Molecular Classification Of Hepatocellular Carcinoma Research Articles

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a primary liver cancer characterized by hepatocellular differentiation. HCC is molecularly heterogeneous with a wide spectrum of histopathology. The prognosis of patients with HCC is generally poor, especially in those with advanced stages. HCC remains a diagnostic challenge for pathologists because of its morphological and phenotypic diversity. However, recent advances have enhanced our understanding of the molecular genetics and histological subtypes of HCC. Accurate diagnosis of HCC is important for patient management and prognosis. This review provides an update on HCC pathology, focusing on molecular genetics, histological subtypes, and diagnostic approaches.

A novel liver zonation phenotype-associated molecular classification of hepatocellular carcinoma.

Liver zonation is a unique phenomenon in which the liver exhibits distinct functions among hepatocytes along the radial axis of the lobule. This phenomenon can cause the sectionalized initiation of several liver diseases, including hepatocellular carcinoma (HCC). However, few studies have explored the zonation features of HCC. Four single-cell RNA sequencing datasets were used to identify hepatocyte-specific zonation markers. Integrative analysis was then performed with a training RNA-seq cohort (616 HCC samples) and an external validating microarray cohort (285 HCC samples) from the International Cancer Genome Consortium, The Cancer Genome Atlas, Gene Expression Omnibus, and EMBL's European Bioinformatics Institute for clustering using non-negative matrix factorization consensus clustering based on zonation genes. Afterward, we evaluated the prognostic value, clinical characteristics, transcriptome and mutation features, immune infiltration, and immunotherapy response of the HCC subclasses. A total of 94 human hepatocyte-specific zonation markers (39 central markers and 55 portal markers) were identified for the first time. Subsequently, three subgroups of HCC, namely Cluster1, Cluster2, and Cluster3 were identified. Cluster1 exhibited a non-zonational-like signature with the worst prognosis. Cluster2 was intensively associated with a central-like signature and exhibited low immune infiltration and sensitivity toward immune blockade therapy. Cluster3 was intensively correlated with a portal-like signature with the best prognosis. Finally, we identified candidate therapeutic targets and agents for Cluster1 HCC samples. The current study established a novel HCC classification based on liver zonation signature. By classifying HCC into three clusters with non-zonational-like (Cluster1), central-like (Cluster2), and portal-like (Cluster3) features, this study provided new perspectives on the heterogeneity of HCC and shed new light on delivering precision medicine for HCC patients.

A novel molecular subtype of hepatocellular carcinoma based on the tumor purity and tumor microenvironment-related polygenic risk scores.

e15040 Background: The molecular classification of hepatocellular carcinoma (HCC) plays a vital role in the management of precision therapy. Several molecular classification systems, mainly focusing on the tumor cells, were developed according to distinct omics features of HCC. Heterogeneous tumor microenvironment (TME) in HCC is recognized as a crucial part of inter-tumor heterogeneity. Few molecular classifications of HCC have so far taken into account both the related molecules of tumor cells and TME. Methods: Wefirstly identified the tumor purity (TP)-related and TME-related genes in the differentially expressed genes in HCC using GSE14520 data set, and separately constructed the TP-related and TME-related polygenic risk score (PRS). Secondly, according to the TP-related and TME-related PRSs, we proposed the TP-TME risk classification which was validated in two external data sets from The Cancer Genome Atlas Program and International Cancer Genome Consortium database. We also performed functional enrichment and drug repositioning analysis to reveal the potential biological heterogeneity among different subtypes. Results: The three TP-TME risk subtypes of HCC had significantly different prognosis and biological characteristics. The TP-TME low risk subtype had the best prognosis and was characterized by well-differentiated, the TP-TME high risk subtype had the worst prognosis and was characterized by aberrant activation of TGFβ and WNT pathways, and the TP-TME high risk subtype had the moderate prognosis and was characterized by exhibited activated MYC targets and proliferation-related gene sets. We also found that these three TP-TME risk subtypes may respond differently to immunotherapy (e.g., immune checkpoint inhibitors and chimeric antigen receptor-modified T cells) or other drug therapies. Conclusions: By combining separately constructed TP-related PRS and TME-related PRS, we proposed and validated a novel molecular classification system, the TP-TME risk subtyping system, to divide patients with HCC into three subtypes with distinct biological characteristics and prognosis. These findings highlight the significant clinical implications of the TP-TME risk subtyping system and provide potential personalized immunotherapy strategies for patients with HCC.

