Current and Emerging 3D Models to Study Breast Cancer

Translational medicine requires facile experimental systems to replicate the dynamic biological systems of diseases. Drug approval continues to lag, partly due to incongruencies in the research pipeline that traditionally involve 2D models, which could be improved with 3D models. The bone marrow (BM) poses challenges to harvest as an intact organ, making it difficult to study disease processes such as breast cancer (BC) survival in BM, and to effective evaluation of drug response in BM. Furthermore, it is a challenge to develop 3D BM structures due to its weak physical properties, and complex hierarchical structure and cellular landscape. To address this, we leveraged 3D bioprinting to create a BM structure with varied methylcellulose (M): alginate (A) ratios. We selected hydrogels containing 4% (w/v) M and 2% (w/v) A, which recapitulates rheological and ultrastructural features of the BM while maintaining stability in culture. This hydrogel sustained the culture of two key primary BM microenvironmental cells found at the perivascular region, mesenchymal stem cells and endothelial cells. More importantly, the scaffold showed evidence of cell autonomous dedifferentiation of BC cells to cancer stem cell properties. This scaffold could be the platform to create BM models for various diseases and also for drug screening.

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Fucoxanthin Holds Potential to Become a Drug Adjuvant in Breast Cancer Treatment: Evidence from 2D and 3D Cell Cultures

Molecules ◽

10.3390/molecules26144288 ◽

2021 ◽

Vol 26 (14) ◽

pp. 4288

Author(s):

Fernanda Malhão ◽

Ana Catarina Macedo ◽

Carla Costa ◽

Eduardo Rocha ◽

Alice Abreu Ramos

Keyword(s):

Breast Cancer ◽

Cell Lines ◽

3D Models ◽

Anticancer Activities ◽

Cytotoxic Effects ◽

3D Cultures ◽

3D Cell Cultures ◽

Tumoral Cell ◽

Microscopy Techniques ◽

2D And 3D

Fucoxanthin (Fx) is a carotenoid derived from marine organisms that exhibits anticancer activities. However, its role as a potential drug adjuvant in breast cancer (BC) treatment is still poorly explored. Firstly, this study investigated the cytotoxic effects of Fx alone and combined with doxorubicin (Dox) and cisplatin (Cis) on a panel of 2D-cultured BC cell lines (MCF7, SKBR3 and MDA-MB-231) and one non-tumoral cell line (MCF12A). Fucoxanthin induced cytotoxicity against all the cell lines and potentiated Dox cytotoxic effects towards the SKBR3 and MDA-MB-231 cells. The combination triggering the highest cytotoxicity (Fx 10 µM + Dox 1 µM in MDA-MB-231) additionally showed significant induction of cell death and genotoxic effects, relative to control. In sequence, the same combination was tested on 3D cultures using a multi-endpoint approach involving bioactivity assays and microscopy techniques. Similar to 2D cultures, the combination of Fx and Dox showed higher cytotoxic effects on 3D cultures compared to the isolated compounds. Furthermore, this combination increased the number of apoptotic cells, decreased cell proliferation, and caused structural and ultrastructural damages on the 3D models. Overall, our findings suggest Fx has potential to become an adjuvant for Dox chemotherapy regimens in BC treatment.

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Prevascularized, Co-Culture Model for Breast Cancer Drug Development

ASME 2012 Summer Bioengineering Conference, Parts A and B ◽

10.1115/sbc2012-80409 ◽

2012 ◽

Author(s):

Lauren Marshall ◽

Isabel Löwstedt ◽

Paul Gatenholm ◽

Joel Berry

Keyword(s):

Breast Cancer ◽

Drug Development ◽

Three Dimensional ◽

Human Tumor ◽

3D Models ◽

Cancer Drug ◽

Cancer Therapies ◽

Anti Cancer

The objective of this study was to create 3D engineered tissue models to accelerate identification of safe and efficacious breast cancer drug therapies. It is expected that this platform will dramatically reduce the time and costs associated with development and regulatory approval of anti-cancer therapies, currently a multi-billion dollar endeavor [1]. Existing two-dimensional (2D) in vitro and in vivo animal studies required for identification of effective cancer therapies account for much of the high costs of anti-cancer medications and health insurance premiums borne by patients, many of whom cannot afford it. An emerging paradigm in pharmaceutical drug development is the use of three-dimensional (3D) cell/biomaterial models that will accurately screen novel therapeutic compounds, repurpose existing compounds and terminate ineffective ones. In particular, identification of effective chemotherapies for breast cancer are anticipated to occur more quickly in 3D in vitro models than 2D in vitro environments and in vivo animal models, neither of which accurately mimic natural human tumor environments [2]. Moreover, these 3D models can be multi-cellular and designed with extracellular matrix (ECM) function and mechanical properties similar to that of natural in vivo cancer environments [3].

