Research

@article{pmid36429096,

title = {Effects of Nitisinone on Oxidative and Inflammatory Markers in Alkaptonuria: Results from SONIA1 and SONIA2 Studies},

author = {Daniela Braconi and Michela Geminiani and Eftychia Eirini Psarelli and Daniela Giustarini and Barbara Marzocchi and Ranieri Rossi and Giulia Bernardini and Ottavia Spiga and James A Gallagher and Kim-Hanh Le Quan Sang and Jean-Baptiste Arnoux and Richard Imrich and Mohammed S Al-Sbou and Matthew Gornall and Richard Jackson and Lakshminarayan R Ranganath and Annalisa Santucci},

doi = {10.3390/cells11223668},

issn = {2073-4409},

year  = {2022},

date = {2022-11-01},

journal = {Cells},

volume = {11},

number = {22},

abstract = {Nitisinone (NTBC) was recently approved to treat alkaptonuria (AKU), but there is no information on its impact on oxidative stress and inflammation, which are observed in AKU. Therefore, serum samples collected during the clinical studies SONIA1 (40 AKU patients) and SONIA2 (138 AKU patients) were tested for Serum Amyloid A (SAA), CRP and IL-8 by ELISA; Advanced Oxidation Protein Products (AOPP) by spectrophotometry; and protein carbonyls by Western blot. Our results show that NTBC had no significant effects on the tested markers except for a slight but statistically significant effect for NTBC, but not for the combination of time and NTBC, on SAA levels in SONIA2 patients. Notably, the majority of SONIA2 patients presented with SAA > 10 mg/L, and 30 patients in the control group (43.5%) and 40 patients (58.0%) in the NTBC-treated group showed persistently elevated SAA > 10 mg/L at each visit during SONIA2. Higher serum SAA correlated with lower quality of life and higher morbidity. Despite no quantitative differences in AOPP, the preliminary analysis of protein carbonyls highlighted patterns that deserve further investigation. Overall, our results suggest that NTBC cannot control the sub-clinical inflammation due to increased SAA observed in AKU, which is also a risk factor for developing secondary amyloidosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35870512,

title = {An improved NMR approach for metabolomics of intact serum samples},

author = {Daniela Grasso and Serena Pillozzi and Ilaria Tazza and Matteo Bertelli and Domenico Andrea Campanacci and Ilaria Palchetti and Andrea Bernini},

doi = {10.1016/j.ab.2022.114826},

issn = {1096-0309},

year  = {2022},

date = {2022-10-01},

journal = {Anal Biochem},

volume = {654},

pages = {114826},

abstract = {NMR metabolomics has inherent capabilities for studying biofluids, such as reproducibility, minimal sample preparation, non-destructiveness, and molecular structure elucidation; however, reliable quantitation of metabolites is still a challenge because of the complex matrix of the samples. The serum is one of the most common samples in clinical studies but possibly the most difficult for NMR analysis because of the high content of proteins, which hampers the detection and quantification of metabolites. Different processes for protein removal, such as ultrafiltration and precipitation, have been proposed, but require sample manipulation, increase time and cost, and possibly lead to loss of information in the metabolic profile. Alternative methods that rely on filtering protein signals by NMR pulse sequencing are commonly used, but standardisation of acquisition parameters and spectra calibration is far from being reached. The present technical note is a critical assessment of the sparsely suggested calibrants, pulse sequences and acquisition parameters toward an optimised combination of the three for accurate and reproducible quantification of metabolites in intact serum.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35955506,

title = {Alteration of the Nucleotide Excision Repair (NER) Pathway in Soft Tissue Sarcoma},

author = {Adriano Pasqui and Anna Boddi and Domenico Andrea Campanacci and Guido Scoccianti and Andrea Bernini and Daniela Grasso and Elisabetta Gambale and Federico Scolari and Ilaria Palchetti and Annarita Palomba and Sara Fancelli and Enrico Caliman and Lorenzo Antonuzzo and Serena Pillozzi},

doi = {10.3390/ijms23158360},

issn = {1422-0067},

year  = {2022},

date = {2022-07-01},

journal = {Int J Mol Sci},

volume = {23},

number = {15},

abstract = {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  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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35090868,

title = {Homogentisic acid induces autophagy alterations leading to chondroptosis in human chondrocytes: Implications in Alkaptonuria},

