Human primary dermal fibroblasts interacting with 3-dimensional matrices for surgical application show specific growth and gene expression programs

Several types of 3-dimensional (3D) biological matrices are employed for clinical and surgical applications, but few indications are available to guide surgeons in the choice among these materials. Here we compare the in vitro growth of human primary fibroblasts on different biological matrices commonly used for clinical and surgical applications and the activation of specific molecular pathways over 30 days of growth. Morphological analyses by Scanning Electron Microscopy and proliferation curves showed that fibroblasts have different ability to attach and proliferate on the different biological matrices. They activated similar gene expression programs, reducing the expression of collagen genes and myofibroblast differentiation markers compared to fibroblasts grown in 2D. However, differences among 3D matrices were observed in the expression of specific metalloproteinases and interleukin-6. Indeed, cell proliferation and expression of matrix degrading enzymes occur in the initial steps of interaction between fibroblast and the investigated meshes, whereas collagen and interleukin-6 expression appear to start later. The data reported here highlight features of fibroblasts grown on different 3D biological matrices and warrant further studies to understand how these findings may be used to help the clinicians choose the correct material for specific applications

The role of the multifaceted long non-coding RNAs: A nuclear-cytosolic interplay to regulate hyaluronan metabolism

In the extracellular matrix (ECM), the glycosaminoglycan (GAG) hyaluronan (HA) has different physiological roles favouring hydration, elasticity and cell survival. Three different isoforms of HA synthases (HAS1, 2, and 3) are responsible for the production of HA. In several pathologies the upregulation of HAS enzymes leads to an abnormal HA accumulation causing cell dedifferentiation, proliferation and migration thus favouring cancer progression, fibrosis and vascular wall thickening. An intriguing new player in HAS2 gene expression regulation and HA production is the long non-coding RNA (lncRNA) hyaluronan synthase 2 antisense 1 (HAS2-AS1). A significant part of mammalian genomes corresponds to genes that transcribe lncRNAs; they can regulate gene expression through several mechanisms, being involved not only in maintaining the normal homeostasis of cells and tissues, but also in the onset and progression of different diseases, as demonstrated by the increasing number of studies published through the last decades. HAS2-AS1 is no exception: it can be localized both in the nucleus and in the cytosol, regulating cancer cells as well as vascular smooth muscle cells behaviour

The hyaluronan-related genes HAS2, HYAL1-4, PH20 and HYALP1 are associated with prognosis, cell viability and spheroid formation capacity in ovarian cancer

Purpose: Hyaluronan modulates tumour progression, including cell adhesion, cohesion, proliferation and invasion, and the cancer stem cell phenotype. In ovarian cancer, high levels of stromal hyaluronan are associated with poor prognosis. In this work, hyaluronan synthases (HAS1-3) and hyaluronidases (HYAL1-4, PH-20, HYALP1) were examined with regard to different levels of gene expression and its influence on ovarian cancer patients’ survival. The impact of a siRNA depletion of HAS2 was investigated in vitro. Methods: Using the Kaplan–Meier Plotter tool, we investigated the influence of hyaluronic synthases and hyaluronidases on the survival of a collective of 1435 ovarian cancer patients. Differences in gene expression between normal (n = 46) and cancerous (n = 744) ovarian tissue were examined using the TNMplot database. Following an evaluation of hyaluronan-related gene expression in the ATCC ovarian cancer panel, we studied SKOV3 and SW 626 ovarian cancer cells subjected to HAS2 siRNA or control siRNA treatment in terms of HAS1-3, HYAL2 and HYAL3 mRNA expression. We investigated the ability to form spheroids using the Hanging Drop method and the response to chemotherapy at different concentrations using the MTT Assay. By STRING analysis, interactions within the enzymes of the hyaluronic acid system and with binding partners were visualized. Results: HAS1, HYAL1 and HYAL4 mRNA expression is significantly upregulated, whereas HAS2, HYAL2 and HYAL3 mRNA expression is significantly downregulated in ovarian cancer tissue compared to controls. HAS2 improves cell viability, the capability to form tumour spheroids and has a negative prognostic value regarding overall survival. Lower HAS2 expression and high expression of HYAL2 and HYAL3 favours the survival of ovarian cancer patients. HAS2 knockdown cells and control cells showed a moderate response to combinatorial in vitro chemotherapy with taxol and cisplatin. Conclusion: In conclusion, our study shows that the hyaluronic acid system has a relevant influence on the survival of ovarian cancer patients and could therefore be considered as a possible prognostic factor

