Final Report Summary - HEPTROMIC (Genomic predictors and oncogenic drivers in hepatocellular carcinoma)
Executive Summary:
HEPTROMIC is a translational research project aiming to solve core problems in the management of hepatocellular carcinoma. HEPTROMIC’s core team comprises leading European researchers in the basic, translational and clinical fields of liver cancer. Our aim was to lay down a foundation for a sustainable network of expertise in liver cancer, identifying new genomic predictors and oncogenic drivers of liver cancer and incorporating these research findings in innovative predictive tools that would contribute to better allocate resources in the clinical scene as well as to refine therapeutic strategies. Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide. It is a major health problem due to its dismal survival rates, its increasing incidence (more than 780,000 new cases per year worldwide, of which 70,000 occur in Europe). The main risk factors for HCC are chronic hepatitis (B and C) and alcohol abuse leading to cirrhosis, a true pre-neoplastic condition. HCC is resistant to conventional chemotherapy and, thus, there is a clear need for novel primary systemic therapies for this difficult-to-treat neoplasm. Since molecular therapies could be pivotal in this setting, HEPTROMIC has been essential to improve the understanding of the molecular determinants for HCC development and progression. Novel high-throughput genomic technologies have allowed the identification of crucial molecular subclasses with different prognostic implications, and secondly, the identification of key genetic and epigenetic drivers of specific subclasses which will now enable development of more personalised treatment algorithms.
A tissue bank composed of 637 samples from 270 patients, with tumour, cirrhotic counterparts and normal livers was collected and annotated with clinical variables. Samples were analysed at the transcriptomic level (mRNA and miRNA) and data was used to develop a composite prognostic model for HCC recurrence, based on gene expression patterns in tumour and adjacent tissues (Villanueva et al, Gastroenterology 2011). Gene signatures were generated and predicted early and overall recurrence in patients with HCC, and complemented
findings from clinical and pathology analyses (Villanueva et al, Gastroenterology 2011). Strikingly, genomic information from the adjacent non-tumoral cirrhotic tissue also provided prognostic information and complemented the information of tumour signatures. In addition, a 5-gene score, based on mRNA data was associated with disease specific survival times of patients with resected HCC. In multivariate analyses, the 5-gene score was associated with disease-specific survival, independent of other clinical and pathology feature of HCC. Disease specific survival was also predicted by combining data on microvascular invasion, the Barcelona Clinic Liver Cancer classification system. Combining the 5-gene score with the expression pattern of 186 genes in corresponding cirrhotic tissues increased its prognostic accuracy (Nault et al., Gastroenterology 2013). miRNA profiling enabled further characterization of the poor-prognosis subclass, and enabled the identification of 4 different groups of patients that overlapped with mRNA-based classes (Toffanin et al. Gastroenterology 2011). One of these subclasses (C3, 7% of patients), defined by coherent overexpression of 20 snoRNAs, was associated with higher early recurrence (Wang et al. PNAS 2012). Analysis of the methylation status of 225 HCC and 136 non-tumoral adjacent paired samples and 14 controls from non-cirrhotic livers allowed the generation of an externally validated methylation signature based on 36 probes that retained independent prognostic capacity of survival along with multinodularity and platelet count. Moreover, patients with this methylation profile harboured mRNA-based signatures indicating tumours with progenitor cell features (Villanueva et al., Hepatology 2014, submitted). Moreover, massive parallel sequencing unravelled the mutational landscape of HCC. We showed that TERT promoter (59%), CTNNB1 (32%), P53 (21%), and AXIN1 (15%) were altered in HCC. ARID1A and ARID2 were also frequently altered. Other genes were rarely mutated; CDKN2A (8%), HNF1alpha (4%), KRAS (1.6%), PIK3CA (1.6%), and GP130 (1.6%) (Guichard et al., Nature Genetics, 2012; Nault et al., Nature Communications 2013). In addition, we delivered in vitro and in vivo data supporting a role of the IGF pathway in hepatocarcinogenesis, and showed that IGF2 blockage by a novel anti-IGF therapy results in a decrease of cell viability, providing the rationale for exploring IGF2 as target of therapies in pre-clinical and early clinical studies in HCC (manuscript in preparation). Finally, first steps were performed in order to step towards effective and efficient clinical translation through by exploring robust methylation-based assays for the design of prognostic devices.
Project Context and Objectives:
The HEPTROMIC context
The HEPTROMIC project, which has received a funding boost from the European Commission’s FP7, has been a 3.5 years translational research initiative designed to solve core problems in the treatment of hepatocellular carcinoma (HCC). The project was planned to make step change advances in the field by defining biomarkers for identification of HCC patients with poor-prognosis and novel genetic or epigenetic drivers which would be critical for a more personalized therapeutic approach. Findings obtained from human tissue samples applying high-end technology have been confirmed using sophisticated experimental models and translation into novel biomarkers and targets for high impact clinical use is currently ongoing.
Epidemiological impact and lethality of the disease: HCC is the 2nd cause of cancer-related mortality and represents a major health problem due to its dismal survival rates. The incidence of the disease is increasing with more than 780,000 new cases per year worldwide, of which 70,000 occur in Europe (www.globocan.iarc.fr). Unlike most solid tumors, cancer-related death due to HCC has significantly increased in the last decade. Overall, less than 30% of newly diagnosed HCC patients are eligible for potentially curative therapies such as resection, liver transplantation and local ablation. Major scientific breakthroughs are urgently needed to improve the life expectancy of patients suffering this cancer.
Relevance of understanding the molecular biology of this cancer: Only one molecular therapy, sorafenib, have been able to improve patient’s outcome and represents the dawn of a new era in the treatment approach to this cancer. Indeed, this major advancement underscored the importance of understanding the key molecular drivers of HCC and has effectively changed the landscape of translational research in the field. Nowadays, a number of molecular compounds are moving to late clinical developmental phases, clearly highlighting several unmet needs remaining in the primary and adjuvant settings. Accurate prediction of patient’s outcome based on tumor molecular singularities is likely to further improve the selection of candidates for molecular therapies.
Technological revolution in oncological sciences has the potential to produce a step change advance in treatment of HCC: The last decade has witnessed a revolution in the way scientists characterize the human genome. These advances resulted from an exponential increase in the throughput capacity of new genomic technologies such as next-generation sequencing. The whole genome is currently accessible for thorough scrutiny. The vast amount of information generated requires integrated approaches within a systems biology framework. Since HCC remained largely unaddressed before HEPTROMIC, the project brought into the liver cancer field such innovative and complex approaches.
