Clara Alsinet

Pivotal Role of mTOR Signaling in Hepatocellular Carcinoma

BACKGROUND & AIMS The advent of targeted therapies in hepatocellular carcinoma (HCC) has underscored the importance of pathway characterization to identify novel molecular targets for treatment. We evaluated mTOR signaling in human HCC, as well as the antitumoral effect of a dual-level blockade of the mTOR pathway. METHODS The mTOR pathway was assessed using integrated data from mutation analysis (direct sequencing), DNA copy number changes (SNP-array), messenger RNA levels (quantitative reverse-transcription polymerase chain reaction and gene expression microarray), and protein activation (immunostaining) in 351 human samples [HCC (n = 314) and nontumoral tissue (n = 37)]. Effects of dual blockade of mTOR signaling using a rapamycin analogue (everolimus) and an epidermal/vascular endothelial growth factor receptor inhibitor (AEE788) were evaluated in liver cancer cell lines and in a xenograft model. RESULTS Aberrant mTOR signaling (p-RPS6) was present in half of the cases, associated with insulin-like growth factor pathway activation, epidermal growth factor up-regulation, and PTEN dysregulation. PTEN and PI3KCA-B mutations were rare events. Chromosomal gains in RICTOR (25% of patients) and positive p-RPS6 staining correlated with recurrence. RICTOR-specific siRNA down-regulation reduced tumor cell viability in vitro. Blockage of mTOR signaling with everolimus in vitro and in a xenograft model decelerated tumor growth and increased survival. This effect was enhanced in vivo after epidermal growth factor blockade. CONCLUSIONS MTOR signaling has a critical role in the pathogenesis of HCC, with evidence for the role of RICTOR in hepato-oncogenesis. MTOR blockade with everolimus is effective in vivo. These findings establish a rationale for targeting the mTOR pathway in clinical trials in HCC.

Combining Clinical, Pathology, and Gene Expression Data to Predict Recurrence of Hepatocellular Carcinoma

BACKGROUND & AIMS In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.

Integrative Molecular Analysis of Intrahepatic Cholangiocarcinoma Reveals 2 Classes That Have Different Outcomes

BACKGROUND & AIMS Cholangiocarcinoma, the second most common liver cancer, can be classified as intrahepatic cholangiocarcinoma (ICC) or extrahepatic cholangiocarcinoma. We performed an integrative genomic analysis of ICC samples from a large series of patients. METHODS We performed a gene expression profile, high-density single-nucleotide polymorphism array, and mutation analyses using formalin-fixed ICC samples from 149 patients. Associations with clinicopathologic traits and patient outcomes were examined for 119 cases. Class discovery was based on a non-negative matrix factorization algorithm and significant copy number variations were identified by Genomic Identification of Significant Targets in Cancer (GISTIC) analysis. Gene set enrichment analysis was used to identify signaling pathways activated in specific molecular classes of tumors, and to analyze their genomic overlap with hepatocellular carcinoma (HCC). RESULTS We identified 2 main biological classes of ICC. The inflammation class (38% of ICCs) is characterized by activation of inflammatory signaling pathways, overexpression of cytokines, and STAT3 activation. The proliferation class (62%) is characterized by activation of oncogenic signaling pathways (including RAS, mitogen-activated protein kinase, and MET), DNA amplifications at 11q13.2, deletions at 14q22.1, mutations in KRAS and BRAF, and gene expression signatures previously associated with poor outcomes for patients with HCC. Copy number variation-based clustering was able to refine these molecular groups further. We identified high-level amplifications in 5 regions, including 1p13 (9%) and 11q13.2 (4%), and several focal deletions, such as 9p21.3 (18%) and 14q22.1 (12% in coding regions for the SAV1 tumor suppressor). In a complementary approach, we identified a gene expression signature that was associated with reduced survival times of patients with ICC; this signature was enriched in the proliferation class (P < .001). CONCLUSIONS We used an integrative genomic analysis to identify 2 classes of ICC. The proliferation class has specific copy number alterations, activation of oncogenic pathways, and is associated with worse outcome. Different classes of ICC, based on molecular features, therefore might require different treatment approaches.