Cell Energy Metabolism and Hyaluronan Synthesis

Hyaluronan (HA) is a linear glycosaminoglycan (GAG) of extracellular matrix (ECM) synthesized by three hyaluronan synthases (HASes) at the plasma membrane using uridine diphosphate (UDP)-glucuronic acid (UDP-GlcUA) and UDP-N-acetylglucosamine (UDP-GlcNAc) as substrates. The production of HA is mainly regulated by hyaluronan synthase 2 (HAS2), that can be controlled at different levels, from epigenetics to transcriptional and post-translational modifications. HA biosynthesis is an energy-consuming process and, along with HA catabolism, is strongly connected to the maintenance of metabolic homeostasis. The cytoplasmic pool of UDP-sugars is critical for HA synthesis. UDP-GlcNAc is an important nutrient sensor and serves as donor substrate for the O-GlcNAcylation of many cytosolic proteins, including HAS2. This post-translational modification stabilizes HAS2 in the membrane and increases HA production. Conversely, HAS2 can be phosphorylated by AMP activated protein kinase (AMPK), a master metabolic regulator activated by low ATP/AMP ratios, which inhibits HA secretion. Similarly, HAS2 expression and the deposition of HA within the pericellular coat are inhibited by sirtuin 1 (SIRT1), another important energetic sensor, confirming the tight connection between nutrients availability and HA metabolism

Thinking Big: Local Food & Large Institutions

This is a panel discussion moderated by Dr. Scott Smith

Hyaluronan in pathophysiology of vascular diseases: specific roles in smooth muscle cells, endothelial cells, and macrophages

One of the main components of the extracellular matrix (ECM) of blood vessels is hyaluronic acid or hyaluronan (HA). It is a ubiquitous polysaccharide belonging to the family of glycosaminoglycans, but, differently from other proteoglycan-associated glycosaminoglycans, it is synthesized on the plasma membrane by a family of three HA synthases (HAS). HA can be released as a free polymer in the extracellular space or remain associated with the plasma membrane in the pericellular space via HAS or HA-binding proteins. Several cell surface proteins can interact with HA working as HA receptors, like CD44, RHAMM, and LYVE-1. In physiological conditions, HA is localized in the glycocalyx and the adventitia where it is responsible for the loose and hydrated vascular structure favoring flexibility and allowing the stretching of vessels in response to mechanical forces. During atherogenesis, ECM undergoes dramatic alterations that have a crucial role in lipoprotein retention and in triggering multiple signaling cascades that induce the cells to exit from their quiescent status. HA becomes highly present in the media and neointima favoring smooth muscle cells dedifferentiation, migration, and proliferation that strongly contribute to vessel wall thickening. Furthermore, HA is able to modulate immune cell recruitment both within the vessel wall and on the endothelial cell layer. This review is focused on deeply analyzing the effects of HA on vascular cell behavior

Inflammation, extracellular matrix remodeling, and proteostasis in tumor microenvironment