Preliminary steps in personalized management of HCC: Two major advancements could critically improve the outcome of patients with liver cancer: Firstly, the identification of crucial molecular subclasses with different prognostic implications. Secondly, the identification of key genetic or epigenetic drivers of specific subclasses will enable development of more personalized treatment algorithms. Both challenges are bounded by the complexity of the molecular basis of HCC and HEPTROMIC was designed to overcome these limitations and open a new range of management options.
The HEPTROMIC objectives
OBJECTIVE 1: Genomic characterization of poor prognosis subclass of hepatocellular carcinoma.
The first HEPTROMIC objective was to define the molecular subclass of poor prognosis in patients with early HCC through integrated analysis of mRNA, miRNA and methylome profiles. The characterization, at the molecular level, of patients with poor prognosis would enable to significantly improve prognostic prediction and current staging systems in order to optimize candidate selection for treatments.
This objective directly assessing the topics of the call to which the HEPTROMIC project was addressed, “validating better therapeutic strategies that increase patient survival” and “consortia should include clinical expertise to guarantee a clinical proof of principle” (HEALTH 2010.2.4.1-6) and “assessment of prognostic interventions” (HEALTH 2010 2.4.1).
HEPTROMIC has been a translational collaborative project aiming to identify transcriptomic predictors of poor outcome (i.e. tumor recurrence or death) in patients with early HCC treated with surgical resection by using an extensive tissue bank of 1,140 samples from 900 HCC patients following a training-validation scheme. To identify the poor prognostic subclass, HEPTROMIC has conducted genome-wide scrutiny of gene expression (WP1) and epigenomic alterations (WP2) using array-based profiling both in tumor and non-tumoral adjacent cirrhotic tissue. Prof. Llovet (Project Coordinator, Partner 1) and Mazzaferro (Partner 5) collected all samples, and have been responsible for tissue banking management and generation of the clinical annotated database. Experience in transcriptomic data mining was secured by Prof. Llovet’s and Prof. Golub’s (Partner 6) research background.
In addition, HEPTROMIC has obtained the whole-genome portrait of DNA methylation implications in HCC prognosis. Prof. Esteller (Partner 3) has been responsible for WP2 and contributed with his worldwide-recognized expertise in epigenomics. Prof. Esteller’s team has used high-end technology, which has been validated using ultra-deep sequencing in collaboration with the SME Diagenode (Partner 7).
OBJECTIVE 2: Identify driver oncogenic events as potential treatment targets.
The second HEPTROMIC objective was to identify novel driver oncogenic events by massive parallel sequencing and kinase phosphorylation profiling of human HCC samples and validation of the oncogenic loops in sophisticated experimental models. This objective addressed to the topics of the call by testing “molecular findings in innovative cancer models closely mimicking the disease” (HEALTH 2010.2.4.1.6) and “identification and validation of drug targets” (HEALTH 2010. 2.4.1).
Identification of driver oncogenic events has been accomplished by using deep sequencing and tyrosine kinase profiling. HEPTROMIC has identified new somatic mutations in tumor suppressors and oncogenes from those samples defining the worst prognostic HCC subclass. Among genes newly identified as mutated, candidates for functional validation were selected and their role was analyzed in tumorigenesis and in response to targeted therapies. The originality of this approach was to combine a genome wide sequencing analysis of the human coding sequences together with an enrichment of the sequencing on chromosome regions recurrently gained or deleted in HCC. The partners involved in this task included Prof. Zucman-Rossi (Partner 2) who leads an internationally recognized group at INSERM.
Poor-prognostic tumors are likely to harbor activation of multiple kinases, most of which were never explored in HCC. For this purpose, HEPTROMIC’s objective was to use the technology developed by Dr. Golub’s team a method based on multiplexed coupling of kinase-specific antibodies to polystyrene microspheres-beads. This platform allows assessment of the tyrosine phosphorylation status of kinases of the human kinome, and was applied to assess 62 kinases in 80 samples of patients with poor-prognosis. Recurrent events were planned to be validated in a set of 120 FFPE-HCC using immunohistochemistry. Prof. Llovet and Prof. Golub’s team (latter on led by Yujin Hoshida) lead data analysis and interpretation.
Those candidate mutations and kinases with potential beneficial impact in HCC therapeutics had been planned to be functionally validate in sophisticated animal models that allow for efficient in vivo modeling of complex genetic lesions by Prof Zender (Partner 4). Prof. Zender provided his strong expertise in HCC cancer mosaic mouse modeling and functional oncogenomics. siRNA strategies were launched in chimaeric mice to investigate the therapeutic relevance of the drivers identified. Based on these models, cross species oncogenomic comparison were planned to establish new algorithms for accelerated cancer gene discovery in HCC. These innovative cancer models closely mimicking the disease allow scientists to evaluate therapeutic response to specific blockade of oncogene activation. Exploratory efforts were also planned to pinpoint biomarkers of response in these animals.
OBJECTIVE 3: Design of prognostic devices for clinical translation.
The third HEPTROMIC objective was to achieve effective and efficient clinical translation through the design of prognostic devices to significantly improve prognosis assessment and therapeutic decision-making. This objective addressed the topics of the call by “contribute to reduce cancer mortality and improving quality of life” (HEALTH 2010. 2.4.1) and also with the general objective of the FP7 Work Programme-Health 2010: “to increase the competitiveness and innovative capacity of European health-related industries and businesses”.
Once molecular determinants of HCC poor prognosis and driver oncogenic loops were identified and validated, efforts were planned to be focused in translating these findings into routine clinical management. At this point, two European-based SMEs (Diagenode and TcLand Expression) had to provide their services for design, production and delivery of tools for prognosis assessment and prediction of response to drug treatments. Diagenode’s (Partner 7) main focus was to develop cutting-edge products that advance research in the rapidly evolving field of epigenetics. TcLand Expression (Partner 8) had to provide complementary skills and should have been involved in transcriptomic technology transfer.
Project Results:
This section summarises the major scientific contributions generated from each work package (WP) during the HEPTROMIC project.
