Dynamic network biomarker indicates pulmonary metastasis at the tipping point of hepatocellular carcinoma

Abstract

Developing predictive biomarkers that can detect the tipping point before metastasis of hepatocellular carcinoma (HCC), is critical to prevent further irreversible deterioration. To discover such early-warning signals or biomarkers of pulmonary metastasis in HCC, we analyse time-series gene expression data in spontaneous pulmonary metastasis mice HCCLM3-RFP model with our dynamic network biomarker (DNB) method, and identify CALML3 as a core DNB member. All experimental results of gain-of-function and loss-of-function studies show that CALML3 could indicate metastasis initiation and act as a suppressor of metastasis. We also reveal the biological role of CALML3 in metastasis initiation at a network level, including proximal regulation and cascading influences in dysfunctional pathways. Our further experiments and clinical samples show that DNB with CALML3 reduced pulmonary metastasis in liver cancer. Actually, loss of CALML3 predicts shorter overall and relapse-free survival in postoperative HCC patients, thus providing a prognostic biomarker and therapy target in HCC.

Abstract

Biomarkers of the tipping point before metastasis in hepatocellular carcinoma (HCC) could help stratify patient treatment. Here, the authors study dynamic network biomarkers to identify CALM3 as a potential suppressor of metastasis, the level of which can predict overall survival and relapse-free survival in postoperative HCC.