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Harnessing 3D models of mammary epithelial morphogenesis: An off the beaten path approach to identify candidate biomarkers of early stage breast cancer

Cancer Letters ◽

10.1016/j.canlet.2016.07.003 ◽

2016 ◽

Vol 380 (2) ◽

pp. 375-383 ◽

Cited By ~ 5

Author(s):

Stefano Rossetti ◽

Wiam Bshara ◽

Johanna A. Reiners ◽

Francesca Corlazzoli ◽

Austin Miller ◽

...

Keyword(s):

Breast Cancer ◽

Early Stage ◽

3D Models ◽

Mammary Epithelial ◽

Epithelial Morphogenesis ◽

Early Stage Breast Cancer

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Human Plasma-Derived 3D Cultures Model Breast Cancer Treatment Responses and Predict Clinically Effective Drug Treatment Concentrations

Cancers ◽

10.3390/cancers12071722 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1722 ◽

Cited By ~ 1

Author(s):

Kristin Calar ◽

Simona Plesselova ◽

Somshuvra Bhattacharya ◽

Megan Jorgensen ◽

Pilar de la Puente

Keyword(s):

Breast Cancer ◽

Cancer Treatment ◽

Human Plasma ◽

Cell Lines ◽

Single Cells ◽

3D Culture ◽

3D Models ◽

Preclinical Models ◽

Culture Model ◽

3D Culture Model

Lack of efficacy and a low overall success rate of phase I-II clinical trials are the most common failures when it comes to advancing cancer treatment. Current drug sensitivity screenings present several challenges including differences in cell growth rates, the inconsistent use of drug metrics, and the lack of translatability. Here, we present a patient-derived 3D culture model to overcome these limitations in breast cancer (BCa). The human plasma-derived 3D culture model (HuP3D) utilizes patient plasma as the matrix, where BCa cell lines and primary BCa biopsies were grown and screened for drug treatments. Several drug metrics were evaluated from relative cell count and growth rate curves. Correlations between HuP3D metrics, established preclinical models, and clinical effective concentrations in patients were determined. HuP3D efficiently supported the growth and expansion of BCa cell lines and primary breast cancer tumors as both organoids and single cells. Significant and strong correlations between clinical effective concentrations in patients were found for eight out of ten metrics for HuP3D, while a very poor positive correlation and a moderate correlation was found for 2D models and other 3D models, respectively. HuP3D is a feasible and efficacious platform for supporting the growth and expansion of BCa, allowing high-throughput drug screening and predicting clinically effective therapies better than current preclinical models.

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Histamine-functionalized copolymer micelles as a drug delivery system in 2D and 3D models of breast cancer

Journal of Materials Chemistry B ◽

10.1039/c4tb02051k ◽

2015 ◽

Vol 3 (12) ◽

pp. 2472-2486 ◽

Cited By ~ 17

Author(s):

Yuning Zhang ◽

Pontus Lundberg ◽

Maren Diether ◽

Christian Porsch ◽

Caroline Janson ◽

...

Keyword(s):

Breast Cancer ◽

Drug Delivery ◽

Block Copolymers ◽

Click Chemistry ◽

Drug Delivery System ◽

Delivery System ◽

3D Models ◽

Copolymer Micelles ◽

2D And 3D

Histamine functionalized block copolymers were prepared with different ratios of histamine and octyl or benzyl groups using UV-initiated thiol-ene click chemistry.

