Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model.

Comprehensive molecular characterization of cancer subtypes is essential for predicting clinical outcomes and searching for personalized treatments. We present bnClustOmics, a statistical model and computational tool for multi-omics unsupervised clustering, which serves a dual purpose: Clustering patient samples based on a Bayesian network mixture model and learning the networks of omics variables representing these clusters. The discovered networks encode interactions among all omics variables and provide a molecular characterization of each patient subgroup. We conducted simulation studies that demonstrated the advantages of our approach compared to other clustering methods in the case where the generative model is a mixture of Bayesian networks. We applied bnClustOmics to a hepatocellular carcinoma (HCC) dataset comprising genome (mutation and copy number), transcriptome, proteome, and phosphoproteome data. We identified three main HCC subtypes together with molecular characteristics, some of which are associated with survival even when adjusting for the clinical stage. Cluster-specific networks shed light on the links between genotypes and molecular phenotypes of samples within their respective clusters and suggest targets for personalized treatments.

Response prediction of hepatocellular carcinoma undergoing transcatheter arterial chemoembolization: unlocking the potential of CT texture analysis through nested decision tree models.

OBJECTIVES: To investigate if nested multiparametric decision tree models based on tumor size and CT texture parameters from pre-therapeutic imaging can accurately predict hepatocellular carcinoma (HCC) lesion response to transcatheter arterial chemoembolization (TACE). MATERIALS AND METHODS: This retrospective study (January 2011-September 2017) included consecutive pre- and post-therapeutic dynamic CT scans of 37 patients with 92 biopsy-proven HCC lesions treated with drug-eluting bead TACE. Following manual segmentation of lesions according to modified Response Evaluation Criteria in Solid Tumors criteria on baseline arterial phase CT images, tumor size and quantitative texture parameters were extracted. HCCs were grouped into lesions undergoing primary TACE (VT-lesions) or repeated TACE (RT-lesions). Distinct multiparametric decision tree models to predict complete response (CR) and progressive disease (PD) for the two groups were generated. AUC and model accuracy were assessed. RESULTS: Thirty-eight of 72 VT-lesions (52.8%) and 8 of 20 RT-lesions (40%) achieved CR. Sixteen VT-lesions (22.2%) and 8 RT-lesions (40%) showed PD on follow-up imaging despite TACE treatment. Mean of positive pixels (MPP) was significantly higher in VT-lesions compared to RT-lesions (180.5 vs 92.8, p = 0.001). The highest AUC in ROC curve analysis and accuracy was observed for the prediction of CR in VT-lesions (AUC 0.96, positive predictive value 96.9%, accuracy 88.9%). Prediction of PD in VT-lesions (AUC 0.88, accuracy 80.6%), CR in RT-lesions (AUC 0.83, accuracy 75.0%), and PD in RT-lesions (AUC 0.86, accuracy 80.0%) was slightly inferior. CONCLUSIONS: Nested multiparametric decision tree models based on tumor heterogeneity and size can predict HCC lesion response to TACE treatment with high accuracy. They may be used as an additional criterion in the multidisciplinary treatment decision-making process. KEY POINTS: • HCC lesion response to TACE treatment can be predicted with high accuracy based on baseline tumor heterogeneity and size. • Complete response of HCC lesions undergoing primary TACE was correctly predicted with 88.9% accuracy and a positive predictive value of 96.9%. • Progressive disease was correctly predicted with 80.6% accuracy for lesions undergoing primary TACE and 80.0% accuracy for lesions undergoing repeated TACE.

Circulating Cell-Free DNA Captures the Intratumor Heterogeneity in Multinodular Hepatocellular Carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, with more than 40% of patients initially diagnosed with multinodular HCCs. Although circulating cell-free DNA (cfDNA) has been shown to effectively detect somatic mutations, little is known about its utility to capture intratumor heterogeneity in patients with multinodular HCC undergoing systemic treatment. MATERIALS AND METHODS: Tumor biopsies and plasma were synchronously collected from seven prospectively recruited patients with HCC before and during systemic therapy. Plasma-derived cfDNA and matched germline were subjected to high-depth targeted sequencing with molecular barcoding. The mutational profile of the cfDNA was compared with whole-exome sequencing from matched tumor biopsies. RESULTS: Genomic data revealed that out of the seven patients, five were considered intrahepatic metastasis and two multicentric HCCs. cfDNA captured the majority of mutations in the tumors and detected significantly more mutations than tumor biopsies. Driver mutations such as CTNNB1 S33C, NRAS Q61R, ARID1A R727fs, and NF1 E2368fs as well as standard-of-care biomarkers of response to targeted therapy were detected only in cfDNA. In the two patients with multicentric HCC, cfDNA detected mutations derived from the genetically independent and spatially distinct nodules. Moreover, cfDNA was not only able to capture clonal mutations but also the subclonal mutations detected in only one of the multiple biopsied nodules. Furthermore, serial cfDNA detected variants of tumor origin emerging during treatment. CONCLUSION: This study revealed that the genetic analysis of cfDNA captures the intratumor heterogeneity in multinodular HCC highlighting the potential for cfDNA as a sensitive and noninvasive tool for precision medicine.