After completion of the tissue bank collection, which included 637 samples from 270 patients, with tumour, cirrhotic counterparts and normal livers, and respective annotation of the patients with clinical variables, samples were characterized at the transcriptomic level (WP1, Transcriptome analysis: mRNA and miRNA). Genomic profiling was performed using whole-genome last-generation devices from Affymetrix. Analysis included integrative prognostic prediction and combination of mRNA and miRNA information to improve prognosis-based molecular classification. In addition, data were integrated with previous studies conducted in the HCC Genomic consortium in molecular profiling and classification of primary liver cancer including a total of 665 patients. Transcriptome profiling enabled the identification of HCC patients with poor prognosis, approximately 30% of the whole patient population. Poor prognosis gene signatures from the tumour (e.g. Proliferation class, G3, EpCAM) were significantly associated with recurrence after surgery (Villanueva et al, Gastroenterology 2011). Despite the fact that the genes defining these signatures were different, they were all capturing similar background biological signals related to aggressive tumour behaviour. Strikingly, genomic information from the adjacent non-tumoral cirrhotic tissue also provided prognostic information and complemented the information of tumour signatures. In addition, a 5-gene score, based on mRNA data was associated with disease specific survival times of patients with resected HCC. In multivariate analyses, the 5-gene score was associated with disease-specific survival, independent of other clinical and pathology feature of HCC. Disease specific survival was also predicted by combining data on microvascular invasion, the Barcelona Clinic Liver Cancer classification system. Combining the 5-gene score with the expression pattern of 186 genes in corresponding cirrhotic tissues increased its prognostic accuracy (Nault et al., Gastroenterology 2013). In summary, patient stratification based on combined genomic profiling of tumor and adjacent non-tumor cirrhotic tissue enabled the identification of HCC with poor prognosis.
Also the microRNA data showed prognosis value. miR-16a was able to predict early recurrence of HCC in the Heptromic cohort (data not published). Moreover, miRNA profiling enabled further characterization of the poor-prognosis subclass, and in fact, it enabled the identification of 4 different groups of patients that overlapped with mRNA-based classes (Toffanin et al. Gastroenterology 2011). One of these subclasses (C3, 7% of patients), defined by coherent overexpression of 20 snoRNAs, was associated with higher early recurrence (Wang et al. PNAS 2012).
We next assessed the methylation profile in HCC (WP2: Epigenetic analysis: DNA methylome). Analysis of 225 HCC and 136 non-tumoral adjacent paired samples and 14 controls from non-cirrhotic livers were performed using next generation methylation platforms (Infinium HumanMethylation450). Methylation data was correlated here with transcriptomic data and clinical data. This integrative analysis allowed the generation of a methylation signature based on 36 probes that retained independent prognostic capacity of survival along with multinodularity and platelet count. Moreover, patients with this methylation profile harboured mRNA-based signatures indicating tumours with progenitor cell features. The study confirmed a high prevalence of genes known de-regulated by aberrant methylation in hepatocellular carcinoma (i.e. RASSF1, IGF2, APC) and other solid tumours (i.e NOTCH3), and described potential candidate epidrivers (i.e SEPT9, EFNB2). The prediction power of this signature was validated in an independent cohort. (Villanueva et al., Hepatologu 2014, submitted).
Massive parallel sequencing (WP3) to unravel the mutational landscape of HCC through a catalogue of somatic mutations identified by exome sequencing and regional sequencing, was been performed. 230 HCC samples in total have been analysed by exome sequencing, 50 samples from the Heptromic cohort corresponding to aggressive clinical behaviour, and 180 samples from the French ICGC consortium. Master genes recurrently mutated were further validated by Sanger sequencing and CGH-SNP in a validation cohort of 125 HCC. This analysis demonstrated that CTNNB1 (32%), P53 (21%), and AXIN1 (15%) were altered and mutually exclusive. ARID1A and ARID2 were also frequently altered. Some genes were more rarely mutated in HCC; CDKN2A (8%), HNF1alpha (4%), KRAS (1.6%), PIK3CA (1.6%), and GP130 (1.6%) (Guichard et al., Nature Genetics, 2012). We identified somatic mutations of the TERT promoter in 179 (59%) among 305 human hepatocellular carcinomas. These mutations were localized at the two hot spot previously described in melanoma (-124G>A and -146G>A from the ATG site). TERT promoter mutations were significantly associated with CTNNB1 mutations and were more frequent in small HCC (< 5cm), with low serum AFP level and non-related to chronic HBV infection. TERT expression was significantly higher in HCC with TERT promoter mutations compared to normal liver and cirrhosis (Nault et al., Nature Communications 2013). Nowadays, the landscape of genomic alterations in HCC (Figures 1 and 2) treated surgically is completed by the sequencing analysis of a large series of HCC (manuscript in preparation). In summary, we have provided the first extensive characterization of HCC at the mutational level, and have identified novel HCC driver genes.
Since tumors are likely to harbor activation of multiple kinases, we performed a kinome profiling from 191 HCC samples (WP4: Kinome phosphorylation profiling). Most samples showed only a limited number of phosphorylation events, and only 13/80 kinases were activated in more than 25% of samples: IGFR1, FGFR4, EGFR, JAK1, HCK, NTRK1, LCK, ERBB3, PTK6, SYK, YES1 or YWHAZ. Activation of some kinases was enriched in specific molecular classes: IGFR1 in the proliferation class (Chiang, Cancer Res 2008, P<0.001); JAK1 and SYK in non-proliferation subclasses (P<0.001); EGFR in the Poly7 class (P<0.05). As predicted, HCC samples with phosphorylation of EGFR and IGFR in the kinome map showed induction of experimentally defined respective gene signatures (P<0.01) indicating that the kinome profiles recapitulate signaling pathway activation. The signaling pathway associated to the IGF1R identified kinase has been further characterized. We showed that the IGF axis is activated in 21% of HCC and that several molecular alterations such as IGF2 overexpression or IGFBP3 down-regulation was significant in HCC (Tovar et al., 2010). We also characterized the IFG pathway activation in Heptromic cohort and identified 12% of IGF2 overexpression, accompanied by a 28% of IGF1R kinase activation (data from the kinome profile) and 43% of pIGF1R signature activation. We also provided in vivo data (WP5) supporting a role of the IGF pathway in hepatocarcinogenesis. In summary, our data point towards IGF2 as potential oncogene in HCC mouse model and as key driver of IGF signaling activation. We also showed that IGF2 blockage by a novel anti-IGF therapy results in a decrease of cell viability. Our study provides the rationale for exploring IGF2 as target of therapies in pre-clinical and early clinical studies in HCC (results accepted as oral presentation at ILCA Annual Meeting, Kyoto 2014. Manuscript in preparation).