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Anticancer activity of the seaweed compound fucoxanthin in breast cancer cell lines cultured as 2D and 3D models

10.3390/ecmc2019-06346 ◽

2019 ◽

Author(s):

Ana Catarina Macedo ◽

Fernanda Malhão ◽

Eduardo Rocha ◽

Alice Ramos

Keyword(s):

Breast Cancer ◽

Anticancer Activity ◽

Cell Lines ◽

Cancer Cell ◽

Breast Cancer Cell ◽

3D Models ◽

Cancer Cell Lines ◽

Breast Cancer Cell Lines ◽

2D And 3D

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Exploration and analysis of molecularly annotated, 3D models of breast cancer at single-cell resolution using virtual reality

10.1101/2021.06.28.448342 ◽

2021 ◽

Author(s):

Dario Bressan ◽

Claire M Mulvey ◽

Fatime Qosaj ◽

Robert Becker ◽

Flaminia Grimaldi ◽

...

Keyword(s):

Breast Cancer ◽

Virtual Reality ◽

Cancer Biology ◽

Time Series Data ◽

Three Dimensional ◽

3D Models ◽

Three Dimensions ◽

Series Data ◽

Spatially Resolved ◽

Molecular Features

A set of increasingly powerful approaches are enabling spatially resolved measurements of growing numbers of molecular features in biological samples. While important insights can be derived from the two-dimensional data that many of these technologies generate, it is clear that extending these approaches into the third and fourth dimensions will magnify their impact. Realizing biological insights from datasets where thousands to millions of cells are annotated with tens to hundreds of parameters in space will require the development of new computational and visualization strategies. Here, we describe Theia, a virtual reality-based platform, which enables exploration and analysis of either volumetric or segmented, molecularly-annotated, three-dimensional datasets, with the option to extend the analysis to time-series data. We also describe our pipeline for generating annotated 3D models of breast cancer and supply several datasets to enable users to explore the utility of Theia for understanding cancer biology in three dimensions.

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Synthesis of micellar-like terpolymer nanoparticles with reductively-cleavable cross-links and evaluation of efficacy in 2D and 3D models of triple negative breast cancer

Journal of Controlled Release ◽

10.1016/j.jconrel.2020.04.049 ◽

2020 ◽

Vol 323 ◽

pp. 549-564 ◽

Cited By ~ 2

Author(s):

Patrícia F. Monteiro ◽

Muhammad Gulfam ◽

Cíntia J. Monteiro ◽

Alessandra Travanut ◽

Thais Fedatto Abelha ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

3D Models ◽

Cross Links ◽

2D And 3D

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Development of Breast Cancer Spheroids to Evaluate Cytotoxic Response to an Anticancer Peptide

Pharmaceutics ◽

10.3390/pharmaceutics13111863 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1863

Author(s):

Marco Cavaco ◽

Patrícia Fraga ◽

Javier Valle ◽

David Andreu ◽

Miguel A. R. B. Castanho ◽

...

Keyword(s):

Breast Cancer ◽

Drug Development ◽

Three Dimensional ◽

3D Models ◽

Cell Permeabilization ◽

Anticancer Peptide ◽

Cell Monolayers ◽

Common Causes ◽

Cancer Spheroids

Breast cancer (BC) is the most commonly diagnosed cancer in women and one of the most common causes of cancer-related deaths. Despite intense research efforts, BC treatment still remains challenging. Improved drug development strategies are needed for impactful benefit to patients. Current preclinical studies rely mostly on cell-based screenings, using two-dimensional (2D) cell monolayers that do not mimic in vivo tumors properly. Herein, we explored the development and characterization of three-dimensional (3D) models, named spheroids, of the most aggressive BC subtypes (triple-negative breast cancer-TNBC; and human-epidermal growth receptor-2-HER2+), using the liquid overlay technique with several selected cell lines. In these cell line-derived spheroids, we studied cell density, proliferation, ultrastructure, apoptosis, reactive oxygen species (ROS) production, and cell permeabilization (live/dead). The results showed a formation of compact and homogeneous spheroids on day 7 after seeding 2000 cells/well for MDA-MB-231 and 5000 cells/well for BT-20 and BT-474. Next, we compared the efficacy of a model anticancer peptide (ACP) in cell monolayers and spheroids. Overall, the results demonstrated spheroids to be less sensitive to treatment than cell monolayers, revealing the need for more robust models in drug development.

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