Structural and functional analysis of centromeric chromatin

Animal neocentromeres are defined as ectopic centromeres that have formed in non-centromeric locations and avoid some of the features, like the DNA satellite sequence, that normally characterize canonical centromeres. Despite this, they are stable functional centromeres inherited through generations. The only existence of neocentromeres provide convincing evidence that centromere specification is determined by epigenetic rather than sequence-specific mechanisms. For all this reasons, we used them as simplified models to investigate the molecular mechanisms that underlay the formation and the maintenance of functional centromeres. We collected human cell lines carrying neocentromeres in different positions. To investigate the region involved in the process at the DNA sequence level we applied a recent technology that integrates Chromatin Immuno-Precipitation and DNA microarrays (ChIP-on-chip) using rabbit polyclonal antibodies directed against CENP-A or CENP-C human centromeric proteins. These DNA binding-proteins are required for kinetochore function and are exclusively targeted to functional centromeres. Thus, the immunoprecipitation of DNA bound by these proteins allows the isolation of centromeric sequences, including those of the neocentromeres. Neocentromeres arise even in protein-coding genes region. We further analyzed if the increased scaffold attachment sites and the corresponding tighter chromatin of the region involved in the neocentromerization process still were permissive or not to transcription of within encoded genes. Centromere repositioning is a phenomenon in which a neocentromere arisen without altering the gene order, followed by the inactivation of the canonical centromere, becomes fixed in population. It is a process of chromosome rearrangement fundamental in evolution, at the bases of speciation. The repeat-free region where the neocentromere initially forms, progressively acquires extended arrays of satellite tandem repeats that may contribute to its functional stability. In this view our attention focalized to the repositioned horse ECA11 centromere. ChIP-on-chip analysis was used to define the region involved and SNPs studies, mapping within the region involved into neocentromerization, were carried on. We have been able to describe the structural polymorphism of the chromosome 11 centromeric domain of Caballus population. That polymorphism was seen even between homologues chromosome of the same cells. That discovery was the first described ever. Genomic plasticity had a fundamental role in evolution. Centromeres are not static packaged region of genomes. The key question that fascinates biologists is to understand how that centromere plasticity could be combined to the stability and maintenance of centromeric function. Starting from the epigenetic point of view that underlies centromere formation, we decided to analyze the RNA content of centromeric chromatin. RNA, as well as secondary chemically modifications that involve both histones and DNA, represents a good candidate to guide somehow the centromere formation and maintenance. Many observations suggest that transcription of centromeric DNA or of other non-coding RNAs could affect centromere formation. To date has been no thorough investigation addressing the identity of the chromatin-associated RNAs (CARs) on a global scale. This prompted us to develop techniques to identify CARs in a genome-wide approach using high-throughput genomic platforms. The future goal of this study will be to focalize the attention on what strictly happens specifically inside centromere chromatin.

MetaVaccinology: a new vaccine discovery tool

In the last decade, the reverse vaccinology approach shifted the paradigm of vaccine discovery from conventional culture-based methods to high-throughput genome-based approaches for the development of recombinant protein-based vaccines against pathogenic bacteria. Besides reaching its main goal of identifying new vaccine candidates, this new procedure produced also a huge amount of molecular knowledge related to them. In the present work, we explored this knowledge in a species-independent way and we performed a systematic in silico molecular analysis of more than 100 protective antigens, looking at their sequence similarity, domain composition and protein architecture in order to identify possible common molecular features. This meta-analysis revealed that, beside a low sequence similarity, most of the known bacterial protective antigens shared structural/functional Pfam domains as well as specific protein architectures. Based on this, we formulated the hypothesis that the occurrence of these molecular signatures can be predictive of possible protective properties of other proteins in different bacterial species. We tested this hypothesis in Streptococcus agalactiae and identified four new protective antigens. Moreover, in order to provide a second proof of the concept for our approach, we used Staphyloccus aureus as a second pathogen and identified five new protective antigens. This new knowledge-driven selection process, named MetaVaccinology, represents the first in silico vaccine discovery tool based on conserved and predictive molecular and structural features of bacterial protective antigens and not dependent upon the prediction of their sub-cellular localization.

