@article{%a1:%Ybv,

title = {Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions},

author = {Salviato E and Djordjilovic V and Hariprakash JM and Tagliaferri I and Pal K and Ferrari F},

url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab547/6312759},

doi = {10.1093/nar/gkab547},

year  = {2021},

date = {2021-10-18},

urldate = {2021-08-25},

journal = {Nucleic acids research},

volume = {49},

number = {17},

abstract = {A growing amount of evidence in literature suggests that germline sequence variants and somatic mutations in non-coding distal regulatory elements may be crucial for defining disease risk and prognostic stratification of patients, in genetic disorders as well as in cancer. Their functional interpretation is challenging because genome-wide enhancer-target gene (ETG) pairing is an open problem in genomics. The solutions proposed so far do not account for the hierarchy of structural domains which define chromatin three-dimensional (3D) architecture. Here we introduce a change of perspective based on the definition of multi-scale structural chromatin domains, integrated in a statistical framework to define ETG pairs. In this work (i) we develop a computational and statistical framework to reconstruct a comprehensive map of ETG pairs leveraging functional genomics data; (ii) we demonstrate that the incorporation of chromatin 3D architecture information improves ETG pairing accuracy and (iii) we use multiple experimental datasets to extensively benchmark our method against previous solutions for the genome-wide reconstruction of ETG pairs. This solution will facilitate the annotation and interpretation of sequence variants in distal non-coding regulatory elements. We expect this to be especially helpful in clinically oriented applications of whole genome sequencing in cancer and undiagnosed genetic diseases research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Yb_71,

title = {Oncolytic adenovirus and gene therapy with EphA2-BiTE for the treatment of pediatric high-grade gliomas},

author = {Arnone CM and Polito VA and Mastronuzzi A and Carai A and Diomedi FC and Antonucci L and Petrilli LL and Vinci M and Ferrari F and Salviato E and Scarsella M and De Stefanis C and Weber G and Quintarelli C and De Angelis B and Brenner MK and Gottschalk S and Hoyos V and Locatelli F and Caruana I and Del Bufalo F},

url = {https://jitc.bmj.com/content/9/5/e001930.long},

doi = {10.1136/jitc-2020-001930},

year  = {2021},

date = {2021-11-19},

urldate = {2021-11-19},

journal = {Journal for immunotherapy of cancer},

volume = {9},

issue = {5},

abstract = {Background: Pediatric high-grade gliomas (pHGGs) are among the most common and incurable malignant neoplasms of childhood. Despite aggressive, multimodal treatment, the outcome of children with high-grade gliomas has not significantly improved over the past decades, prompting the development of innovative approaches. Methods: To develop an effective treatment, we aimed at improving the suboptimal antitumor efficacy of oncolytic adenoviruses (OAs) by testing the combination with a gene-therapy approach using a bispecific T-cell engager (BiTE) directed towards the erythropoietin-producing human hepatocellular carcinoma A2 receptor (EphA2), conveyed by a replication-incompetent adenoviral vector (EphA2 adenovirus (EAd)). The combinatorial approach was tested in vitro, in vivo and thoroughly characterized at a molecular level. Results: After confirming the relevance of EphA2 as target in pHGGs, documenting a significant correlation with worse clinical outcome of the patients, we showed that the proposed strategy provides significant EphA2-BiTE amplification and enhanced tumor cell apoptosis, on coculture with T cells. Moreover, T-cell activation through an agonistic anti-CD28 antibody further increased the activation/proliferation profiles and functional response against infected tumor cells, inducing eradication of highly resistant, primary pHGG cells. The gene-expression analysis of tumor cells and T cells, after coculture, revealed the importance of both EphA2-BiTE and costimulation in the proposed system. These in vitro observations translated into significant tumor control in vivo, in both subcutaneous and a more challenging orthotopic model. Conclusions: The combination of OA and EphA2-BiTE gene therapy strongly enhances the antitumor activity of OA, inducing the eradication of highly resistant tumor cells, thus supporting the clinical translation of the approach.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Ybv,