To functionally validate gene candidates and assess their oncogenic/tumour suppressor properties in HCC, sophisticated animal models were generated (WP5: Modelling HCC in vivo). Aurora A kinase (AURKA) came up as a hit in an in vivo RNAi screen aiming to identify new tumor suppressor genes whose loss facilitate Ras-driven hepatocarcinogenesis from hepatocytes with altered p53 function. AURKA was one of the marker genes that define the Proliferation class of the molecular classification (WP1). Murine livers overexpressing IGF2 or IGFR1 were generated in a c-myc/Akt background HCC model. These mouse models overexpressing IGF2 or IGFR1 exclusively in the liver presented liver tumorigenesis and lower survival rates. Mice overexpressing IGF2 showed increased number of tumors, and significantly reduced survival (p=0.02) compared to those with the c-myc/Akt alone. These results demonstrate the IGF2 oncogenic properties in HCC mouse model (manuscript in preparation). In the next future, these innovative cancer models closely mimicking the disease will allow us to evaluate therapeutic response to specific blockade of oncogene activation. Future exploratory efforts will also point to biomarkers of response in these animals.
The Heptromic consortium highlighted a signature of 36 CpGs differentially methylated, predictors of poor prognosis among patients with hepatocellular carcinoma. Based on that list of biomarkers, the SME Diagenode has made efforts to design a robust assay (WP6: Design of prognostic devices) to set the basis for the later development of a diagnostic kit for quick prognosis in patients. That part of the project was initially supposed to be conducted in collaboration with TCland, a company expert in the development of diagnostic tools. In May 2013, TCland filed for bankruptcy, leaving Diagenode on its own. Though extensive analysis have been performed, the variability of the methylation status of the other CpGs in the sequence, did not allow to obtain solid results in this WP. Risks and benefits of other methods allowing the design of a diagnostic device were assessed. At this point we envision that additional efforts will need to be put together in order to further develop this assay.
Potential Impact:
The HEPTROMIC project has had a range of impacts during the project which will continue to change the HCC field well beyond the project’s life. The immediate impacts of the project are:
Improve prognosis prediction: HEPTROMIC has provided molecular poor-prognosis identifiers that are ready to be included in clinical-based staging systems and change the current paradigm that guides decision-making in HCC, which is solely based in clinical variables. We expect that refining the risk stratification of patients according to solid biomarkers will lead to a direct improvement in outcome and resource allocation in the following areas, altogether aimed to ultimately reducing patient mortality
-Implementation of adjuvant therapies after potentially curatives procedures.
-Risk stratification of patients in clinical trials according to tumour aggressiveness.
-Improvements in the cost-benefit perspective of HCC candidates for liver transplantation.
Discovery of potential oncogenic addictive loops: The benefits of selective blockade of oncogenic addiction loops have been already demonstrated in other malignancies. However, no loop had been yet identified in HCC. HEPTROMIC has provided evidences suggesting that IGF-pathway genes might cause oncogenic addiction. One therapeutic treatments blocking the IGF axis is currently being tested and would validate this result. Moreover, by better refining the targets for therapies with the comprehensive high-throughput approach performed within the HEPTROMIC project, should ultimately lead to gains in life expectancy. Long-term implications of this finding will be to lead the field towards a more personalized and cost-effective medicine by tailoring cancer therapies to specific patients subclasses.
Provide innovative cancer models mimicking the disease: Our consortium brought together state of the art profiling platforms that enable the interrogation of human HCC oncogenomes, kinomes and epigenomes with cutting-edge HCC mouse modeling and in vivo RNAi technology. This has enabled the reverse-translation of clinical observations into innovative cancer models closely mimicking the disease while validating better therapeutic strategies. Establishing novel experimental models for drug testing in HCC research will be crucial for drug testing in the future.
In the years following the end of the HEPTROMIC project the results will have the following impacts:
Optimize treatment allocation policies in cancer: Misleading prognosis predictions lead to inadequate therapeutic decisions. HETROMIC results will allow tackling these inaccuracies. HEPTROMIC will contribute providing novel prognostic tools and introducing sophisticated animal models pivotal for the validation of drug targets and treatment biomarkers as well as on assessment of preventive and therapeutic interventions. Appropriate selection of therapeutic interventions according to individual risk of recurrence or death will ultimately improve quality of life and care with fewer side-effects to patients.
Identify cancer at-risk populations in cirrhotic patients: Despite the fact that in Europe more than 80% of HCC arise on cirrhotic livers, there were no clear genomic-based tools to identify patients at-risk factors for tumor development in this population. HEPTROMIC has pushed forward the knowledge in this area and has identified genomic determinants of tumor recurrence (poor prognosis) potentially amenable for translation in the secondary prevention setting. This data will now allow exploring chemopreventive strategies in cirrhotic patients, and clear the path for reducing cancer incidence in this target population. We believe it will be possible in the medium term to extrapolate this genomic information to other inflammation-related cancers such as colorectal cancer in ulcerative colitis or pancreatic cancer in chronic pancreatitis.
In the longer term and in the wider research, treatment and product innovation fields the impacts of HEPTROMIC will be:
Establish a European network of excellence in liver cancer research. HEPTROMIC brought together the leading EU researchers in the basic, translational and clinical field of liver cancer, and contributed in establishing nodes of future networks for innovative, system-level approaches in this and closely related disease areas. HEPTROMIC laid down the foundations for sustainable networks of expertise based on complex, system level, translational research approaches, which we expect to open up new research horizons over the next decade.
Integration of genomic and clinical data using a translational approach. The integration of genomic data and clinical data will help to address the key challenge of providing tools for translational research in the field of cancer. HEPTROMIC has linked all stakeholders in the ‘triple helix’ of researchers, clinicians and business/regulators in the field of liver cancer, and has demonstrated to other project teams working on similarly complex diseases, how translational work can be done effectively and simply.
SME-relevant research leading to the development of commercial prototypes for clinical translation. We expect that HEPTROMIC-identified prognostic biomarkers and novel drivers will lead to the development of onco-chips and/or devices through partnership between academy and industry. Hence, our consortium has experienced and brought down to reality the first steps towards the development of commercial devices for clinical translation.
Regarding the exploitation and dissemination of the HEPTROMIC project, different dissemination activities have been promoted and are detailed in section A (4.2.1) from 4.2 Use and Dissemination of Foreground.