Novel tools for conservation genetics in marine fish: population structure and evolution of the European hake (Merluccius merluccius) inferred by SNP variation and applications to traceability

The research presented in my PhD thesis is part of a wider European project, FishPopTrace, focused on traceability of fish populations and products. My work was aimed at developing and analyzing novel genetic tools for a widely distributed marine fish species, the European hake (Merluccius merluccius), in order to investigate population genetic structure and explore potential applications to traceability scenarios. A total of 395 SNPs (Single Nucleotide Polymorphisms) were discovered from a massive collection of Expressed Sequence Tags, obtained by high-throughput sequencing, and validated on 19 geographic samples from Atlantic and Mediterranean. Genome-scan approaches were applied to identify polymorphisms on genes potentially under divergent selection (outlier SNPs), showing higher genetic differentiation among populations respect to the average observed across loci. Comparative analysis on population structure were carried out on putative neutral and outlier loci at wide (Atlantic and Mediterranean samples) and regional (samples within each basin) spatial scales, to disentangle the effects of demographic and adaptive evolutionary forces on European hake populations genetic structure. Results demonstrated the potential of outlier loci to unveil fine scale genetic structure, possibly identifying locally adapted populations, despite the weak signal showed from putative neutral SNPs. The application of outlier SNPs within the framework of fishery resources management was also explored. A minimum panel of SNP markers showing maximum discriminatory power was selected and applied to a traceability scenario aiming at identifying the basin (and hence the stock) of origin, Atlantic or Mediterranean, of individual fish. This case study illustrates how molecular analytical technologies have operational potential in real-world contexts, and more specifically, potential to support fisheries control and enforcement and fish and fish product traceability.

Continuos Flow Single Cell Separation into Open Microwell Arrays

A novel design based on electric field-free open microwell arrays for the automated continuous-flow sorting of single or small clusters of cells is presented. The main feature of the proposed device is the parallel analysis of cell-cell and cell-particle interactions in each microwell of the array. High throughput sample recovery with a fast and separate transfer from the microsites to standard microtiter plates is also possible thanks to the flexible printed circuit board technology which permits to produce cost effective large area arrays featuring geometries compatible with laboratory equipment. The particle isolation is performed via negative dielectrophoretic forces which convey the particles’ into the microwells. Particles such as cells and beads flow in electrically active microchannels on whose substrate the electrodes are patterned. The introduction of particles within the microwells is automatically performed by generating the required feedback signal by a microscope-based optical counting and detection routine. In order to isolate a controlled number of particles we created two particular configurations of the electric field within the structure. The first one permits their isolation whereas the second one creates a net force which repels the particles from the microwell entrance. To increase the parallelism at which the cell-isolation function is implemented, a new technique based on coplanar electrodes to detect particle presence was implemented. A lock-in amplifying scheme was used to monitor the impedance of the channel perturbed by flowing particles in high-conductivity suspension mediums. The impedance measurement module was also combined with the dielectrophoretic focusing stage situated upstream of the measurement stage, to limit the measured signal amplitude dispersion due to the particles position variation within the microchannel. In conclusion, the designed system complies with the initial specifications making it suitable for cellomics and biotechnology applications.

Development and characterization of micromachined devices for separation techniques

