Publications

(For a full list see below)

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Bertucci, F. et al. Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature. J Immunother Cancer 10, e003687 (2022). Cite Download
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McLaughlin, R. T. et al. Attentive deep learning-based tumor-only somatic mutation classifier achieves high accuracy agnostic of tissue type and capture kit. http://biorxiv.org/lookup/doi/10.1101/2021.12.07.471513 (2021) doi:10.1101/2021.12.07.471513. Cite Download
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De Falco, A., Caruso, F. P., Su, X. D., Iavarone, A. & Ceccarelli, M. A fast variational algorithm to detect the clonal copy number substructure of tumors from single-cell data. http://biorxiv.org/lookup/doi/10.1101/2021.11.20.469390 (2021) doi:10.1101/2021.11.20.469390. Cite Download
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Petralia, F. et al. BayesDeBulk: A Flexible Bayesian Algorithm for the Deconvolution of Bulk Tumor Data. http://biorxiv.org/lookup/doi/10.1101/2021.06.25.449763 (2021) doi:10.1101/2021.06.25.449763. Cite Download
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Mall, R. et al. Network-based identification of key master regulators associated with an immune-silent cancer phenotype. Briefings in Bioinformatics bbab168 (2021) http://doi.org/10.1093/bib/bbab168. Cite Download
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Paladino, A., D’Angelo, F., Noviello, T. M. R., Iavarone, A. & Ceccarelli, M. Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach. J. Chem. Inf. Model. acs.jcim.1c00296 (2021) http://doi.org/10.1021/acs.jcim.1c00296. Cite Download
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Caruso, F. P., Scala, G., Cerulo, L. & Ceccarelli, M. A review of COVID-19 biomarkers and drug targets: resources and tools. Briefings in Bioinformatics 22, 701–713 (2021). Cite Download
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Petrillo, F. et al. Dysregulation of Principal Cell miRNAs Facilitates Epigenetic Regulation of AQP2 and Results in Nephrogenic Diabetes Insipidus. J Am Soc Nephrol (2021) http://doi.org/10.1681/ASN.2020010031. Cite
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Di Munno, C. et al. Adaptive Thermogenesis Driving Catch-Up Fat Is Associated With Increased Muscle Type 3 and Decreased Hepatic Type 1 Iodothyronine Deiodinase Activities: A Functional and Proteomic Study. Front. Endocrinol. 12, 631176 (2021). Cite
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De Marco, C. et al. Genome-wide analysis of copy number alterations led to the characterisation of PDCD10 as oncogene in ovarian cancer. Translational Oncology 14, 101013 (2021). Cite Download
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Turan, T. et al. A balance score between immune stimulatory and suppressive microenvironments identifies mediators of tumour immunity and predicts pan-cancer survival. Br J Cancer 124, 760–769 (2021). Cite Download
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Sayaman, R. W. et al. Germline genetic contribution to the immune landscape of cancer. Immunity 54, 367-386.e8 (2021). Cite Download
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Garofano, L. et al. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer (2021) http://doi.org/10.1038/s43018-020-00159-4. Cite Download
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Maio, M. et al. A vision of immuno-oncology: the Siena think tank of the Italian network for tumor biotherapy (NIBIT) foundation. J Exp Clin Cancer Res 40, 240 (2021). Cite Download
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Wang, L.-B. et al. Proteogenomic and metabolomic characterization of human glioblastoma. Cancer Cell (2021) http://doi.org/10.1016/j.ccell.2021.01.006. Cite Download
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Remo, A. et al. Wnt (canonical and non canonical) pathways in Breast carcinoma with extensive vascular invasion and Inflammatory Breast Carcinoma. Pathology-Research and Practice 153347 (2021). Cite Download
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Pagano, M. et al. Mi-RNA-888-5p Is Involved in S-Adenosylmethionine Antitumor Effects in Laryngeal Squamous Cancer Cells. Cancers 12, 3665 (2020). Cite Download
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Blomquist, M. R. et al. Temporospatial genomic profiling in glioblastoma identifies commonly altered core pathways underlying tumor progression. Neurooncol Adv 2, vdaa078 (2020). Cite Download
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Noviello, T. M. R., Ceccarelli, F., Ceccarelli, M. & Cerulo, L. Deep learning predicts short non-coding RNA functions from only raw sequence data. PLoS Comput Biol 16, e1008415 (2020). Cite Download
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de Falco, A. et al. Adaptive One-Class gaussian processes allow accurate prioritization of oncology drug targets. Bioinformatics btaa968 (2020) http://doi.org/10.1093/bioinformatics/btaa968. Cite Download
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Caruso, F. P., Scala, Giovanni, Cerulo, L. & Ceccarelli, M. A review of COVID-19 biomarkers and drug targets: resources and tools. Briefings in Bioinformatics (2020) http://doi.org/10.1093/bib/bbaa328. Cite Download
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Caruso, F. P. et al. A map of tumor–host interactions in glioma at single-cell resolution. GigaScience 9, giaa109 (2020). Cite Download
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Noviello, T. M. R., Ceccarelli, M. & Cerulo, L. Deep learning predicts non-coding RNA functions from only raw sequence data. http://biorxiv.org/lookup/doi/10.1101/2020.05.27.118778 (2020) doi:10.1101/2020.05.27.118778. Cite Download
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Roelands, J. et al. Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response. J Immunother Cancer 8, (2020). Cite Download