Ras pathway activation in hepatocellular carcinoma and anti-tumoral effect of combined sorafenib and rapamycin in vivo ☆

BACKGROUND/AIMS The success of sorafenib in the treatment of advanced hepatocellular carcinoma (HCC) has focused interest on the role of Ras signaling in this malignancy. We investigated the molecular alterations of the Ras pathway in HCC and the antineoplastic effects of sorafenib in combination with rapamycin, an inhibitor of mTOR pathway, in experimental models. METHODS Gene expression (qRT-PCR, oligonucleotide microarray), DNA copy number changes (SNP-array), methylation of tumor suppressor genes (methylation-specific PCR) and protein activation (immunohistochemistry) were analysed in 351 samples. Anti-tumoral effects of combined therapy targeting the Ras and mTOR pathways were evaluated in cell lines and HCC xenografts. RESULTS Different mechanisms accounted for Ras pathway activation in HCC. H-ras was up-regulated during different steps of hepatocarcinogenesis. B-raf was overexpressed in advanced tumors and its expression was associated with genomic amplification. Partial methylation of RASSF1A and NORE1A was detected in 89% and 44% of tumors respectively, and complete methylation was found in 11 and 4% of HCCs. Activation of the pathway (pERK immunostaining) was identified in 10.3% of HCC. Blockade of Ras and mTOR pathways with sorafenib and rapamycin reduced cell proliferation and induced apoptosis in cell lines. In vivo, the combination of both compounds enhanced tumor necrosis and ulceration when compared with sorafenib alone. CONCLUSIONS Ras activation results from several molecular alterations, such as methylation of tumor suppressors and amplification of oncogenes (B-raf). Sorafenib blocks signaling and synergizes with rapamycin in vivo, preventing tumor progression. These data provide the rationale for testing this combination in clinical studies.

IGF activation in a molecular subclass of hepatocellular carcinoma and pre-clinical efficacy of IGF-1R blockage

BACKGROUND & AIMS IGF signaling has a relevant role in a variety of human malignancies. We analyzed the underlying molecular mechanisms of IGF signaling activation in early hepatocellular carcinoma (HCC; BCLC class 0 or A) and assessed novel targeted therapies blocking this pathway. METHODS An integrative molecular dissection of the axis was conducted in a cohort of 104 HCCs analyzing gene and miRNA expression, structural aberrations, and protein activation. The therapeutic potential of a selective IGF-1R inhibitor, the monoclonal antibody A12, was assessed in vitro and in a xenograft model of HCC. RESULTS Activation of the IGF axis was observed in 21% of early HCCs. Several molecular aberrations were identified, such as overexpression of IGF2 -resulting from reactivation of fetal promoters P3 and P4-, IGFBP3 downregulation and allelic losses of IGF2R (25% of cases). A gene signature defining IGF-1R activation was developed. Overall, activation of IGF signaling in HCC was significantly associated with mTOR signaling (p=0.035) and was clearly enriched in the Proliferation subclass of the molecular classification of HCC (p=0.001). We also found an inverse correlation between IGF activation and miR-100/miR-216 levels (FDR<0.05). In vitro studies showed that A12-induced abrogation of IGF-1R activation and downstream signaling significantly decreased cell viability and proliferation. In vivo, A12 delayed tumor growth and prolonged survival, reducing proliferation rates and inducing apoptosis. CONCLUSIONS Integrative genomic analysis showed enrichment of activation of IGF signaling in the Proliferation subclass of HCC. Effective blockage of IGF signaling with A12 provides the rationale for testing this therapy in clinical trials.

Notch Signaling Is Activated in Human Hepatocellular Carcinoma and Induces Tumor Formation in Mice

BACKGROUND & AIMS The Notch signaling pathway is activated in leukemia and solid tumors (such as lung cancer), but little is known about its role in liver cancer. METHODS The intracellular domain of Notch was conditionally expressed in hepatoblasts and their progeny (hepatocytes and cholangiocytes) in mice. This was achieved through Cre expression under the control of an albumin and α-fetoprotein (AFP) enhancer and promoter (AFP-Notch intracellular domain [NICD]). We used comparative functional genomics to integrate transcriptome data from AFP-NICD mice and human hepatocellular carcinoma (HCC) samples (n = 683). A Notch gene signature was generated using the nearest template prediction method. RESULTS AFP-NICD mice developed HCC with 100% penetrance when they were 12 months old. Activation of Notch signaling correlated with activation of 3 promoters of insulin-like growth factor 2; these processes appeared to contribute to hepatocarcinogenesis. Comparative functional genomic analysis identified a signature of Notch activation in 30% of HCC samples from patients. These samples had altered expression in Notch pathway genes and activation of insulin-like growth factor signaling, despite a low frequency of mutations in regions of NOTCH1 associated with cancer. Blocking Notch signaling in liver cancer cells with the Notch activation signature using γ-secretase inhibitors or by expressing a dominant negative form of mastermind-like 1 reduced their proliferation in vitro. CONCLUSIONS Notch signaling is activated in human HCC samples and promotes formation of liver tumors in mice. The Notch signature is a biomarker of response to Notch inhibition in vitro.

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.