Mechanical compression drives cancer cells toward invasive phenotype

Uncontrolled growth in a confined space generates mechanical compressive stress within tumors, but little is known about how such stress affects tumor cell behavior. Here we show that compressive stress stimulates migration of mammary carcinoma cells. The enhanced migration is accomplished by a subset of "leader cells" that extend filopodia at the leading edge of the cell sheet. Formation of these leader cells is dependent on cell microorganization and is enhanced by compressive stress. Accompanied by fibronectin deposition and stronger cell-matrix adhesion, the transition to leader-cell phenotype results in stabilization of persistent actomyosin-independent cell extensions and coordinated migration. Our results suggest that compressive stress accumulated during tumor growth can enable coordinated migration of cancer cells by stimulating formation of leader cells and enhancing cell-substrate adhesion. This novel mechanism represents a potential target for the prevention of cancer cell migration and invasion.

Abstract 4811: Compression-induced cell distension stimulates coordinated migration of mammary carcinoma cells

Uncontrolled cell proliferation of a solid tumor in a confined space not only creates oxidative stress (hypoxia), but also generates mechanical compressive stress, which can influence the tumor cells and modify their interactions with neighboring cells and the extracellular matrix. Little is known about how such compressive stress affects cancer progression. Here we show, for the first time, that externally-applied compressive stress results in faster migration of mammary carcinoma cells. Compression induces migration of mammary carcinoma cells in a coordinated sheet, initiated by “leader cells” - single cells at the leading edge of the sheet, extending long filopodia. The formation of leader cells is dependent on the geometry of association with neighboring cells, but the frequency of leader-cell formation - and sheet migration speed - is increased by applying compression perpendicular to the sheet. Accompanied by redistribution of fibronectin deposition, applied compression enhances cell-matrix adhesion and stabilizes cell distension independent of actomyosin contractile machinery. Our results suggest that mechanical stress accumulated during tumor growth is sufficient to enhance cell-substrate adhesion and stimulate cancer cell migration. This mechanism opens the door to a new class of targets for blocking mechanical stress pathways.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4811.

Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging

Intravital multiphoton microscopy has provided powerful mechanistic insights into health and disease and has become a common instrument in the modern biological laboratory. The requisite high numerical aperture and exogenous contrast agents that enable multiphoton microscopy, however, limit the ability to investigate substantial tissue volumes or to probe dynamic changes repeatedly over prolonged periods. Here we introduce optical frequency domain imaging (OFDI) as an intravital microscopy that circumvents the technical limitations of multiphoton microscopy and, as a result, provides unprecedented access to previously unexplored, crucial aspects of tissue biology. Using unique OFDI-based approaches and entirely intrinsic mechanisms of contrast, we present rapid and repeated measurements of tumor angiogenesis, lymphangiogenesis, tissue viability and both vascular and cellular responses to therapy, thereby demonstrating the potential of OFDI to facilitate the exploration of physiological and pathological processes and the evaluation of treatment strategies.

PDGF-C induces maturation of blood vessels in a model of glioblastoma and attenuates the response to anti-VEGF treatment

Background

Recent clinical trials of VEGF inhibitors have shown promise in the treatment of recurrent glioblastomas (GBM). However, the survival benefit is usually short-lived as tumors escape anti-VEGF therapies. Here we tested the hypothesis that Platelet Derived Growth Factor-C (PDGF-C), an isoform of the PDGF family, affects GBM progression independent of VEGF pathway and hinders anti-VEGF therapy.

Principal Findings

We first showed that PDGF-C is present in human GBMs. Then, we overexpressed or downregulated PDGF-C in a human GBM cell line, U87MG, and grew them in cranial windows in nude mice to assess vessel structure and function using intravital microscopy. PDGF-C overexpressing tumors had smaller vessel diameters and lower vascular permeability compared to the parental or siRNA-transfected tumors. Furthermore, vessels in PDGF-C overexpressing tumors had more extensive coverage with NG2 positive perivascular cells and a thicker collagen IV basement membrane than the controls. Treatment with DC101, an anti-VEGFR-2 antibody, induced decreases in vessel density in the parental tumors, but had no effect on the PDGF-C overexpressing tumors.

Conclusion

These results suggest that PDGF-C plays an important role in glioma vessel maturation and stabilization, and that it can attenuate the response to anti-VEGF therapy, potentially contributing to escape from vascular normalization.

A 2-D/3-D model-based method to quantify the complexity of microvasculature imaged by in vivo multiphoton microscopy

This paper presents model-based information-theoretic methods to quantify the complexity of tumor microvasculature, taking into account shape, textural, and structural irregularities. The proposed techniques are completely automated, and are applicable to optical slices (3-D) or projection images (2-D). Improvements upon the prior literature include: (i) measuring local (vessel segment) as well as global (entire image) vascular complexity without requiring explicit segmentation or tracing; (ii) focusing on the vessel boundaries in the complexity estimate; and (iii) added robustness to image artifacts common to tumor microvasculature images. Vessels are modeled using a family of super-Gaussian functions that are based on the superquadric modeling primitive common in computer vision. The superquadric generalizes a simple ellipsoid by including shape parameters that allow it to approximate a cylinder with elliptical cross-sections (generalized cylinder). The super-Gaussian is obtained by composing a superquadric with an exponential function giving a form that is similar to a standard Gaussian function but with the ability to produce level sets that approximate generalized cylinders. Importantly, the super-Gaussian is continuous and differentiable so it can be fit to image data using robust non-linear regression. This fitting enables quantification of the intrinsic complexity of vessel data vis-a-vis the super-Gaussian model within a minimum message length (MML) framework. The resulting measures are expressed in units of information (bits). Synthetic and real-data examples are provided to illustrate the proposed measures.