Nowadays microfluidic is becoming an important technology in many chemical and biological processes and analysis applications. The potential to replace large-scale conventional laboratory instrumentation with miniaturized and self-contained systems, (called lab-on-a-chip (LOC) or point-of-care-testing (POCT)), offers a variety of advantages such as low reagent consumption, faster analysis speeds, and the capability of operating in a massively parallel scale in order to achieve high-throughput. Micro-electro-mechanical-systems (MEMS) technologies enable both the fabrication of miniaturized system and the possibility of developing compact and portable systems. The work described in this dissertation is towards the development of micromachined separation devices for both high-speed gas chromatography (HSGC) and gravitational field-flow fractionation (GrFFF) using MEMS technologies. Concerning the HSGC, a complete platform of three MEMS-based GC core components (injector, separation column and detector) is designed, fabricated and characterized. The microinjector consists of a set of pneumatically driven microvalves, based on a polymeric actuating membrane. Experimental results demonstrate that the microinjector is able to guarantee low dead volumes, fast actuation time, a wide operating temperature range and high chemical inertness. The microcolumn consists of an all-silicon microcolumn having a nearly circular cross-section channel. The extensive characterization has produced separation performances very close to the theoretical ideal expectations. A thermal conductivity detector (TCD) is chosen as most proper detector to be miniaturized since the volume reduction of the detector chamber results in increased mass and reduced dead volumes. The microTDC shows a good sensitivity and a very wide dynamic range. Finally a feasibility study for miniaturizing a channel suited for GrFFF is performed. The proposed GrFFF microchannel is at early stage of development, but represents a first step for the realization of a highly portable and potentially low-cost POCT device for biomedical applications.

Detection and molecular characterization of viruses infecting Actinidia spp.

Kiwifruit (genus Actinidia) is an important horticultural crop grown in the temperate regions. The four world’s largest producers are China, Italy, New Zealand and Chile. More than 50 species are recognized in the genus but the principal species in cultivation are A. deliciosa and A. chinensis. In Italy, as well as in many other countries, the kiwifruit crop has been considered to be relatively disease free and then no certification system for this species has been developed to regulate importation of propagation plant material in the European Union. During the last years a number of fungal and bacterial diseases have been recorded such as Botrytis cinerea and Pseudomonas syringae pv. actinidiae. Since 2003, several viruses and virus-like diseases have been identified and more recent studies demonstrated that Actinidia spp can be infected by a wide range of viral agents. In collaboration with the University of Auckland we have been detected thirteen different viral species on kiwifruit plants. During the three years of my PhD I worked on the characterization of Cucumber mosaic virus (CMV) and Pelargonium zonate spot virus (PZSV). The determination of causal agents has been based on host range, symptom expression in the test plant species and morphological properties of the virus particles using transmission electron microscopy (TEM) and using specific oligonucleotide primers in reverse transcription-polymerase chain reaction (RT-PCR). Both viruses induced several symptoms on kiwifruit plants. Moreover with new technologies such as high-throughput sequencing we detected additional viruses, a new member of the family Closteroviridae and a new member of the family Totiviridae. Taking together all results of my studies it is clear that, in order to minimize the risk of serious viral disease in kiwifruit, it is vital to use virus-free propagation material in order to prevent the spread of these viruses.

Microbial ecology of biotechnological processes

The investigation of phylogenetic diversity and functionality of complex microbial communities in relation to changes in the environmental conditions represents a major challenge of microbial ecology research. Nowadays, particular attention is paid to microbial communities occurring at environmental sites contaminated by recalcitrant and toxic organic compounds. Extended research has evidenced that such communities evolve some metabolic abilities leading to the partial degradation or complete mineralization of the contaminants. Determination of such biodegradation potential can be the starting point for the development of cost effective biotechnological processes for the bioremediation of contaminated matrices. This work showed how metagenomics-based microbial ecology investigations supported the choice or the development of three different bioremediation strategies. First, PCR-DGGE and PCR-cloning approaches served the molecular characterization of microbial communities enriched through sequential development stages of an aerobic cometabolic process for the treatment of groundwater contaminated by chlorinated aliphatic hydrocarbons inside an immobilized-biomass packed bed bioreactor (PBR). In this case the analyses revealed homogeneous growth and structure of immobilized communities throughout the PBR and the occurrence of dominant microbial phylotypes of the genera Rhodococcus, Comamonas and Acidovorax, which probably drive the biodegradation process. The same molecular approaches were employed to characterize sludge microbial communities selected and enriched during the treatment of municipal wastewater coupled with the production of polyhydroxyalkanoates (PHA). Known PHA-accumulating microorganisms identified were affiliated with the genera Zooglea, Acidovorax and Hydrogenophaga. Finally, the molecular investigation concerned communities of polycyclic aromatic hydrocarbon (PAH) contaminated soil subjected to rhizoremediation with willow roots or fertilization-based treatments. The metabolic ability to biodegrade naphthalene, as a representative model for PAH, was assessed by means of stable isotope probing in combination with high-throughput sequencing analysis. The phylogenetic diversity of microbial populations able to derive carbon from naphthalene was evaluated as a function of the type of treatment.