author = {Silvia Galderisi and Maria Serena Milella and Martina Rossi and Vittoria Cicaloni and Ranieri Rossi and Daniela Giustarini and Ottavia Spiga and Laura Tinti and Laura Salvini and Cristina Tinti and Daniela Braconi and Lia Millucci and Pietro Lupetti and Filippo Prischi and Giulia Bernardini and Annalisa Santucci},

doi = {10.1016/j.abb.2022.109137},

issn = {1096-0384},

year  = {2022},

date = {2022-03-01},

journal = {Arch Biochem Biophys},

volume = {717},

pages = {109137},

abstract = {Alkaptonuria (AKU) is an ultra-rare genetic disease caused by a deficient activity of the enzyme homogentisate 1,2-dioxygenase (HGD) leading to the accumulation of homogentisic acid (HGA) on connective tissues. Even though AKU is a multi-systemic disease, osteoarticular cartilage is the most affected system and the most damaged tissue by the disease. In chondrocytes, HGA causes oxidative stress dysfunctions, which induce a series of not fully characterized cellular responses. In this study, we used a human chondrocytic cell line as an AKU model to evaluate, for the first time, the effect of HGA on autophagy, the main homeostasis system in articular cartilage. Cells responded timely to HGA treatment with an increase in autophagy as a mechanism of protection. In a chronic state, HGA-induced oxidative stress decreased autophagy, and chondrocytes, unable to restore balance, activated the chondroptosis pathway. This decrease in autophagy also correlated with the accumulation of ochronotic pigment, a hallmark of AKU. Our data suggest new perspectives for understanding AKU and a mechanistic model that rationalizes the damaging role of HGA.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36353214,

title = {Bioinformatics Approaches to Predict Mutation Effects in the Binding Site of the Proangiogenic Molecule CD93},

author = {Vittoria Cicaloni and Malancha Karmakar and Luisa Frusciante and Francesco Pettini and Anna Visibelli and Maurizio Orlandini and Federico Galvagni and Maurizio Mongiat and Michael Silk and Federica Nardi and David Ascher and Annalisa Santucci and Ottavia Spiga},

doi = {10.3389/fbinf.2022.891553},

issn = {2673-7647},

year  = {2022},

date = {2022-01-01},

journal = {Front Bioinform},

volume = {2},

pages = {891553},

abstract = {The transmembrane glycoprotein CD93 has been identified as a potential new target to inhibit tumor angiogenesis. Recently, Multimerin-2 (MMRN2), a pan-endothelial extracellular matrix protein, has been identified as a ligand for CD93, but the interaction mechanism between these two proteins is yet to be studied. In this article, we aim to investigate the structural and functional effects of induced mutations on the binding domain of CD93 to MMRN2. Starting from experimental data, we assessed how specific mutations in the C-type lectin-like domain (CTLD) affect the binding interaction profile. We described a four-step workflow in order to predict the effects of variations on the inter-residue interaction network at the PPI, based on evolutionary information, complex network metrics, and energetic affinity. We showed that the application of computational approaches, combined with experimental data, allowed us to gain more in-depth molecular insights into the CD93-MMRN2 interaction, offering a platform for developing innovative therapeutics able to target these molecules and block their interaction. This comprehensive molecular insight might prove useful in drug design in cancer therapy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36201265,

title = {Artificial Intelligence Approaches in Drug Discovery: Towards the Laboratory of the Future},

author = {Luisa Frusciante and Anna Visibelli and Michela Geminiani and Annalisa Santucci and Ottavia Spiga},

doi = {10.2174/1568026622666221006140825},

issn = {1873-4294},

year  = {2022},

date = {2022-01-01},

journal = {Curr Top Med Chem},

volume = {22},

number = {26},

pages = {2176--2189},

abstract = {The role of computational tools in the drug discovery and development process is becoming central, thanks to the possibility to analyze large amounts of data. The high throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets, has exponentially increased the volume of scientific data available. The quality of the data and the speed with which in silico predictions can be validated in vitro is instrumental in accelerating clinical laboratory medicine, significantly and substantially impacting Precision Medicine (PM). PM affords the basis to develop new drugs by providing a wide knowledge of the patient as an essential step towards individualized medicine. It is, therefore, essential to collect as much information and data as possible on each patient to identify the causes of the different responses to drugs from a pharmacogenomics perspective and to identify biological biomarkers capable of accurately describing the risk signals to develop specific diseases. Furthermore, the role of biomarkers in early drug discovery is increasing, as they can significantly reduce the time it takes to develop new drugs. This review article will discuss how Artificial Intelligence fits in the drug discovery pipeline, covering the benefits of an automated, integrated laboratory framework where the application of Machine Learning methodologies to interpret omics-based data can avail the future perspective of Translational Precision Medicine.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36118553,