List of Websites:
The project web page is: http://www.heptromic.eu
HEPTROMIC is a translational research project aiming to solve core problems in the management of hepatocellular carcinoma. HEPTROMIC’s core team comprises leading European researchers in the basic, translational and clinical fields of liver cancer. Our aim was to lay down a foundation for a sustainable network of expertise in liver cancer, identifying new genomic predictors and oncogenic drivers of liver cancer and incorporating these research findings in innovative predictive tools that would contribute to better allocate resources in the clinical scene as well as to refine therapeutic strategies. Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide. It is a major health problem due to its dismal survival rates, its increasing incidence (more than 780,000 new cases per year worldwide, of which 70,000 occur in Europe). The main risk factors for HCC are chronic hepatitis (B and C) and alcohol abuse leading to cirrhosis, a true pre-neoplastic condition. HCC is resistant to conventional chemotherapy and, thus, there is a clear need for novel primary systemic therapies for this difficult-to-treat neoplasm. Since molecular therapies could be pivotal in this setting, HEPTROMIC has been essential to improve the understanding of the molecular determinants for HCC development and progression. Novel high-throughput genomic technologies have allowed the identification of crucial molecular subclasses with different prognostic implications, and secondly, the identification of key genetic and epigenetic drivers of specific subclasses which will now enable development of more personalised treatment algorithms.
A tissue bank composed of 637 samples from 270 patients, with tumour, cirrhotic counterparts and normal livers was collected and annotated with clinical variables. Samples were analysed at the transcriptomic level (mRNA and miRNA) and data was used to develop a composite prognostic model for HCC recurrence, based on gene expression patterns in tumour and adjacent tissues (Villanueva et al, Gastroenterology 2011). Gene signatures were generated and predicted early and overall recurrence in patients with HCC, and complemented
findings from clinical and pathology analyses (Villanueva et al, Gastroenterology 2011). Strikingly, genomic information from the adjacent non-tumoral cirrhotic tissue also provided prognostic information and complemented the information of tumour signatures. In addition, a 5-gene score, based on mRNA data was associated with disease specific survival times of patients with resected HCC. In multivariate analyses, the 5-gene score was associated with disease-specific survival, independent of other clinical and pathology feature of HCC. Disease specific survival was also predicted by combining data on microvascular invasion, the Barcelona Clinic Liver Cancer classification system. Combining the 5-gene score with the expression pattern of 186 genes in corresponding cirrhotic tissues increased its prognostic accuracy (Nault et al., Gastroenterology 2013). miRNA profiling enabled further characterization of the poor-prognosis subclass, and enabled the identification of 4 different groups of patients that overlapped with mRNA-based classes (Toffanin et al. Gastroenterology 2011). One of these subclasses (C3, 7% of patients), defined by coherent overexpression of 20 snoRNAs, was associated with higher early recurrence (Wang et al. PNAS 2012). Analysis of the methylation status of 225 HCC and 136 non-tumoral adjacent paired samples and 14 controls from non-cirrhotic livers allowed the generation of an externally validated methylation signature based on 36 probes that retained independent prognostic capacity of survival along with multinodularity and platelet count. Moreover, patients with this methylation profile harboured mRNA-based signatures indicating tumours with progenitor cell features (Villanueva et al., Hepatology 2014, submitted). Moreover, massive parallel sequencing unravelled the mutational landscape of HCC. We showed that TERT promoter (59%), CTNNB1 (32%), P53 (21%), and AXIN1 (15%) were altered in HCC. ARID1A and ARID2 were also frequently altered. Other genes were rarely mutated; CDKN2A (8%), HNF1alpha (4%), KRAS (1.6%), PIK3CA (1.6%), and GP130 (1.6%) (Guichard et al., Nature Genetics, 2012; Nault et al., Nature Communications 2013). In addition, we delivered in vitro and in vivo data supporting a role of the IGF pathway in hepatocarcinogenesis, and showed that IGF2 blockage by a novel anti-IGF therapy results in a decrease of cell viability, providing the rationale for exploring IGF2 as target of therapies in pre-clinical and early clinical studies in HCC (manuscript in preparation). Finally, first steps were performed in order to step towards effective and efficient clinical translation through by exploring robust methylation-based assays for the design of prognostic devices.
Project Context and Objectives:
The HEPTROMIC context
The HEPTROMIC project, which has received a funding boost from the European Commission’s FP7, has been a 3.5 years translational research initiative designed to solve core problems in the treatment of hepatocellular carcinoma (HCC). The project was planned to make step change advances in the field by defining biomarkers for identification of HCC patients with poor-prognosis and novel genetic or epigenetic drivers which would be critical for a more personalized therapeutic approach. Findings obtained from human tissue samples applying high-end technology have been confirmed using sophisticated experimental models and translation into novel biomarkers and targets for high impact clinical use is currently ongoing.
Epidemiological impact and lethality of the disease: HCC is the 2nd cause of cancer-related mortality and represents a major health problem due to its dismal survival rates. The incidence of the disease is increasing with more than 780,000 new cases per year worldwide, of which 70,000 occur in Europe (www.globocan.iarc.fr). Unlike most solid tumors, cancer-related death due to HCC has significantly increased in the last decade. Overall, less than 30% of newly diagnosed HCC patients are eligible for potentially curative therapies such as resection, liver transplantation and local ablation. Major scientific breakthroughs are urgently needed to improve the life expectancy of patients suffering this cancer.
Relevance of understanding the molecular biology of this cancer: Only one molecular therapy, sorafenib, have been able to improve patient’s outcome and represents the dawn of a new era in the treatment approach to this cancer. Indeed, this major advancement underscored the importance of understanding the key molecular drivers of HCC and has effectively changed the landscape of translational research in the field. Nowadays, a number of molecular compounds are moving to late clinical developmental phases, clearly highlighting several unmet needs remaining in the primary and adjuvant settings. Accurate prediction of patient’s outcome based on tumor molecular singularities is likely to further improve the selection of candidates for molecular therapies.
Technological revolution in oncological sciences has the potential to produce a step change advance in treatment of HCC: The last decade has witnessed a revolution in the way scientists characterize the human genome. These advances resulted from an exponential increase in the throughput capacity of new genomic technologies such as next-generation sequencing. The whole genome is currently accessible for thorough scrutiny. The vast amount of information generated requires integrated approaches within a systems biology framework. Since HCC remained largely unaddressed before HEPTROMIC, the project brought into the liver cancer field such innovative and complex approaches.
