12 research outputs found

    Bioengineering Models for Breast Cancer Research

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    Despite substantial advances in early diagnosis, breast cancer (BC) still remains a clinical challenge. Most BC models use complex in vivo models and two-dimensional monolayer cultures that do not fully mimic the tumor microenvironment. The integration of cancer biology and engineering can lead to the development of novel in vitro approaches to study BC behavior and quantitatively assess different features of the tumor microenvironment that may influence cell behavior. In this review, we present tissue engineering approaches to model BC in vitro. Recent advances in the use of three-dimensional cell culture models to study various aspects of BC disease in vitro are described. The emerging area of studying BC dormancy using these models is also reviewed

    Investigating Breast Cancer Cell Behavior Using Tissue Engineering Scaffolds - Fig 4

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    <p>Flow cytometry analysis of CD44/CD24 expression of A) Top left: suspension of MDA-MB-231 treated cells analyzed based on size with forward-scattered light (FSC) and side-scattered light (SSC). Top right: R1 population further analyzed by specifically gating for CD44/CD24 expressing cells. Bottom left: histogram of MDA isotype control and CD24-FITC with histogram marker M1 designating CD24-FITC positive events. Bottom right: histogram of MDA isotype control and CD44-PE with histogram marker M1, designating CD44-PE positive events. B) Top left: suspension of T47D treated cells analyzed based on size with FSC and SSC. Top right: R1 population further analyzed by specifically gating for CD44/CD24 expressing cells. Bottom left: histogram of T47D isotype control and CD24-FITC with histogram marker M1 designating CD24-FITC positive events. Bottom right: histogram of T47D isotype control and CD44-PE with histogram marker M1, designating CD44-PE positive events.</p

    Western blot of breast cancer cell lines with chemotherapy treatment.

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    <p>Bax, Bcl2, Oct4, and Sox2 expression was determined for A) MDA-MB-231 cells and B) T47D cells. Densitometric bands normalized to β-actin have been provided in supplemental <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118724#pone.0118724.s001" target="_blank">S1 Fig</a>.</p

    SEM images of MDA-MB-231 cells on fibrous scaffolds after day 1 and day 7 of culture.

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    <p>The arrows depict the cell body and the arrowheads depict the fibers. Supplemental data showing higher magnification analysis of adhesion and infiltration has been provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118724#pone.0118724.s002" target="_blank">S2 Fig</a>.</p

    Effect of carboplatin treatment on the viability of breast cancer cell lines.

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    <p>a) Percentage of non-viable cells at 2 days post treatment with carboplatin. The results are shown as the mean±SD, n = 7 of non-viable cells. <sup>a</sup> p<0.05, significant increase in non-viable BCCs at 30 μg/ml as compared to 0 μg/ml. <sup>b</sup> p<0.05, significant increase in non-viable BCCs at 50 μg/ml as compared to 0 μg/ml and 30 μg/ml. b) Percentage of non-viable cells 3 days post treatment. <sup>a</sup> p<0.05, significant increase in non-viable BCCs at 30 μg/ml as compared to 0 μg/ml. <sup>b</sup> p<0.05, significant increase in non-viable BCCs at 50 μg/ml as compared to 0 μg/ml and 30 μg/ml. c) Carboplatin survival curve for chemotherapy treated and non-treated MDA-MB-231 cells, <sup>a</sup> p<0.05, significant decrease in percent viability (30%) of non-treated cells treated with carboplatin dosages between 100 μg/ml to 120 μg/ml as compared to treated cells (10%). <sup>b</sup> p<0.05, significant decrease in percent viability (40%) of non-treated cells treated with carboplatin dosages between 140 μg/ml to 170 μg/ml as compared to treated cells (20%).<sup>c</sup> p<0.05, significant decrease in percent viability (80%) of non-treated cells treated with carboplatin dosages 170 μg/ml to 220 μg/ml as compared to treated cells (20%).</p

    A: BCC growth on random and aligned fibrous scaffolds in comparison to TCP.

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    <p>a) TCP. <sup>a</sup> p<0.05, significant increase in growth of non treated BCCs at day 4 as compared to day 1. <sup>b</sup> p<0.05, significant increase in growth of non-treated BCCs at day 7 as compared to day 1and day 4. b) Random fibers. <sup>a</sup> p<0.05, significant increase in growth of non-treated BCCs at day 4 as compared to day 1 and day 7. c) Aligned fibers. Values are mean ±SD.</p

    Analysis of cell cycle phase for non-treated BCCs by flow cytometry on: TCP at a) day 1 and d) day 7, random fibrous scaffolds at b) day 1 and e) day 7, and aligned fibrous scaffolds at c) day 1 and f) day 7.

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    <p>Analysis of cell cycle phase for non-treated BCCs by flow cytometry on: TCP at a) day 1 and d) day 7, random fibrous scaffolds at b) day 1 and e) day 7, and aligned fibrous scaffolds at c) day 1 and f) day 7.</p

    Confocal fluorescent microscope images of MDA-MB-231 BCCs on the PCL random and aligned fibrous scaffolds and TCP control.

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    <p>Blue indicates nuclei (DAPI); green indicates F-actin (Alexa 488) and red is for anti-cyclin D1 expression. A) Non-treated BCCs on random scaffolds (a through d at day 1; e through h at day 7) and aligned scaffolds (i through l at day 1; m through p at day 7). B) Treated BCCs on random scaffolds (a through d at day 1; e through h at day 7) and aligned scaffolds (i through l at day 1; m through p at day 7). C) Non-treated BCCs (a through d at day 1; e through h at day 7) and treated BCCs (i through l at day 1; m through p at day 7) on TCP. All scale bars are 50 μm. D) Volume View of MDA-MB-231 BCCs, green indicates F-actin. On random fibers, non-treated cells at a) day 1 and b) day 7, and treated cells at e) day 1 and f) day 7. On aligned fibers, non-treated cells at c) day 1 and d) day 7 and treated cells at g) day 1 and h) day 7. 60x objective. Scale bar is 25 μm. The arrows show the cell body orientation along the fibers.</p
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