Andrea Bernini
@unisi.it
Dept. of Biotechnology, Chemistry and Pharmacy
University of Siena
RESEARCH INTERESTS
Current research involves the proteomics and metabolomics studies of diseases such as the ultra-rare metabolic disorder Alkaptonuria, the rare malignancies soft tissue sarcomas, steroid converting enzymes linked diseases such as lipedema and lymphedema, by use of NMR, MS, and computational methods.
Scopus Publications
Scopus Publications
J. Kaftalli, G. Bonetti, G. Marceddu, K. Dhuli, P. E. Maltese, K. Donato, K. L. Herbst, S. Michelini, P. Chiurazzi, M. Hill,et al.
OBJECTIVE
Lipedema is an autosomal dominant genetic disease that mainly affects women. It is characterized by excess deposition of subcutaneous adipose tissue, pain, and anxiety. The genetic and environmental etiology of lipedema is still largely unknown. Although considered a rare disease, this pathology has been suggested to be underdiagnosed or misdiagnosed as obesity or lymphedema. Steroid hormones seem to be involved in the pathogenesis of lipedema. Indeed, aldo-keto reductase family 1 member C1 (AKR1C1), a gene coding for a protein involved in steroid hormones metabolism, was the first proposed to be correlated with lipedema.
PATIENTS AND METHODS
In this study, we employed a molecular dynamics approach to assess the pathogenicity of AKR1C1 genetic variants found in patients with lipedema. Moreover, we combined information theory and structural bioinformatics to identify AKR1C1 polymorphisms from the gnomAD database that could predispose to the development of lipedema.
RESULTS
Three genetic variants in AKR1C1 found in patients with lipedema were disruptive to the protein's function. Furthermore, eight AKR1C1 variants found in the general population could predispose to the development of lipedema.
CONCLUSIONS
The results of this study provide evidence that AKR1C1 may be a key gene in lipedema pathogenesis, and that common polymorphisms could predispose to lipedema development.
Gabriele Bonetti, William Cozza, Andrea Bernini, Jurgen Kaftalli, Chiara Mareso, Francesca Cristofoli, Maria Chiara Medori, Leonardo Colombo, Salvatore Martella, Giovanni Staurenghi,et al.
MDPI AG
Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGRORF15, aiding in the correct annotation of genetic variants in online databases.
M. Medori, C. Micheletti, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli, D. Generali, C. A. Donofrio, M. Cominetti, A. Fioravanti,et al.
Abstract
In the last decade, Prostate Cancer (PCa) has emerged as the second most prevalent and serious medical condition, and is considered one of the leading factors contributing to global mortality rates. Several factors (genetic as well as environmental) contribute to its development and seriousness. Since the disease is usually asymptomatic at early stages, it is typically misdiagnosed or over-diagnosed by the diagnostic procedures currently in use, leading to improper treatment. Effective biomarkers and diagnostic techniques are desperately needed in clinical settings for better management of PCa patients. Studies integrating omics sciences have shown that the accuracy and dependability of diagnostic and prognostic evaluations have increased because of the use of omics data; also, the treatment plans using omics can be facilitated by personalized medicine. The present review emphasizes innovative multi-omics methodologies, encompassing proteomics, genomics, microbiomics, metabolomics, and transcriptomics, with the aim of comprehending the molecular alterations that trigger and contribute to PCa. The review shows how early genomic and transcriptomic research has made it possible to identify PCa-related genes that are controlled by tumor-relevant signaling pathways. Proteomic and metabolomic analyses have recently been integrated, advancing our understanding of the complex mechanisms at play, the multiple levels of regulation, and how they interact. By applying the omics approach, new vulnerabilities may be discovered, and customized treatments with improved efficacy will soon be accessible.
G. Bonetti, K. Donato, K. Dhuli, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli, D. Generali, C. A. Donofrio, M. Cominetti,et al.
Background
Sarcomas are a relatively rare but diverse group of cancers that typically develop in the mesenchymal cells of bones and soft tissues. Occurring in more than 70 subtypes, sarcomas have broad histological presentations, posing significant challenges of prognosis and treatment. Modern multi-omics studies, which include genomics, proteomics, metabolomics, and micro-biomics, are vital to understand the underlying mechanisms of sarcoma development and progression, identify molecular biomarkers for early detection, develop personalized treatment plans, and discover drug resistance mechanisms in sarcomas to upsurge the survival rate.
