Anja Lachenmayer

Molecular classification and novel targets in hepatocellular carcinoma: recent advancements.

Hepatocellular carcinoma (HCC) is one of most lethal cancers worldwide. Strategic decisions for the advancement of molecular therapies in this neoplasm require a clear understanding of its molecular classification. Studies indicate aberrant activation of signaling pathways involved in cellular proliferation (e.g., epidermal growth factor and RAS/mitogen-activated protein kinase pathways), survival (e.g., Akt/mechanistic target of rapamycin pathway), differentiation (e.g., Wnt and Hedgehog pathways), and angiogenesis (e.g., vascular endothelial growth factor and platelet-derived growth factor), which is heterogeneously presented in each tumor. Integrative analysis of accumulated genomic datasets has revealed a global scheme of molecular classification of HCC tumors observed across diverse etiologic factors and geographic locations. Such a framework will allow systematic understanding of the frequently co-occurring molecular aberrations to design treatment strategy for each specific subclass of tumors. Accompanied by a growing number of clinical trials of molecular targeted drugs, diagnostic and prognostic biomarker development will be facilitated with special attention on study design and with new assay technologies specialized for archived fixed tissues. A new class of genomic information, microRNA dysregulation and epigenetic alterations, will provide insight for more precise understanding of disease mechanism and expand the opportunity of biomarker/therapeutic target discovery. These efforts will eventually enable personalized management of HCC.

Advances in targeted therapies for hepatocellular carcinoma in the genomic era

Mortality owing to liver cancer has increased in the past 20 years, and the latest estimates indicate that the global health burden of this disease will continue to grow. Most patients with hepatocellular carcinoma (HCC) are still diagnosed at intermediate or advanced disease stages, where curative approaches are often not feasible. Among the treatment options available, the molecular targeted agent sorafenib is able to significantly increase overall survival in these patients. Thereafter, up to seven large, randomized phase III clinical trials investigating other molecular therapies in the first-line and second-line settings have failed to improve on the results observed with this agent. Potential reasons for this include intertumour heterogeneity, issues with trial design and a lack of predictive biomarkers of response. During the past 5 years, substantial advances in our knowledge of the human genome have provided a comprehensive picture of commonly mutated genes in patients with HCC. This knowledge has not yet influenced clinical decision-making or current clinical practice guidelines. In this Review the authors summarize the molecular concepts of progression, discuss the potential reasons for clinical trial failure and propose new concepts of drug development, which might lead to clinical implementation of emerging targeted agents.

MicroRNA-Based Classification of Hepatocellular Carcinoma and Oncogenic Role of miR-517a

BACKGROUND & AIMS Hepatocellular carcinoma (HCC) is a heterogeneous tumor that develops via activation of multiple pathways and molecular alterations. It has been a challenge to identify molecular classes of HCC and design treatment strategies for each specific subtype. MicroRNAs (miRNAs) are involved in HCC pathogenesis, and their expression profiles have been used to classify cancers. We analyzed miRNA expression in human HCC samples to identify molecular subclasses and oncogenic miRNAs. METHODS We performed miRNA profiling of 89 HCC samples using a ligation-mediated amplification method. Subclasses were identified by unsupervised clustering analysis. We identified molecular features specific for each subclass using expression pattern (Affymetrix U133 2.0; Affymetrix, Santa Clara, CA), DNA change (Affymetrix STY Mapping Array), mutation (CTNNB1), and immunohistochemical (phosphor[p]-protein kinase B, p-insulin growth factor-IR, p-S6, p-epidermal growth factor receptor, β-catenin) analyses. The roles of selected miRNAs were investigated in cell lines and in an orthotopic model of HCC. RESULTS We identified 3 main clusters of HCCs: the wingless-type MMTV integration site (32 of 89; 36%), interferon-related (29 of 89; 33%), and proliferation (28 of 89; 31%) subclasses. A subset of patients with tumors in the proliferation subclass (8 of 89; 9%) overexpressed a family of poorly characterized miRNAs from chr19q13.42. Expression of miR-517a and miR-520c (from ch19q13.42) increased proliferation, migration, and invasion of HCC cells in vitro. MiR-517a promoted tumorigenesis and metastatic dissemination in vivo. CONCLUSIONS We propose miRNA-based classification of 3 subclasses of HCC. Among the proliferation class, miR-517a is an oncogenic miRNA that promotes tumor progression. There is rationale for developing therapies that target miR-517a for patients with HCC.

