The biology of the metastatic colonization process remains a poorly understood phenomenon. To improve our knowledge of its dynamics, we conducted a modelling study based on multi-modal data from an orthotopic murine experimental system of metastatic renal cell carcinoma. The standard theory of metastatic colonization usually assumes that secondary tumours, once established at a distant site, grow independently from each other and from the primary tumour. Using a mathematical model that translates this assumption into equations, we challenged this theory against our data that included: 1) dynamics of primary tumour cells in the kidney and metastatic cells in the lungs, retrieved by green fluorescent protein tracking, and 2) magnetic resonance images (MRI) informing on the number and size of macroscopic lesions. Critically, when calibrated on the growth of the primary tumour and total metastatic burden, the predicted theoretical size distributions were not in agreement with the MRI observations. Moreover, tumour expansion only based on proliferation was not able to explain the volume increase of the metastatic lesions. These findings strongly suggested rejection of the standard theory, demonstrating that the time development of the size distribution of metastases could not be explained by independent growth of metastatic foci. This led us to investigate the effect of spatial interactions between merging metastatic tumours on the dynamics of the global metastatic burden. We derived a mathematical model of spatial tumour growth, confronted it with experimental data of single metastatic tumour growth, and used it to provide insights on the dynamics of multiple tumours growing in close vicinity. Together, our results have implications for theories of the metastatic process and suggest that global dynamics of metastasis development is dependent on spatial interactions between metastatic lesions.

Polo-like kinase 1 (Plk1) expression is inversely correlated with survival advantages in many cancers. However, molecular mechanisms that underlie Plk1 expression are poorly understood. Here, we uncover a hypoxia-regulated mechanism of Plk1-mediated cancer metastasis and drug resistance. We demonstrated that a HIF-2-dependent regulatory pathway drives Plk1 expression in clear cell renal cell carcinoma (ccRCC). Mechanistically, HIF-2 transcriptionally targets the hypoxia response element of the Plk1 promoter. In ccRCC patients, high expression of Plk1 was correlated to poor disease-free survival and overall survival. Loss-of-function of Plk1 in vivo markedly attenuated ccRCC growth and metastasis. High Plk1 expression conferred a resistant phenotype of ccRCC to targeted therapeutics such as sunitinib, in vitro, in vivo, and in metastatic ccRCC patients. Importantly, high Plk1 expression was defined in a subpopulation of ccRCC patients that are refractory to current therapies. Hence, we propose a therapeutic paradigm for improving outcomes of ccRCC patients.

Renal cell carcinoma (RCC) represents the main renal tumors and are highly metastatic. They are heterogeneous tumors and are subdivided in 12 different subtypes where clear cell RCC (ccRCC) represents the main subtype. Tumor extracellular matrix (ECM) is composed, in RCC, mainly of different fibrillar collagens, fibronectin, and components of the basement membrane such as laminin, collagen IV, and heparan sulfate proteoglycan.Little is known about the role of these ECM components on RCC cell behavior. Analysis from The Human Protein Atlas dataset shows that high collagen 1 or 4A2, fibronectin, entactin, or syndecan 3 expression is associated with poor prognosis whereas high collagen 4A3, syndecan 4, or glypican 4 expression is associated with increased patient survival. We then analyzed the impact of collagen 1, fibronectin 1 or Matrigel on three different RCC cell lines (Renca, 786-O and Caki-2) in vitro. We found that all the different matrices have little effect on RCC cell proliferation. The three cell lines adhere differently on the three matrices, suggesting the involvement of a different set of integrins. Among the 3 matrices tested, collagen 1 is the only component able to increase migration in the three cell lines as well as MMP-2 and 9 activity. Moreover, collagen 1 induces MMP-2 mRNA expression and is implicated in the epithelial to mesenchymal transition of two RCC cell lines via Zeb2 (Renca) or Snail 2 (Caki-2) mRNA expression. Taken together, our results show that collagen 1 is the main component of the ECM that enhances tumor cell invasion in RCC, which is important for the metastasic process.