Monica Santamaria

Amphiregulin Contributes to the Transformed Phenotype of Human Hepatocellular Carcinoma Cells

Hepatocellular carcinoma is a major cause of cancer-related deaths. Current treatments are not effective, and the identification of relevant pathways and novel therapeutic targets are much needed. Increasing evidences point to the activation of the epidermal growth factor receptor (EGFR) as an important mechanism in the development of hepatocarcinoma. We previously described that amphiregulin (AR), a ligand of the EGFR, is not expressed in healthy liver but is up-regulated during chronic liver injury, the background on which most liver tumors develop. Now, we have studied the expression and role of AR in human hepatocarcinoma. AR expression and function was studied in human liver tumors and cell lines. AR is expressed in human hepatocellular carcinoma tissues and cell lines and behaves as a mitogenic and antiapoptotic growth factor for hepatocarcinoma cells. We provide several lines of evidence, including AR silencing by small interfering RNAs and inhibition of amphiregulin by neutralizing antibodies, showing the existence of an AR-mediated autocrine loop that contributes to the transformed phenotype. Indeed, interference with endogenous AR production resulted in reduced constitutive EGFR signaling, inhibition of cell proliferation, anchorage-independent growth, and enhanced apoptosis. Moreover, knockdown of AR potentiated transforming growth factor-beta and doxorubicin-induced apoptosis. Conversely, overexpression of AR in SK-Hep1 cells enhanced their proliferation rate, anchorage-independent growth, drug resistance, and in vivo tumorigenic potential. These observations suggest that AR is involved in the acquisition of neoplastic traits in the liver and thus constitutes a novel therapeutic target in human hepatocarcinoma.

The Epidermal Growth Factor Receptor: A Link Between Inflammation and Liver Cancer

Epidemiological studies have established that many tumours occur in association with persistent inflammation. One clear example of inflammation-related cancer is hepatocellular carcinoma (HCC). HCC slowly unfolds on a background of chronic inflammation triggered by exposure to infectious agents (hepatotropic viruses), toxic compounds (ethanol), or metabolic impairment. The molecular links that connect inflammation and cancer are not completely known, but evidence gathered over the past few years is beginning to define the precise mechanisms. A central role for cytokines such as interleukin-6 (IL-6) and IL-1 (α and β) in liver cancer has been established in experimental models. Besides these inflammatory mediators, mounting evidence points to the dysregulation of specific growth and survival-related pathways in HCC development. Among them is the pathway governed by the epidermal growth factor receptor (EGFR), which can be bound and activated by a broad family of ligands. Of special relevance is the fact that the EGFR engages in extensive crosstalk with other signaling pathways, serving as a “signaling hub” for an increasing list of growth factors, cytokines, and inflammatory mediators. In this review, we summarize the most recent evidences supporting a role for the EGFR system in inflammation-related cell signaling, with special emphasis in liver inflammation and HCC. The molecular dissection of the pathways connecting the inflammatory reaction and neoplasia will facilitate the development of novel and more effective antitumor strategies.

Reference databases for taxonomic assignment in metagenomics

Metagenomics is providing an unprecedented access to the environmental microbial diversity. The amplicon-based metagenomics approach involves the PCR-targeted sequencing of a genetic locus fitting different features. Namely, it must be ubiquitous in the taxonomic range of interest, variable enough to discriminate between different species but flanked by highly conserved sequences, and of suitable size to be sequenced through next-generation platforms. The internal transcribed spacers 1 and 2 (ITS1 and ITS2) of the ribosomal DNA operon and one or more hyper-variable regions of 16S ribosomal RNA gene are typically used to identify fungal and bacterial species, respectively. In this context, reliable reference databases and taxonomies are crucial to assign amplicon sequence reads to the correct phylogenetic ranks. Several resources provide consistent phylogenetic classification of publicly available 16S ribosomal DNA sequences, whereas the state of ribosomal internal transcribed spacers reference databases is notably less advanced. In this review, we aim to give an overview of existing reference resources for both types of markers, highlighting strengths and possible shortcomings of their use for metagenomics purposes. Moreover, we present a new database, ITSoneDB, of well annotated and phylogenetically classified ITS1 sequences to be used as a reference collection in metagenomic studies of environmental fungal communities. ITSoneDB is available for download and browsing at http://itsonedb.ba.itb.cnr.it/.

Methylthioadenosine reverses brain autoimmune disease

To assess the immunomodulatory activity of methylthioadenosine (MTA) in rodent experimental autoimmune encephalomyelitis (EAE) and in patients with multiple sclerosis.