Aim
This study aims to highlight the genetic risk factors responsible for sarcoma-genesis, and to present a comprehensive review of multi-omics studies about sarcoma.
Methods
Extensive literature research was undertaken using reliable and authentic medical journals, e-books, and online cancer research databases. Mendelian inheritance in man database (OMIM) was explored to study particular genes and their loci that are responsible to cause various sarcomas.
Result
This in-depth research led to the finding out that omics studies provide a more comprehensive understanding of underlying molecular mechanisms of sarcomas. Through genomics, we can reveal genetic alterations that predispose to sarcoma, like mutation in TP53, NF1, and so on. Pharmacogenomics enable us to find molecular targets for specific drugs. Whereas, proteomic and metabolomic studies provide insights into the biological pathways involved in sarcoma development and progression.
Conclusion
Future advancements in omics sciences for sarcoma are on the cutting-edge of defining precision treatment plans and improved resilience of sarcoma patients.
C. Micheletti, G. Bonetti, G. Madeo, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli, D. Generali, C. A. Donofrio, M. Cominetti,et al.
Abstract
Glioblastoma is a highly aggressive and malignant type of brain cancer with a poor prognosis, despite current treatment options of surgery, radiation therapy, and chemotherapy. These treatments have limitations due to the aggressive nature of the cancer and the difficulty in completely removing the tumor without damaging healthy brain tissue. Personalized medicine, using genomic profiling to tailor treatment to the patient's specific tumor, and immunotherapy have shown promise in clinical trials. The blood-brain barrier also poses a challenge in delivering treatments to the brain, and researchers are exploring various approaches to bypass it. More effective, personalized treatment approaches are needed to improve outcomes for glioblastoma patients. This tumor is studied using genomics, transcriptomics, and proteomics techniques, to better understand its underlying molecular mechanisms. Recent studies have used these techniques to identify potential therapeutic targets, molecular subtypes, and heterogeneity of tumor cells. Advancements in omics sciences have improved our understanding of glioblastoma biology, and precision medicine approaches have impli-cations for more accurate diagnoses, improved treatment outcomes, and personalized preventive care. Precision medicine can match patients with drugs that target specific genetic mutations, improve clinical trials, and identify individuals at higher risk for certain diseases. Precision medicine, which involves customizing medical treatment based on an individual's genetic makeup, lifestyle, and environmental factors, has shown promise in improving treatment outcomes for glioblastoma patients. Identifying biomarkers is essential for patient stratification and treatment selection in precision medicine approaches for glioblastoma, and several biomarkers have shown promise in predicting patient response to treatment. Targeted therapies are a key component of precision medicine approaches in glioblastoma, but there is still a need to improve their effectiveness. Technical challenges, such as sample quality and availability, and challenges in analyzing and interpreting large amounts of data remain significant obstacles in omics sciences and precision medicine for glioblastoma. The clinical implementation of precision medicine in glioblastoma treatment faces challenges related to patient selection, drug development, and clinical trial design, as well as ethical and legal considerations related to patient privacy, informed consent, and access to expensive treatments.
C. Micheletti, K. Dhuli, K. Donato, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli, D. Generali, C. A. Donofrio, M. Cominetti,et al.
Abstract
Lung cancer is a complex disease, with a wide range of genetic alterations and clinical presentations. Understanding the natural and clinical history of the disease is crucial for developing effective diagnostic and treatment strategies. Omics approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools for understanding the molecular mechanisms underlying lung cancer and for identifying novel biomarkers and therapeutic targets. These approaches enable researchers to examine the entire genome, transcriptome, proteome, or metabolome of a cell or tissue, providing a comprehensive view of the biological processes involved in lung cancer development and progression. Targeted therapies that address specific genetic mutations and pathways hold promise for improving the diagnosis and treatment of this disease.