MRI-based radiomics and molecular classification of hepatocellular carcinoma — is there a correlation between them?

Introduction: Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor, usually developing in the context of chronic liver disease, most commonly associated with hepatitis B (HBV) or C (HCV) infection, alcohol use, or metabolic syndrome. Hepatocellular carcinoma is a very heterogeneous cancer, both at the histological and molecular level. According to recent scientific studies based on gene expression profiling, regardless of the nomenclature used by different authors, HCC can be divided into 2 main subgroups: the non-proliferative type and the proliferative type.Purpose. A review and analysis of the available foreign literature on the textural analysis of magnetic resonance imaging in noninvasive prediction of molecular classification and molecular structure of hepatocellular carcinoma.Material and methods. We searched for scientific publications and clinical guidelines in the PubMed information and analytical system for 2016–2021 using the keywords: «MRI», «radiomics», «texture analysis», «radiogenomics», «HCC», «proliferative», «nonproliferative», «molecular». After excluding studies devoted to technical aspects and the description of individual clinical observations, 16 articles were selected for analyzes.Results. The presented review has demonstrated the broad possibilities and prospects of the use of texture analysis of magnetic resonance imaging in the study of hepatocellular cancer, including the first results in the study of molecular characteristics (signatures) of this tumor. Correlation of textural characteristics with the expression of genes of immunotherapeutic targets CTLA-4 and PD-1 was shown, and a correlation was also shown between ring enhancement of a tumor in the arterial phase by MRI with gadoxetic acid (hepatospecific contrast agent) and proliferative HCC. Texture analysis scores were the predominant independent predictor of microvascular invasion, which was the main independent risk factor for postoperative recurrence.Conclusion. Although texture analysis in the study of HCC is an actively developing field, further study of the structure of this tumor at the molecular level is necessary to develop an personalized treatment, supplement or replace tumor biopsy, as well as to develop new prognostic biomarkers in patients with HCC.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications.

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

Metabolism-associated molecular classification of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a disease with unique management complexity because it displays high heterogeneity of molecular phenotypes. We herein aimed to characterize the molecular features of HCC by the development of a classification system that was based on the gene expression profile of metabolic genes. Integrative analysis was performed with a metadata set featuring 371 and 231 HCC human samples from the Cancer Genome Atlas and the International Cancer Genome Consortium, respectively. All samples were linked with clinical information. RNA sequencing data of 2752 previously characterized metabolism‐related genes were used for non‐negative matrix factorization clustering, and three subclasses of HCC (C1, C2, and C3) were identified. We then analyzed the metadata set for metabolic signatures, prognostic value, transcriptome features, immune infiltration, clinical characteristics, and drug sensitivity of subclasses, and compared the resulting subclasses with previously published classifications. Subclass C1 displayed high metabolic activity, low α‐fetoprotein (AFP) expression, and good prognosis. Subclass C2 was associated with low metabolic activities and displayed high expression of immune checkpoint genes, demonstrating drug sensitivity toward cytotoxic T‐lymphocyte‐associated protein‐4 inhibitors and the receptor tyrosine kinase inhibitor cabozantinib. Subclass C3 displayed intermediate metabolic activity, high AFP expression level, and bad prognosis. Finally, a 90‐gene classifier was generated to enable HCC classification. This study establishes a new HCC classification based on the gene expression profiles of metabolic genes, thereby furthering the understanding of the genetic diversity of human HCC.

