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Tatsuhiro Shibata, David Wheeler, Hiroyuki Aburatani and colleagues report the genomic, exomic and oncoviral sequencing of hundreds of liver cancers from the United States and Japan. The authors analyzed mutation patterns and identified signatures unique to the Asian cases. Diverse epidemiological factors are associated with hepatocellular carcinoma (HCC) prevalence in different populations. However, the global landscape of the genetic changes in HCC genomes underpinning different epidemiological and ancestral backgrounds still remains uncharted. Here a collection of data from 503 liver cancer genomes from different populations uncovered 30 candidate driver genes and 11 core pathway modules. Furthermore, a collaboration of two large-scale cancer genome projects comparatively analyzed the trans-ancestry substitution signatures in 608 liver cancer cases and identified unique mutational signatures that predominantly contribute to Asian cases. This work elucidates previously unexplored ancestry-associated mutational processes in HCC development. A combination of hotspot TERT promoter mutation, TERT focal amplification and viral genome integration occurs in more than 68% of cases, implicating TERT as a central and ancestry-independent node of hepatocarcinogenesis. Newly identified alterations in genes encoding metabolic enzymes, chromatin remodelers and a high proportion of mTOR pathway activations offer potential therapeutic and diagnostic opportunities.

ObjectivesWe aimed to assess the diagnostic performance of MR elastography (MRE) in predicting esophageal varices (EVs) in patients with chronic liver disease.MethodsWe prospectively performed liver (LSM) and spleen stiffness measurements (SSM) using MRE and endoscopic screening for EVs to determine if patients with hepatocellular carcinoma were eligible for resection. We investigated whether LSM, SSM, and other non-invasive preoperative parameters were associated with the presence of EVs. In order to predict EVs, 211 patients were divided into training (n = 140) and test (n = 71) groups. A nomogram was built using independent factors based on logistic regression analysis in the training group and its accuracy was validated using an independent cohort.ResultsForty-six patients (21.8%) were diagnosed as having EVs (mild, n = 36; severe, n = 10). According to multiple regression analysis, LSM (odds ratio, 2.362; 95% confidence interval [CI], 1.341–4.923; p = 0.001) and SSM (1.489; 1.095–2.235; p = 0.010) were independent predictors of EVs in the training group. The nomogram showed good discrimination, with a C-index of 0.942 (95% CI, 0.892–0.974) through internal validation, and good calibration. Application of the nomogram in the test group still gave good discrimination (C-index, 0.948; 95% CI, 0.868–0.995).ConclusionsThe combination of LSM and SSM using MRE is an accurate tool to identify patients at risk for EVs.Key Points•Performance of MR elastography can estimate the presence of esophageal varices non-invasively.•Liver and spleen stiffness measurements are independent predictors for esophageal varices.•The nomogram using a combination of liver and spleen stiffness measurements allows for the risk of esophageal varices.

Background Although clinical applications of intraoperative fluorescence imaging of liver cancer using indocyanine green (ICG) have begun, the mechanistic background of ICG accumulation in the cancerous tissues remains unclear. Methods In 170 patients with hepatocellular carcinoma cells (HCC), the liver surfaces and resected specimens were intraoperatively examined by using a near-infrared fluorescence imaging system after preoperative administration of ICG (0.5 mg/kg i.v.). Microscopic examinations, gene expression profile analysis, and immunohistochemical staining were performed for HCCs, which showed ICG fluorescence in the cancerous tissues (cancerous-type fluorescence), and HCCs showed fluorescence only in the surrounding non-cancerous liver parenchyma (rim-type fluorescence). Results ICG fluorescence imaging enabled identification of 273 of 276 (99 %) HCCs in the resected specimens. HCCs showed that cancerous-type fluorescence was associated with higher cancer cell differentiation as compared with rim-type HCCs ( P  < 0.001). Fluorescence microscopy identified the presence of ICG in the canalicular side of the cancer cell cytoplasm, and pseudoglands of the HCCs showed a cancerous-type fluorescence pattern. The ratio of the gene and protein expression levels in the cancerous to non-cancerous tissues for Na + /taurocholate cotransporting polypeptide (NTCP) and organic anion-transporting polypeptide 8 (OATP8), which are associated with portal uptake of ICG by hepatocytes that tended to be higher in the HCCs that showed cancerous-type fluorescence than in those that showed rim-type fluorescence. Conclusions Preserved portal uptake of ICG in differentiated HCC cells by NTCP and OATP8 with concomitant biliary excretion disorders causes accumulation of ICG in the cancerous tissues after preoperative intravenous administration. This enables highly sensitive identification of HCC by intraoperative ICG fluorescence imaging.