title = {HGDiscovery: An online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase},

author = {Malancha Karmakar and Vittoria Cicaloni and Carlos H M Rodrigues and Ottavia Spiga and Annalisa Santucci and David B Ascher},

doi = {10.1016/j.crstbi.2022.08.001},

issn = {2665-928X},

year  = {2022},

date = {2022-01-01},

journal = {Curr Res Struct Biol},

volume = {4},

pages = {271--277},

abstract = {Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in the body. Affected individuals lack functional levels of an enzyme required to breakdown HGA. Mutations in the homogentisate 1,2-dioxygenase (HGD) gene cause AKU and they are responsible for deficient levels of functional HGD, which, in turn, leads to excess levels of HGA. Although HGA is rapidly cleared from the body by the kidneys, in the long term it starts accumulating in various tissues, especially cartilage. Over time (rarely before adulthood), it eventually changes the color of affected tissue to slate blue or black. Here we report a comprehensive mutation analysis of 111 pathogenic and 190 non-pathogenic HGD missense mutations using protein structural information. Using our comprehensive suite of graph-based signature methods, mCSM complemented with sequence-based tools, we studied the functional and molecular consequences of each mutation on protein stability, interaction and evolutionary conservation. The scores generated from the structure and sequence-based tools were used to train a supervised machine learning algorithm with 89% accuracy. The empirical classifier was used to generate the variant phenotype for novel HGD missense mutations. All this information is deployed as a user friendly freely available web server called HGDiscovery (https://biosig.lab.uq.edu.au/hgdiscovery/).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35123198,

title = {Pharmacogenomics of soft tissue sarcomas: New horizons to understand efficacy and toxicity},

author = {Elisabetta Gambale and Anna Boddi and Adriano Pasqui and Domenico Andrea Campanacci and Guido Scoccianti and Ilaria Palchetti and Andrea Bernini and Lorenzo Antonuzzo and Serena Pillozzi},

doi = {10.1016/j.ctarc.2022.100528},

issn = {2468-2942},

year  = {2022},

date = {2022-01-01},

journal = {Cancer Treat Res Commun},

volume = {31},

pages = {100528},

abstract = {Clinical responses to anticancer therapies in advanced soft tissue sarcoma (STS) are unfortunately limited to a small subset of patients. Much of the inter-individual variability in treatment efficacy and risk of toxicities is as result of polymorphisms in genes encoding proteins involved in drug pharmacokinetics and pharmacodynamics. Therefore, the detection of pharmacogenomics (PGx) biomarkers that might predict drug response and toxicity can be useful to explain the genetic basis for the differences in treatment efficacy and toxicity among STS patients. PGx markers are frequently located in transporters, drug-metabolizing enzyme genes, drug targets, or HLA alleles. Along this line, genetic variability harbouring in the germline genome of the patients can influence systemic pharmacokinetics and pharmacodynamics of the treatments, acting as predictive biomarkers for drug-induced toxicity and treatment efficacy. By linking drug activity to the functional complexity of cancer genomes, also systematic pharmacogenomic profiling in cancer cell lines and primary STS samples represents area of active investigation that could eventually lead to enhanced efficacy and offer a powerful biomarker discovery platform to optimize current treatments and improve the knowledge about the individual's drug response in STS patients into the clinical practice.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34799606,

title = {A molecular spectroscopy approach for the investigation of early phase ochronotic pigment development in Alkaptonuria},

author = {Andrea Bernini and Elena Petricci and Andrea Atrei and Maria Camilla Baratto and Fabrizio Manetti and Annalisa Santucci},

doi = {10.1038/s41598-021-01670-z},

issn = {2045-2322},

year  = {2021},

date = {2021-11-01},

journal = {Sci Rep},

volume = {11},

number = {1},

pages = {22562},

abstract = {Alkaptonuria (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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}