Wnt-pathway activation in two molecular classes of hepatocellular carcinoma and experimental modulation by sorafenib.

Purpose: Hepatocellular carcinoma (HCC) is a heterogeneous cancer with active Wnt signaling. Underlying biologic mechanisms remain unclear and no drug targeting this pathway has been approved to date. We aimed to characterize Wnt-pathway aberrations in HCC patients, and to investigate sorafenib as a potential Wnt modulator in experimental models of liver cancer. Experimental Design: The Wnt-pathway was assessed using mRNA (642 HCCs and 21 liver cancer cell lines) and miRNA expression data (89 HCCs), immunohistochemistry (108 HCCs), and CTNNB1-mutation data (91 HCCs). Effects of sorafenib on Wnt signaling were evaluated in four liver cancer cell lines with active Wnt signaling and a tumor xenograft model. Results: Evidence for Wnt activation was observed for 315 (49.1%) cases, and was further classified as CTNNB1 class (138 cases [21.5%]) or Wnt-TGFβ class (177 cases [27.6%]). CTNNB1 class was characterized by upregulation of liver-specific Wnt-targets, nuclear β-catenin and glutamine-synthetase immunostaining, and enrichment of CTNNB1-mutation-signature, whereas Wnt-TGFβ class was characterized by dysregulation of classical Wnt-targets and the absence of nuclear β-catenin. Sorafenib decreased Wnt signaling and β-catenin protein in HepG2 (CTNNB1 class), SNU387 (Wnt-TGFβ class), SNU398 (CTNNB1-mutation), and Huh7 (lithium-chloride-pathway activation) cell lines. In addition, sorafenib attenuated expression of liver-related Wnt-targets GLUL, LGR5, and TBX3. The suppressive effect on CTNNB1 class–specific Wnt-pathway activation was validated in vivo using HepG2 xenografts in nude mice, accompanied by decreased tumor volume and increased survival of treated animals. Conclusions: Distinct dysregulation of Wnt-pathway constituents characterize two different Wnt-related molecular classes (CTNNB1 and Wnt-TGFβ), accounting for half of all HCC patients. Sorafenib modulates β-catenin/Wnt signaling in experimental models that harbor the CTNNB1 class signature. Clin Cancer Res; 18(18); 4997–5007. ©2012 AACR.

UHRF1 overexpression drives DNA hypomethylation and hepatocellular carcinoma.

Ubiquitin-like with PHD and RING finger domains 1 (UHRF1) is an essential regulator of DNA methylation that is highly expressed in many cancers. Here, we use transgenic zebrafish, cultured cells, and human tumors to demonstrate that UHRF1 is an oncogene. UHRF1 overexpression in zebrafish hepatocytes destabilizes and delocalizes Dnmt1 and causes DNA hypomethylation and Tp53-mediated senescence. Hepatocellular carcinoma (HCC) emerges when senescence is bypassed. tp53 mutation both alleviates senescence and accelerates tumor onset. Human HCCs recapitulate this paradigm, as UHRF1 overexpression defines a subclass of aggressive HCCs characterized by genomic instability, TP53 mutation, and abrogation of the TP53-mediated senescence program. We propose that UHRF1 overexpression is a mechanism underlying DNA hypomethylation in cancer cells and that senescence is a primary means of restricting tumorigenesis due to epigenetic disruption.

New strategies in hepatocellular carcinoma: genomic prognostic markers.