G. Madeo, G. Bonetti, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli, D. Generali, C. A. Donofrio, M. Cominetti, A. Fioravanti,et al.
Abstract
Colon cancer presents a complex pathophysiological landscape, which poses a significant challenge to the precise prediction of patient prognosis and treatment response. However, the emergence of omics sciences such as genomics, transcriptomics, proteomics, and metabolomics has provided powerful tools to identify molecular alterations and pathways involved in colon cancer development and progression. To address the lack of literature exploring the intersection of omics sciences, precision medicine, and colon cancer, we conducted a comprehensive search in ScienceDirect and PubMed databases. We included systematic reviews, reviews, case studies, clinical studies, and randomized controlled trials that were published between 2015-2023. To refine our search, we excluded abstracts and non-English studies. This review provides a comprehensive summary of the current understanding of the latest developments in precision medicine and omics sciences in the context of colon cancer. Studies have identified molecular subtypes of colon cancer based on genomic and transcrip-tomic profiles, which have implications for prognosis and treatment selection. Furthermore, precision medicine (which involves tailoring treatments, based on the unique molecular characteristics of each patient's tumor) has shown promise in improving outcomes for colon cancer patients. Omics sciences and precision medicine hold great promise for identifying new therapeutic targets and developing more effective treatments for colon cancer. Although not strictly designed as a systematic review, this review provides a readily accessible and up-to-date summary of the latest developments in the field, highlighting the challenges and opportunities for future research.
G. Bonetti, G. Madeo, S. Michelini, M. Ricci, M. Cestari, S. Michelini, M. Gadler, S. Benedetti, G. Guerri, F. Cristofoli,et al.
Background
Human breast carcinoma is a complex disease, affecting 1 in 8 women worldwide. The seriousness of the disease increases when the definite cause of the disease remains obscure, thus making prognosis challenging. Researchers are emphasizing on adapting more advanced and targeted therapeutic approaches to address the multifaceted impacts of the disease. Hence, modern multi-omics systems have gained popularity among clinicians, as they offer insights into the genomic, pharmacogenomic, metabolomic, and microbiomic factors, thus allowing researchers to develop targeted and personalized approaches for breast cancer prevention and early detection, and eventually improving patient outcomes.
Aim
The primary focus of this study is to elucidate, through the integration of multi-omics research findings, the inherent molecular origins of diverse subtypes of breast cancer and to evaluate the effectiveness of these findings in reducing breast cancer-related mortalities.
Methods
Thorough investigation was conducted by reviewing reputable and authoritative medical journals, e-books, and online databases dedicated to cancer research. The Mendelian inheritance in man database (OMIM) was used to scrutinize specific genes and their respective loci associated with the development of different types of breast cancer.
Results
Our present research revealed the holistic picture of sundry molecular, genomic, pharmacogenomic, metabolomic, and microbiomic features of breast cancer. Such findings, like genetic alterations in highly penetrant genes, plus metabolomic and microbiomic signatures of breast cancer, unveil valuable insights and show great potential for multi-omics research in breast oncology.
Conclusion
Further research in omics sciences pertaining to breast cancer are at the forefront of shaping precise treatment and bolstering patient survival.
Rossella Cannarella, Carmelo Gusmano, Rosita A. Condorelli, Andrea Bernini, Jurgen Kaftalli, Paolo Enrico Maltese, Stefano Paolacci, Astrit Dautaj, Giuseppe Marceddu, Matteo Bertelli,et al.
