongly correlated with overall MD. AFM showed that the localised micro-stiffness of dense areas increased significantly in the breast stroma of patients with high overall MD (Volpara score > 15) compared with those of low overall MD (Volpara score < 5). Conclusions High MD is a significant risk factor for breast cancer, yet its molecular determinants in the normal, non-cancerous breast are poorly defined. We have shown that high MD is associated with more organised fibrillar collagen, leading to increased stiffness of the periductal breast stroma. Women with low and high MD all have regions with localised density, which contain both stromal connective tissue and epithelial ducts/lobules. However, our results show that these localised areas have differences in collagen organisation and tissue micro-mechanics. We now hypothesise that in the connective tissue of women with high MD, altered synthesis, deposition and turnover of stromal proteins alters the local biomechanical properties within the breast, providing a stiffer microenvironment, and contributing to cancer onset. Citation Format: Ashu Gandhi, Cliona C Kirwan, James C McConnell, Oliver V O'Connell, Michael J Sherratt, Charles H Streuli. High mammographic density is associated with deposition of organised fibrillar collagen and increased stiffness in periductal breast stroma [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-04-14.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.310
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
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