Serum Wisteria Floribunda Agglutinin-Positive Sialylated Mucin 1 as a Marker of Progenitor/Biliary Features in Hepatocellular Carcinoma

Histological molecular classification of hepatocellular carcinoma (HCC) is clinically important for predicting the prognosis. However, a reliable serum marker has not been established. The aim of this study was to evaluate the diagnostic value of serum Wisteria Floribunda agglutinin-positive sialylated mucin 1 (WFA-sialylated MUC1), which is a novel biliary marker, as a marker of HCC with hepatic progenitor cell (HPC)/biliary features and of prognosis. A total of 144 consecutive patients who underwent complete radiofrequency ablation of primary HCC were enrolled. A serum WFA-sialylated MUC1 level of 900 μL/mL was determined as the optimal cutoff value for prediction of immunohistochemical staining for HPC/biliary features [sialylated MUC1 and cytokeratin 19 (CK19)]. Positive staining rate of sialylated MUC1 and CK19 was significantly higher in patients with WFA-sialylated MUC1 ≥900 than those with WFA-sialylated MUC1 <900. Furthermore, cumulative incidence of HCC recurrence was significantly higher in patients with WFA-sialylated MUC1 ≥900 and on multivariate analysis, serum WFA-sialylated MUC1 levels was an independent predictor of HCC recurrence. These results revealed that serum WFA-sialylated MUC1 was associated with histological feature of HCC and recurrence after curative therapy and it could be a novel marker of HPC/biliary features in HCC and of prognosis.

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.

Immunohistochemistry panel segregates molecular types of hepatocellular carcinoma in Brazilian autopsy cases.

To assess the distribution of proteins coded by genes reported as relevant for the molecular classification of hepatocellular carcinoma (HCC). In this retrospective cross-sectional study, the following clinicopathological data were analyzed in 80 autopsied HCC patients: sex, age, ethnicity, alcohol intake, infection with hepatitis B and/or C virus, infection with human immunodeficiency virus, prior treatment, basic and immediate causes of death, liver weight, presence of cirrhosis, number and size of nodules, gross pattern, histological grade and variants, architectural pattern, invasion of large veins, and presence and location of extrahepatic metastases. The protein products of genes known to be involved in molecular pathogenesis of HCC, including epidermal growth factor receptor (EGFR), MET, keratin 19 (K19), vimentin, beta-catenin, mechanistic target of rapamycin (mTOR), extracellular signaling-related kinase (ERK)1, ERK2, Ki67, cyclin D1, caspase 3 and p53, were detected by immunohistochemistry on tissue microarrays. The expression levels were scored and statistically assessed for correlation with HCC parameters. Infection with hepatitis C virus was identified in 49% of the 80 autopsy patients, cirrhosis in 90%, advanced tumors in 95%, and extrahepatic metastases in 38%. Expression of K19, p53 and ERK1 correlated to high-grade lesions. Expression of ERK1, nuclear beta-catenin, cyclin D1 and ERK2 correlated to higher rates of cell proliferation as determined by Ki67. Expression of MET, EGFR (> 0) and caspase 3 correlated with lower histological grades. Expression of EGFR correlated to that of caspase 3, and overexpression of EGFR (≥ 200/300) was observed in low-grade tumors more frequently (grades 1 and 2: 67% vs grade 3: 27% and grade 4: 30%). Expression of ERK1 was associated with that of K19 and vimentin, whereas expression of ERK2 was associated with that of cyclin D1, MET and membrane beta-catenin. Expression of vimentin was strongly correlated with that of K19. Expression of K19, p53, ERK1, ERK2, vimentin and nuclear beta-catenin was related to higher-grade markers, as opposed to expression/overexpression of EGFR, MET and caspase 3.

Molecular classification of hepatocellular carcinoma: potential therapeutic implications.

Genomic profiling of hepatocellular carcinoma (HCC) tumors has elucidated recurrent molecular aberrations common or specific to disease etiology, patient race or geographic regions, allowing the classification of HCC tumors into subclasses sharing similar molecular and clinical characteristics. Previously reported transcriptome-based molecular subclasses have highlighted several common themes. Aggressive tumors are characterized by TP53 inactivation mutations and activation of pro-oncogenic signaling pathways, and further subclassified according to expression of stemness markers. The stemness marker-negative aggressive tumors display preferential TGF-β activation. Another group of less aggressive tumors contains a subclass characterized by CTNNB1 mutations accompanied with overexpression of liver-specific WNT targets such as GLUL. Molecular therapies selectively targeting features of the HCC subclasses have suggested their utility in enriching potential responders in clinical trials and guiding therapeutic decision-making for HCC patients.