MDPI AG
Congenital hypogonadotropic hypogonadism (cHH)/Kallmann syndrome (KS) is a rare genetic disorder with variable penetrance and a complex inheritance pattern. Consequently, it does not always follow Mendelian laws. More recently, digenic and oligogenic transmission has been recognized in 1.5–15% of cases. We report the results of a clinical and genetic investigation of five unrelated patients with cHH/KS analyzed using a customized gene panel. Patients were diagnosed according to the clinical, hormonal, and radiological criteria of the European Consensus Statement. DNA was analyzed using next-generation sequencing with a customized panel that included 31 genes. When available, first-degree relatives of the probands were also analyzed to assess genotype–phenotype segregation. The consequences of the identified variants on gene function were evaluated by analyzing the conservation of amino acids across species and by using molecular modeling. We found one new pathogenic variant of the CHD7 gene (c.576T>A, p.Tyr1928) and three new variants of unknown significance (VUSs) in IL17RD (c.960G>A, p.Met320Ile), FGF17 (c.208G>A, p.Gly70Arg), and DUSP6 (c.434T>G, p.Leu145Arg). All were present in the heterozygous state. Previously reported heterozygous variants were also found in the PROK2 (c.163del, p.Ile55*), CHD7 (c.c.2750C>T, p.Thr917Met and c.7891C>T, p.Arg2631*), FLRT3 (c.1106C>T, p.Ala369Val), and CCDC103 (c.461A>C, p.His154Pro) genes. Molecular modeling, molecular dynamics, and conservation analyses were performed on three out of the nine variants identified in our patients, namely, FGF17 (p.Gly70Arg), DUSP6 (p.Leu145Arg), and CHD7 p.(Thr917Met). Except for DUSP6, where the L145R variant was shown to disrupt the interaction between β6 and β3, needed for extracellular signal-regulated kinase 2 (ERK2) binding and recognition, no significant changes were identified between the wild-types and mutants of the other proteins. We found a new pathogenic variant of the CHD7 gene. The molecular modeling results suggest that the VUS of the DUSP6 (c.434T>G, p.Leu145Arg) gene may play a role in the pathogenesis of cHH. However, our analysis indicates that it is unlikely that the VUSs for the IL17RD (c.960G>A, p.Met320Ile) and FGF17 (c.208G>A, p.Gly70Arg) genes are involved in the pathogenesis of cHH. Functional studies are needed to confirm this hypothesis.
Daniela Grasso, Silvia Galderisi, Annalisa Santucci, and Andrea Bernini
MDPI AG
Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases. Small molecules like these bind poorly folded proteins similarly to physiological chaperones, bridging non-covalent interactions (hydrogen bonds, electrostatic interactions, and van der Waals contacts) loosened or lost due to mutations. Pharmacological chaperone development involves, among other things, structural biology investigation of the target protein and its misfolding and refolding. Such research can take advantage of computational methods at many stages. Here, we present an up-to-date review of the computational structural biology tools and approaches regarding protein stability evaluation, binding pocket discovery and druggability, drug repurposing, and virtual ligand screening. The tools are presented as organized in an ideal workflow oriented at pharmacological chaperones’ rational design, also with the treatment of rare diseases in mind.
J. Kaftalli, K. Donato, G. Bonetti, K. Dhuli, A. Macchia, P. E. Maltese, K. Louise Herbst, S. Michelini, P. Chiurazzi, M. Hill,et al.
OBJECTIVE
Lipedema is a debilitating chronic condition predominantly affecting women, characterized by the abnormal accumulation of fat in a symmetrical, bilateral pattern in the extremities, often coinciding with hormonal imbalances.
PATIENTS AND METHODS
Despite the conjectured role of sex hormones in its etiology, a definitive link has remained elusive. This study explores the case of a patient possessing a mutation deletion within the C-terminal region of Aldo-keto reductases Member C2 (AKR1C2), Ser320PheTer2, that could lead to heightened enzyme activity. A cohort of 19 additional lipedema patients and 2 additional affected family members14 were enrolled in this study. The two additional affected family members are relatives of the patient with the AKR1C1 L213Q variant, which is included in the 19 cohorts and described in literature.
RESULTS
Our investigation revealed that AKR1C2 was overexpressed, as quantified by qPCR, in 5 out of 21 (24%) lipedema patients who did not possess mutations in the AKR1C2 gene. Collectively, these findings implicate AKR1C2 in the pathogenesis of lipedema, substantiating its causative role.
CONCLUSIONS
This study demonstrates that the activating mutation in the enzyme or its overexpression is a causative factor in the development of lipedema. Further exploration and replication in diverse populations will bolster our understanding of this significant connection.
