Immune Exclusion-Wnt/CTNNB1 Class Predicts Resistance to Immunotherapies in HCC

Next-generation sequencing has provided information on actionable targets and biomarkers of response in oncology. In hepatocellular carcinoma (HCC), Wnt/CTNNB1 mutations characterize the immune-excluded class (cold tumors) and might represent the biomarkers predicting resistance to immune checkpoint inhibitors. Large-scale validation of these data is needed to customize immunotherapy in advanced HCC.See related article by Harding et al.©2019 American Association for Cancer Research

Molecular therapies and precision medicine for hepatocellular carcinoma

The global burden of hepatocellular carcinoma (HCC) is increasing and might soon surpass an annual incidence of 1 million cases. Genomic studies have established the landscape of molecular alterations in HCC; however, the most common mutations are not actionable, and only ~25% of tumours harbour potentially targetable drivers. Despite the fact that surveillance programmes lead to early diagnosis in 40–50% of patients, at a point when potentially curative treatments are applicable, almost half of all patients with HCC ultimately receive systemic therapies. Sorafenib was the first systemic therapy approved for patients with advanced-stage HCC, after a landmark study revealed an improvement in median overall survival from 8 to 11 months. New drugs — lenvatinib in the frontline and regorafenib, cabozantinib, and ramucirumab in the second line — have also been demonstrated to improve clinical outcomes, although the median overall survival remains ~1 year; thus, therapeutic breakthroughs are still needed. Immune-checkpoint inhibitors are now being incorporated into the HCC treatment armamentarium and combinations of molecularly targeted therapies with immunotherapies are emerging as tools to boost the immune response. Research on biomarkers of a response or primary resistance to immunotherapies is also advancing. Herein, we summarize the molecular targets and therapies for the management of HCC and discuss the advancements expected in the near future, including biomarker-driven treatments and immunotherapies

Liver Cancer Cell of Origin, Molecular Class, and Effects on Patient Prognosis

Primary liver cancer is the second leading cause of cancer-related death worldwide and therefore a major public health challenge. We review hypotheses of the cell of origin of liver tumorigenesis and clarify the classes of liver cancer based on molecular features and how they affect patient prognosis. Primary liver cancer comprises hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and other rare tumors, notably fibrolamellar carcinoma and hepatoblastoma. The molecular and clinical features of HCC versus iCCA are distinct, but these conditions have overlapping risk factors and pathways of oncogenesis. A better understanding of the cell types originating liver cancer can aid in exploring molecular mechanisms of carcinogenesis and therapeutic options. Molecular studies have identified adult hepatocytes as the cell of origin. These cells have been proposed to transform directly into HCC cells (via a sequence of genetic alterations), to dedifferentiate into hepatocyte precursor cells (which then become HCC cells that express progenitor cell markers), or to transdifferentiate into biliary-like cells (which give rise to iCCA). Alternatively, progenitor cells also give rise to HCCs and iCCAs with markers of progenitor cells. Advances in genome profiling and next-generation sequencing have led to the classification of HCCs based on molecular features and assigned them to categories such as proliferation-progenitor, proliferation-transforming growth factor β, and Wnt-catenin β1. iCCAs have been assigned to categories of proliferation and inflammation. Overall, proliferation subclasses are associated with a more aggressive phenotype and poor outcome of patients, although more specific signatures have refined our prognostic abilities. Analyses of genetic alterations have identified those that might be targeted therapeutically, such as fusions in the FGFR2 gene and mutations in genes encoding isocitrate dehydrogenases (in approximately 60% of iCCAs) or amplifications at 11q13 and 6p21 (in approximately 15% of HCCs). Further studies of these alterations are needed before they can be used as biomarkers in clinical decision making

Cost-effectiveness of adjuvant therapy for hepatocellular carcinoma during the waiting list for liver transplantation.