Translational medicine in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly complex disease that is generally resistant to commonly used chemotherapy and radiotherapy. Consequently, there is an urgent need for the development of new treatment strategies for this devastating disease. In the past decade, tremendous progress has been achieved in the molecular stratification of HCCs for diagnosis, prognosis, and therapeutic decision-making. To date, the molecular classification of HCCs has been carried out through transcriptomic, genetic and epigenetic profiling of tumors. Such research has led to identification of several potential molecular targets in HCC, and subsequently, development of novel systemic agents for the treatment of HCC has begun in earnest. In this article, we review the current knowledge of the molecular pathogenesis of HCC and outline potential areas for application of this knowledge in a clinical setting. As a typical virus and inflammation-associated cancer, both host immune response and tumor microenvironment have crucial roles in HCC pathogenesis. In addition, we examine the potential of immunotherapy and strategies targeting various components of the tumor microenvironment, as well as novel molecular and cellular targets in HCC such as cancer stem cells.

IV-HCC: Clinical and prognostic implications of plasma IGF-1 and VEGF in patients with hepatocellular carcinoma.

155 Background: Hepatocellular carcinoma (HCC) is a vascular tumor, derived mainly by vascular endothelial growth factor (VEGF)-mediated angiogenesis. It is always associated with chronic liver disease (CLD) and cirrhosis, which directly affect survival of HCC patients. Insulin-like growth factor-1 (IGF-1) is produced predominantly in the liver, and therefore, CLD is associated with low levels of IGF-1. Methods: 288 new consecutive patients with HCC were eligible for the study between 2001 and 2008 at M. D. Anderson Cancer Center. Baseline clinicopathologic features, CLIP and BCLC staging, plasma IGF-1 and VEGF levels were available and multivariate Cox regression models and median survival were calculated. Kaplan-Meier curves were used to estimate overall survival and the log-rank test was used to compare survival probabilities in patients with different IGF-1 and VEGF levels. Recursive partitioning was used to determine the optimal cut point for IGF-1 and VEGF, using repeated training/validation samples, each using 2/3 of the data to determine the best cut point and the remaining 1/3 to validate it. Prognostic ability of different molecular staging systems was compared using C-index. Results: Lower plasma IGF-1 and higher plasma VEGF levels significantly correlated with advanced clinicopathologic parameters and poor overall survival, with an optimal cut point of 26 pg/mL and 450 pg/mL respectively. The combination of low IGF-1 and high VEGF predicts median OS of 2.7 months compared with 19 month for patients with high IGF-1 and low VEGF (p-value=&lt;0.0001), and further refines the prognostic ability of BCLC and CLIP HCC staging systems (p&lt;0.0001). Conclusions: Molecular classification of HCC using baseline plasma IGF-1 and VEGF significantly correlated with clinical features and survival of HCC patients. Furthermore, integrating IGF-1 and VEGF into HCC staging systems, CLIP and BCLC, significantly enhanced their ability to predict prognosis. It may prove to be useful in designing strategies to personalize treatment approaches to these patients. No significant financial relationships to disclose.

Molecular classification of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most frequent tumour derived from the malignant transformation of hepatocytes. It is well established that cancer is a disease of the genome and, as in other types of solid tumours, a large number of genetic and epigenetic alterations are accumulated during the hepatocarcinogenesis process. Recent developments using comprehensive genomic tools have enabled the identification of the molecular diversity in human HCC. Consequently, several molecular classifications have been described using different approaches and important progress has been made particularly with the transcriptomic, genetic, chromosomal, miRNA and methylation profiling. On the whole, all these molecular classifications are related and one of the major determinants of the identified subgroups of tumours are gene mutations found in oncogenes and tumour suppressors. However, the full understanding of the HCC molecular classification requires additional comprehensive studies using both genomic and pathway analyses. Finally, a refinement of the molecular classification of HCC, taking into account the geographical and genetic diversity of the patients, will be essential for an efficient design of the forthcoming personalized clinical treatments.