Computed tomography (CT) and magnetic resonance imaging (MRI) of diffuse liver disease: a multiparametric predictive modelling algorithm can aid categorization of liver parenchyma.

BACKGROUND: Liver steatosis is common and tracking disease evolution to steatohepatitis and cirrhosis is essential for risk stratification and resultant patient management. Consequently, diagnostic tools allowing categorization of liver parenchyma based on routine imaging are desirable. The study objective was to compare established mono-factorial, dynamic single parameter and iterative multiparametric routine computed tomography (CT) and magnetic resonance imaging (MRI) analyses to distinguish between liver steatosis, steatohepatitis, cirrhosis and normal liver parenchyma. METHODS: A total of 285 multi-phase contrast enhanced CT and 122 MRI studies with histopathological correlation of underlying parenchymal condition were retrospectively included. Parenchymal conditions were characterized based on CT Hounsfield units (HU) or MRI signal intensity (SI) measurements and calculated HU or SI ratios between non-contrast and contrast enhanced imaging time points. First, the diagnostic accuracy of mono-factorial analyses using established, static non-contrast HU and in- to opposed phase SI change cut-offs to distinguish between parenchymal conditions was established. Second, single dynamic discriminator analyses, with optimized non-contrast and enhancement HU and SI ratio cut-off values derived from the data, employing receiver operating characteristic (ROC) curve areas under the curve (AUCs) and the Youden index for maximum accuracy, were used for disease diagnosis. Third, multifactorial analyses, employing multiple non-contrast and contrast enhanced HU and SI ratio cut-offs in a nested, predictive-modelling algorithm were performed to distinguish between normal parenchyma, liver steatosis, steatohepatitis and cirrhosis. CT and MRI analyses were performed separately. RESULTS: No single CT or MRI parameter showed significant difference between all four parenchymal conditions (each P>0.05). Mono-factorial static-CT-discriminator analyses identified liver steatosis with 75% accuracy. Mono-factorial MRI analyses identified steatosis with 89% accuracy. Single-dynamic CT parameter analyses identified normal parenchyma with 72% accuracy and cirrhosis with 75% accuracy. Single-dynamic MRI parameter analyses identified fatty parenchyma with 90% accuracy. Multifactorial CT analyzes identified normal parenchyma with 84%, liver steatosis with 95%, steatohepatitis with 95% and cirrhosis with 80% accuracy. Multifactorial predictive modelling of MRI parameters identified normal parenchyma with 79%, liver steatosis with 89%, steatohepatitis with 92% and cirrhosis with 89% accuracy. CONCLUSIONS: Multiparametric analyses of quantitative measurements derived from routine CT and MRI, utilizing a predictive modelling algorithm, can help to distinguish between normal liver parenchyma, liver steatosis, steatohepatitis and cirrhosis.

Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages.

Proteogenomic analyses of hepatocellular carcinomas (HCC) have focused on early-stage, HBV-associated HCCs. Here we present an integrated proteogenomic analysis of HCCs across clinical stages and etiologies. Pathways related to cell cycle, transcriptional and translational control, signaling transduction, and metabolism are dysregulated and differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. We describe candidate copy number-driven driver genes involved in epithelial-to-mesenchymal transition, the Wnt-ß-catenin, AKT/mTOR and Notch pathways, cell cycle and DNA damage regulation. The targetable aurora kinase A and CDKs are upregulated. CTNNB1 and TP53 mutations are associated with altered protein phosphorylation related to actin filament organization and lipid metabolism, respectively. Integrative proteogenomic clusters show that HCC constitutes heterogeneous subgroups with distinct regulation of biological processes, metabolic reprogramming and kinase activation. Our study provides a comprehensive overview of the proteomic and phophoproteomic landscapes of HCCs, revealing the major pathways altered in the (phospho)proteome.

Genomic analysis of focal nodular hyperplasia with associated hepatocellular carcinoma unveils its malignant potential: a case report.

Background: Focal nodular hyperplasia (FNH) is typically considered a benign tumor of the liver without malignant potential. The co-occurrence of FNH and hepatocellular carcinoma (HCC) has been reported in rare cases. In this study we sought to investigate the clonal relationship between these lesions in a patient with FNH-HCC co-occurrence. Methods: A 74-year-old female patient underwent liver tumor resection. The resected nodule was subjected to histologic analyses using hematoxylin and eosin stain and immunohistochemistry. DNA extracted from microdissected FNH and HCC regions was subjected to whole exome sequencing. Clonality analysis were performed using PyClone. Results: Histologic analysis reveals that the nodule consists of an FNH and two adjoining HCC components with distinct histopathological features. Immunophenotypic characterization and genomic analyses suggest that the FNH is clonally related to the HCC components, and is composed of multiple clones at diagnosis, that are likely to have progressed to HCC through clonal selection and/or the acquisition of additional genetic events. Conclusion: To the best of our knowledge, our work is the first study showing a clonal relationship between FNH and HCC. We show that FNH may possess the capability to undergo malignant transformation and to progress to HCC in very rare cases.

miR-579-3p Controls Hepatocellular Carcinoma Formation by Regulating the Phosphoinositide 3-Kinase-Protein Kinase B Pathway in Chronically Inflamed Liver.