Preliminary steps in personalized management of HCC: Two major advancements could critically improve the outcome of patients with liver cancer: Firstly, the identification of crucial molecular subclasses with different prognostic implications. Secondly, the identification of key genetic or epigenetic drivers of specific subclasses will enable development of more personalized treatment algorithms. Both challenges are bounded by the complexity of the molecular basis of HCC and HEPTROMIC was designed to overcome these limitations and open a new range of management options.
The HEPTROMIC objectives
OBJECTIVE 1: Genomic characterization of poor prognosis subclass of hepatocellular carcinoma.
The first HEPTROMIC objective was to define the molecular subclass of poor prognosis in patients with early HCC through integrated analysis of mRNA, miRNA and methylome profiles. The characterization, at the molecular level, of patients with poor prognosis would enable to significantly improve prognostic prediction and current staging systems in order to optimize candidate selection for treatments.
This objective directly assessing the topics of the call to which the HEPTROMIC project was addressed, “validating better therapeutic strategies that increase patient survival” and “consortia should include clinical expertise to guarantee a clinical proof of principle” (HEALTH 2010.2.4.1-6) and “assessment of prognostic interventions” (HEALTH 2010 2.4.1).
HEPTROMIC has been a translational collaborative project aiming to identify transcriptomic predictors of poor outcome (i.e. tumor recurrence or death) in patients with early HCC treated with surgical resection by using an extensive tissue bank of 1,140 samples from 900 HCC patients following a training-validation scheme. To identify the poor prognostic subclass, HEPTROMIC has conducted genome-wide scrutiny of gene expression (WP1) and epigenomic alterations (WP2) using array-based profiling both in tumor and non-tumoral adjacent cirrhotic tissue. Prof. Llovet (Project Coordinator, Partner 1) and Mazzaferro (Partner 5) collected all samples, and have been responsible for tissue banking management and generation of the clinical annotated database. Experience in transcriptomic data mining was secured by Prof. Llovet’s and Prof. Golub’s (Partner 6) research background.
In addition, HEPTROMIC has obtained the whole-genome portrait of DNA methylation implications in HCC prognosis. Prof. Esteller (Partner 3) has been responsible for WP2 and contributed with his worldwide-recognized expertise in epigenomics. Prof. Esteller’s team has used high-end technology, which has been validated using ultra-deep sequencing in collaboration with the SME Diagenode (Partner 7).
OBJECTIVE 2: Identify driver oncogenic events as potential treatment targets.
The second HEPTROMIC objective was to identify novel driver oncogenic events by massive parallel sequencing and kinase phosphorylation profiling of human HCC samples and validation of the oncogenic loops in sophisticated experimental models. This objective addressed to the topics of the call by testing “molecular findings in innovative cancer models closely mimicking the disease” (HEALTH 2010.2.4.1.6) and “identification and validation of drug targets” (HEALTH 2010. 2.4.1).
Identification of driver oncogenic events has been accomplished by using deep sequencing and tyrosine kinase profiling. HEPTROMIC has identified new somatic mutations in tumor suppressors and oncogenes from those samples defining the worst prognostic HCC subclass. Among genes newly identified as mutated, candidates for functional validation were selected and their role was analyzed in tumorigenesis and in response to targeted therapies. The originality of this approach was to combine a genome wide sequencing analysis of the human coding sequences together with an enrichment of the sequencing on chromosome regions recurrently gained or deleted in HCC. The partners involved in this task included Prof. Zucman-Rossi (Partner 2) who leads an internationally recognized group at INSERM.
Poor-prognostic tumors are likely to harbor activation of multiple kinases, most of which were never explored in HCC. For this purpose, HEPTROMIC’s objective was to use the technology developed by Dr. Golub’s team a method based on multiplexed coupling of kinase-specific antibodies to polystyrene microspheres-beads. This platform allows assessment of the tyrosine phosphorylation status of kinases of the human kinome, and was applied to assess 62 kinases in 80 samples of patients with poor-prognosis. Recurrent events were planned to be validated in a set of 120 FFPE-HCC using immunohistochemistry. Prof. Llovet and Prof. Golub’s team (latter on led by Yujin Hoshida) lead data analysis and interpretation.
Those candidate mutations and kinases with potential beneficial impact in HCC therapeutics had been planned to be functionally validate in sophisticated animal models that allow for efficient in vivo modeling of complex genetic lesions by Prof Zender (Partner 4). Prof. Zender provided his strong expertise in HCC cancer mosaic mouse modeling and functional oncogenomics. siRNA strategies were launched in chimaeric mice to investigate the therapeutic relevance of the drivers identified. Based on these models, cross species oncogenomic comparison were planned to establish new algorithms for accelerated cancer gene discovery in HCC. These innovative cancer models closely mimicking the disease allow scientists to evaluate therapeutic response to specific blockade of oncogene activation. Exploratory efforts were also planned to pinpoint biomarkers of response in these animals.
OBJECTIVE 3: Design of prognostic devices for clinical translation.
The third HEPTROMIC objective was to achieve effective and efficient clinical translation through the design of prognostic devices to significantly improve prognosis assessment and therapeutic decision-making. This objective addressed the topics of the call by “contribute to reduce cancer mortality and improving quality of life” (HEALTH 2010. 2.4.1) and also with the general objective of the FP7 Work Programme-Health 2010: “to increase the competitiveness and innovative capacity of European health-related industries and businesses”.
Once molecular determinants of HCC poor prognosis and driver oncogenic loops were identified and validated, efforts were planned to be focused in translating these findings into routine clinical management. At this point, two European-based SMEs (Diagenode and TcLand Expression) had to provide their services for design, production and delivery of tools for prognosis assessment and prediction of response to drug treatments. Diagenode’s (Partner 7) main focus was to develop cutting-edge products that advance research in the rapidly evolving field of epigenetics. TcLand Expression (Partner 8) had to provide complementary skills and should have been involved in transcriptomic technology transfer.
Project Results:
This section summarises the major scientific contributions generated from each work package (WP) during the HEPTROMIC project.