Hepatocellular carcinoma – from macroscopy to molecular pathology

Hepatocellular carcinoma (HCC) is a tumor with rather bad prognosis. Recent years, however, have seen considerable progress in the diagnostics and treatment of this disease, contributing to better understanding of its molecular pathogenesis. Large regenerative nodules, low and high grade dysplastic nodules are premalignant alterations of HCC developing on the grounds of cirrhosis. Microscopically the WHO distinguishes trabecular, acinar (pseudoglandular), scirrhous and solid forms. Special histological subtypes are the clear cell, fibrolamellar and mixed hepato-cholangiocellular variants. The prognostic significance of these histological types is argued. The fibrolamellar, non-cirrhotic form of HCC occurring in young age is considered to be of better prognosis, but this is probably due to the fact that this type is not accompanied by cirrhosis. Certain tumor markers may help the diagnosis, such as alpha-fetoprotein (AFP), glypican-3, survivin, the recently described agrin and claudins, furthermore, the hepatocyte specific antigen (HSA), which confirms the hepatocytic origin of the tumor. Recently, the diagnostic significance of microRNAs, primarily of the hepatocyte-specific mir122 has also emerged. In addition to the Barcelona Clinic Liver Cancer (BCLC) staging classification which determines the course of therapy, the molecular classification of HCC is based on key molecular alterations, many of which are observable in all HCC cases, whereas some alterations are only detectable in certain tumors.

Abstract 2996: Overexpression of potential oncogenic microRNAs defines a new molecular subclass of hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is the most common form of liver cancer and the third cause of cancer-related death worldwide. Its incidence is increasing mainly due to hepatitis C virus (HCV) infection. A molecular classification of HCC is still lacking. microRNAs (miRNAs) are small non-coding RNA involved in HCC pathogenesis. Their expression profiling represents a powerful tool to classify cancers. Objectives: (1) To provide a miRNA-based molecular classification of HCC and, (2) To investigate the function of potential oncogenic miRNAs in HCC models. Methods: Expression of 358 miRNAs was analyzed in 89 HCV-related HCCs using a bead-based miRNA expression profiling method. Integrative analysis including miRNA profiling, gene expression (Affymetrix U133 2.0®), DNA changes (Affymetrix STY Mapping Array®), IHC (p-Akt, p-IGF-IR, p-S6, p-EGFR, β-catenin) and mutation analysis (β-catenin) was performed. Expression of selected miRNA was validated in a validation set (n=167) by qRT-PCR. Methylation-specific PCR, FISH and SNP-array analyses were performed to identify mechanisms of miRNA deregulation. The function of miRNAs of interest was investigated in vitro by analyzing cell proliferation (thymidine incorporation), migration and invasion (trans-well migration and invasion assays, wound healing assay). Tumor development and growth following direct injection of luciferase-expressing cells stably transfected with specific miRNAs into the liver of nude mice were monitored to investigate their function in vivo. The bioluminescent signal emitted by luciferase-expressing cells was used as indicator of tumor growth. Results: Three classes of HCC patients were identified and defined by activation of different pathways: Wnt signalling (32/89, 36%), IFN-related genes (29/89, 33%) and proliferative cascades (IGF, Akt/mTOR) (28/89, 31%). A subgroup within the proliferative class (8/89, 9% overexpressed a cluster of miRNAs on 19q13.42 (median fold change: 8.8). Hypomethylation of CpG island upstream the miRNA cluster (2/8, 25%) and copy number gains (1/8, 12.5%) were detected. Their overexpression was confirmed in a validation set (17/167, 10.2%). Members of the cluster family significantly increased proliferation (p&amp;lt;0.05), migration (p&amp;lt;0.02) and invasive capability (p&amp;lt;0.05) in vitro and promoted tumor development in vivo (detectable liver tumor in 4/6 mice compared with 0/6 of the controls after 4 weeks following injection). One mouse of the active arm was sacrificed at week 5 showing large invasive HCC at pathological study, while the others are still alive. Conclusions: Overexpression of 19q miRNA family and activation of proliferative pathways defined a subclass of HCC. Members of 19q miRNA family increased cell proliferation, migration and invasion in vitro and promoted tumor development in vivo suggesting their role as novel potential oncogenic drivers in HCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2996.

