A deep learning model for prediction of post hepatectomy liver failure after hemihepatectomy using preoperative contrast-enhanced computed tomography: a retrospective study

ObjectivePost-hepatectomy liver failure (PHLF) remains clinical challenges after major hepatectomy. The aim of this study was to establish and validate a deep learning model to predict PHLF after hemihepatectomy using preoperative contrast-enhancedcomputed tomography with three phases (Non-contrast, arterial phase and venous phase).Methods265 patients undergoing hemihepatectomy in Sir Run Run Shaw Hospital were enrolled in this study. The primary endpoint was PHLF, according to the International Study Group of Liver Surgery’s definition. In this study, to evaluate the proposed method, 5-fold cross-validation technique was used. The dataset was split into 5 folds of equal size, and each fold was used as a test set once, while the other folds were temporarily combined to form a training set. Performance metrics on the test set were then calculated and stored. At the end of the 5-fold cross-validation run, the accuracy, precision, sensitivity and specificity for predicting PHLF with the deep learning model and the area under receiver operating characteristic curve (AUC) were calculated.ResultsOf the 265 patients, 170 patients with left liver resection and 95 patients with right liver resection. The diagnosis had 6 types: hepatocellular carcinoma, intrahepatic cholangiocarcinoma, liver metastases, benign tumor, hepatolithiasis, and other liver diseases. Laparoscopic liver resection was performed in 187 patients. The accuracy of prediction was 84.15%. The AUC was 0.7927. In 170 left hemihepatectomy cases, the accuracy was 89.41% (152/170), and the AUC was 82.72%. The accuracy was 77.47% (141/182) with liver mass, 78.33% (47/60) with liver cirrhosis and 80.46% (70/87) with viral hepatitis.ConclusionThe deep learning model showed excellent performance in prediction of PHLF and could be useful for identifying high-risk patients to modify the treatment planning

Co-occurrence of BAP1 and SF3B1 mutations in uveal melanoma induces cellular senescence.

Uveal melanoma (UM) is the most common intraocular tumor in adults. Recurrent mutations in BRCA1-associated protein 1 (BAP1) and splicing factor 3B subunit 1 (SF3B1) display a mutually exclusive pattern in UM, but the underlying mechanism is unknown. We show that combined BAP1 deficiency and SF3B1 hotspot mutation lead to senescence and growth arrest in human UM cells. Although p53 protein expression is induced, deletion of TP53 (encoding p53) only modestly rescues the observed senescent phenotype. UM cells with BAP1 loss or SF3B1 mutation are more sensitive to chemotherapeutic drugs compared with their isogenic parental cells. Transcriptome analysis shows that DNA-repair genes are downregulated upon co-occurrence of BAP1 deletion and SF3B1 mutation, thus leading to impaired DNA damage response and the induction of senescence. The co-occurrence of these two mutations reduces invasion of UM cells in zebrafish xenograft models and suppresses growth of melanoma xenografts in nude mice. Our findings provide a mechanistic explanation for the mutual exclusivity of BAP1 and SF3B1 mutations in human UM

Systematic genome editing of the genes on zebrafish Chromosome 1 by CRISPR/Cas9

Genome editing by the well-established CRISPR/Cas9 technology has greatly facilitated our understanding of many biological processes. However, a complete whole-genome knockout for any species or model organism has rarely been achieved. Here, we performed a systematic knockout of all the genes (1333) on Chromosome 1 in zebrafish, successfully mutated 1029 genes, and generated 1039 germline-transmissible alleles corresponding to 636 genes. Meanwhile, by high-throughput bioinformatics analysis, we found that sequence features play pivotal roles in effective gRNA targeting at specific genes of interest, while the success rate of gene targeting positively correlates with GC content of the target sites. Moreover, we found that nearly one-fourth of all mutants are related to human diseases, and several representative CRISPR/Cas9-generated mutants are described here. Furthermore, we tried to identify the underlying mechanisms leading to distinct phenotypes between genetic mutants and antisense morpholino-mediated knockdown embryos. Altogether, this work has generated the first chromosome-wide collection of zebrafish genetic mutants by the CRISPR/Cas9 technology, which will serve as a valuable resource for the community, and our bioinformatics analysis also provides some useful guidance to design gene-specific gRNAs for successful gene editing