title = {Single-cell profiling reveals the dynamics of cytomegalovirusspecific T-cells in haploidentical hematopoietic stem cell transplantation},

author = {Van Beek JJP and Puccio S and Roberto A and De Paoli F and Graziano G and Salviato E and Alvisi G and Zanon V and Scarpa A and Zaghi E and Calvi M and Di Vito C and Mineri R and Sarina B and De Philippis C and Santoro A and Mariotti J and Bramanti S and Ferrari F and Castagna L and Mavilio D and Lugli E},

url = {https://haematologica.org/article/view/haematol.2020.276352},

doi = {10.3324/haematol.2020.276352},

year  = {2021},

date = {2021-09-06},

urldate = {2021-08-25},

journal = {Haematologica},

volume = {106},

number = {10},

pages = {2768-2773},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Ybv,

title = {T Cells Expressing Receptor Recombination/Revision Machinery Are Detected in the Tumor Microenvironment and Expanded in Genomically Over-unstable Models},

author = {Morello G and Cancila V and La Rosa M and Germano G and Lecis D and Amodio V and Zanardi F and Iannelli F and Greco D and La Paglia L and Fiannaca A and Urso AM and Graziano G and Ferrari F and Pupa SM and Sangaletti S and Chiodoni C and Pruneri G and Bardelli A and Colombo MP and Tripodo C},

url = {https://cancerimmunolres.aacrjournals.org/content/early/2021/06/08/2326-6066.CIR-20-0645.long},

doi = {10.1158/2326-6066.CIR-20-0645},

year  = {2021},

date = {2021-08-25},

journal = {Cancer immunology research},

abstract = {Tumors undergo dynamic immunoediting as part of a process that balances immunologic sensing of emerging neoantigens and evasion from immune responses. Tumor-infiltrating lymphocytes (TIL) comprise heterogeneous subsets of peripheral T cells characterized by diverse functional differentiation states and dependence on T-cell receptor (TCR) specificity gained through recombination events during their development. We hypothesized that within the tumor microenvironment (TME), an antigenic milieu and immunologic interface, tumor-infiltrating peripheral T cells could reexpress key elements of the TCR recombination machinery, namely, Rag1 and Rag2 recombinases and Tdt polymerase, as a potential mechanism involved in the revision of TCR specificity. Using two syngeneic invasive breast cancer transplantable models, 4T1 and TS/A, we observed that Rag1, Rag2, and Dntt in situ mRNA expression characterized rare tumor-infiltrating T cells. In situ expression of the transcripts was increased in coisogenic Mlh1-deficient tumors, characterized by genomic overinstability, and was also modulated by PD-1 immune-checkpoint blockade. Through immunolocalization and mRNA hybridization analyses, we detected the presence of rare TDT+RAG1/2+ cells populating primary tumors and draining lymph nodes in human invasive breast cancer. Analysis of harmonized single-cell RNA-sequencing data sets of human cancers identified a very small fraction of tumor-associated T cells, characterized by the expression of recombination/revision machinery transcripts, which on pseudotemporal ordering corresponded to differentiated effector T cells. We offer thought-provoking evidence of a TIL microniche marked by rare transcripts involved in TCR shaping.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Ybv,

title = {Visualizing and Annotating Hi-C Data},

author = {Pal K and Ferrari F},

url = {https://link.springer.com/protocol/10.1007%2F978-1-0716-1390-0_5},

doi = {10.1007/978-1-0716-1390-0_5},

year  = {2021},

date = {2021-08-25},

journal = {Methods in molecular biology},

volume = {2301},

pages = {97-132},

abstract = {Epigenomics studies require the combined analysis and integration of multiple types of data and annotations to extract biologically relevant information. In this context, sophisticated data visualization techniques are fundamental to identify meaningful patterns in the data in relation to the genomic coordinates. Data visualization for Hi-C contact matrices is even more complex as each data point represents the interaction between two distant genomic loci and their three-dimensional positioning must be considered. In this chapter we illustrate how to obtain sophisticated plots showing Hi-C data along with annotations for other genomic features and epigenomics data. For the example code used in this chapter we rely on a Bioconductor package able to handle even high-resolution Hi-C datasets. The provided examples are explained in details and highly customizable, thus facilitating their extension and adoption by end users for other studies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_426,

