Age is a leading risk factor for developing breast cancer. This may be in part to the time required for acquiring sufficient cancer mutations; however, stromal cells that accumulate in tissues and undergo senescence eventually develop a senescence-associated secretory phenotype that alters the microenvironment to promote cancer. Our focus is on mesenchymal stem cells (MSCs) – stromal cells recruited to tumors due to their natural tropism for inflammatory tissues; MSCs have been shown to enhance the metastatic potential of tumor cells through direct interactions or paracrine signaling within the tumor. In the tumor, MSCs can differentiate into carcinoma-associated fibroblasts that play a central role in tumor growth and matrix remodeling. We recently investigated the molecular and mechanical differences in pre- and post- senescent MSCs and how their interactions with MDA-MB-231 breast cancer cells contribute to malignancy. Our data show post-senescent MSCs are larger and less motile, with more homogeneous mechanical properties than pre-senescent MSCs. In-depth omics analysis revealed differentially regulated genes and peptides including factors related to inflammatory cytokines, cell adhesion to the extracellular matrix, and cytoskeletal regulation. A 3D co-culture model was used to assess the effects of pre- and post- senescent MSCs on collagen matrix remodeling. Although post-senescent MSCs were far less motile than pre-senescent MSCs and less contractile with the matrix, they profoundly altered matrix protein deposition and crosslinking, which resulted in local matrix stiffening effects. Post-senescent MSCs also induced an invasive breast cancer cell phenotype, characterized by increased proliferation and invasion of breast cancer cells. This invasive breast cancer cell behavior was further amplified when MDA-MB-231 was co-cultured with a mixture of pre- and post- senescent MSCs; this result was attributed to matrix remodeling and soluble factor secretion effects of post-senescent MSCs, which enhanced the migration of pre-senescent MSCs allowing them to form tracks in the collagen network for cancer cells to follow. Finally, molecular inhibitors targeting actomyosin contractility and adhesion were used to alter MSC interactions with breast cancer cells. Actin depolymerizing agent and focal adhesion kinase inhibitor were most efficient and completely able to block the effects of post-senescent MSCs on MDA-MB-231 invasion in collagen gels. This comprehensive approach can be used to identify molecular pathways regulating heterotypic interactions of post-senescent MSCs with other cells in the tumor. Furthermore, the local matrix stiffening effect of post-senescent MSCs may play a critical role in breast cancer progression.
more »
« less
Cancer Cell Invasion of Mammary Organoids with Basal‐In Phenotype
This paper describes mammary organoids with a basal‐in phenotype where the basement membrane is located on the interior surface of the organoid. A key materials consideration to induce this basal‐in phenotype is the use of a minimal gel scaffold that the epithelial cells self‐assemble around and encapsulate. When MDA‐MB‐231 breast cancer cells are co‐cultured with epithelial cells from day 0 under these conditions, cells self‐organize into patterns with distinct cancer cell populations both inside and at the periphery of the epithelial organoid. In another type of experiment, the robust formation of the basement membrane on the epithelial organoid interior enables convenient studies of MDA‐MB‐231 invasion in a tumor progression‐relevant direction relative to epithelial cell‐basement membrane positioning. That is, the study of cancer invasion through the epithelium first, followed by the basement membrane to the basal side, is realized in an experimentally convenient manner where the cancer cells are simply seeded on the outside of preformed organoids, and their invasion into the organoid is monitored. Interestingly, invasion is more prominent when tumor cells are added to day 7 organoids with less developed basement membranes compared to day 16 organoids with more defined ones.
more » « less- Award ID(s):
- 1648035
- NSF-PAR ID:
- 10453603
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Healthcare Materials
- Volume:
- 10
- Issue:
- 4
- ISSN:
- 2192-2640
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Abstract Uncontrolled growth of tumor cells in confined spaces leads to the accumulation of compressive stress within the tumor. Although the effects of tension within 3D extracellular matrices (ECMs) on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored. In this study, we modified a Transwell assay such that it provides constant compressive loads to spheroids embedded within a collagen matrix. We used microscopic imaging to follow the single cell dynamics of the cells within the spheroids, as well as invasion into the 3D ECMs. Our experimental results showed that malignant breast tumor (MDA-MB-231) and non-tumorigenic epithelial (MCF10A) spheroids responded differently to a constant compression. Cells within the malignant spheroids became more motile within the spheroids and invaded more into the ECM under compression; whereas cells within non-tumorigenic MCF10A spheroids became less motile within the spheroids and did not display apparent detachment from the spheroids under compression. These findings suggest that compression may play differential roles in healthy and pathogenic epithelial tissues and highlight the importance of tumor mechanics and invasion.