J. Kaftalli, A. Bernini, G. Bonetti, S. Cristoni, G. Marceddu and M. Bertelli
Molecular docking simulation of small molecule drugs to macromolecules is valuable in structural biology and medicinal chemistry research. Its spread is supported by freely available software and databases. Like many resources in the free domain, docking software is command-line based, which comes to a limitation when defining the volume encompassing an active site, the so-called docking box. The box center and size, usually specified as cartesian coordinates, can be adjusted to correctly cover the active site only with a third-party molecular graphics program compatible with the docking input/output files, which reduces the choice to a few options. Moreover, the additional staff training may hamper the adoption of such software, e.g., in an enterprise environment. We exposed the functionality of Autodock and Autodock Vina into a graphical user interface extending upon that of PyMOL. Both the functionality of PyMOL and Autodock are merged, synergizing the capabilities of each program. To overcome such limitations, here we present MAGI-Dock. This graphical user interface combines the power of two of the most used free software for docking and graphics, Autodock Vina and PyMOL. MAGI-Dock is a free open-source software available under the GPL and can be downloaded from https://github.com/gjonwick/MAGI-Dock. The coupling of Autodock Vina with PyMOL through a graphical interface removes the molecular modeling limitations that come with Autodock. Therefore, MAGI-Dock could be conducive to lowering the learning curve for molecular docking simulation, with benefits for trainees in both academia and enterprise environments.
Annalisa Santucci, Andrea Bernini, and Ottavia Spiga
Bentham Science Publishers Ltd.
Abstract: Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs, which occurs because the homogentisate 1,2-dioxygenase (HGD) enzyme is not functional due to gene variants. Over time, HGA oxidation and accumulation cause the formation of the ochronotic pigment, a deposit that provokes tissue degeneration and organ malfunction. Here, we report a comprehensive review of the variants so far reported, the structural studies on the molecular consequences of protein stability and interaction, and molecular simulations for pharmacological chaperones as protein rescuers. Moreover, evidence accumulated so far in alkaptonuria research will be re-proposed as the bases for a precision medicine approach in a rare disease.
Daniela Grasso, Michela Geminiani, Silvia Galderisi, Gabriella Iacomelli, Luana Peruzzi, Barbara Marzocchi, Annalisa Santucci, and Andrea Bernini
MDPI AG
Alkaptonuria (AKU) is an ultra-rare metabolic disease caused by the accumulation of homogentisic acid (HGA), an intermediate product of phenylalanine and tyrosine degradation. AKU patients carry variants within the gene coding for homogentisate-1,2-dioxygenase (HGD), which are responsible for reducing the enzyme catalytic activity and the consequent accumulation of HGA and formation of a dark pigment called the ochronotic pigment. In individuals with alkaptonuria, ochronotic pigmentation of connective tissues occurs, leading to inflammation, degeneration, and eventually osteoarthritis. The molecular mechanisms underlying the multisystemic development of the disease severity are still not fully understood and are mostly limited to the metabolic pathway segment involving HGA. In this view, untargeted metabolomics of biofluids in metabolic diseases allows the direct investigation of molecular species involved in pathways alterations and their interplay. Here, we present the untargeted metabolomics study of AKU through the nuclear magnetic resonance of urine from a cohort of Italian patients; the study aims to unravel molecular species and mechanisms underlying the AKU metabolic disorder. Dysregulation of metabolic pathways other than the HGD route and new potential biomarkers beyond homogentisate are suggested, contributing to a more comprehensive molecular signature definition for AKU and the development of future adjuvant treatment.
Daniela Grasso, Serena Pillozzi, Ilaria Tazza, Matteo Bertelli, Domenico Andrea Campanacci, Ilaria Palchetti, and Andrea Bernini
Elsevier BV
Adriano Pasqui, Anna Boddi, Domenico Andrea Campanacci, Guido Scoccianti, Andrea Bernini, Daniela Grasso, Elisabetta Gambale, Federico Scolari, Ilaria Palchetti, Annarita Palomba,et al.