Molecular targeting for treatment of advanced hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major global health problem, which has a grave morbidity and mortality. Over the past few decades, no effective systemic therapeutic modalities have been established for patients with the unresectable HCC in advanced stage. Sorafenib is a small molecule that blocks cancer cell proliferation by targeting the intracellular signaling pathway at the level of Raf-1 and B-Raf serine-threonine kinases, and exerts an anti-angiogenic effect by targeting the vascular endothelial growth factor receptor-1, 2 and 3, and platelet-derived growth factor receptor-beta tyrosine kinases. Recently, two clinical successful applications, SHARP and Asia-Pacific trial, of multikinase inhibitor sorafenib represent a significant advance in the treatment of advanced HCC patients without a curative chance. However, because the results of clinical trials show diverse responses in a subset of HCC patients, a molecular classification of HCC through the excavation of specific biomarkers related to its biological behavior is necessary for sorting HCC patients to each group with a biological homogeneity, ultimately leading to the most suitable individualization of molecular targeted therapy in HCC.

Linking molecular classification of hepatocellular carcinoma and personalized medicine: preliminary steps

The development of high-throughput technologies able to simultaneously investigate thousands of genes (e.g. single nucleotide polymorphism-array, gene expression microarray, etc.) has opened a new era in translational research. Obtaining a molecular classification of hepatocellular carcinoma, however, remains a striking challenge. This review summarizes the molecular classifications of hepatocellular carcinoma reported so far, analyzes the status of targeted therapies tested in clinical trials, and evaluates feasibility of personalized medicine approaches in hepatocellular carcinoma. Different investigators attempted to classify patients according to their liver cancer molecular background, a feature that will path the way for trial enrichment and personalized medicine. Currently, hepatocellular carcinoma can be classified in molecular classes according to Wnt-beta-catenin pathway activation, proliferation signature activation (associated with chromosomal instability), and other subgroups. In parallel, the first-time-ever positive results of a phase III trial in advanced hepatocellular carcinoma with the multikinase inhibitor sorafenib have encouraged this approach. Selection of patient candidates according to their tumor molecular background is a reality in human malignancies. Thus, a molecular classification is essential to allow the development of new targets, and to customize therapies in patients with hepatocellular carcinoma.

Clinical and molecular classification of hepatocellular carcinoma

Clinical and molecular classification of hepatocellular carcinoma

Molecular Diagnosis of Chronic Liver Disease and Hepatocellular Carcinoma: The Potential of Gene Expression Profiling

Gene expression profile analysis through DNA microarrays and other high-throughput technologies permit simultaneous investigation of all genes within a biologic sample, providing a snapshot of the transcriptional state of healthy or diseased tissue. Although most of the current applications are still geared toward research (study of disease mechanisms/signaling pathways involved, identification of novel oncogenes/tumor suppressor genes), clinical diagnostic applications of this approach are beginning to enter more routine molecular usage. There are clear examples where a group of genes, or "signature," can provide clinically useful information (e.g., cancer prognosis and response to treatment). Importantly, the identification of genes that are up-regulated during tumorigenesis is heralding a new era of targeted molecular therapies in oncology. In addition, the high capacity of the technologies available allow for the identification of new biomarkers for early diagnosis. In the future, gene expression profiling ("disease fingerprinting") is likely to complement liver biopsy in the molecular differential diagnosis of chronic liver diseases and hepatocellular carcinoma (HCC). There has already been some success in the identification of subtypes of HCC based on derived sets of signature gene clusters. Data recently reported have been able to provide the first molecular classification of HCC, although more comprehensive studies are required to confirm these results and translate them into the clinical practice. In fact, variations in gene expression in normal and diseased livers, as well technical factors, are obstacles to the routine use of microarray-based methods in the liver clinic. Continued progress is anticipated in the practical application of gene array methods to refine diagnosis and therapy of HCC.