Several mathematical formulations have analyzed the time-dependent behaviour of a tumor mass. However, most of these propose simplifications that compromise the physical soundness of the model. Here, multiphase porous media mechanics is extended to model tumor evolution, using governing equations obtained via the Thermodynamically Constrained Averaging Theory (TCAT). A tumor mass is treated as a multiphase medium composed of an extracellular matrix (ECM); tumor cells (TC), which may become necrotic depending on the nutrient concentration and tumor phase pressure; healthy cells (HC); and an interstitial fluid (IF) for the transport of nutrients. The equations are solved by a Finite Element method to predict the growth rate of the tumor mass as a function of the initial tumor-to-healthy cell density ratio, nutrient concentration, mechanical strain, cell adhesion and geometry. Results are shown for three cases of practical biological interest such as multicellular tumor spheroids (MTS) and tumor cords. First, the model is validated by experimental data for time-dependent growth of an MTS in a culture medium. The tumor growth pattern follows a biphasic behaviour: initially, the rapidly growing tumor cells tend to saturate the volume available without any significant increase in overall tumor size; then, a classical Gompertzian pattern is observed for the MTS radius variation with time. A core with necrotic cells appears for tumor sizes larger than 150 μm, surrounded by a shell of viable tumor cells whose thickness stays almost constant with time. A formula to estimate the size of the necrotic core is proposed. In the second case, the MTS is confined within a healthy tissue. The growth rate is reduced, as compared to the first case – mostly due to the relative adhesion of the tumor and healthy cells to the ECM, and the less favourable transport of nutrients. In particular, for tumor cells adhering less avidly to the ECM, the healthy tissue is progressively displaced as the malignant mass grows, whereas tumor cell infiltration is predicted for the opposite condition. Interestingly, the infiltration potential of the tumor mass is mostly driven by the relative cell adhesion to the ECM. In the third case, a tumor cord model is analyzed where the malignant cells grow around microvessels in a 3D geometry. It is shown that tumor cells tend to migrate among adjacent vessels seeking new oxygen and nutrient. This model can predict and optimize the efficacy of anticancer therapeutic strategies. It can be further developed to answer questions on tumor biophysics, related to the effects of ECM stiffness and cell adhesion on tumor cell proliferation.

Angiogenesis has been known as a hallmark of solid tumor cancers for decades, yet ultrasound has been limited in its ability to detect the microvascular changes associated with malignancy. Here, we demonstrate the potential of 'ultrasound localization microscopy' applied volumetrically in combination with quantitative analysis of microvascular morphology, as an approach to overcome this limitation. This pilot study demonstrates our ability to image complex microvascular patterns associated with tumor angiogenesis in-vivo at a resolution of tens of microns -substantially better than the diffraction limit of traditional clinical ultrasound, yet using an 8 MHz clinical ultrasound probe. Furthermore, it is observed that data from healthy and tumor-bearing tissue exhibit significant differences in microvascular pattern and density. Results suggests that with continued development of these novel technologies, ultrasound has the potential to detect biomarkers of cancer based on the microvascular 'fingerprint' of malignant angiogenesis rather than through imaging of blood flow dynamics or the tumor mass itself.

The recent design of ultra-broadband, multi-frequency ultrasound transducers has enabled high sensitivity, high-resolution contrast imaging, with very efficient suppression of tissue background using a technique called acoustic angiography. Here we perform the first application of acoustic angiography to evolving tumors in mice predisposed to develop mammary carcinoma, with the intent of visualizing and quantifying angiogenesis progression associated with tumor growth. Metrics compared include vascular density and two measures of vessel tortuosity quantified from segmentations of vessels traversing and surrounding 24 tumors and abdominal vessels from control mice. Quantitative morphological analysis of tumor vessels demonstrated significantly increased vascular tortuosity abnormalities associated with tumor growth with the distance metric elevated approximately 14% and the sum of angles metric increased 60% in tumor vessels versus controls. Future applications of this imaging approach may provide clinicians a new tool in tumor detection, differentiation, or evaluation, though with limited depth of penetration using the current configuration.

Targeting the vasculature remains a promising approach for treating solid tumors; however, the mechanisms of tumor neovascularization are diverse and complex. Here we uncover a new subpopulation of melanoma cells that express the vascular cell adhesion molecule PECAM1, but not VEGFR-2, and participate in a PECAM1-dependent form of vasculogenic mimicry (VM). Clonally-derived PECAM1+ tumor cells coalesce to form PECAM1-dependent networks in vitro and they generate well-perfused, VEGF-independent channels in mice. The neural crest specifier AP-2α is diminished in PECAM1+ melanoma cells and is a transcriptional repressor of PECAM1. Reintroduction of AP-2α into PECAM1+ tumor cells represses PECAM1 and abolishes tube-forming ability whereas AP-2α knockdown in PECAM1− tumor cells up-regulates PECAM1 expression and promotes tube formation. Thus, VM-competent subpopulations, rather than all cells within a tumor, may instigate VM, supplant host-derived endothelium, and form PECAM1-dependent conduits that are not diminished by neutralizing VEGF.