Accurate prognosis prediction in oncology is critical. In patients with hepatocellular carcinoma (HCC), unlike most solid tumors, the coexistence of two life-threatening conditions, cancer and cirrhosis, makes prognostic assessments difficult. Despite the usefulness of clinical staging systems for HCC in routine clinical decision making (e.g., Barcelona-Clinic Liver Cancer algorithm), there is still a need to refine and complement outcome predictions. Recent data suggest the ability of gene signatures from the tumor (e.g., EpCAM signature) and adjacent tissue (e.g., poor-survival signature) to predict outcome in HCC (either recurrence or overall survival), although independent external validation is still required. In addition, novel information is being produced by alternative genomic sources such as microRNA (miRNA; e.g., miR-26a) or epigenomics, areas in which promising preliminary data are thoroughly explored. Prognostic models need to contemplate the impact of liver dysfunction and risk of subsequent de novo tumors in a patient’s life expectancy. The challenge for the future is to precisely depict genomic predictors (e.g., gene signatures, miRNA, or epigenetic biomarkers) at each stage of the disease and their specific influence to determine patient prognosis. Clin Cancer Res; 16(19); 4688–94. ©2010 AACR.

Combination therapy for hepatocellular carcinoma: Additive preclinical efficacy of the HDAC inhibitor panobinostat with sorafenib

BACKGROUND & AIMS Hepatocellular carcinoma (HCC) is a heterogeneous cancer in which sorafenib is the only approved systemic therapy. Histone deacetylases (HDAC) are commonly dysregulated in cancer and therefore represent promising targets for therapies, however their role in HCC pathogenesis is still unknown. We analyzed the expression of 11 HDACs in human HCCs and assessed the efficacy of the pan-HDAC inhibitor panobinostat alone and in combination with sorafenib in preclinical models of liver cancer. METHODS Gene expression and copy number changes were analyzed in a cohort of 334 human HCCs, while the effects of panobinostat and sorafenib were evaluated in three liver cancer cell lines and a murine xenograft model. RESULTS Aberrant HDAC expression was identified and validated in 91 and 243 HCCs, respectively. Upregulation of HDAC3 and HDAC5 mRNAs was significantly correlated with DNA copy number gains. Inhibiting HDACs with panobinostat led to strong anti-tumoral effects in vitro and vivo, enhanced by the addition of sorafenib. Cell viability and proliferation declined, while apoptosis and autophagy increased. Panobinostat increased histone H3 and HSP90 acetylation, downregulated BIRC5 (survivin) and upregulated CDH1. Combination therapy with panobinostat and sorafenib significantly decreased vessel density, and most significantly decreased tumor volume and increased survival in HCC xenografts. CONCLUSIONS Aberrant expression of several HDACs and copy number gains of HDAC3 and HDAC5 occur in HCC. Treatment with panobinostat combined with sorafenib demonstrated the highest preclinical efficacy in HCC models, providing the rationale for clinical studies with this novel combination.

Genome-Wide Methylation Analysis and Epigenetic Unmasking Identify Tumor Suppressor Genes in Hepatocellular Carcinoma

BACKGROUND & AIMS Epigenetic silencing of tumor suppressor genes contributes to the pathogenesis of hepatocellular carcinoma (HCC). To identify clinically relevant tumor suppressor genes silenced by DNA methylation in HCC, we integrated DNA methylation data from human primary HCC samples with data on up-regulation of gene expression after epigenetic unmasking. METHODS We performed genome-wide methylation analysis of 71 human HCC samples using the Illumina HumanBeadchip27K array; data were combined with those from microarray analysis of gene re-expression in 4 liver cancer cell lines after their exposure to reagents that reverse DNA methylation (epigenetic unmasking). RESULTS Based on DNA methylation in primary HCC and gene re-expression in cell lines after epigenetic unmasking, we identified 13 candidate tumor suppressor genes. Subsequent validation led us to focus on functionally characterizing 2 candidates, sphingomyelin phosphodiesterase 3 (SMPD3) and neurofilament, heavy polypeptide (NEFH), which we found to behave as tumor suppressor genes in HCC. Overexpression of SMPD3 and NEFH by stable transfection of inducible constructs into an HCC cell line reduced cell proliferation by 50% and 20%, respectively (SMPD3, P = .003 and NEFH, P = .003). Conversely, knocking down expression of these genes with small hairpin RNA promoted cell invasion and migration in vitro (SMPD3, P = .0001 and NEFH, P = .022), and increased their ability to form tumors after subcutaneous injection or orthotopic transplantation into mice, confirming their role as tumor suppressor genes in HCC. Low levels of SMPD3 were associated with early recurrence of HCC after curative surgery in an independent patient cohort (P = .001; hazard ratio = 3.22; 95% confidence interval: 1.6-6.5 in multivariate analysis). CONCLUSIONS Integrative genomic analysis identified SMPD3 and NEFH as tumor suppressor genes in HCC. We provide evidence that SMPD3 is a potent tumor suppressor gene that could affect tumor aggressiveness; a reduced level of SMPD3 is an independent prognostic factor for early recurrence of HCC.