Background: Survival after liver transplantation for early hepatocellular carcinoma (HCC) is worsened by the increasing dropout rate while waiting for a donor. Aims: To assess the cost effectiveness of adjuvant therapy while waiting for liver transplantation in HCC patients. Method: Using a Markov model, a hypothetical cohort of cirrhotic patients with early HCC was considered for: (1) adjuvant treatment—resection was limited to Child-Pugh's A patients with single tumours, and percutaneous treatment was considered for Child-Pugh's A and B patients with single tumours unsuitable for resection or with up to three nodules < 3 cm; and (2) standard management. Length of waiting time ranged from six to 24 months. Results: Surgical resection increased the transplantation rate (>10%) and provided gains in life expectancy of 4.8–6.1 months with an acceptable cost ($40 000/ year of life gained) for waiting lists ≥1 year whereas it was not cost effective ($74 000/life of year gained) for shorter waiting times or high dropout rate scenarios. Percutaneous treatment increased life expectancy by 5.2–6.7 months with a marginal cost of approximately $20 000/year of life gained in all cases, remaining cost effective for all waiting times. Conclusions: Adjuvant therapies for HCC while waiting for liver transplantation provide moderate gains in life expectancy and are cost effective for waiting lists of one year or more. For shorter waiting times, only percutaneous treatment confers a relevant survival advantage

Hepatocellular carcinoma

Liver cancer is the second leading cause of cancer-related deaths globally and has an incidence of approximately 850,000 new cases per year. Hepatocellular carcinoma (HCC) represents approximately 90% of all cases of primary liver cancer. The main risk factors for developing HCC are well known and include hepatitis B and C virus infection, alcohol intake and ingestion of the fungal metabolite aflatoxin B1. Additional risk factors such as non-alcoholic steatohepatitis are also emerging. Advances in the understanding of the molecular pathogenesis of HCC have led to identification of critical driver mutations; however, the most prevalent of these are not yet druggable targets. The molecular classification of HCC is not established, and the Barcelona Clinic Liver Cancer staging classification is the main clinical algorithm for the stratification of patients according to prognosis and treatment allocation. Surveillance programmes enable the detection of early-stage tumours that are amenable to curative therapies - resection, liver transplantation or local ablation. At more developed stages, only chemoembolization (for intermediate HCC) and sorafenib (for advanced HCC) have shown survival benefits. There are major unmet needs in HCC management that might be addressed through the discovery of new therapies and their combinations for use in the adjuvant setting and for intermediate- and advanced-stage disease. Moreover, biomarkers for therapy stratification, patient-tailored strategies targeting driver mutations and/or activating signalling cascades, and validated measurements of quality of life are needed. Recent failures in the testing of systemic drugs for intermediate and advanced stages have indicated a need to refine trial designs and to define novel approaches

Liver Cancer Disparities in New York City: A neighborhood wiew of risk and harm reduction factors

Introduction: Liver cancer is the fastest increasing cancer in the United States and is one of the leading causes of cancer-related death in New York City (NYC), with wide disparities among neighborhoods. The purpose of this cross-sectional study was to describe liver cancer incidence by neighborhood and examine its association with risk factors. This information can inform preventive and treatment interventions. Materials and methods: Publicly available data were collected on adult NYC residents (n = 6,407,022). Age-adjusted data on liver and intrahepatic bile duct cancer came from the New York State Cancer Registry (1) (2007-2011 average annual incidence); and the NYC Vital Statistics Bureau (2015, mortality). Data on liver cancer risk factors (2012-2015) were sourced from the New York City Department of Health and Mental Hygiene: (1) Community Health Survey, (2) A1C registry, and (3) NYC Health Department Hepatitis surveillance data. They included prevalence of obesity, diabetes, diabetic control, alcohol-related hospitalizations or emergency department visits, hepatitis B and C rates, hepatitis B vaccine coverage, and injecting drug use. Results: Liver cancer incidence in NYC was strongly associated with neighborhood poverty after adjusting for race/ethnicity (β = 0.0217, p = 0.013); and with infection risk scores (β = 0.0389, 95% CI = 0.0088-0.069, p = 0.011), particularly in the poorest neighborhoods (β = 0.1207, 95% CI = 0.0147-0.2267, p = 0.026). Some neighborhoods with high hepatitis rates do not have a proportionate number of hepatitis prevention services. Conclusion: High liver cancer incidence is strongly associated with infection risk factors in NYC. There are gaps in hepatitis prevention services like syringe exchange and vaccination that should be addressed. The role of alcohol and metabolic risk factors on liver cancer in NYC warrants further study

