Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters—fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3′ untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein–DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores—mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer. Significance: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes. Cancer Discov; 7(10); 1116–35. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 1047

Intrahepatic cholangiocarcinoma is the second most common primary hepatic tumor. Various risk factors have been reported for intrahepatic cholangiocarcinoma, and the radiologic and pathologic findings of this disease entity may differ depending on the underlying risk factors. Intrahepatic cholangiocarcinoma can be classified into three types on the basis of gross morphologic features: mass-forming (the most common), periductal infiltrating, and intraductal growth. At computed tomography (CT), mass-forming intrahepatic cholangiocarcinoma usually appears as a homogeneous low-attenuation mass with irregular peripheral enhancement and can be accompanied by capsular retraction, satellite nodules, and peripheral intrahepatic duct dilatation. Periductal infiltrating cholangiocarcinoma is characterized by growth along the dilated or narrowed bile duct without mass formation. At CT and magnetic resonance imaging, diffuse periductal thickening and increased enhancement can be seen with a dilated or irregularly narrowed intrahepatic duct. Intraductal cholangiocarcinoma may manifest with various imaging patterns, including diffuse and marked ductectasia either with or without a grossly visible papillary mass, an intraductal polypoid mass within localized ductal dilatation, intraductal castlike lesions within a mildly dilated duct, and a focal stricture-like lesion with mild proximal ductal dilatation. Awareness of the underlying risk factors and morphologic characteristics of intrahepatic cholangiocarcinoma is important for accurate diagnosis and for differentiation from other hepatic tumorous and nontumorous lesions.

Hepatocellular nodules in cirrhosis include regenerative (large regenerative, LRN) and dysplastic (low and high grade, LGDN and HGDN) nodules, early and grade 1 HCC (eHCC-G1), and overt HCC. The differential diagnosis may be particularly difficult when lesions such as HGDN and eHCC-G1 are involved. We investigated the diagnostic yield of a panel of 3 putative markers of hepatocellular malignancy such as HSP70, glypican 3 (GPC3), and glutamine synthetase (GS). We selected 52 surgically removed nonmalignant nodules (15 LRNs, 15 LGDNs, 22 HGDNs) and 53 HCCs (10 early, 22 grade 1, and 21 grade 2-3) and immunostained them for HSP70, GPC3, and GS. The sensitivity and specificity of the individual markers for the detection of eHCC-G1 were 59% and 86% for GS, 69% and 91% for GPC3, and 78% and 95% for HSP70. We identified 2 main phenotypes: (1) all negative, seen in 100% LRN and LGDN, 73% HGDN and 3% eHCC-G1; (2) all positive, a feature detected in less than half the eHCC-G1. Using a 3-marker panel, when at least 2 of them, regardless which, were positive, the sensitivity and specificity for the detection of eHCC-G1 were respectively 72% and 100%; the most sensitive combination was HSP70+/GPC3+ (59%) when a 2-marker panel was used. Conclusion: The adopted panel of 3 markers is very helpful in distinguishing eHCC-G1 from dysplastic nodules arising in cirrhosis. (Hepatology 2007;45:725–734.)

Liver stiffness measurement (LSM) using FibroScan accurately assesses the degree of liver fibrosis and the risk of hepatocellular carcinoma (HCC) development in patients with chronic hepatitis C. This study investigated the usefulness of LSM as a predictor of HCC development in patients with chronic hepatitis B (CHB). A total of 1,130 patients with non-biopsy–proven CHB who underwent LSM between May 2005 and December 2007 were enrolled in this prospective study. After LSM was performed, patients attended regular follow-up as part of a surveillance program for the detection of HCC. The mean age of the patients (767 men, 363 women) was 50.2 years, and the median LSM was 7.7 kPa. Six hundred seventy-two (59.5%) patients received antiviral treatment before or after enrollment. During the follow-up period (median, 30.7 months; range, 24.0-50.9 months), HCC developed in 57 patients (2.0% per 1 person-year). The 1-, 2-, and 3-year cumulative incidence rates of HCC were 0.80%, 3.26%, and 5.98%, respectively. On multivariate analysis, together with old age, male sex, heavy alcohol consumption (>80 g/day), serum albumin, and hepatitis B e antigen positivity, patients with a higher LSM (>8 kPa) were at a significantly greater risk of HCC development, with the following hazard ratios: 3.07 (95% confidence interval [CI], 1.01-9.31; P = 0.047) for LSM 8.1-13 kPa; 4.68 (95% CI, 1.40-15.64; P = 0.012) for LSM 13.1-18 kPa; 5.55 (95% CI, 1.53–20.04; P = 0.009) for LSM 18.1-23 kPa; and 6.60 (95% CI, 1.83-23.84; P = 0.004) for LSM >23 kPa. Conclusion: Our data suggest that LSM could be a useful predictor of HCC development in patients with CHB. (Hepatology 2011)

Purpose: Despite continual efforts to develop a prognostic model of gastric cancer by using clinical and pathologic parameters, a clinical test that can discriminate patients with good outcomes from those with poor outcomes after gastric cancer surgery has not been established. We aim to develop practical biomarker-based risk score that can predict relapse of gastric cancer after surgical treatment. Experimental Design: Microarray technologies were used to generate and analyze gene expression profiling data from 65 gastric cancer patients to identify biomarker genes associated with relapse. The association of expression patterns of identified genes with relapse and overall survival was validated in independent gastric cancer patients. Results: We uncovered two subgroups of gastric cancer that were strongly associated with the prognosis. For the easy translation of our findings into practice, we developed a scoring system based on the expression of six genes that predicted the likelihood of relapse after curative resection. In multivariate analysis, the risk score was an independent predictor of relapse in a cohort of 96 patients. We were able to validate the robustness of the six-gene signature in an additional independent cohort. Conclusions: The risk score derived from the six-gene set successfully prognosticated the relapse of gastric cancer patients after gastrectomy. Clin Cancer Res; 17(7); 1850–7. ©2011 AACR.