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Abstract P4-03-11: Fibroblasts isolated from the “normal-like” tissue adjacent to breast tumours suppress healthy epithelial progenitor cell proliferation while supporting tumour cell growth

2017· article· en· W2944006832 on OpenAlexaff
Sharmistha Chatterjee, A. Berdnikov, Victoria Lee-Wing, Janice R. Safneck, Edward W. Buchel, Afshin Raouf

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of ManitobaResearch Institute in Oncology and Hematology
Fundersnot available
KeywordsProgenitor cellMatrigelBreast cancerCancer researchCell growthBreast tissueBiologyFibroblastPathologyStem cellCellCell cultureMedicineCancerAngiogenesisCell biology

Abstract

fetched live from OpenAlex

Abstract The tissue adjacent to breast tumors has been referred to as “normal-like” tissue despite exhibiting many alterations at epigenetic and gene expression levels consistent with enhanced proliferation and wound healing signatures. However, the influence of such alterations on the proliferation and differentiation of healthy breast progenitors is currently unknown. Fibroblasts are a major component of microenvironment for the healthy and malignant breast cells. We therefore, isolate fibroblast from primary breast tumors, tissue adjacent to tumors (TAT) and the healthy breast tissue and examine their ability to support proliferation of healthy and malignant breast cells. To characterize the TAT samples we first utilized clonal co-culture assays using breast cells obtained from the healthy breast tissue (reduction mammoplasty sample, RM) and the healthy fibroblasts. Our results suggested that the TAT samples surprisingly contained significantly decreased pool of progenitors compared to the RM samples. In order to study the underlying mechanism, we characterized fibroblasts derived from either the breast tumours (TAFs) or the TAT samples (TATF) or the RM normal samples (NAFs) and assessed their role on breast progenitor cell functions. Fibroblasts were isolated from the ER+ and ER- breast tumours and their adjacent breast tissue. We observed that matrigel co-cultures consisting of RM samples and NAFs led to a 5.5-fold expansion of the progenitors, whereas the co-cultures of TAT or the RM samples with either TAFs or TATFs failed to show expansion of epithelial progenitors. The comparative secretome analysis of the NAFs and the TATFs identified TGFβ as a candidate molecule primarily secreted only by the TATFs and not by NAFs. Interestingly, blocking TGFβ signaling restored both TAFs' and TATFs' ability to support the expansion of healthy progenitors in matrigel cultures. Lastly, we found that TAFs were able to enhanced breast cancer cell proliferation in vivo and in vitro but to a lesser extent than the TAFs. Our observations suggest that the tissues adjacent to breast tumours are transformed into a TGFβ-enriched environment that is supportive of breast tumour growth while suppressing the proliferation and differentiation potentials of the healthy breast progenitors. Our data also suggest that the use of TGFβ blockers may be important in reducing risk of local breast tumour recurrence. Citation Format: Chatterjee S, Berdnikov A, Lee-Wing V, Safneck J, Buchel E, Raouf A. Fibroblasts isolated from the “normal-like” tissue adjacent to breast tumours suppress healthy epithelial progenitor cell proliferation while supporting tumour cell growth [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-03-11.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.373
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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