After completion of the tissue bank collection, which included 637 samples from 270 patients, with tumour, cirrhotic counterparts and normal livers, and respective annotation of the patients with clinical variables, samples were characterized at the transcriptomic level (WP1, Transcriptome analysis: mRNA and miRNA). Genomic profiling was performed using whole-genome last-generation devices from Affymetrix. Analysis included integrative prognostic prediction and combination of mRNA and miRNA information to improve prognosis-based molecular classification. In addition, data were integrated with previous studies conducted in the HCC Genomic consortium in molecular profiling and classification of primary liver cancer including a total of 665 patients. Transcriptome profiling enabled the identification of HCC patients with poor prognosis, approximately 30% of the whole patient population. Poor prognosis gene signatures from the tumour (e.g. Proliferation class, G3, EpCAM) were significantly associated with recurrence after surgery (Villanueva et al, Gastroenterology 2011). Despite the fact that the genes defining these signatures were different, they were all capturing similar background biological signals related to aggressive tumour behaviour. Strikingly, genomic information from the adjacent non-tumoral cirrhotic tissue also provided prognostic information and complemented the information of tumour signatures. In addition, a 5-gene score, based on mRNA data was associated with disease specific survival times of patients with resected HCC. In multivariate analyses, the 5-gene score was associated with disease-specific survival, independent of other clinical and pathology feature of HCC. Disease specific survival was also predicted by combining data on microvascular invasion, the Barcelona Clinic Liver Cancer classification system. Combining the 5-gene score with the expression pattern of 186 genes in corresponding cirrhotic tissues increased its prognostic accuracy (Nault et al., Gastroenterology 2013). In summary, patient stratification based on combined genomic profiling of tumor and adjacent non-tumor cirrhotic tissue enabled the identification of HCC with poor prognosis.
Also the microRNA data showed prognosis value. miR-16a was able to predict early recurrence of HCC in the Heptromic cohort (data not published). Moreover, miRNA profiling enabled further characterization of the poor-prognosis subclass, and in fact, it enabled the identification of 4 different groups of patients that overlapped with mRNA-based classes (Toffanin et al. Gastroenterology 2011). One of these subclasses (C3, 7% of patients), defined by coherent overexpression of 20 snoRNAs, was associated with higher early recurrence (Wang et al. PNAS 2012).
We next assessed the methylation profile in HCC (WP2: Epigenetic analysis: DNA methylome). Analysis of 225 HCC and 136 non-tumoral adjacent paired samples and 14 controls from non-cirrhotic livers were performed using next generation methylation platforms (Infinium HumanMethylation450). Methylation data was correlated here with transcriptomic data and clinical data. This integrative analysis allowed the generation of a methylation signature based on 36 probes that retained independent prognostic capacity of survival along with multinodularity and platelet count. Moreover, patients with this methylation profile harboured mRNA-based signatures indicating tumours with progenitor cell features. The study confirmed a high prevalence of genes known de-regulated by aberrant methylation in hepatocellular carcinoma (i.e. RASSF1, IGF2, APC) and other solid tumours (i.e NOTCH3), and described potential candidate epidrivers (i.e SEPT9, EFNB2). The prediction power of this signature was validated in an independent cohort. (Villanueva et al., Hepatologu 2014, submitted).
Massive parallel sequencing (WP3) to unravel the mutational landscape of HCC through a catalogue of somatic mutations identified by exome sequencing and regional sequencing, was been performed. 230 HCC samples in total have been analysed by exome sequencing, 50 samples from the Heptromic cohort corresponding to aggressive clinical behaviour, and 180 samples from the French ICGC consortium. Master genes recurrently mutated were further validated by Sanger sequencing and CGH-SNP in a validation cohort of 125 HCC. This analysis demonstrated that CTNNB1 (32%), P53 (21%), and AXIN1 (15%) were altered and mutually exclusive. ARID1A and ARID2 were also frequently altered. Some genes were more rarely mutated in HCC; CDKN2A (8%), HNF1alpha (4%), KRAS (1.6%), PIK3CA (1.6%), and GP130 (1.6%) (Guichard et al., Nature Genetics, 2012). We identified somatic mutations of the TERT promoter in 179 (59%) among 305 human hepatocellular carcinomas. These mutations were localized at the two hot spot previously described in melanoma (-124G>A and -146G>A from the ATG site). TERT promoter mutations were significantly associated with CTNNB1 mutations and were more frequent in small HCC (< 5cm), with low serum AFP level and non-related to chronic HBV infection. TERT expression was significantly higher in HCC with TERT promoter mutations compared to normal liver and cirrhosis (Nault et al., Nature Communications 2013). Nowadays, the landscape of genomic alterations in HCC (Figures 1 and 2) treated surgically is completed by the sequencing analysis of a large series of HCC (manuscript in preparation). In summary, we have provided the first extensive characterization of HCC at the mutational level, and have identified novel HCC driver genes.
Since tumors are likely to harbor activation of multiple kinases, we performed a kinome profiling from 191 HCC samples (WP4: Kinome phosphorylation profiling). Most samples showed only a limited number of phosphorylation events, and only 13/80 kinases were activated in more than 25% of samples: IGFR1, FGFR4, EGFR, JAK1, HCK, NTRK1, LCK, ERBB3, PTK6, SYK, YES1 or YWHAZ. Activation of some kinases was enriched in specific molecular classes: IGFR1 in the proliferation class (Chiang, Cancer Res 2008, P<0.001); JAK1 and SYK in non-proliferation subclasses (P<0.001); EGFR in the Poly7 class (P<0.05). As predicted, HCC samples with phosphorylation of EGFR and IGFR in the kinome map showed induction of experimentally defined respective gene signatures (P<0.01) indicating that the kinome profiles recapitulate signaling pathway activation. The signaling pathway associated to the IGF1R identified kinase has been further characterized. We showed that the IGF axis is activated in 21% of HCC and that several molecular alterations such as IGF2 overexpression or IGFBP3 down-regulation was significant in HCC (Tovar et al., 2010). We also characterized the IFG pathway activation in Heptromic cohort and identified 12% of IGF2 overexpression, accompanied by a 28% of IGF1R kinase activation (data from the kinome profile) and 43% of pIGF1R signature activation. We also provided in vivo data (WP5) supporting a role of the IGF pathway in hepatocarcinogenesis. In summary, our data point towards IGF2 as potential oncogene in HCC mouse model and as key driver of IGF signaling activation. We also showed that IGF2 blockage by a novel anti-IGF therapy results in a decrease of cell viability. Our study provides the rationale for exploring IGF2 as target of therapies in pre-clinical and early clinical studies in HCC (results accepted as oral presentation at ILCA Annual Meeting, Kyoto 2014. Manuscript in preparation).
To functionally validate gene candidates and assess their oncogenic/tumour suppressor properties in HCC, sophisticated animal models were generated (WP5: Modelling HCC in vivo). Aurora A kinase (AURKA) came up as a hit in an in vivo RNAi screen aiming to identify new tumor suppressor genes whose loss facilitate Ras-driven hepatocarcinogenesis from hepatocytes with altered p53 function. AURKA was one of the marker genes that define the Proliferation class of the molecular classification (WP1). Murine livers overexpressing IGF2 or IGFR1 were generated in a c-myc/Akt background HCC model. These mouse models overexpressing IGF2 or IGFR1 exclusively in the liver presented liver tumorigenesis and lower survival rates. Mice overexpressing IGF2 showed increased number of tumors, and significantly reduced survival (p=0.02) compared to those with the c-myc/Akt alone. These results demonstrate the IGF2 oncogenic properties in HCC mouse model (manuscript in preparation). In the next future, these innovative cancer models closely mimicking the disease will allow us to evaluate therapeutic response to specific blockade of oncogene activation. Future exploratory efforts will also point to biomarkers of response in these animals.
The Heptromic consortium highlighted a signature of 36 CpGs differentially methylated, predictors of poor prognosis among patients with hepatocellular carcinoma. Based on that list of biomarkers, the SME Diagenode has made efforts to design a robust assay (WP6: Design of prognostic devices) to set the basis for the later development of a diagnostic kit for quick prognosis in patients. That part of the project was initially supposed to be conducted in collaboration with TCland, a company expert in the development of diagnostic tools. In May 2013, TCland filed for bankruptcy, leaving Diagenode on its own. Though extensive analysis have been performed, the variability of the methylation status of the other CpGs in the sequence, did not allow to obtain solid results in this WP. Risks and benefits of other methods allowing the design of a diagnostic device were assessed. At this point we envision that additional efforts will need to be put together in order to further develop this assay.
Potential Impact:
The HEPTROMIC project has had a range of impacts during the project which will continue to change the HCC field well beyond the project’s life. The immediate impacts of the project are:
Improve prognosis prediction: HEPTROMIC has provided molecular poor-prognosis identifiers that are ready to be included in clinical-based staging systems and change the current paradigm that guides decision-making in HCC, which is solely based in clinical variables. We expect that refining the risk stratification of patients according to solid biomarkers will lead to a direct improvement in outcome and resource allocation in the following areas, altogether aimed to ultimately reducing patient mortality
-Implementation of adjuvant therapies after potentially curatives procedures.
-Risk stratification of patients in clinical trials according to tumour aggressiveness.
-Improvements in the cost-benefit perspective of HCC candidates for liver transplantation.
Discovery of potential oncogenic addictive loops: The benefits of selective blockade of oncogenic addiction loops have been already demonstrated in other malignancies. However, no loop had been yet identified in HCC. HEPTROMIC has provided evidences suggesting that IGF-pathway genes might cause oncogenic addiction. One therapeutic treatments blocking the IGF axis is currently being tested and would validate this result. Moreover, by better refining the targets for therapies with the comprehensive high-throughput approach performed within the HEPTROMIC project, should ultimately lead to gains in life expectancy. Long-term implications of this finding will be to lead the field towards a more personalized and cost-effective medicine by tailoring cancer therapies to specific patients subclasses.
Provide innovative cancer models mimicking the disease: Our consortium brought together state of the art profiling platforms that enable the interrogation of human HCC oncogenomes, kinomes and epigenomes with cutting-edge HCC mouse modeling and in vivo RNAi technology. This has enabled the reverse-translation of clinical observations into innovative cancer models closely mimicking the disease while validating better therapeutic strategies. Establishing novel experimental models for drug testing in HCC research will be crucial for drug testing in the future.
In the years following the end of the HEPTROMIC project the results will have the following impacts:
Optimize treatment allocation policies in cancer: Misleading prognosis predictions lead to inadequate therapeutic decisions. HETROMIC results will allow tackling these inaccuracies. HEPTROMIC will contribute providing novel prognostic tools and introducing sophisticated animal models pivotal for the validation of drug targets and treatment biomarkers as well as on assessment of preventive and therapeutic interventions. Appropriate selection of therapeutic interventions according to individual risk of recurrence or death will ultimately improve quality of life and care with fewer side-effects to patients.
Identify cancer at-risk populations in cirrhotic patients: Despite the fact that in Europe more than 80% of HCC arise on cirrhotic livers, there were no clear genomic-based tools to identify patients at-risk factors for tumor development in this population. HEPTROMIC has pushed forward the knowledge in this area and has identified genomic determinants of tumor recurrence (poor prognosis) potentially amenable for translation in the secondary prevention setting. This data will now allow exploring chemopreventive strategies in cirrhotic patients, and clear the path for reducing cancer incidence in this target population. We believe it will be possible in the medium term to extrapolate this genomic information to other inflammation-related cancers such as colorectal cancer in ulcerative colitis or pancreatic cancer in chronic pancreatitis.
In the longer term and in the wider research, treatment and product innovation fields the impacts of HEPTROMIC will be:
Establish a European network of excellence in liver cancer research. HEPTROMIC brought together the leading EU researchers in the basic, translational and clinical field of liver cancer, and contributed in establishing nodes of future networks for innovative, system-level approaches in this and closely related disease areas. HEPTROMIC laid down the foundations for sustainable networks of expertise based on complex, system level, translational research approaches, which we expect to open up new research horizons over the next decade.
Integration of genomic and clinical data using a translational approach. The integration of genomic data and clinical data will help to address the key challenge of providing tools for translational research in the field of cancer. HEPTROMIC has linked all stakeholders in the ‘triple helix’ of researchers, clinicians and business/regulators in the field of liver cancer, and has demonstrated to other project teams working on similarly complex diseases, how translational work can be done effectively and simply.
SME-relevant research leading to the development of commercial prototypes for clinical translation. We expect that HEPTROMIC-identified prognostic biomarkers and novel drivers will lead to the development of onco-chips and/or devices through partnership between academy and industry. Hence, our consortium has experienced and brought down to reality the first steps towards the development of commercial devices for clinical translation.
Regarding the exploitation and dissemination of the HEPTROMIC project, different dissemination activities have been promoted and are detailed in section A (4.2.1) from 4.2 Use and Dissemination of Foreground.
List of Websites:
The project web page is: http://www.heptromic.eu