Optimal timing of portal vein embolization (PVE) after preoperative biliary drainage for hilar cholangiocarcinoma.

BACKGROUND: Preoperative biliary drainage (PBD) followed by portal vein embolization (PVE) has increased the chance of resection for hilar cholangiocarcinoma (CCC). We aim to identify the optimal timing of PVE after PBD in patients undergoing hepatectomy for hilar CCC. METHODS: We retrospectively reviewed 64 patients who underwent hepatectomy after PBD and PVE for hilar CCC. The patients were classified into 3 groups: Group 1 (PBD-PVE interval ≤7 days), Group2 (8-14 days) and Group 3 (>14 days). The primary end points were 90 days mortality and grade B/C posthepatectomy liver failure (PHLF). RESULTS: There was no significant difference in primary end points between three groups. A marginally significant difference was found in the incidence of Clavien-Dindo grade ≥3 complications and wound infection (57.1% vs 38.1% vs 72.4%, p = 0.053 and 21.4% vs 38.1% vs 55.2%, p = 0.099). In multivariable analysis, Bismuth type IIIb or IV was independent risk factors for grade B/C PHLF (HR: 4.782, 95% CI 1.365-16.759, p = 0.014). CONCLUSIONS: Considering that the PBD-PVE interval did not affect PHLF, and the surgical complications increased as the interval increases, PVE as early as possible after PBD would be beneficial.

PPARγ Ligand-induced Annexin A1 Expression Determines Chemotherapy Response via Deubiquitination of Death Domain Kinase RIP in Triple-negative Breast Cancers.

Metastatic breast cancer is still incurable so far; new specifically targeted and more effective therapies for triple-negative breast cancer (TNBC) are required in the clinic. In this study, our clinical data have established that basal and claudin-low subtypes of breast cancer (TNBC types) express significantly higher levels of Annexin A1 (ANXA1) with poor survival outcomes. Using human cancer cell lines that model the TNBC subtype, we observed a strong positive correlation between expression of ANXA1 and PPARγ. A similar correlation between these two markers was also established in our clinical breast cancer patients' specimens. To establish a link between these two markers in TNBC, we show de novo expression of ANXA1 is induced by activation of PPARγ both in vitro and in vivo and it has a predictive value in determining chemosensitivity to PPARγ ligands. Mechanistically, we show for the first time PPARγ-induced ANXA1 protein directly interacts with receptor interacting protein-1 (RIP1), promoting its deubiquitination and thereby activating the caspase-8-dependent death pathway. We further identified this underlying mechanism also involved a PPARγ-induced ANXA1-dependent autoubiquitination of cIAP1, the direct E3 ligase of RIP1, shifting cIAP1 toward proteosomal degradation. Collectively, our study provides first insight for the suitability of using drug-induced expression of ANXA1 as a new player in RIP1-induced death machinery in TNBCs, presenting itself both as an inclusion criterion for patient selection and surrogate marker for drug response in future PPARγ chemotherapy trials. Mol Cancer Ther; 16(11); 2528-42. ©2017 AACR.

A new algorithm for detecting low-complexity regions in protein sequences.

MOTIVATION: Pair-wise alignment of protein sequences and local similarity searches produce many false positives because of compositionally biased regions, also called low-complexity regions (LCRs), of amino acid residues. Masking and filtering such regions significantly improves the reliability of homology searches and, consequently, functional predictions. Most of the available algorithms are based on a statistical approach. We wished to investigate the structural properties of LCRs in biological sequences and develop an algorithm for filtering them. RESULTS: We present an algorithm for detecting and masking LCRs in protein sequences to improve the quality of database searches. We developed the algorithm based on the complexity analysis of subsequences delimited by a pair of identical, repeating subsequences. Given a protein sequence, the algorithm first computes the suffix tree of the sequence. It then collects repeating subsequences from the tree. Finally, the algorithm iteratively tests whether each subsequence delimited by a pair of repeating subsequences meets a given criteria. Test results with 1000 proteins from 20 families in Pfam show that the repeating subsequences are a good indicator for the low-complexity regions, and the algorithm based on such structural information strongly compete with others. AVAILABILITY: http://bioinfo.knu.ac.kr/research/CARD/ CONTACT: swshin@bioinfo.knu.ac.kr