Dissecting the Heat-Stress Tolerance QTLome in Durum Wheat

Heat stress negatively affects wheat performance during its entire cycle, particularly during the reproductive stage. In view of the climate change and the prediction of a continued increase in temperature in the new future, it is urgent to concentrate efforts to discover novel genetic sources able to improve the resilience of wheat to heat stress. In this direction, this study addressed two different experiments in durum wheat to identify novel QTLs suitable to be applied in marker-assisted selection for heat tolerance. Chlorophyll fluorescence (ChlF) is a valuable indicator of plant response to environmental changes allowing a detailed assessment of PSII activity in view of its non-invasive measurement and high-throughput phenotyping. In the first study (Chapter 2), the Light-Induced Fluorescence Transient (LIFT) method was used to access ChlF data to map QTLs for ChlF-related traits during the vegetative growth stage in durum wheat under heat stress condition. Our results provide evidence that LIFT consistently measures ChlF at the level of high-throughput phenotyping combined with high accuracy which is required for Genome-Wide Association Study (GWAS) aimed at identifying genomic regions affecting PSII activity. The 50 QTLs identified for ChlF-related traits under heat stress mostly clustered into five chromosomes hotspots unrelated to phenology, a feature that makes these QTLs a valuable asset for marker-assisted breeding programs across different latitudes. In the second study (Chapter 3), a set of 183 accessions suitable for GWAS, was exposed to optimal and high temperature during two crop seasons under field conditions. Important agronomic traits were evaluated in order to identify valuable QTLs for GY and its components. The GWAS analysis identified several QTLs in the single years as well as in the joint analysis. From the total QTLs identified, 13 QTL clusters can be highlighted to be affecting heat tolerance across different years and/or different traits.

Non-Equilibrium Atmospheric Plasma As A Novel Route To Nanomaterial Synthesis And Processing For Biomedical Applications

Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

Computational resources for structural and metagenomic characterization of functions in bacteria and bacterial communities. Antimicrobial resistance, pathways for xenobiotic degradation and relationship between gut microbiome and ageing.

Prokaryotic organisms are one of the most successful forms of life, they are present in all known ecosystems. The deluge diversity of bacteria reflects their ability to colonise every environment. Also, human beings host trillions of microorganisms in their body districts, including skin, mucosae, and gut. This symbiosis is active for all other terrestrial and marine animals, as well as plants. With the term holobiont we refer, with a single word, to the systems including both the host and its symbiotic microbial species. The coevolution of bacteria within their ecological niches reflects the adaptation of both host and guest species, and it is shaped by complex interactions that are pivotal for determining the host state. Nowadays, thanks to the current sequencing technologies, Next Generation Sequencing, we have unprecedented tools for investigating the bacterial life by studying the prokaryotic genome sequences. NGS revolution has been sustained by the advancements in computational performance, in terms of speed, storage capacity, algorithm development and hardware costs decreasing following the Moore’s Law. Bioinformaticians and computational biologists design and implement ad hoc tools able to analyse high-throughput data and extract valuable biological information. Metagenomics requires the integration of life and computational sciences and it is uncovering the deluge diversity of the bacterial world. The present thesis work focuses mainly on the analysis of prokaryotic genomes under different aspects. Being supervised by two groups at the University of Bologna, the Biocomputing group and the group of Microbial Ecology of Health, I investigated three different topics: i) antimicrobial resistance, particularly with respect to missense point mutations involved in the resistant phenotype, ii) bacterial mechanisms involved in xenobiotic degradation via the computational analysis of metagenomic samples, and iii) the variation of the human gut microbiota through ageing, in elderly and longevous individuals.