Pattern of progression in advanced hepatocellular carcinoma treated with ramucirumab

Background & aims: Radiological progression patterns to first-line sorafenib have been associated with post-progression and overall survival in advanced hepatocellular carcinoma, but these associations remain unknown for therapies in second- and later-line settings. This post hoc analysis of REACH and REACH-2 examined outcomes by radiological progression patterns in the second-line setting of patients with advanced hepatocellular carcinoma treated with ramucirumab or placebo.Methods: Patients with advanced hepatocellular carcinoma, Child-Pugh A and Eastern Cooperative Oncology Group Performance Status 0 or 1 with prior sorafenib were randomized to receive ramucirumab 8mg/kg or placebo every 2 weeks. Among 625 patients with ≥1 progression pattern (new extrahepatic lesion [including new macrovascular invasion], new intrahepatic lesion, extrahepatic growth or intrahepatic growth), data were analysed by trial and for pooled individual patient data for REACH-2 and REACH (alpha-fetoprotein ≥400 ng/mL). Cox models evaluated prognostic implications of progression patterns on overall and post-progression survival. Results: Post-progression survival was worse among those with new extrahepatic lesions in REACH (HR 2.33, 95% CI 1.51-3.60), REACH-2 (HR 1.49, 95% CI 0.72-3.08) and the pooled population (HR 1.75, 95% CI 1.12-2.74) compared to other progression patterns. Overall survival was also significantly reduced in those with new extrahepatic lesions across studies. Ramucirumab provided an overall survival benefit across progression patterns, including patients with new extrahepatic lesions (HR 0.56, 95% CI 0.39-0.80) in the pooled population. Conclusions: The emergence of new extrahepatic lesions in the second-line setting is a poor prognostic factor for post-progression survival. The benefit of ramucirumab for overall survival was consistent across progression patterns

Tumour initiating cells and IGF/FGF signalling contribute to sorafenib resistance in hepatocellular carcinoma

Objective: Sorafenib is effective in hepatocellular carcinoma (HCC), but patients ultimately present disease progression. Molecular mechanisms underlying acquired resistance are still unknown. Herein, we characterise the role of tumour-initiating cells (T-ICs) and signalling pathways involved in sorafenib resistance. Design: HCC xenograft mice treated with sorafenib (n=22) were explored for responsiveness (n=5) and acquired resistance (n=17). Mechanism of acquired resistance were assessed by: (1) role of T-ICs by in vitro sphere formation and in vivo tumourigenesis assays using NOD/SCID mice, (2) activation of alternative signalling pathways and (3) efficacy of anti-FGF and anti-IGF drugs in experimental models. Gene expression (microarray, quantitative real-time PCR (qRT-PCR)) and protein analyses (immunohistochemistry, western blot) were conducted. A novel gene signature of sorafenib resistance was generated and tested in two independent cohorts. Results: Sorafenib-acquired resistant tumours showed significant enrichment of T-ICs (164 cells needed to create a tumour) versus sorafenib-sensitive tumours (13 400 cells) and non-treated tumours (1292 cells), p<0.001. Tumours with sorafenib-acquired resistance were enriched with insulin-like growth factor (IGF) and fibroblast growth factor (FGF) signalling cascades (false discovery rate (FDR)<0.05). In vitro, cells derived from sorafenib-acquired resistant tumours and two sorafenib-resistant HCC cell lines were responsive to IGF or FGF inhibition. In vivo, FGF blockade delayed tumour growth and improved survival in sorafenib-resistant tumours. A sorafenib-resistance 175 gene signature was characterised by enrichment of progenitor cell features, aggressive tumorous traits and predicted poor survival in two cohorts (n=442 patients with HCC). Conclusion: Acquired resistance to sorafenib is driven by T-ICs with enrichment of progenitor markers and activation of IGF and FGF signalling. Inhibition of these pathways would benefit a subset of patients after sorafenib progression

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications.

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/