Towards barcode markers in Fungi: an intron map of Ascomycota mitochondria

BackgroundA standardized and cost-effective molecular identification system is now an urgent need for Fungi owing to their wide involvement in human life quality. In particular the potential use of mitochondrial DNA species markers has been taken in account. Unfortunately, a serious difficulty in the PCR and bioinformatic surveys is due to the presence of mobile introns in almost all the fungal mitochondrial genes. The aim of this work is to verify the incidence of this phenomenon in Ascomycota, testing, at the same time, a new bioinformatic tool for extracting and managing sequence databases annotations, in order to identify the mitochondrial gene regions where introns are missing so as to propose them as species markers.MethodsThe general trend towards a large occurrence of introns in the mitochondrial genome of Fungi has been confirmed in Ascomycota by an extensive bioinformatic analysis, performed on all the entries concerning 11 mitochondrial protein coding genes and 2 mitochondrial rRNA (ribosomal RNA) specifying genes, belonging to this phylum, available in public nucleotide sequence databases. A new query approach has been developed to retrieve effectively introns information included in these entries.ResultsAfter comparing the new query-based approach with a blast-based procedure, with the aim of designing a faithful Ascomycota mitochondrial intron map, the first method appeared clearly the most accurate. Within this map, despite the large pervasiveness of introns, it is possible to distinguish specific regions comprised in several genes, including the full NADH dehydrogenase subunit 6 (ND6) gene, which could be considered as barcode candidates for Ascomycota due to their paucity of introns and to their length, above 400 bp, comparable to the lower end size of the length range of barcodes successfully used in animals.ConclusionThe development of the new query system described here would answer the pressing requirement to improve drastically the bioinformatics support to the DNA Barcode Initiative. The large scale investigation of Ascomycota mitochondrial introns performed through this tool, allowing to exclude the introns-rich sequences from the barcode candidates exploration, could be the first step towards a mitochondrial barcoding strategy for these organisms, similar to the standard approach employed in metazoans.

Searching for a needle in the haystack: Comparing six methods to evaluate heteroplasmy in difficult sequence context

Mitochondrial DNA (mtDNA) mutations have been involved in disease, aging and cancer and furthermore exploited for evolutionary and forensic investigation. When investigating mtDNA mutations the peculiar aspects of mitochondrial genetics, such as heteroplasmy and threshold effect, require suitable approaches which must be sensitive enough to detect low-level heteroplasmy and, precise enough to quantify the exact mutational load. In order to establish the optimal approach for the evaluation of heteroplasmy, six methods were experimentally compared for their capacity to reveal and quantify mtDNA variants. Drawbacks and advantages of cloning, Fluorescent PCR (F-PCR), denaturing High Performance Liquid Chromatography (dHPLC), quantitative Real-Time PCR (qRTPCR), High Resolution Melting (HRM) and 454 pyrosequencing were determined. In particular, detection and quantification of a mutation in a difficult sequence context were investigated, through analysis of an insertion in a homopolymeric stretch (m.3571insC).

Towards global interoperability for supporting biodiversity research on essential biodiversity variables (EBVs)

Essential biodiversity variables (EBVs) have been proposed by the Group on Earth Observations Biodiversity Observation Network (GEO BON) to identify a minimum set of essential measurements that are required for studying, monitoring and reporting biodiversity and ecosystem change. Despite the initial conceptualisation, however, the practical implementation of EBVs remains challenging. There is much discussion about the concept and implementation of EBVs: which variables are meaningful; which data are needed and available; at which spatial, temporal and topical scales can EBVs be calculated; and how sensitive are EBVs to variations in underlying data? To advance scientific progress in implementing EBVs we propose that both scientists and research infrastructure operators need to cooperate globally to serve and process the essential large datasets for calculating EBVs. We introduce GLOBIS-B (GLOBal Infrastructures for Supporting Biodiversity research), a global cooperation funded by the Horizon 2020 research and innovation framework programme of the European Commission. The main aim of GLOBIS-B is to bring together biodiversity scientists, global research infrastructure operators and legal interoperability experts to identify the research needs and infrastructure services underpinning the concept of EBVs. The project will facilitate the multi-lateral cooperation of biodiversity research infrastructures worldwide and identify the required primary data, analysis tools, methodologies and legal and technical bottlenecks to develop an agenda for research and infrastructure development to compute EBVs. This requires development of standards, protocols and workflows that are ‘self-documenting’ and openly shared to allow the discovery and analysis of data across large spatial extents and different temporal resolutions. The interoperability of existing biodiversity research infrastructures will be crucial for integrating the necessary biodiversity data to calculate EBVs, and to advance our ability to assess progress towards the Aichi targets for 2020 of the Convention on Biological Diversity (CBD).

Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence‐only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi‐source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter‐ or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi‐source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA‐based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.

Regulation of amphiregulin gene expression by β-catenin signaling in human hepatocellular carcinoma cells: a novel crosstalk between FGF19 and the EGFR system.

Hepatocellular carcinoma (HCC) is the most prevalent liver tumor and a deadly disease with limited therapeutic options. Dysregulation of cell signaling pathways is a common denominator in tumorigenesis, including hepatocarcinogenesis. The epidermal growth factor receptor (EGFR) signaling system is commonly activated in HCC, and is currently being evaluated as a therapeutic target in combination therapies. We and others have identified a central role for the EGFR ligand amphiregulin (AR) in the proliferation, survival and drug resistance of HCC cells. AR expression is frequently up-regulated in HCC tissues and cells through mechanisms not completely known. Here we identify the β-catenin signaling pathway as a novel mechanism leading to transcriptional activation of the AR gene in human HCC cells. Activation of β-catenin signaling, or expression of the T41A β-catenin active mutant, led to the induction of AR expression involving three specific β-catenin-Tcf responsive elements in its proximal promoter. We demonstrate that HCC cells expressing the T41A β-catenin active mutant show enhanced proliferation that is dependent in part on AR expression and EGFR signaling. We also demonstrate here a novel cross-talk of the EGFR system with fibroblast growth factor 19 (FGF19). FGF19 is a recently identified driver gene in hepatocarcinogenesis and an activator of β-catenin signaling in HCC and colon cancer cells. We show that FGF19 induced AR gene expression through the β-catenin pathway in human HCC cells. Importantly, AR up-regulation and EGFR signaling participated in the induction of cyclin D1 and cell proliferation elicited by FGF19. Finally, we demonstrate a positive correlation between FGF19 and AR expression in human HCC tissues, therefore supporting in clinical samples our experimental observations. These findings identify the AR/EGFR system as a key mediator of FGF19 responses in HCC cells involving β-catenin signaling, and suggest that combined targeting of FGF19 and AR/EGFR may enhance therapeutic efficacy.

Nuclear α1-Antichymotrypsin Promotes Chromatin Condensation and Inhibits Proliferation of Human Hepatocellular Carcinoma Cells

BACKGROUND & AIMS α1-Antichymotrypsin (α1-ACT), a member of the serpin family (SERPINA3), is an acute-phase protein secreted by hepatocytes in response to cytokines such as oncostatin M. α1-ACT is a protease inhibitor thought to limit tissue damage produced by excessive inflammation-associated proteolysis. However, α1-ACT also is detected in the nuclei of cells, where its activities are unknown. Expression of α1-ACT is down-regulated in human hepatocellular carcinoma (HCC) tissues and cells; we examined its roles in liver regeneration and HCC proliferation. METHODS We measured levels of α1-ACT messenger RNA in human HCC samples and healthy liver tissue. We reduced levels of α1-ACT using targeted RNA interference in human HCC (HepG2) and mouse hepatocyte (AML12) cell lines, and overexpressed α1-ACT from lentiviral vectors in Huh7 (HCC) cells and adeno-associated viral vectors in livers of mice. We assessed proliferation, differentiation, and chromatin compaction in cultured cells, and liver regeneration and tumor formation in mice. RESULTS Reducing levels of α1-ACT promoted proliferation of HCC cells in vitro. Oncostatin M up-regulated α1-ACT expression and nuclear translocation, which inhibited HCC cell proliferation and activated differentiation of mouse hepatocytes. We identified amino acids required for α1-ACT nuclear localization, and found that α1-ACT inhibits cell-cycle progression and anchorage-independent proliferation of HCC cells. HCC cells that overexpressed α1-ACT formed smaller tumors in mice than HCC cells that did not express the protein. α1-ACT was observed to self-associate and polymerize in the nuclei of cells; nuclear α1-ACT strongly bound chromatin to promote a condensed state that could prevent cell proliferation. CONCLUSIONS α1-ACT localizes to the nuclei of hepatic cells to control chromatin condensation and proliferation. Overexpression of α1-ACT slows the growth of HCC xenograft tumors in nude mice.