Tumor heterogeneity in Esophageal Adenocarcinoma: a genomic approach

INTRODUCTION: Esophageal adenocarcinoma (EAC) is a severe malignancy in terms of prognosis and mortality rate. Because its great genetic heterogeneity, disputes regarding classification, prevention and treatments are still unsolved. AIM: We investigated intra- and inter-EAC heterogeneity by defining EAC’s somatic mutational profile and the role of candidate microRNAs, to correlate the molecular profile of tumors to clinical outcomes and to identify biomarkers for classification. METHODS: 38 EAC cases were analyzed via high-throughput cell sorting technology combined with targeted sequencing and whole genome low-pass sequencing. Targeted sequencing of further 169 cases was performed to widen the study. miR221 and miR483-3p expression was profiled via qPCR in 112 EACs and correlation with clinical outcomes was investigated. RESULTS: 35/38 EACs carried at least one somatic mutation absent in stromal cells. TP53 was found mutated in 73.7% of cases. Selective sorting revealed tumor subclones with different mutational loads and copy number alterations, confirming the high intra-tumor heterogeneity of EAC. Mutations were in most cases at homozygous state, and we identified alterations that were missed with the whole-tumor analysis. Mutations in HNF1A gene, not previously associated with EAC, were identified in both cohorts. Higher expression of miR483-3p and miR221 was associated with poorer cancer specific survival (P=0.0293 and P=0.0059), and recurrence in the Lauren intestinal subtype (P=0.0459 and P=0.0002). Median expression levels of miRNAs were higher in patients with advanced tumor stages. The loss of SMAD4 immunoreactivity was significantly associated with poorer cancer specific survival and recurrence (P=0.0452; P=0.022 respectively). CONCLUSION: Combining selective sorting technology and next generation sequencing allowed to better define EAC inter- and intra-tumor heterogeneity. We identified HNF1A as a new mutated gene associated to EAC that could be involved in tumor progression and promising biomarkers such as SMAD4, miR221 and miR483-3p to identify patients at higher risk for more aggressive tumors.

Whole Exome Sequencing widens the genetic landscape of Hereditary Optic Neuropathies

Hereditary optic neuropathies (HON) are a genetic cause of visual impairment characterized by degeneration of retinal ganglion cells. The majority of HON are caused by pathogenic variants in mtDNA genes and in gene OPA1. However, several other genes can cause optic atrophy and can only be identified by high throughput genetic analysis. Whole Exome Sequencing (WES) is becoming the primary choice in rare disease molecular diagnosis, being both cost effective and informative. We performed WES on a cohort of 106 cases, of which 74 isolated ON patients (ON) and 32 syndromic ON patients (sON). The total diagnostic yield amounts to 27%, slightly higher for syndromic ON (31%) than for isolated ON (26%). The majority of genes found are related to mitochondrial function and already reported for harbouring HON pathogenic variants: ACO2, AFG3L2, C19orf12, DNAJC30, FDXR, MECR, MTFMT, NDUFAF2, NDUFB11, NDUFV2, OPA1, PDSS1, SDHA, SSBP1, and WFS1. Among these OPA1, ACO2, and WFS1 were confirmed as the most relevant genetic causes of ON. Moreover, several genes were identified, especially in sON patients, with direct impairment of non-mitochondrial molecular pathways: from autophagy and ubiquitin system (LYST, SNF8, WDR45, UCHL1), to neural cells development and function (KIF1A, GFAP, EPHB2, CACNA1A, CACNA1F), but also vitamin metabolism (SLC52A2, BTD), cilia structure (USH2A), and nuclear pore shuttling (NUTF2). Functional validation on yeast model was performed for pathogenic variants detected in MECR, MTFMT, SDHA, and UCHL1 genes. For SDHA and UCHL1 also muscle biopsy and fibroblast cell lines from patients were analysed, pointing to possible pathogenic mechanisms that will be investigated in further studies. In conclusion, WES proved to be an efficient tool when applied to our ON cohort, for both common disease-genes identification and novel genes discovery. It is therefore recommended to consider WES in ON molecular diagnostic pipeline, as for other rare genetic diseases.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