title = {Dysfunctional polycomb transcriptional repression contributes to lamin A/C-dependent muscular dystrophy.},

author = {Bianchi A and Mozzetta C and Pegoli G and Lucini F and Valsoni S and Rosti V and Petrini C and Cortesi A and Gregoretti F and Antonelli L and Oliva G and {De Bardi M} and Rizzi R and Bodega B and Pasini D and Ferrari F and Bearzi C and Lanzuolo C},

url = {https://www.jci.org/articles/view/128161},

doi = {10.1172/JCI128161},

year  = {2020},

date = {2020-01-01},

journal = {Journal of clinical investigation},

volume = {130},

number = {5},

pages = {2408-2421},

abstract = {Lamin A is a component of the inner nuclear membrane that, together with epigenetic factors, organizes the genome in higher order structures required for transcriptional control. Mutations in the lamin A/C gene cause several diseases belonging to the class of laminopathies, including muscular dystrophies. Nevertheless, molecular mechanisms involved in the pathogenesis of lamin A-dependent dystrophies are still largely unknown. The polycomb group (PcG) of proteins are epigenetic repressors and lamin A interactors, primarily involved in the maintenance of cell identity. Using a murine model of Emery-Dreifuss muscular dystrophy (EDMD), we show here that lamin A loss deregulated PcG positioning in muscle satellite stem cells, leading to derepression of non-muscle-specific genes and p16INK4a, a senescence driver encoded in the Cdkn2a locus. This aberrant transcriptional program caused impairment in self-renewal, loss of cell identity, and premature exhaustion of the quiescent satellite cell pool. Genetic ablation of the Cdkn2a locus restored muscle stem cell properties in lamin A/C-null dystrophic mice. Our findings establish a direct link between lamin A and PcG epigenetic silencing and indicate that lamin A-dependent muscular dystrophy can be ascribed to intrinsic epigenetic dysfunctions of muscle stem cells.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_462,

title = {HiCBricks: building blocks for efficient handling of large Hi-C datasets.},

author = {Pal K and Tagliaferri I and Livi CM and Ferrari F},

url = {https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz808/5614425},

doi = {10.1093/bioinformatics/btz808},

year  = {2020},

date = {2020-01-01},

journal = {Bioinformatics},

volume = {36},

number = {6},

pages = {1917-1919},

abstract = {Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high quality data visualization.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_477,

title = {SAMMY-seq reveals early alteration of heterochromatin and deregulation of bivalent genes in Hutchinson-Gilford Progeria Syndrome. },

author = {Sebestyen E and Marullo F and Lucini F and Petrini C and Bianchi A and Valsoni S and Olivieri I and Antonelli L and Gregoretti F and Oliva G and Ferrari F and Lanzuolo C},

url = {https://www.nature.com/articles/s41467-020-20048-9},

doi = {10.1038/s41467-020-20048-9},

year  = {2020},

date = {2020-01-01},

journal = {Nature communications},

volume = {11},

number = {1},

pages = {6274},

abstract = {Hutchinson-Gilford progeria syndrome is a genetic disease caused by an aberrant form of Lamin A resulting in chromatin structure disruption, in particular by interfering with lamina associated domains. Early molecular alterations involved in chromatin remodeling have not been identified thus far. Here, we present SAMMY-seq, a high-throughput sequencing-based method for genome-wide characterization of heterochromatin dynamics. Using SAMMY-seq, we detect early stage alterations of heterochromatin structure in progeria primary fibroblasts. These structural changes do not disrupt the distribution of H3K9me3 in early passage cells, thus suggesting that chromatin rearrangements precede H3K9me3 alterations described at later passages. On the other hand, we observe an interplay between changes in chromatin accessibility and Polycomb regulation, with site-specific H3K27me3 variations and transcriptional dysregulation of bivalent genes. We conclude that the correct assembly of lamina associated domains is functionally connected to the Polycomb repression and rapidly lost in early molecular events of progeria pathogenesis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y%_42,

