Dataset Information

Amplification of RANK- and c-Met-mediated signaling promotes metastatic colonization

ABSTRACT: We found that RANKL, expressed by cancer cells or derived from exogenous sources, consistently induced human prostate, breast, kidney, lung and liver cancer cells to colonize or metastasize to bone in an animal model of cancer bone metastasis. RANK-mediated signaling established a premetastatic niche through a forward feedback loop by inducing RANKL and c-Met expression and downstream signaling via upregulation of master regulator transcription factors regulating EMT (Twist1, Slug, Zeb1, Zeb2), stem cells (Sox2, Myc, Oct3/4 and Nanog), neuroendocrine cells (Sox 9, HIF-1α and FoxA2) and osteomimicry (c-Myc/Max, Sox2, Sox9, HIF1α and Runx2). Abrogating RANK or its downstream signaling network, c-Myc/Max or c-Met, abolished PCa skeletal metastasis in mice. We observed that a small number of RANKL-expressing PCa cells can initiate bone and soft tissue metastases by recruiting non-tumorigenic or bystander PCa or host cells from the circulation or at metastatic sites to co-colonize bone. The recruited bystander PCa cells assume the phenotypes of RANKL-expressing PCa cells by expressing increased c-Met, phosphorylated c-Met and RANKL. RANKL expression at a single cell level in primary PCa tissues predicted disease-specific survival, reflecting the significant role of RANKL-RANK signaling in the development of lethal bone metastasis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE48432 | GEO | 2014/02/06

SECONDARY ACCESSION(S): PRJNA210118

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Background This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure. Results Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way. Conclusions We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics Model is encoded by Ruby and submitted and curated to BioModels by Ahmad Zyoud

Dataset Information

Amplification of RANK- and c-Met-mediated signaling promotes metastatic colonization

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure