Faculty Bibliography

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.

PURPOSE/OBJECTIVE:To evaluate the prevalence of major and ancillary imaging features from liver imaging reporting and data systems (LI-RADS) version 2014 and their interreader agreement when comparing hepatocellular carcinoma (HCC) to intrahepatic cholangiocarcinoma (ICC) and combined tumor (cHCC-CC). METHODS:The Institutional Review Board approved this HIPAA-compliant retrospective study and waived the requirement for patients' informed consent. Patients with resected HCC (n = 51), ICC (n = 40), and cHCC-CC (n = 11) and available pre-operative contrast-enhanced MRI were included from 2000 to 2015. Imaging features and final LI-RADS category were evaluated by four radiologists. Imaging features were compared by Fisher's exact test and interreader agreements were assessed by κ statistics. RESULTS:None of the features were unique to either HCC or non-HCC. Imaging features that were significantly more common among HCC compared to ICC and cHCC-CC included washout (76%-78% vs. 10%-35%, p < 0.001), capsule (55%-71% vs. 16%-49%, p < 0.05), and intralesional fat (27%-52% vs. 2%-12%, p < 0.002). Features that were more common among ICC and cHCC-CC included peripheral arterial phase hyperenhancement (40%-64% vs. 10%-14%, p < 0.001) and progressive central enhancement (65%-82% vs. 14%-25%, p < 0.001). The interreader agreement was moderate for each of these imaging features (κ = 0.41-0.55). Moderate agreement was also achieved in the assignment of LR-M (κ = 0.53), with an overall sensitivity and specificity for non-HCC malignancy of 86.3% and 78.4%, respectively. CONCLUSION/CONCLUSIONS:HCC and non-HCC show significant differences in the prevalence of imaging features defined by LI-RADS, and are identified by radiologists with moderate interreader agreement. Using LI-RADS, radiologists also achieved moderate interreader agreement in the assignment of the LR-M category.

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 operation. This study aims to predict MVI preoperatively using quantitative image analysis. STUDY DESIGN/METHODS:One hundred and twenty patients from 2 institutions underwent 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 tumors ≤5 cm, none of the clinical findings or radiographic descriptors were associated with MVI; however, quantitative features based on angle co-occurrence matrix predicted MVI with an area under curve of 0.80, positive predictive value of 63%, and negative predictive value of 85%. In patients with tumors >5 cm, higher α-fetoprotein level, larger tumor size, and viral hepatitis history were associated with MVI, and radiographic descriptors were not. However, a multivariate model combining α-fetoprotein, tumor size, hepatitis status, and quantitative feature based on local binary pattern predicted MVI with area under curve of 0.88, positive predictive value of 72%, and negative predictive value of 96%. CONCLUSIONS:This study reveals the potential importance of quantitative image analysis as a predictor of MVI.

Protein kinases represent the most effective class of therapeutic targets in cancer; therefore, determination of kinase aberrations is a major focus of cancer genomic studies. Here, we analyzed transcriptome sequencing data from a compendium of 482 cancer and benign samples from 25 different tissue types, and defined distinct "outlier kinases" in individual breast and pancreatic cancer samples, based on highest levels of absolute and differential expression. Frequent outlier kinases in breast cancer included therapeutic targets like ERBB2 and FGFR4, distinct from MET, AKT2, and PLK2 in pancreatic cancer. Outlier kinases imparted sample-specific dependencies in various cell lines, as tested by siRNA knockdown and/or pharmacologic inhibition. Outlier expression of polo-like kinases was observed in a subset of KRAS-dependent pancreatic cancer cell lines, and conferred increased sensitivity to the pan-PLK inhibitor BI-6727. Our results suggest that outlier kinases represent effective precision therapeutic targets that are readily identifiable through RNA sequencing of tumors.