Cancer is a multifaceted and complex pathology characterized by uncontrolled cell proliferation and decreased apoptosis. Most cancers are recognized by an inflammatory environment rich in a myriad of factors produced by immune infiltrate cells that induce host cells to differentiate and to produce a matrix that is more favorable to tumor cells\u2019 survival and metastasis. As a result, the extracellular matrix (ECM) is changed in terms of macromolecules content, degrading enzymes, and proteins. Altered ECM components, derived from remodeling processes, interact with a variety of surface receptors triggering intracellular signaling that, in turn, cancer cells exploit to their own benefit. This review aims to present the role of different aspects of ECM components in the tumor microenvironment. Particularly, we highlight the effect of pro-and inflammatory factors on ECM degrading enzymes, such as metalloproteases, and in a more detailed manner on hyaluronan metabolism and the signaling pathways triggered by the binding of hyaluronan with its receptors. In addition, we sought to explore the role of extracellular chaperones, especially of clusterin which is one of the most prominent in the extracellular space, in proteostasis and signaling transduction in the tumor microenvironment. Although the described tumor microenvironment components have different biological roles, they may engage common signaling pathways that favor tumor growth and metastasis

Revisiting the hallmarks of cancer: The role of hyaluronan

Extracellular matrix (ECM) is a complex network of macromolecules such as proteoglycans (PGs), glycosaminoglycans (GAGs) and fibrous proteins present within all tissues and organs. The main role of ECM is not only to provide an essential mechanical scaffold for the cells but also to mediate crucial biochemical cues that are required for tissue homeostasis. Dysregulations in ECM deposition alter cell microenvironment, triggering the onset or the rapid progression of several diseases, including cancer. Hyaluronan (HA) is a ubiquitous component of ECM considered as one of the main players of cancer initiation and progression. This review discusses how HA participate in and regulate several aspects of tumorigenesis, with particular attention to the hallmarks of cancer proposed by Hanahan and Weinberg such as sustaining of the proliferative signaling, evasion of apoptosis, angiogenesis, activation of invasion and metastases, reprogramming of energy metabolism and evasion of immune response

Ha and hs changes in endothelial inflammatory activation

Cardiovascular diseases are a group of disorders caused by the presence of a combination of risk factors, such as tobacco use, unhealthy diet and obesity, physical inactivity, etc., which cause the modification of the composition of the vessel’s matrix and lead to the alteration of blood flow, matched with an inflammation condition. Nevertheless, it is not clear if the inflammation is a permissive condition or a consequent one. In order to investigate the effect of inflammation on the onset of vascular disease, we treated endothelial cells with the cytokine TNF-α that is increased in obese patients and is reported to induce cardiometabolic diseases. The inflammation induced a large change in the extracellular matrix, increasing the pericellular hyaluronan and altering the heparan sulfate Syndecans sets, which seems to be related to layer permeability but does not influence cell proliferation or migration nor induce blood cell recruitment or activation

InterpolatiON of InSAR Time series for the dEtection of ground deforMatiOn eVEnts (ONtheMOVE): application to slow-moving landslides

The aim of this work is to develop an innovative methodology to analyse the time series (TS) of interferometric satellite data. TS are important tools for the ground displacement monitoring, mostly in areas in which in situ instruments are scarce. The proposed methodology allows to classify the trend of TS in three classes (uncorrelated, linear, non-linear) and to obtain the parameters of non-linear time series to characterise the magnitude and timing of changes of ground instabilities. These parameters are the beginning and end of the non-linear deformation break(s), the length of the event(s) in days, and the quantification of the cumulative displacement in mm. The methodology was tested on two Sentinel- 1 datasets (2014–2020) covering the Alpine and Apennine sectors of the Piemonte region, an area prone to slow-moving slope instabilities. The results were validated at the basin scale (Pellice-Chisone and Piota basin) and at a local scale (Brenvetto, Champlas du Col and Casaleggio Boiro landslides) comparing with in situ monitoring system measurements, possible triggering factors (rainfall, snow) and already-collected events of the territory. The good correlation of the results has proven that the methodology can be a useful tool to local and regional authorities for risk planning and management of the area, also in terms of near real-time monitoring of the territory both at local and regional scale