Chen, Dung‐Tsa

Abstract Lessons Learned The combination of trametinib and sorafenib has an acceptable safety profile, albeit at doses lower than approved for monotherapy. Maximum tolerated dose is trametinib 1.5 mg daily and sorafenib 200 mg twice daily. The limited anticancer activity observed in this unselected patient population does not support further exploration of trametinib plus sorafenib in patients with hepatocellular carcinoma. Background The RAS/RAF/MEK/ERK signaling pathway is associated with proliferation and progression of hepatocellular carcinoma (HCC). Preclinical data suggest that paradoxical activation of the MAPK pathway may be one of the resistance mechanisms of sorafenib; therefore, we evaluated trametinib plus sorafenib in HCC. Methods This was a phase I study with a 3+3 design in patients with treatment-naïve advanced HCC. The primary objective was safety and tolerability. The secondary objective was clinical efficacy. Results A total of 17 patients were treated with three different doses of trametinib and sorafenib. Two patients experienced dose-limiting toxicity, including grade 4 hypertension and grade 3 elevation of aspartate aminotransferase (AST)/alanine aminotransferase (ALT)/bilirubin over 7 days. Maximum tolerated dose was trametinib 1.5 mg daily and sorafenib 200 mg twice a day. The most common grade 3/4 treatment-related adverse events were elevated AST (37%) and hypertension (24%). Among 11 evaluable patients, 7 (63.6%) had stable disease with no objective response. The median progression-free survival (PFS) and overall survival (OS) were 3.7 and 7.8 months, respectively. Phosphorylated-ERK was evaluated as a pharmacodynamic marker, and sorafenib plus trametinib inhibited phosphorylated-ERK up to 98.1% (median: 81.2%) in peripheral blood mononuclear cells. Conclusion Trametinib and sorafenib can be safely administered up to trametinib 1.5 mg daily and sorafenib 200 mg twice a day with limited anticancer activity in advanced HCC.

Abstract Motivation Testing SNP–SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP–SNP interactions are underdeveloped. Results We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR, EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP–SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/. Supplementary information Supplementary data are available at Bioinformatics online.