MDPI AG
Clinical responses to anticancer therapies in advanced soft tissue sarcoma (STS) are unluckily restricted to a small subgroup of patients. Much of the inter-individual variability in treatment efficacy is as result of polymorphisms in genes encoding proteins involved in drug pharmacokinetics and pharmacodynamics. The nucleotide excision repair (NER) system is the main defense mechanism for repairing DNA damage caused by carcinogens and chemotherapy drugs. Single nucleotide polymorphisms (SNPs) of NER pathway key genes, altering mRNA expression or protein activity, can be significantly associated with response to chemotherapy, toxicities, tumor relapse or risk of developing cancer. In the present study, in a cohort of STS patients, we performed DNA extraction and genotyping by SNP assay, RNA extraction and quantitative real-time reverse transcription PCR (qPCR), a molecular dynamics simulation in order to characterize the NER pathway in STS. We observed a severe deregulation of the NER pathway and we describe for the first time the effect of SNP rs1047768 in the ERCC5 structure, suggesting a role in modulating single-stranded DNA (ssDNA) binding. Our results evidenced, for the first time, the correlation between a specific genotype profile of ERCC genes and proficiency of the NER pathway in STS.
Claudia Patiti, Patrick Severin Sfragano, Serena Laschi, Serena Pillozzi, Anna Boddi, Olivia Crociani, Andrea Bernini, and Ilaria Palchetti
MDPI AG
The determination of nucleic acids has become an analytical diagnostic method with many applications in fields such as biomedical sciences, environmental monitoring, forensic identification, and food safety. Among the different methods for nucleic acid analysis, those based on the polymerase chain reaction (PCR) are nowadays considered the gold standards. Isothermal amplification methods are an interesting alternative, especially in the design of chip-based architectures. Biosensing platforms hold great promise for the simple and rapid detection of nucleic acids since they can be embedded in lab-on-a-chip tools to perform nucleic acid extraction, amplification, and detection steps. Electrochemical transduction schemes are particularly interesting in the design of small and portable devices due to miniaturization, low-energy consumption, and multianalyte detection capability. The aim of this review is to summarize the different applications of isothermal amplification methods combined with electrochemical biosensing techniques in the development of lab-on-a-chip tools and wearable sensors. Different isothermal amplification methods are revised, and examples of different applications are discussed. Finally, a discussion on patented devices is also included.
Elisabetta Gambale, Anna Boddi, Adriano Pasqui, Domenico Andrea Campanacci, Guido Scoccianti, Ilaria Palchetti, Andrea Bernini, Lorenzo Antonuzzo, and Serena Pillozzi
Elsevier BV
A. K. Kiani, M. Mor, A. Bernini, E. Fulcheri, S. Michelini, K. Herbst, F. Buffelli, J. Belgrado, J. Kaftalli, L. Stuppia,et al.
Adipocytes express various enzymes, such as aldo-keto reductases (AKR1C), 11β-hydroxysteroid dehydrogenase (11β-HSD), aromatase, 5α-reductases, 3β-HSD, and 17β-HSDs involved in steroid hormone metabolism in adipose tissues. Increased activity of AKR1C enzymes and their expression in mature adipocytes might indicate the association of these enzymes with subcutaneous adipose tissue deposition. The inactivation of androgens by AKR1C enzymes increases adipogenesis and fat mass, particularly subcutaneous fat. AKR1C also causes reduction of estrone, a weak estrogen, to produce 17β-estradiol, a potent estrogen and, in addition, it plays a role in progesterone metabolism. Functional impairments of adipose tissue and imbalance of steroid biosynthesis could lead to metabolic disturbances. In this review, we will focus on the enzymes involved in steroid metabolism and fat tissue deposition.
G. Camilleri, A. K. Kiani, K. Herbst, J. Kaftalli, A. Bernini, K. Dhuli, E. Manara, G. Bonetti, L. Stuppia, S. Paolacci,et al.
Adipose tissue distribution usually varies among men and women. In men, adipose tissue is known to accumulate in the abdominal region surrounding the visceral organs (android fat distribution) whereas, in women, the accumulation of adipose tissue generally occurs in the gluteal-femoral regions (gynoid fat distribution). In some cases, however, android distribution can be found in women and gynoid distribution can be found in men. The regulation of adipose tissue accumulation involves interaction of a variety of genetic and environmental factors. This review examines genetic factors that cause differential distribution of adipose tissue in different depots of the body, between men and women and between different ethnicities. Genome-wide association studies can be used to identify genetic associations with the distribution and accumulation of adipose tissue. Insight into adipose tissue accumulation and distribution mechanisms could lead to development of personalized interventions for people who develop increased fat mass.