Development of advanced analytical methodologies for Alzheimer’s disease drug discovery

Advanced analytical methodologies were developed to characterize new potential active MTDLs on isolated targets involved in the first stages of Alzheimer’s disease (AD). In addition, the methods investigated drug-protein bindings and evaluated protein-protein interactions involved in the neurodegeneration. A high-throughput luminescent assay allowed the study of the first in class GSK-3β/ HDAC dual inhibitors towards the enzyme GSK-3β. The method was able to identify an innovative disease-modifying agent with an activity in the micromolar range both on GSK-3β, HDAC1 and HDAC6. Then, the same assay reliably and quickly selected true positive hit compounds among natural Amaryllidaceae alkaloids tested against GSK-3β. Hence, given the central role of the amyloid pathway in the multifactorial nature of AD, a multi-methodological approach based on mass spectrometry (MS), circular dichroism spectroscopy (CD) and ThT assay was applied to characterize the potential interaction of CO releasing molecules (CORMs) with Aβ1-42 peptide. The comprehensive method provided reliable information on the different steps of the fibrillation process and regarding CORMs mechanism of action. Therefore, the optimal CORM-3/Aβ1−42 ratio in terms of inhibitory effect was identified by mass spectrometry. CD analysis confirmed the stabilizing effect of CORM-3 on the Aβ1−42 peptide soluble form and the ThT Fluorescent Analysis ensured that the entire fibrillation process was delayed. Then the amyloid aggregation process was studied in view of a possible correlation with AD lipid brain alterations. Therefore, SH-SY5Y cells were treated with increasing concentration of Aß1-42 at different times and the samples were analysed by a RP-UHPLC system coupled with a high-resolution quadrupole TOF mass spectrometer in comprehensive data-independent SWATH acquisition mode. Each lipid class profiling in SH-SY5Y cells treated with Aß1-42 was compared to the one obtained from the untreated. The approach underlined some peculiar lipid alterations, suitable as biomarkers, that might be correlated to Aß1-42 different aggregation species.

Identification of outcome-oriented cut-offs for copy number alterations in multiple myeloma: predictive biomarkers with improved prognostic accuracy

Aim of the present study was to develop a statistical approach to define the best cut-off Copy number alterations (CNAs) calling from genomic data provided by high throughput experiments, able to predict a specific clinical end-point (early relapse, 18 months) in the context of Multiple Myeloma (MM). 743 newly diagnosed MM patients with SNPs array-derived genomic and clinical data were included in the study. CNAs were called both by a conventional (classic, CL) and an outcome-oriented (OO) method, and Progression Free Survival (PFS) hazard ratios of CNAs called by the two approaches were compared. The OO approach successfully identified patients at higher risk of relapse and the univariate survival analysis showed stronger prognostic effects for OO-defined high-risk alterations, as compared to that defined by CL approach, statistically significant for 12 CNAs. Overall, 155/743 patients relapsed within 18 months from the therapy start. A small number of OO-defined CNAs were significantly recurrent in early-relapsed patients (ER-CNAs) - amp1q, amp2p, del2p, del12p, del17p, del19p -. Two groups of patients were identified either carrying or not ≥1 ER-CNAs (249 vs. 494, respectively), the first one with significantly shorter PFS and overall survivals (OS) (PFS HR 2.15, p<0001; OS HR 2.37, p<0.0001). The risk of relapse defined by the presence of ≥1 ER-CNAs was independent from those conferred both by R-IIS 3 (HR=1.51; p=0.01) and by low quality (< stable disease) clinical response (HR=2.59 p=0.004). Notably, the type of induction therapy was not descriptive, suggesting that ER is strongly related to patients’ baseline genomic architecture. In conclusion, the OO- approach employed allowed to define CNAs-specific dynamic clonality cut-offs, improving the CNAs calls’ accuracy to identify MM patients with the highest probability to ER. As being outcome-dependent, the OO-approach is dynamic and might be adjusted according to the selected outcome variable of interest.