title = {Computational Biology Solutions to Identify Enhancers-target Gene Pairs},

author = {Hariprakash JM and Ferrari F},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611831/},

doi = {10.1016/j.csbj.2019.06.012},

year  = {2019},

date = {2019-01-17},

journal = {Computational and structural biotechnology journal},

volume = {17},

pages = {821-831},

abstract = {Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_61,

title = {Global chromatin conformation differences in the Drosophila dosage compensated chromosome X.},

author = {Pal K and Forcato M and Jost D and Sexton T and Vaillant C and Salviato E and Mazza EMC and Lugli E and Cavalli G and Ferrari F},

url = {https://www.nature.com/articles/s41467-019-13350-8},

doi = {Nature Communications},

year  = {2019},

date = {2019-02-27},

journal = {Nature Communications},

volume = {25},

number = {10},

pages = {5355},

abstract = {In Drosophila melanogaster the single male chromosome X undergoes an average twofold transcriptional upregulation for balancing the transcriptional output between sexes. Previous literature hypothesised that a global change in chromosome structure may accompany this process. However, recent studies based on Hi-C failed to detect these differences. Here we show that global conformational differences are specifically present in the male chromosome X and detectable using Hi-C data on sex-sorted embryos, as well as male and female cell lines, by leveraging custom data analysis solutions. We find the male chromosome X has more mid-/long-range interactions. We also identify differences at structural domain boundaries containing BEAF-32 in conjunction with CP190 or Chromator. Weakening of these domain boundaries in male chromosome X co-localizes with the binding of the dosage compensation complex and its co-factor CLAMP, reported to enhance chromatin accessibility. Together, our data strongly indicate that chromosome X dosage compensation affects global chromosome structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_62,

title = {Hi-C analysis: from data generation to integration},

author = {Pal K and Forcato M and Ferrari F},

url = {https://link.springer.com/article/10.1007%2Fs12551-018-0489-1},

doi = {10.1007/s12551-018-0489-1},

year  = {2019},

date = {2019-02-21},

journal = {Biophysical reviews},

volume = {11},

number = {1},

pages = {67-78},

abstract = {In the epigenetics field, large-scale functional genomics datasets of ever-increasing size and complexity have been produced using experimental techniques based on high-throughput sequencing. In particular, the study of the 3D organization of chromatin has raised increasing interest, thanks to the development of advanced experimental techniques. In this context, Hi-C has been widely adopted as a high-throughput method to measure pairwise contacts between virtually any pair of genomic loci, thus yielding unprecedented challenges for analyzing and handling the resulting complex datasets. In this review, we focus on the increasing complexity of available Hi-C datasets, which parallels the adoption of novel protocol variants. We also review the complexity of the multiple data analysis steps required to preprocess Hi-C sequencing reads and extract biologically meaningful information. Finally, we discuss solutions for handling and visualizing such large genomics datasets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{%a1:%Y_63,

title = {HiCBricks: building blocks for efficient handling of large Hi-C datasets.},

author = {Pal K and Tagliaferri I and Livi CM and Ferrari F},

url = {https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz808/5614425},

doi = {10.1093/bioinformatics/btz808},

year  = {2019},

date = {2019-11-28},

journal = {Bioinformatics},

abstract = {Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high quality data visualization.},

keywords = {},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{%a1:%Y_183,

title = {WoPPER: Web server for Position Related data analysis of gene Expression in Prokaryotes.},

author = {Puccio S and Grillo G and Licciulli F and Severgnini M and Liuni S and Bicciato S and De Bellis G and Ferrari F and Peano C},

url = {https://academic.oup.com/nar/article/45/W1/W109/3782601},

doi = {10.1093/nar/gkx329},

year  = {2017},

date = {2017-07-13},

journal = {Nucleic Acids Research},

volume = {45},

number = {W1},

pages = {W109-W115},

abstract = {The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}