ABSTRACT
Chronic inflammation is associated with the development of human hepatocellular carcinoma (HCC), an essentially incurable cancer. Anti-inflammatory nutraceuticals have emerged as promising candidates against HCC, yet the mechanisms through which they influence the cell signaling machinery to impose phenotypic changes remain unresolved. Herein we implemented a systems biology approach in HCC cells, based on the integration of cytokine release and phospoproteomic data from high-throughput xMAP Luminex assays to elucidate the action mode of prominent nutraceuticals in terms of topology alterations of HCC-specific signaling networks. An optimization algorithm based on SigNetTrainer, an Integer Linear Programming formulation, was applied to construct networks linking signal transduction to cytokine secretion by combining prior knowledge of protein connectivity with proteomic data. Our analysis identified the most probable target phosphoproteins of interrogated compounds and predicted translational control as a new mechanism underlying their anticytokine action. Induced alterations corroborated with inhibition of HCC-driven angiogenesis and metastasis.
ABSTRACT
OBJECTIVE: Chondrocyte signaling is widely identified as a key component in cartilage homeostasis. Dysregulations of the signaling processes in chondrocytes often result in degenerative diseases of the tissue. Traditionally, the literature has focused on the study of major players in chondrocyte signaling, but without considering the cross-talks between them. In this paper, we systematically interrogate the signal transduction pathways in chondrocytes, on both the phosphoproteomic and cytokine release levels. METHODS: The signaling pathways downstream 78 receptors of interest are interrogated. On the phosphoproteomic level, 17 key phosphoproteins are measured upon stimulation with single treatments of 78 ligands. On the cytokine release level, 55 cytokines are measured in the supernatant upon stimulation with the same treatments. Using an Integer Linear Programming (ILP) formulation, the proteomic data is combined with a priori knowledge of proteins' connectivity to construct a mechanistic model, predictive of signal transduction in chondrocytes. RESULTS: We were able to validate previous findings regarding major players of cartilage homeostasis and inflammation (e.g., IL1B, TNF, EGF, TGFA, INS, IGF1 and IL6). Moreover, we studied pro-inflammatory mediators (IL1B and TNF) together with pro-growth signals for investigating their role in chondrocytes hypertrophy and highlighted the role of underreported players such as Inhibin beta A (INHBA), Defensin beta 1 (DEFB1), CXCL1 and Flagellin, and uncovered the way they cross-react in the phosphoproteomic level. CONCLUSIONS: The analysis presented herein, leveraged high throughput proteomic data via an ILP formulation to gain new insight into chondrocytes signaling and the pathophysiology of degenerative diseases in articular cartilage.
