Search Results (6)

Hepatocellular carcinoma (HCC) accounts for 90% of primary hepatic malignancies and is one of the major causes of cancer-related death. Over the last 15 years, the molecular landscape of HCC has been deciphered, with the identification of the main driver genes of liver carcinogenesis that belong to six major biological pathways, such as telomere maintenance, Wnt/b-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase. The combination of genetic and transcriptomic data composed various HCC subclasses strongly related to risk factors, pathological features and prognosis. However, translation into clinical practice is not achieved, mainly because the most frequently mutated genes are undruggable. Moreover, the results derived from the analysis of a single tissue sample may not adequately catch the intra- and intertumor heterogeneity. The analysis of circulating tumor DNA (ctDNA) is broadly developed in other types of cancer for early diagnosis, prognosis and monitoring under systemic treatment in order to identify primary and secondary mechanisms of resistance. The aim of this review is to describe recent data about the HCC molecular landscape and to discuss how ctDNA could be used in the future for HCC detection and management. Full article

Treatments aimed to reverse the tumor-induced immune tolerance represent a promising approach for advanced hepatocellular carcinoma (HCC). Notwithstanding, primary nonresponse, early, and late disease reactivation still represent major clinical challenges. Here, we focused on microRNAs (miRNAs) acting both as modulators of cancer cell hallmarks and immune system response. We outlined the bidirectional function that some oncogenic miRNAs play in the differentiation and program activation of the immune system development and, at the same time, in the progression of HCC. Indeed, the multifaceted spectrum of miRNA targets allows the modulation of both immune-associated factors and oncogenic or tumor suppressor drivers at the same time. Understanding the molecular changes contributing to disease onset, progression, and resistance to treatments might help to identify possible novel biomarkers for selecting patient subgroups, and to design combined tailored treatments to potentiate antitumor approaches. Preliminary findings seem to argue in favor of a bidirectional function of some miRNAs, which enact an effective modulation of molecular pathways driving oncogenic and immune-skipping phenotypes associated with cancer aggressiveness. The identification of these miRNAs and the characterization of their ‘dual’ role might help to unravel novel biomarkers identifying those patients more likely to respond to immune checkpoint inhibitors and to identify possible therapeutic targets with both antitumor and immunomodulatory functions. In the present review, we will focus on the restricted panel of miRNAs playing a bidirectional role in HCC, influencing oncogenic and immune-related pathways at once. Even though this field is still poorly investigated in HCC, it might represent a source of candidate molecules acting as both biomarkers and therapeutic targets in the setting of immune-based treatments. Full article

Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC), frequently with HBV integrating into the host genome. HBV integration, found in 85% of HBV-associated HCC (HBV–HCC) tissue samples, has been suggested to be oncogenic. Here, we investigated the potential of HBV–HCC driver identification via the characterization of recurrently targeted genes (RTGs). A total of 18,596 HBV integration sites from our in-house study and others were analyzed. RTGs were identified by applying three criteria: at least two HCC subjects, reported by at least two studies, and the number of reporting studies. A total of 396 RTGs were identified. Among the 28 most frequent RTGs, defined as affected in at least 10 HCC patients, 23 (82%) were associated with carcinogenesis and 5 (18%) had no known function. Available breakpoint positions from the three most frequent RTGs, TERT, MLL4/KMT2B, and PLEKHG4B, were analyzed. Mutual exclusivity of TERT promoter mutation and HBV integration into TERT was observed. We present an RTG consensus through comprehensive analysis to enable the potential identification and discovery of HCC drivers for drug development and disease management. Full article

The recent advancement of omic technologies provides researchers with the possibility to search for disease-associated biomarkers at the system level. The integrative analysis of data from a large number of molecules involved at various layers of the biological system offers a great opportunity to rank disease biomarker candidates. In this paper, we propose MOTA, a network-based method that uses data acquired at multiple layers to rank candidate disease biomarkers. The networks constructed by MOTA allow users to investigate the biological significance of the top-ranked biomarker candidates. We evaluated the performance of MOTA in ranking disease-associated molecules from three sets of multi-omic data representing three cohorts of hepatocellular carcinoma (HCC) cases and controls with liver cirrhosis. The results demonstrate that MOTA allows the identification of more top-ranked metabolite biomarker candidates that are shared by two different cohorts compared to traditional statistical methods. Moreover, the mRNA candidates top-ranked by MOTA comprise more cancer driver genes compared to those ranked by traditional differential expression methods. Full article

Hepatocellular carcinoma (HCC) is the third and the fifth leading cause of cancer related death worldwide in men and in women, respectively. HCC generally has a poor prognosis, with a very low 5-year overall survival, due to delayed diagnosis and treatment. Early tumour detection and timely intervention are the best strategies to reduce morbidity and mortality in HCC patients. Histological evaluation of liver biopsies is the gold standard for cancer diagnosis, although it is an invasive, time-consuming and expensive procedure. Recently, the analysis of circulating free DNA (cfDNA) and RNA molecules released by tumour cells in body fluids, such as blood serum, saliva and urine, has attracted great interest for development of diagnostic assays based on circulating liver cancer molecular biomarkers. Such “liquid biopsies” have shown to be useful for the identification of specific molecular signatures in nucleic acids released by cancer cells, such as gene mutations and altered methylation of DNA as well as variations in the levels of circulating microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Body fluids analysis may represent a valuable strategy to monitor liver disease progression in subjects chronically infected with hepatitis viruses or cancer relapse in HCC treated patients. Several studies showed that qualitative and quantitative assays evaluating molecular profiles of circulating cell-free nucleic acids could be successfully employed for early diagnosis and therapeutic management of HCC patients. This review describes the state of art on the use of liquid biopsy for cancer driver gene mutations, deregulated DNA methylation as well as miRNA levels in HCC diagnosis. Full article

Hepatocellular carcinoma (HCC) is one of the most common cancers with a dismal outcome. The complicated molecular pathogenesis of HCC caused by tumor heterogeneity makes it difficult to identify druggable targets useful for treating HCC patients. One approach that has a potential for the improvement of patient prognosis is the identification of cancer driver genes that play a critical role in the development of HCC. Recent technological advances of high-throughput methods, such as gene expression profiles, DNA copy number alterations and somatic mutations, have expanded our understanding of the comprehensive genetic profiles of HCC. Integrative analysis of these omics profiles enables us to classify the molecular subgroups of HCC patients. As each subgroup classified according to genetic profiles has different clinical features, such as recurrence rate and prognosis, the tumor subclassification tools are useful in clinical practice. Furthermore, a global genetic analysis, including genome-wide RNAi functional screening, makes it possible to identify cancer vulnerable genes. Identification of common cancer driver genes in HCC leads to the development of an effective molecular target therapy. Full article