Background and Aim Genetic alterations in intrahepatic cholangiocarcinoma (iCCA) are increasingly well characterized, but their impact on outcome and prognosis remains unknown. Approach and Results This bi‐institutional study of patients with confirmed iCCA (n = 412) used targeted next‐generation sequencing of primary tumors to define associations among genetic alterations, clinicopathological variables, and outcome. The most common oncogenic alterations were isocitrate dehydrogenase 1 (IDH1; 20%), AT‐rich interactive domain–containing protein 1A (20%), tumor protein P53 (TP53; 17%), cyclin‐dependent kinase inhibitor 2A (CDKN2A; 15%), breast cancer 1–associated protein 1 (15%), FGFR2 (15%), polybromo 1 (12%), and KRAS (10%). IDH1/2 mutations (mut) were mutually exclusive with FGFR2 fusions, but neither was associated with outcome. For all patients, TP53 (P < 0.0001), KRAS (P = 0.0001), and CDKN2A (P < 0.0001) alterations predicted worse overall survival (OS). These high‐risk alterations were enriched in advanced disease but adversely impacted survival across all stages, even when controlling for known correlates of outcome (multifocal disease, lymph node involvement, bile duct type, periductal infiltration). In resected patients (n = 209), TP53mut (HR, 1.82; 95% CI, 1.08‐3.06; P = 0.03) and CDKN2A deletions (del; HR, 3.40; 95% CI, 1.95‐5.94; P < 0.001) independently predicted shorter OS, as did high‐risk clinical variables (multifocal liver disease [P < 0.001]; regional lymph node metastases [P < 0.001]), whereas KRASmut (HR, 1.69; 95% CI, 0.97‐2.93; P = 0.06) trended toward statistical significance. The presence of both or neither high‐risk clinical or genetic factors represented outcome extremes (median OS, 18.3 vs. 74.2 months; P < 0.001), with high‐risk genetic alterations alone (median OS, 38.6 months; 95% CI, 28.8‐73.5) or high‐risk clinical variables alone (median OS, 37.0 months; 95% CI, 27.6‐not available) associated with intermediate outcome. TP53mut, KRASmut, and CDKN2Adel similarly predicted worse outcome in patients with unresectable iCCA. CDKN2Adel tumors with high‐risk clinical features were notable for limited survival and no benefit of resection over chemotherapy. Conclusions TP53, KRAS, and CDKN2A alterations were independent prognostic factors in iCCA when controlling for clinical and pathologic variables, disease stage, and treatment. Because genetic profiling can be integrated into pretreatment therapeutic decision‐making, combining clinical variables with targeted tumor sequencing may identify patient subgroups with poor outcome irrespective of treatment strategy.

Combination HAI and SYS is an effective therapy for high-volume unresectable CRLM, resulting in a high rate of resection, long-term survival, and the potential for cure.

Intrahepatic cholangiocarcinomas are histologically heterogenous. Using a cohort of 184 clinically defined, resected intrahepatic cholangiocarcinomas, we retrospectively classified the histology into 4 subtypes: large duct (LD), small duct (SD) (predominantly tubular [SD1] or predominantly anastomosing/cholangiolar, [SD2]), or indeterminate. Then, we tested the 4 subtypes for associations with risk factors, patient outcomes, histology, and immunophenotypic characteristics. SD was the most common (84%; 24% SD1 and 60% SD2) with lower proportions of LD (8%), and indeterminate (8%). Primary sclerosing cholangitis was rare (2%), but correlated with LD (P=0.005). Chronic hepatitis, frequent alcohol use, smoking, and steatosis had no histologic association. LD was associated with mucin production (P<0.001), perineural invasion (P=0.002), CA19-9 staining (P<0.001), CK7, CK19, CD56 immunophenotype (P=0.005), and negative albumin RNA in situ hybridization (P<0.001). SD was histologically nodular (P=0.019), sclerotic (P<0.001), hepatoid (P=0.042), and infiltrative at the interface with hepatocytes (P<0.001). Albumin was positive in 71% of SD and 18% of LD (P=0.0021). Most albumin positive tumors (85%) lacked extracellular mucin (P<0.001). S100P expression did not associate with subtype (P>0.05). There was no difference in disease-specific or recurrence-free survival among the subtypes. Periductal infiltration and American Joint Committee on Cancer eighth edition pT stage predicted survival by multivariable analysis accounting for gross configuration, pT stage, and histologic type. pT2 had worse outcome relative to other pT stages. Significant differences in histology and albumin expression distinguish LD from SD, but there is insufficient evidence to support further subclassification of SD.

Background Microvascular invasion (MVI) is a significant risk factor for early recurrence after resection or transplantation for hepatocellular carcinoma (HCC). Knowledge of MVI status would help guide treatment recommendations but is generally identified after surgery. This study aims to predict MVI preoperatively using quantitative image analysis. Study Design From 2 institutions, 120 patients submitted to resection of HCC from 2003 to 2015 were included. The largest tumor from preoperative CT was subjected to quantitative image analysis, which uses an automated computer algorithm to capture regional variation in CT enhancement patterns. Quantitative imaging features by automatic analysis, qualitative radiographic descriptors by 2 radiologists, and preoperative clinical variables were included in multivariate analysis to predict histologic MVI. Results Histologic MVI was identified in 19 (37%) patients with tumors ≤5 cm and 34 (49%) patients with tumors > 5 cm. Among patients with ≤5 cm tumors, none of clinical findings or radiographic descriptors was associated with MVI; however, quantitative feature based on angle co-occurrence matrix predicted MVI with area under curve (AUC) 0.80, positive predictive value (PPV) 63% and negative predictive value (NPV) 85%. In patients with > 5 cm tumors, higher α-fetoprotein (AFP) level, larger tumor size, and viral hepatitis history were associated with MVI, whereas radiographic descriptors did not. However, a multivariate model combining AFP, tumor size, hepatitis status, and quantitative feature based on local binary pattern predicted MVI with AUC 0.88, PPV 72% and NPV 96%. Conclusions This study reveals the potential importance of quantitative image analysis as a predictor of MVI.

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