The choroid is a complex vascular tissue that is covered with the retinal pigment epithelium. Ultra high speed swept source optical coherence tomography (SS-OCT) provides us with high-resolution cube scan images of the choroid. Robust segmentation techniques are required to reconstruct choroidal volume using SS-OCT images. For automated segmentation, the delineation of the choroidal-scleral (C-S) boundary is key to accurate segmentation. Low contrast of the boundary, scleral canals formed by the vessel and the nerve, and the posterior stromal layer, may cause segmentation errors. Semantic segmentation is one of the applications of deep learning used to classify the parts of images related to the meanings of the subjects. We applied semantic segmentation to choroidal segmentation and measured the volume of the choroid. The measurement results were validated through comparison with those of other segmentation methods. As a result, semantic segmentation was able to segment the C-S boundary and choroidal volume adequately.

Background We aimed to validate our algorithm for resecting Hepatocellular carcinoma (HCC) in the caudate lobe based on tumor location, tumor size, and indocyanine green clearance rate. Methods Patients who underwent curative resections for solitary HCC in the caudate lobe were included. The surgical outcomes of patients with HCC in the caudate lobe were compared with those of patients with HCC in other sites of the liver. Results After one-to-one matching, the caudate-lobe group ( n  = 150) had longer operation time, greater amount of bleeding, lower weight of resected specimens, and shorter distance between tumor and resection line than the other-sites group ( n  = 150), but the complication rates were not different between the groups (38.0% vs. 34.1%, P  = 0.719). After a median follow-up period of 3.0 years (range, 0.3−16.2 years), the median overall survivals were 6.5 (95% confidence interval [CI], 5.3–7.9) and 7.5 years (95% CI, 6.3–9.7) in the caudate-lobe and other-site groups, respectively ( P  = 0.430). Median recurrence-free survivals in the caudate-lobe group (1.9 years; 95% CI, 1.4–2.7) had a tendency to be shorter than those in the other-sites group (2.3 years; 1.7–3.4) ( P  = 0.052). Conclusions Patients’ survival and complication rates in the caudate-lobe group were comparable to those in the other-sites group; therefore, our algorithm for resecting HCC in the caudate lobe is of clinical use.

We created three types of vessel models: vessel volume, surface, and line models from swept-source optical coherence tomography images and tested experimentally calculated three-dimensional (3D) biomarkers. The choroidal volume (CVolume), surface area (VSurface), and vessel length-associated index (VLI) were measured. The calculated 3D parameters were the mean choroidal thickness, choroidal vascularity index (CVI), vessel length density index (VLDI), vessel length to the stromal (VL–S) ratio, surface-to-volume ratio (S–V ratio), and vessel diameter index (VDI). Cluster analysis showed that the parameters were classified into two clusters: one was represented by the VVolume including the CVolume, VSurface, CVI, S–V ratio, VLI, VDI, and subfoveal choroidal thickness and the other by the VL–S ratio including the VLDI. Regarding the regional distribution, the VVolume, CVolume, VSurface, CVI, VLI, VL–S ratio, and VDI at the foveal center were higher than at the parafovea (P < 0.01). Although the VVolume decreased with age and axial length (AL) elongation, the association of the 3D parameters with age and AL elongation differed. The VLI, VLDI, VL–S ratio, and CVI decreased with age (P < 0.01) but not with AL elongation. The results suggested a structural difference in the choroidal vessel volume reduction between aging and AL elongation. The 3D parameters may provide additional information about the choroidal vasculature.

Background Identifying novel therapeutic targets is crucial for the successful development of drugs. However, the cost to experimentally identify therapeutic targets is huge and only approximately 400 genes are targets for FDA-approved drugs. As a result, it is inevitable to develop powerful computational tools that can identify potential novel therapeutic targets. Fortunately, the human protein-protein interaction network (PIN) could be a useful resource to achieve this objective. Methods In this study, we developed a deep learning-based computational framework that extracts low-dimensional representations of high-dimensional PIN data. Our computational framework uses latent features and state-of-the-art machine learning techniques to infer potential drug target genes. Results We applied our computational framework to prioritize novel putative target genes for Alzheimer’s disease and successfully identified key genes that may serve as novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we could infer repositionable candidate-compounds for the disease (e.g., tamoxifen, bosutinib, and dasatinib). Conclusions Our deep learning-based computational framework could be a powerful tool to efficiently prioritize new therapeutic targets and enhance the drug repositioning strategy.