Gene-expression signature of vascular invasion in hepatocellular carcinoma

BACKGROUND & AIMS Vascular invasion is a major predictor of tumor recurrence after surgical treatments for hepatocellular carcinoma (HCC). While macroscopic vascular invasion can be detected by radiological techniques, pre-operative detection of microscopic vascular invasion, which complicates 30-40% of patients with early tumors, remains elusive. METHODS A total of 214 patients with hepatocellular carcinoma who underwent resection were included in the study. By using genome-wide gene-expression profiling of 79 hepatitis C-related hepatocellular carcinoma samples (training set), a gene-expression signature associated with vascular invasion was defined. The signature was validated in formalin-fixed paraffin-embedded tissues obtained from an independent set of 135 patients with various etiologies. RESULTS A 35-gene signature of vascular invasion was defined in the training set, predicting vascular invasion with an accuracy of 69%. The signature was independently associated with the presence of vascular invasion (OR 3.38, 95% CI 1.48-7.71, p=0.003) along with tumor size (diameter greater than 3 cm, OR 2.66, 95% CI 1.17-6.05, p=0.02). In the validation set, the signature discarded the presence of vascular invasion with a negative predictive value of 0.77, and significantly improved the diagnostic power of tumor size alone (p=0.045). CONCLUSIONS The assessment of a gene-expression signature obtained from resected biopsied tumor specimens improved the diagnosis of vascular invasion beyond clinical variable-based prediction. The signature may aid in candidate selection for liver transplantation, and guide the design of clinical trials with experimental adjuvant therapies.

Diagnostic and Prognostic Molecular Markers in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, representing also the main cause of death among cirrhotic patients. In contrast to most other solid tumors, the underlying cirrhotic liver disease in HCC patients greatly impairs tumor related prognosis, conferring this neoplasm a unique situation, in which accurate prognostic prediction is a relevant and unmet need. Although clinical staging systems have improved significantly and now comprise tumor characteristics, liver function and patient performance status, the integration of molecular data into these algorithms is still hypothetical. Molecular profiling of HCC has led to a better understanding of the physiopathology of this neoplasm and has allowed developing novel therapeutic approaches (e.g. molecular targeted therapies) for a tumor previously considered as therapy-refractory. Integrative analysis of different reported genomic datasets has revealed common subclasses between different studies, highlighting their biological relevance in HCC. Gene signatures derived from tumors and from the adjacent tissue have been able to differentiate subclasses with different outcomes and have been proposed as potential predictive markers in the clinical setting. Genomic characterization of surrounding non-tumor tissue might be of particular interest to identify patients at high risk of developing HCC and therefore to select those patients that would benefit of potential chemopreventive strategies. Epigenetic analyses (methylation and miRNA profiling) are adding up to the knowlegde derived from gene expression data and should not be forgotten in the molecular diagnosis of HCC. Integrative analyses of genetic and epigenetic information of the tumor and the surrounding tissue should be used to identify novel biomarkers and therapeutic targets in HCC, to improve existing treatment algorithms and to eventually design a more personalized medicine in this devastating disease.