Andrea Bernini, Elena Petricci, Andrea Atrei, Maria Camilla Baratto, Fabrizio Manetti, and Annalisa Santucci
Springer Science and Business Media LLC
AbstractAlkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs due to a deficiency in functional levels of the enzyme homogentisate 1,2-dioxygenase (HGD), required for the breakdown of HGA, because of mutations in the HGD gene. Over time, HGA accumulation causes the formation of the ochronotic pigment, a dark deposit that leads to tissue degeneration and organ malfunction. Such behaviour can be observed also in vitro for HGA solutions or HGA-containing biofluids (e.g. urine from AKU patients) upon alkalinisation, although a comparison at the molecular level between the laboratory and the physiological conditions is lacking. Indeed, independently from the conditions, such process is usually explained with the formation of 1,4-benzoquinone acetic acid (BQA) as the product of HGA chemical oxidation, mostly based on structural similarity between HGA and hydroquinone that is known to be oxidized to the corresponding para-benzoquinone. To test such correlation, a comprehensive, comparative investigation on HGA and BQA chemical behaviours was carried out by a combined approach of spectroscopic techniques (UV spectrometry, Nuclear Magnetic Resonance, Electron Paramagnetic Resonance, Dynamic Light Scattering) under acid/base titration both in solution and in biofluids. New insights on the process leading from HGA to ochronotic pigment have been obtained, spotting out the central role of radical species as intermediates not reported so far. Such evidence opens the way for molecular investigation of HGA fate in cells and tissue aiming to find new targets for Alkaptonuria therapy.
Ottavia Spiga, Vittoria Cicaloni, Giovanna Maria Dimitri, Francesco Pettini, Daniela Braconi, Andrea Bernini, and Annalisa Santucci
Oxford University Press (OUP)
Abstract Alkaptonuria (AKU, OMIM: 203500) is an autosomal recessive disorder caused by mutations in the Homogentisate 1,2-dioxygenase (HGD) gene. A lack of standardized data, information and methodologies to assess disease severity and progression represents a common complication in ultra-rare disorders like AKU. This is the reason why we developed a comprehensive tool, called ApreciseKUre, able to collect AKU patients deriving data, to analyse the complex network among genotypic and phenotypic information and to get new insight in such multi-systemic disease. By taking advantage of the dataset, containing the highest number of AKU patient ever considered, it is possible to apply more sophisticated computational methods (such as machine learning) to achieve a first AKU patient stratification based on phenotypic and genotypic data in a typical precision medicine perspective. Thanks to our sufficiently populated and organized dataset, it is possible, for the first time, to extensively explore the phenotype–genotype relationships unknown so far. This proof of principle study for rare diseases confirms the importance of a dedicated database, allowing data management and analysis and can be used to tailor treatments for every patient in a more effective way.
Serena Pillozzi, Andrea Bernini, Ilaria Palchetti, Olivia Crociani, Lorenzo Antonuzzo, Domenico Campanacci, and Guido Scoccianti
MDPI AG
Soft tissue sarcomas (STSs) are a heterogeneous group of rare tumors. Although constituting only 1% of all human malignancies, STSs represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. Over 100 histologic subtypes have been characterized to date (occurring predominantly in the trunk, extremity, and retroperitoneum), and many more are being discovered due to molecular profiling. STS mortality remains high, despite adjuvant chemotherapy. New prognostic stratification markers are needed to help identify patients at risk of recurrence and possibly apply more intensive or novel treatments. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the most relevant cellular, molecular and metabolic biomarkers for STS, and highlight advances in STS-related biomarker research.
Andrea Bernini, Silvia Galderisi, Ottavia Spiga, Chukwudi Onyekachi Amarabom, and Annalisa Santucci
Elsevier BV
Jlenia Brunetti, Chiara Falciani, Andrea Bernini, Silvia Scali, Luisa Bracci, and Luisa Lozzi
Springer Science and Business Media LLC