Small cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. Expression array analysis of 23 SCLC cases and 42 normal tissues revealed that EZH2 and other PRC2 members were highly expressed in SCLC. ChIP-seq for H3K27me3 suggested that genes with H3K27me3(+) in SCLC were extended not only to PRC2-target genes in ES cells but also to other target genes such as cellular adhesion-related genes. These H3K27me3(+) genes in SCLC were repressed significantly and introduction of the most repressed gene JUB into SCLC cell line lead to growth inhibition. Shorter overall survival of clinical SCLC cases correlated to repression of JUB alone, or a set of four genes including H3K27me3(+) genes. Treatment with EZH2 inhibitors, DZNep and GSK126, resulted in growth repression of SCLC cell lines. High PRC2 expression was suggested to contribute to gene repression in SCLC and may play a role in genesis of SCLC.

The ubiquitin proteasome pathway is essential for the proliferation and survival of multiple myeloma (MM) cells. TAS4464, a novel highly potent inhibitor of NEDD8 activating enzyme, selectively inactivates cullin‐RING ubiquitin E3 ligases, resulting in accumulation of their substrates. Here, we examined 14 MM cell lines treated with TAS4464. TAS4464 induced growth arrest and cell death in the MM cell lines even in the presence of bone marrow stromal cells. It also induced the accumulation of phospho‐inhibitor of κBα and phospho‐p100, impaired the activities of nuclear factor κB (NF‐κB) transcription factors p65 and RelB, and decreased the expression of NF‐κB target genes, suggesting that TAS4464 inhibits both the canonical and non–canonical NF‐κB pathways. TAS4464 had similar effects in an in vivo human‐MM xenograft mouse model in which it was also observed to have strong antitumor effects. TAS4464 synergistically enhanced the antitumor activities of the standard MM chemotherapies bortezomib, lenalidomide/dexamethasone, daratumumab and elotuzumab. Together, these results suggest that the anti–MM activity of TAS4464 occurs via inhibition of the NF‐κB pathways, and that treatment with TAS4464 is a potential approach for treating MM by single and combination therapies. In this study, we showed antitumor activity and molecular insight into the mechanism of action of TAS4464, an NEDD8‐activating enzyme inhibitor, in multiple myeloma (MM) cells. TAS4464 led to strong antitumor activity through inactivation of NF‐κB signaling activated in MM cells. This study suggests that treatment with TAS4464 is a potential approach for treating MM.

Anti‐epidermal growth factor receptor (EGFR) treatment is an effective option for metastatic colorectal cancer (CRC) treatment. However, there are few reliable biomarkers to predict the clinical response to anti‐EGFR treatment. We investigated the genome‐wide DNA methylation status in metastatic colorectal cancer to identify associations between the methylation status and clinical response to anti‐EGFR antibody. We retrospectively reviewed the medical records of 97 patients (45 patients for the first cohort and 52 patients for the second cohort) who received anti‐EGFR treatment for KRAS wild‐type metastatic CRC. Then we analyzed the associations between genome‐wide DNA methylation status and clinical response to anti‐EGFR treatment, and evaluated the predictive power and value of the methylation status statistically. As a result, each cohort was classified into highly methylated CRC and low methylated CRC subgroups by unsupervised clustering analyses. In the first cohort, clinical outcomes were significantly better in the low methylated CRC subgroup than in the highly methylated CRC subgroup (response rate, 35.7% vs 6.3%, P = 0.03; disease control rate, 75% vs 31.3%, P = 0.005; hazard ratio for progression‐free survival, 0.27; 95% confidence interval, 0.13–0.57, P < 0.001; overall survival, 0.19; 95% confidence interval, 0.06–0.54, P < 0.001). These results were reproducible in the second cohort. The genome‐wide methylation status was a predictive factor of progression‐free survival and overall survival independently of RAS mutation status. In conclusion, we found that the genome‐wide DNA methylation status is a powerful epigenetic predictor of anti‐EGFR treatment in patients with KRAS wild‐type metastatic colorectal cancer (UMIN000005490). We investigated the genome‐wide DNA methylation status in metastatic colorectal cancer to identify associations between the methylation status and clinical response to anti‐EGFR antibody. We found that the genome‐wide DNA methylation status is a powerful epigenetic predictor of the anti‐EGFR treatment in patients with KRAS wild‐type metastatic colorectal cancer.