MET is required for the recruitment of anti-tumoural neutrophils

Mutations or amplification of the MET proto-oncogene are involved in the pathogenesis of several tumours, which rely on the constitutive engagement of this pathway for their growth and survival. However, MET is expressed not only by cancer cells but also by tumour-associated stromal cells, although its precise role in this compartment is not well characterized. Here we show that MET is required for neutrophil chemoattraction and cytotoxicity in response to its ligand hepatocyte growth factor (HGF). Met deletion in mouse neutrophils enhances tumour growth and metastasis. This phenotype correlates with reduced neutrophil infiltration to both the primary tumour and metastatic sites. Similarly, Met is necessary for neutrophil transudation during colitis, skin rash or peritonitis. Mechanistically, Met is induced by tumour-derived tumour necrosis factor (TNF)-a or other inflammatory stimuli in both mouse and human neutrophils. This induction is instrumental for neutrophil transmigration across an activated endothelium and for inducible nitric oxide synthase production upon HGF stimulation. Consequently, HGF/MET-dependent nitric oxide release by neutrophils promotes cancer cell killing, which abates tumour growth and metastasis. After systemic administration of a MET kinase inhibitor, we prove that the therapeutic benefit of MET targeting in cancer cells is partly countered by the pro-tumoural effect arising from MET blockade in neutrophils. Our work identifies an unprecedented role of MET in neutrophils, suggests a potential 'Achilles' heel' of MET-targeted therapies in cancer, and supports the rationale for evaluating anti-MET drugs in certain inflammatory diseases.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.