Publications

(For a full list see below)

1.
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
1.
Sayaman, R. W. et al. Germline genetic contribution to the immune landscape of cancer. Immunity 54, 367-386.e8 (2021). Cite Download
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
Caruso, F. P. et al. A map of tumor–host interactions in glioma at single-cell resolution. GigaScience 9, giaa109 (2020). Cite Download
1.
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
1.
Roelands, J. et al. Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response. J Immunother Cancer 8, (2020). Cite Download
1.
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
1.
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
1.
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
1.
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
1.
Dezső, Z. & Ceccarelli, M. Machine learning prediction of oncology drug targets based on protein and network properties. BMC Bioinformatics 21, 104 (2020). Cite Download
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
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
1.
D’Angelo, F. et al. The molecular landscape of glioma in patients with Neurofibromatosis 1. Nat Med 25, 176–187 (2019). Cite Download
1.
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
1.
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
1.
Silva, T. C. et al. TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data. F1000Research 7, 439 (2018). Cite Download
1.
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
1.
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
1.
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
1.
Frattini, V. et al. A metabolic function of FGFR3-TACC3 gene fusions in cancer. Nature 553, 222–227 (2018). Cite Download
1.
Yuan, J. et al. Single-cell transcriptome analysis of lineage diversity in high-grade glioma. Genome Medicine 10, (2018). Cite Download
1.
Rosenberg, S. et al. A recurrent point mutation in PRKCA is a hallmark of chordoid gliomas. Nature Communications 9, (2018). Cite Download
1.
Pascarella, A. et al. DNAJC17 is localized in nuclear speckles and interacts with splicing machinery components. Scientific Reports 8, (2018). Cite Download
1.
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
1.
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
1.
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
1.
Mall, R. et al. Differential Community Detection in Paired Biological Networks. (2017) http://doi.org/10.1101/147538. Cite
1.
Roelands, J. et al. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification. F1000Research 6, 296 (2017). Cite Download
1.
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
1.
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
1.
Ventola, G. M. M. et al. Identification of long non-coding transcripts with feature selection: a comparative study. BMC Bioinformatics 18, (2017). Cite Download
1.
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
1.
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