Publications

(For a full list see below)

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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
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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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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 (2020) http://doi.org/10.1038/s41416-020-01145-4. Cite
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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
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Angelova, M. et al. Evolution of Metastases in Space and Time under Immune Selection. Cell (2018) http://doi.org/10.1016/j.cell.2018.09.018. Cite
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De Marco, C. et al. Specific gene expression signatures induced by the multiple oncogenic alterations that occur within the PTEN/PI3K/AKT pathway in lung cancer. PLOS ONE 12, e0178865 (2017). Cite
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Silva, T. C. et al. TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data. (2017) http://doi.org/10.1101/147496. Cite Download
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Mall, R. et al. Differential Community Detection in Paired Biological Networks. (2017) http://doi.org/10.1101/147538. Cite
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Roelands, J. et al. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification. F1000Research 6, 296 (2017). Cite Download
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Pancione, M. et al. Emerging insight into MAPK inhibitors and immunotherapy in colorectal cancer. Curr. Med. Chem. (2017) http://doi.org/10.2174/0929867324666170227114356. Cite
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Hendrickx, W. et al. Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis. OncoImmunology e1253654 (2017) http://doi.org/10.1080/2162402X.2016.1253654. Cite
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Ventola, G. M. M. et al. Identification of long non-coding transcripts with feature selection: a comparative study. BMC Bioinformatics 18, (2017). Cite Download
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Mall, R., Cerulo, L., Bensmail, H., Iavarone, A. & Ceccarelli, M. Detection of statistically significant network changes in complex biological networks. BMC Systems Biology 11, (2017). Cite
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Mall, R. et al. RGBM: Regularized Gradient Boosting Machines For The Identification of Transcriptional Regulators Of Discrete Glioma Subtypes. bioRxiv (2017) http://doi.org/10.1101/132670. Cite
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Porreca, I. et al. Pesticide toxicogenomics across scales: in vitro transcriptome predicts mechanisms and outcomes of exposure in vivo. Scientific Reports 6, 38131 (2016). Cite
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Agnihotri, S. et al. The genomic landscape of schwannoma. Nat. Genet. 48, 1339–1348 (2016). Cite
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Petrizzo, A. et al. Identification and Validation of HCC-specific Gene Transcriptional Signature for Tumor Antigen Discovery. Sci Rep 6, 29258 (2016). Cite
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Silva, T. C. et al. TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages. F1000Research 5, 1542 (2016). Cite