SUMMARY Liver cancer has the second highest worldwide cancer mortality rate and has limited therapeutic options. We analyzed 363 hepatocellular carcinoma (HCC) cases by whole exome sequencing and DNA copy number analyses, and 196 HCC also by DNA methylation, RNA, miRNA, and proteomic expression. DNA sequencing and mutation analysis identified significantly mutated genes including LZTR1, EEF1A1, SF3B1, and SMARCA4. Significant alterations by mutation or down-regulation by hypermethylation in genes likely to result in HCC metabolic reprogramming (ALB, APOB, and CPS1) were observed. Integrative molecular HCC subtyping incorporating unsupervised clustering of five data platforms identified three subtypes, one of which was associated with poorer prognosis in three HCC cohorts. Integrated analyses enabled development of a p53 target gene expression signature correlating with poor survival. Potential therapeutic targets for which inhibitors exist include WNT signaling, MDM4, MET, VEGFA, MCL1, IDH1, TERT, and immune checkpoint proteins CTLA-4, PD-1, and PD-L1.

Purpose The Cancer Genome Atlas (TCGA) project recently uncovered four molecular subtypes of gastric cancer: Epstein-Barr virus (EBV), microsatellite instability (MSI), genomically stable (GS), and chromosomal instability (CIN). However, their clinical significances are currently unknown. We aimed to investigate the relationship between subtypes and prognosis of patients with gastric cancer. Experimental Design Gene expression data from a TCGA cohort (n = 262) were used to develop a subtype prediction model, and the association of each subtype with survival and benefit from adjuvant chemotherapy was tested in 2 other cohorts (n = 267 and 432). An integrated risk assessment model (TCGA risk score) was also developed. Results EBV subtype was associated with the best prognosis and GS subtype was associated with the worst prognosis. Patients with MSI and CIN subtypes had poorer overall survival than those with EBV subtype but better overall survival than those with GS subtype (P = 0.004 and 0.03 in two cohorts respectively). In multivariate Cox regression analyses, TCGA risk score was an independent prognostic factor (hazard ratio [HR] = 1.5; 95% confidence interval [CI] = 1.2–1.9; P = 0.001). Patients with the CIN subtype experienced the greatest benefit from adjuvant chemotherapy (HR = 0.39; 95% CI = 0.16–0.94; P = 0.03) and those with the GS subtype had the least benefit from adjuvant chemotherapy (HR = 0.83; 95% CI = 0.36–1.89; P = 0.65). Conclusion Our prediction model successfully stratified patients by survival and adjuvant chemotherapy outcomes. Further development of the prediction model is warranted.

CSP is superior to CFP for the endoscopic removal of DCPs with regard to completeness of polypectomy. CSP technique should be considered the primary method for endoscopic treatment of polyps in the 4-5-mm size range (ClinicalTrials.gov number: NCT01646242).

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Metabolic activation is a common feature of many cancer cells and is frequently associated with the clinical outcomes of various cancers, including hepatocellular carcinoma (HCC). Thus, aberrantly activated metabolic pathways in cancer cells are attractive targets for cancer therapy. YAP1 and TAZ are oncogenic downstream effectors of the Hippo tumor suppressor pathway, which is frequently inactivated in many cancers. Our study revealed that YAP1/TAZ regulates amino acid metabolism by up-regulating expression of the amino acid transporters SLC38A1 and SLC7A5. Subsequently, increased uptake of amino acids by the transporters activates mTORC1, a master regulator of cell growth, and stimulates cell proliferation. We also show that high expression of SLC38A1 and SLC7A5 is significantly associated with shorter survival in HCC patients. Furthermore, inhibition of the transporters and mTORC1 significantly block YAP1/TAZ-mediated tumorigenesis in the liver. These findings elucidate regulatory networks connecting the Hippo pathway to mTORC1 through amino acid metabolism and the mechanism’s potential clinical implications for treating HCC. Conclusion YAP1 and TAZ regulate cancer metabolism and mTOCR1 through regulation of amino acid transportation and two amino acid transporters, SLC38A1 and SLC7A5, might be important therapeutic targets.

Purpose The Hippo pathway is a tumor suppressor in the liver. However, the clinical significance of Hippo pathway inactivation in HCC is not clearly defined. We analyzed genomic data from human and mouse tissues to determine clinical relevance of Hippo pathway inactivation in HCC. Experimental Design We analyzed gene expression data from Mst1/2−/− and Sav1−/− mice and identified a 610-gene expression signature reflecting Hippo pathway inactivation in the liver (silence of Hippo [SOH] signature). By integrating gene expression data from mouse models with those from human HCC tissues, we developed a prediction model that could identify HCC patients with an inactivated Hippo pathway and used it to test its significance in HCC patients, via univariate and multivariate Cox analyses. Results HCC patients (National Cancer Institute cohort, n = 113) with the SOH signature had a significantly poorer prognosis than those without the SOH signature (P < 0.001 for overall survival [OS]). The significant association of the signature with poor prognosis was further validated in the Korean (n=100, P = 0.006 for OS) and Fudan University cohorts (n=242, P = 0.001 for OS). On multivariate analysis, the signature was an independent predictor of recurrence-free survival (hazard ratio, 1.6; 95% confidence interval, 1.12–2.28: P = 0.008). We also demonstrated significant concordance between the SOH HCC subtype and the hepatic stem cell HCC subtype that had been identified in a previous study (P < 0.001). Conclusions Inactivation of the Hippo pathway in HCC is significantly associated with poor prognosis.

Immunotherapy has emerged as a promising anti-cancer treatment, however, little is known about the genetic characteristics that dictate response to immunotherapy. We develop a transcriptional predictor of immunotherapy response and assess its prediction in genomic data from ~10,000 human tissues across 30 different cancer types to estimate the potential response to immunotherapy. The integrative analysis reveals two distinct tumor types: the mutator type is positively associated with potential response to immunotherapy, whereas the chromosome-instable type is negatively associated with it. We identify somatic mutations and copy number alterations significantly associated with potential response to immunotherapy, in particular treatment with anti-CTLA-4 antibody. Our findings suggest that tumors may evolve through two different paths that would lead to marked differences in immunotherapy response as well as different strategies for evading immune surveillance. Our analysis provides resources to facilitate the discovery of predictive biomarkers for immunotherapy that could be tested in clinical trials.

Mean platelet volume (MPV) has been actively investigated in liver disease such as steatosis, cirrhosis and hepatitis. Recently, MPV/platelet count (PC) ratio has been proposed as a predictor of long-term mortality after myocardial infarction. As PC is known to be decreased in various liver diseases such as cirrhosis, hepatosplenomegaly and malignancy, we planned to evaluate MPV/PC ratio in patients with hepatocellular carcinoma (HCC) in this study. Mean of MPV levels showed significant difference, which were 8.69 fl (range 6.7-12.2 fl) in patients group and 8.02 fl in control group (range 6.7-11.0 fl). In receiver operating characteristic (ROC) curve analysis, the MPV/PC ratio (fl/(10(9)/l)) presented 74.5% of sensitivity and 96.5% of specificity at the criterion > 0.0491 (area under the curve (AUC) = 0.884), while MPV alone showed 57.4% of sensitivity and 81.4% of specificity at the criterion > 8.4 fl. Further studies should evaluate underlying pathogenic mechanisms of MPV/PC ratio difference and various possibilities of this ratio as an indicator of presence of a tumor in HCC.