Physical and biochemical gradients that form within the primary tumor tissue promote tumor cell invasion and drive persistent migration towards blood vessels and the lymphatics to facilitate tumor cell dissemination. These microenvironment cues include hypoxia and pH gradients, gradients of soluble cues that induce chemotaxis, and ions that facilitate galvanotaxis, as well as modifications to the concentration, organization and stiffness of the extracellular matrix that produce haptotactic, alignotactic and durotactic gradients (See Figure 1A, adapted from from Oudin & Weaver, 2017). We and others have shown that invasive cells can become sensitized to individual guidance cues, which then promotes metastasis (Oudin et al, 2016; Oudin et al, 2016). However, how tumor cells integrate their signaling and biophysical responses to multiple, distinct motility cues as they progress through the metastatic cascade remains poorly understood. We hypothesize that tumor cells are particularly sensitive to certain combinations of cues that induce hyper-invasive responses via coordinated signaling events and morphological changes, which in turn promote local invasion, in the primary tumor and/or support colonization in the liver. We will take a data-driven systems-level approach to analyzing how different combinations of GF and ECM cues present within the tumor microenvironment drive motility, using microfluidics and lie imaging in vitro and implantable devices coupled to intravital imaging in vivo (See Figure 1B).
Figure 1: Studying directional migration in cancer A) We are interested in studying the interplay between chemotaxis, the migration of cells towards soluble cues, haptotaxis, the migration of cells towards substrate-bound proteins, and durotaxis, the migration of cells towards areas of higher stiffness. B) We will use both in vitro and in vivo approaches to study directional migration.
Chemotherapy is widely used to treat metastatic disease. However, while many patients initially respond, a high percentage of them ultimately relapse. Cells plated in a monolayer respond much better to cytotoxic therapy than the same cells grown in 3D spheroids, or in xenograft tumors in mice, suggesting that the ECM and stromal cells that make up the tumor microenvironment drive drug resistance. While there has been work highlighting mechanisms of resistance derived from the release of cytokines from stromal cells, the role of the ECM in this process remains understudied in 3D in vitro systems or in vivo using mouse models. In addition, how chemotherapy treatment alters the ECM remains unknown. Finally, most studies focus on the effect chemotherapeutics on cell death, while the potentially dangerous effects of these drugs on tumor cell invasion and metastatic capability remain understudied.
Our preliminary data show that chemotherapeutics can have different effects on growth and motility in vivo, and that effects on tumor size might not correlate with changes in cell motility (Figure 2A-C, Oudin et al, 2017). We also found that chemotherapeutic treatments can lead to changes in ECM amount in the tumor microenvironment and affect how cells respond to tumor ECM (Figure 2D,E). We hypothesize that certain 3D ECM microenvironments may trigger changes in sensitivity to chemotherapy, while regulators of ECM, such as proteases, which can modulate tumor cell invasion, matrix remodeling and metastasis, affect how tumor cells respond to chemotherapy. We will use CRISPR/Cas9 technology to perform a targeted screen of ECM proteins, using high-throughput viral transduction and high-content imaging of tumor sphere growth.
Figure 2: Dissecting the relationship between chemotherapy and the ECM. A) NOD-SCID mice bearing tumors generated from MDA-MB-231 cells treated with Doxorubicin and Paclitaxel. Effects on B) tumor growth and C) motility, as measured by intravital imaging, were quantified. E) Representative images of metastatic breast tumors treated with Paclitaxel showing tumor cells (green) and collagen (magenta). E) Effect of Taxol and Doxorubicin on thickness of collagen capsule surrounding tumors. Results show mean ± SEM, significance by one way ANOVA, **p<0.01.