-
Xu, Jinbo (Ed.)Abstract Motivation Motions of transmembrane receptors on cancer cell surfaces can reveal biophysical features of the cancer cells, thus providing a method for characterizing cancer cell phenotypes. While conventional analysis of receptor motions in the cell membrane mostly relies on the mean-squared displacement plots, much information is lost when producing these plots from the trajectories. Here we employ deep learning to classify breast cancer cell types based on the trajectories of epidermal growth factor receptor (EGFR). Our model is an artificial neural network trained on the EGFR motions acquired from six breast cancer cell lines of varying invasiveness and receptor status: MCF7 (hormone receptor positive), BT474 (HER2-positive), SKBR3 (HER2-positive), MDA-MB-468 (triple negative, TN), MDA-MB-231 (TN) and BT549 (TN). Results The model successfully classified the trajectories within individual cell lines with 83% accuracy and predicted receptor status with 85% accuracy. To further validate the method, epithelial–mesenchymal transition (EMT) was induced in benign MCF10A cells, noninvasive MCF7 cancer cells and highly invasive MDA-MB-231 cancer cells, and EGFR trajectories from these cells were tested. As expected, after EMT induction, both MCF10A and MCF7 cells showed higher rates of classification as TN cells, but not the MDA-MB-231 cells. Whereas deep learning-based cancer cell classifications are primarily based on the optical transmission images of cell morphology and the fluorescence images of cell organelles or cytoskeletal structures, here we demonstrated an alternative way to classify cancer cells using a dynamic, biophysical feature that is readily accessible. Availability and implementation A python implementation of deep learning-based classification can be found at https://github.com/soonwoohong/Deep-learning-for-EGFR-trajectory-classification. Supplementary information Supplementary data are available at Bioinformatics online.more » « less
-
Senescence is a potent tumor-suppressive mechanism that irreversibly arrests the growth of damaged cells. However, senescent cells that accumulate in tissues eventually develop a senescence-associated secretory phenotype (SASP) that alters the microenvironment to promote cancer. Paracrine factors in the SASP may also contribute to the formation of rare giant polyploidal cancer cells (GPCCs). A single-cell mechanical approach was used to profile cytoskeletal and nuclear mechanics, morphology, motility, and adhesion for breast cancer cells treated with conditioned media from senescent fibroblasts. Our study showed that a small but significant population of MDA-MB-231 breast cancer cells (less than 5%) treated with conditioned media from senescent LF-1 fibroblasts develop an enlarged morphology, chromosomal instability, and polyploidy, a phenotype associated with GPCCs. Although GPCCs are highly invasive and chemoresistant, little is known about their biophysical properties. First, we developed a method for identifying the small subpopulation of GPCCs in a heterogeneous population of cancer cells based on increased nuclear area and confirmed that GPCCs are more resistant to paclitaxel than normal-size MDA-MB-231 cells (NCCs). We then compared critical biophysical properties of NCCs and GPCCs, including cytoskeletal and nuclear mechanics, cell and nuclear morphology, motility, and adhesion. Cells were stained for cytoskeletal proteins actin, tubulin, and vinculin. Cytoskeletal organization was dramatically altered in GPCCs compared to NCCs. GPCCs displayed more disorganized microtubule structure, dense actin stress fibers, and mature focal adhesions. Intracellular particle tracking microrheology was used to measure cytoskeletal and nuclear mechanics. These studies demonstrated that although GPCCs are thought to be highly invasive cancer cells, they are inherently stiffer than NCCs, in terms of both their cytoskeletal and nuclear mechanics. This was surprising since more invasive cancer cells are often more compliant than less invasive cancer cells. This result may be in part to the ability for GPCCs to behave like activated stromal cells that stiffen in the tumor; we confirmed that GPCCs display similar adhesive behavior as activated stromal cells. To determine how mechanics correlates with cell migration, we used time-lapse nuclear tracking to measure cell motility. The average cell speed was higher for NCCs than for GPCCs; however, GPCCs moved longer distances over time because their motion was more directional. These findings highlight the unusual biophysical behavior of GPCCs. To develop pharmacologic tools that target GPCCs, it is imperative to understand their biophysical properties.more » « less
-
Abstract Immunotherapy has revolutionized cancer treatment with the advent of advanced cell engineering techniques aimed at targeted therapy with reduced systemic toxicity. However, understanding the underlying immune–cancer interactions require development of advanced three-dimensional (3D) models of human tissues. In this study, we fabricated 3D tumor models with increasing complexity to study the cytotoxic responses of CD8 + T cells, genetically engineered to express mucosal-associated invariant T (MAIT) cell receptors, towards MDA-MB-231 breast cancer cells. Homotypic MDA-MB-231 and heterotypic MDA-MB-231/human dermal fibroblast tumor spheroids were primed with precursor MAIT cell ligand 5-amino-6-D-ribitylaminouracil (5-ARU). Engineered T cells effectively eliminated tumors after a 3 d culture period, demonstrating that the engineered T cell receptor recognized major histocompatibility complex class I-related (MR1) protein expressing tumor cells in the presence of 5-ARU. Tumor cell killing efficiency of engineered T cells were also assessed by encapsulating these cells in fibrin, mimicking a tumor extracellular matrix microenvironment. Expression of proinflammatory cytokines such as interferon gamma, interleukin-13, CCL-3 indicated immune cell activation in all tumor models, post immunotherapy. Further, in corroborating the cytotoxic activity, we found that granzymes A and B were also upregulated, in homotypic as well as heterotypic tumors. Finally, a 3D bioprinted tumor model was employed to study the effect of localization of T cells with respect to tumors. T cells bioprinted proximal to the tumor had reduced invasion index and increased cytokine secretion, which indicated a paracrine mode of immune–cancer interaction. Development of 3D tumor-T cell platforms may enable studying the complex immune–cancer interactions and engineering MAIT cells for cell-based cancer immunotherapies.more » « less