Chronic liver inflammation causes continuous liver damage with progressive liver fibrosis and cirrhosis, which may eventually lead to hepatocellular carcinoma (HCC). Whereas the 10-year incidence for HCC in patients with cirrhosis is approximately 20%, many of these patients remain tumor free for their entire lives. Clarifying the mechanisms that define the various outcomes of chronic liver inflammation is a key aspect in HCC research. In addition to a wide variety of contributing factors, microRNAs (miRNAs) have also been shown to be engaged in promoting liver cancer. Therefore, we wanted to characterize miRNAs that are involved in the development of HCC, and we designed a longitudinal study with formalin-fixed and paraffin-embedded liver biopsy samples from several pathology institutes from Switzerland. We examined the miRNA expression by nCounterNanostring technology in matched nontumoral liver tissue from patients developing HCC (n = 23) before and after HCC formation in the same patient. Patients with cirrhosis (n = 26) remaining tumor free within a similar time frame served as a control cohort. Comparison of the two cohorts revealed that liver tissue from patients developing HCC displayed a down-regulation of miR-579-3p as an early step in HCC development, which was further confirmed in a validation cohort. Correlation with messenger RNA expression profiles further revealed that miR-579-3p directly attenuated phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) expression and consequently protein kinase B (AKT) and phosphorylated AKT. In vitro experiments and the use of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology confirmed that miR-579-3p controlled cell proliferation and cell migration of liver cancer cell lines. Conclusion: Liver tissues from patients developing HCC revealed changes in miRNA expression. miR-579-3p was identified as a novel tumor suppressor regulating phosphoinositide 3-kinase-AKT signaling at the early stages of HCC development.

Small crystals with severe consequences.

We present the case of a 23-year-old patient who developed a severe gastric ischemia after the ingestion of a single dose of sodium polystyrene sulfonate (SPS) orally. Emergency surgery confirmed extensive full thickness gastric necrosis, prompting a total gastrectomy. Histopathology showed kayexalate crystals in the gastric wall, suggesting SPS-related ischemic gastritis. After radical resection of the affected stomach, this young patient was able to fully recover. Although effective, the widespread use of SPS to treat hyperpotassemia remains a debated topic because of rare but serious adverse events like the forming of kayexalate crystal residues in the gastrointestinal tract. These crystal residues are mostly found in the large intestine and can lead to ulceration and necrosis. Physicians need to be aware of this rare but potentially devastating adverse effect of SPS ingestion.

Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.

Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and genomics data in supervised machine-learning models toward the development of a clinically applicable predictive classifier of response to TACE in HCC patients. Our study consists of a discovery cohort of 33 tumors through which we identify predictive biomarkers, which are confirmed in a validation cohort. We find that radiological assessment of tumor area and several transcriptomic signatures, primarily the expression of FAM111B and HPRT1, are most predictive of response to TACE. Logistic regression decision support models consisting of tumor area and RNA-seq gene expression estimates for FAM111B and HPRT1 yield a predictive accuracy of ∼90%. Reverse transcription droplet digital PCR (RT-ddPCR) confirms these genes in combination with tumor area as a predictive classifier for response to TACE.

Expression of AXL receptor tyrosine kinase relates to monocyte dysfunction and severity of cirrhosis.

Infectious complications in patients with cirrhosis frequently initiate episodes of decompensation and substantially contribute to the high mortality. Mechanisms of the underlying immuneparesis remain underexplored. TAM receptors (TYRO3/AXL/MERTK) are important inhibitors of innate immune responses. To understand the pathophysiology of immuneparesis in cirrhosis, we detailed TAM receptor expression in relation to monocyte function and disease severity prior to the onset of acute decompensation. TNF-α/IL-6 responses to lipopolysaccharide were attenuated in monocytes from patients with cirrhosis (n = 96) compared with controls (n = 27) and decreased in parallel with disease severity. Concurrently, an AXL-expressing (AXL+) monocyte population expanded. AXL+ cells (CD14+CD16highHLA-DRhigh) were characterised by attenuated TNF-α/IL-6 responses and T cell activation but enhanced efferocytosis and preserved phagocytosis of Escherichia coli Their expansion correlated with disease severity, complications, infection, and 1-yr mortality. AXL+ monocytes were generated in response to microbial products and efferocytosis in vitro. AXL kinase inhibition and down-regulation reversed attenuated monocyte inflammatory responses in cirrhosis ex vivo. AXL may thus serve as prognostic marker and deserves evaluation as immunotherapeutic target in cirrhosis.