OBJECTIVE:β-Catenin-mutated hepatocellular adenomas (HCAs) carry an increased malignant transformation risk and are screened by interpreting glutamine synthetase (GS) and β-catenin by immunohistochemistry (IHC). Our study aims to assess GS and β-catenin interpretation guidelines for applicability and reproducibility in predicting high-risk HCA and other relevant molecular alterations. METHODS:Hematoxylin and eosin (H&E), β-catenin, GS, and CD34 stains from 75 HCAs were interpreted by three pathologists using Method A (GS interpretation: negative, perivenular patchy, map-like, diffuse, and indeterminate) and Method B criteria (similar GS interpretation scheme based on a recent publication, with and without CD34 expression patterns). Ease of application and interpretation confidence level were assessed. High-risk IHC was defined as nuclear β-catenin and/or diffuse homogeneous GS. Molecular testing was performed on a subset of HCAs and controls. RESULTS:There were 57 resections and 18 biopsy specimens examined. Methods A and B (GS only) were rated as easy to apply, with high interpretation confidence (≥90% using both methods). Consensus rate was comparable in biopsy specimens (100% for both methods) and resections (88% for Method A, 93% for Method B). While the same cases were stratified into high-risk GS categories using both systems, clinically significant genetic alterations (TERT promoter, EGFR, MTOR, and TP53) were identified in 25% of cases stratified as not high risk by IHC. CONCLUSIONS:Both methods have a similar ease of application and level of interpretation confidence, and they also detected β-catenin mutations as expected. Other relevant molecular alterations associated with risk of neoplastic progression and/or bleeding were detected in 25% of HCAs with the non-high-risk IHC phenotype, suggesting the value of molecular testing in this subset.

Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence following liver resection or transplantation is one of the highest contributors to mortality in HCC patients after surgery. Using artificial intelligence (AI), we developed an interdisciplinary model to predict HCC recurrence and patient survival following surgery. We collected whole-slide H&E images, clinical variables, and follow-up data from 300 patients with HCC who underwent transplant and 169 patients who underwent resection at the Cleveland Clinic. A deep learning model was trained to predict recurrence-free survival (RFS) and disease-specific survival (DSS) from the H&E-stained slides. Repeated cross-validation splits were used to compute robust C-index estimates, and the results were compared to those obtained by fitting a Cox proportional hazard model using only clinical variables. While the deep learning model alone was predictive of recurrence and survival among patients in both cohorts, integrating the clinical and histologic models significantly increased the C-index in each cohort. In every subgroup analyzed, we found that a combined clinical and deep learning model better predicted post-surgical outcome in HCC patients compared to either approach independently.

ABSTRACT Recently, the use of immunotherapy has increased substantially for the treatment of several malignancies. It is associated with several gastrointestinal adverse events; however, severe complications such as intestinal perforation are rare. We present a 75-year-old man with metastatic melanoma, presented with profuse diarrhea and abdominal pain, after ipilimumab and nivolumab administration. Shortly after, he developed fulminant colitis and intestinal perforation and was found to have concurrent Rosai-Dorfman disease of pericolonic lymph nodes. With the increasing use of immunotherapy, reporting of serious adverse events and their mimics is essential. In addition, further studies are required to investigate whether an association exists between Rosai-Dorfman disease and immunotherapy.

Colorectal cancer harbors tremendous heterogeneity, with temporal and spatial differences in genetic mutations, epigenetic regulation, and tumor microenvironment. Analyzing the distribution and frequency of genetic, epigenetic, and microenvironment differences within a given tumor and between different sites of a metastatic tumor has been used as a powerful tool to investigate tumorigenesis, tumor progression, and to yield insight into various models of tumor development. A better understanding of tumor heterogeneity would have tremendous clinical relevance, which may manifest most clearly when genetic analyses to inform treatment decisions are performed on a very limited sample of a large tumor. This review summarizes the current concepts of tumor heterogeneity, with a focus on primary colorectal cancers and their corresponding metastases as well as potential clinical implications.

Eligibility for liver transplant is most commonly decided by measuring tumor size and number on radiographic imaging. However, this method often underestimates the extent of disease. Evaluation of tumor histology has been shown to improve risk stratification when compared with imaging-based transplant criteria, but the World Health Organization (WHO) guidelines for grading hepatocellular carcinoma (HCC) are imprecise and require subjective interpretation by the pathologist. We performed a retrospective analysis of 190 explanted livers containing HCC and correlated histologic features with posttransplant recurrence to formulate a three-tiered, point-based scoring system that categorizes tumors as having a low, intermediate, or high risk of recurrence. Our Recurrence Risk Assessment Score (RRAS) evaluates tumor architecture and specific cytologic features—nuclear pleomorphism, cytoplasmic amphophilia, and nuclear-to-cytoplasmic ratio—showing superior stratification of HCC recurrence risk compared with imaging criteria and grade assigned by WHO methodology. Stratifying tumors using RRAS criteria, the rate of recurrence after transplant was 0% among low-risk tumors (compared with 3% of well-differentiated tumors), 12% among intermediate-risk tumors (compared with 15% of moderately differentiated tumors), and 54% among high-risk tumors (compared with 29% of poorly differentiated tumors). Receiver operating characteristic analysis shows significantly improved performance of RRAS criteria in predicting HCC recurrence compared with WHO grade (area under curve of 0.841 and 0.671, respectively; P=0.0061). Our results indicate that evaluation of tumor histology offers superior prediction of recurrence risk following liver transplantation compared with radiographic criteria, and that the RRAS system better stratifies recurrence risk compared with HCC grading by WHO methodology.