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Sayaman, R. W. et al. Germline genetic contribution to the immune landscape of cancer. http://biorxiv.org/lookup/doi/10.1101/2020.01.30.926527 (2020) doi:10.1101/2020.01.30.926527. Cite Download
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Tagliaferri, D. et al. Retinoic Acid Induces Embryonic Stem Cells (ESCs) Transition to 2 Cell-Like State Through a Coordinated Expression of Dux and Duxbl1. Front. Cell Dev. Biol. 7, 385 (2020). Cite Download
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Alexander, J. et al. Multimodal single‐cell analysis reveals distinct radioresistant stem‐like and progenitor cell populations in murine glioma. Glia 68, 2486–2502 (2020). Cite Download
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Sa, J. K. et al. Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma. Genome Biol 21, 216 (2020). Cite Download
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Dezső, Z. & Ceccarelli, M. Machine learning prediction of oncology drug targets based on protein and network properties. BMC Bioinformatics 21, 104 (2020). Cite Download
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Mauriello, A. et al. High Somatic Mutation and Neoantigen Burden Do Not Correlate with Decreased Progression-Free Survival in HCC Patients not Undergoing Immunotherapy. Cancers (Basel) 11, (2019). Cite Download
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Caruso, F. P. et al. A MAP of tumor-host interactions in glioma at single cell resolution. http://biorxiv.org/lookup/doi/10.1101/827758 (2019) doi:10.1101/827758. Cite Download
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Di Iorio, B. R. et al. Treatment of metabolic acidosis with sodium bicarbonate delays progression of chronic kidney disease: the UBI Study. J. Nephrol. (2019) http://doi.org/10.1007/s40620-019-00656-5. Cite Download
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Guerriero, I. et al. Exploring the Molecular Crosstalk between Pancreatic Bud and Mesenchyme in Embryogenesis: Novel Signals Involved. Int J Mol Sci 20, (2019). Cite Download
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Bedognetti, D. et al. Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop. J Immunother Cancer 7, 131 (2019). Cite Download
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Roelands, J. et al. Genomic landscape of tumor-host interactions with differential prognostic and predictive connotations. http://biorxiv.org/lookup/doi/10.1101/546069 (2019) doi:10.1101/546069. Cite Download
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Silvestri, E. et al. 3,5-Diiodo-L-Thyronine Exerts Metabolically Favorable Effects on Visceral Adipose Tissue of Rats Receiving a High-Fat Diet. Nutrients 11, 278 (2019). Cite Download
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Zhang, J. et al. The combination of neoantigen quality and T lymphocyte infiltrates identifies glioblastomas with the longest survival. Communications Biology 2, (2019). Cite Download
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Giordano, G. et al. JAK/Stat5-mediated subtype-specific lymphocyte antigen 6 complex, locus G6D (LY6G6D) expression drives mismatch repair proficient colorectal cancer. Journal of Experimental & Clinical Cancer Research 38, (2019). Cite Download
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Monaco, G. et al. RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types. Cell Reports 26, 1627-1640.e7 (2019). Cite Download
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D’Angelo, F. et al. The molecular landscape of glioma in patients with Neurofibromatosis 1. Nat Med 25, 176–187 (2019). Cite Download
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Bertucci, F. et al. The immunologic constant of rejection classification refines the prognostic value of conventional prognostic signatures in breast cancer. British Journal of Cancer (2018) http://doi.org/10.1038/s41416-018-0309-1. Cite Download
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Ferreira, L. A. M. et al. Circulating microRNAs expression profile in newly diagnosed and imatinib treated chronic phase – chronic myeloid leukemia. Leukemia & Lymphoma 1–7 (2018) http://doi.org/10.1080/10428194.2018.1499905. Cite
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Silva, T. C. et al. TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data. F1000Research 7, 439 (2018). Cite Download
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Mall, R., Ullah, E., Kunji, K., Ceccarelli, M. & Bensmail, H. An unsupervised disease module identification technique in biological networks using novel quality metric based on connectivity, conductance and modularity. F1000Research 7, 378 (2018). Cite Download
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Silvestri, E. et al. 3,5-Diiodo-L-Thyronine Affects Structural and Metabolic Features of Skeletal Muscle Mitochondria in High-Fat-Diet Fed Rats Producing a Co-adaptation to the Glycolytic Fiber Phenotype. Frontiers in Physiology 9, (2018). Cite
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Mall, R. et al. RGBM: regularized gradient boosting machines for identification of the transcriptional regulators of discrete glioma subtypes. Nucleic Acids Research (2018) http://doi.org/10.1093/nar/gky015. Cite Download
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Frattini, V. et al. A metabolic function of FGFR3-TACC3 gene fusions in cancer. Nature 553, 222–227 (2018). Cite Download
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Yuan, J. et al. Single-cell transcriptome analysis of lineage diversity in high-grade glioma. Genome Medicine 10, (2018). Cite Download
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Rosenberg, S. et al. A recurrent point mutation in PRKCA is a hallmark of chordoid gliomas. Nature Communications 9, (2018). Cite Download
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Pascarella, A. et al. DNAJC17 is localized in nuclear speckles and interacts with splicing machinery components. Scientific Reports 8, (2018). Cite Download