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416 results on '"Dal Bo, Michele"'

10. KRAS, NRAS, and BRAF mutations are highly enriched in trisomy 12 chronic lymphocytic leukemia and are associated with shorter treatment-free survival

Author

Vendramini, Elena, Bomben, Riccardo, Pozzo, Federico, Benedetti, Dania, Bittolo, Tamara, Rossi, Francesca Maria, Dal Bo, Michele, Rabe, Kari G., Pozzato, Gabriele, Zaja, Francesco, Chiarenza, Annalisa, Di Raimondo, Francesco, Braggio, Esteban, Parikh, Sameer A., Kay, Neil E., Shanafelt, Tait D., Del Poeta, Giovanni, Gattei, Valter, and Zucchetto, Antonella

Published
2019
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11. Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

Author

Dal Bo, Michele, primary, Polano, Maurizio, additional, Ius, Tamara, additional, Di Cintio, Federica, additional, Mondello, Alessia, additional, Manini, Ivana, additional, Pegolo, Enrico, additional, Cesselli, Daniela, additional, Di Loreto, Carla, additional, Skrap, Miran, additional, and Toffoli, Giuseppe, additional

Published
2023
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12. Targeted chitosan nanobubbles as a strategy to down-regulate microRNA-17 into B-cell lymphoma models

Author

Capolla, Sara, primary, Argenziano, Monica, additional, Bozzer, Sara, additional, D’Agaro, Tiziana, additional, Bittolo, Tamara, additional, De Leo, Luigina, additional, Not, Tarcisio, additional, Busato, Davide, additional, Dal Bo, Michele, additional, Toffoli, Giuseppe, additional, Cavalli, Roberta, additional, Gattei, Valter, additional, Bomben, Riccardo, additional, and Macor, Paolo, additional

Published
2023
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13. CCR Translation for this Article from Expression of Mutated IGHV3-23 Genes in Chronic Lymphocytic Leukemia Identifies a Disease Subset with Peculiar Clinical and Biological Features

Author

Bomben, Riccardo, primary, Dal-Bo, Michele, primary, Benedetti, Dania, primary, Capello, Daniela, primary, Forconi, Francesco, primary, Marconi, Daniela, primary, Bertoni, Francesco, primary, Maffei, Rossana, primary, Laurenti, Luca, primary, Rossi, Davide, primary, Del Principe, Maria Ilaria, primary, Luciano, Fabrizio, primary, Sozzi, Elisa, primary, Cattarossi, Ilaria, primary, Zucchetto, Antonella, primary, Rossi, Francesca Maria, primary, Bulian, Pietro, primary, Zucca, Emanuele, primary, Nicoloso, Milena S., primary, Degan, Massimo, primary, Marasca, Roberto, primary, Efremov, Dimitar G., primary, Del Poeta, Giovanni, primary, Gaidano, Gianluca, primary, and Gattei, Valter, primary

Published
2023
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14. Supplementary Data from Expression of Mutated IGHV3-23 Genes in Chronic Lymphocytic Leukemia Identifies a Disease Subset with Peculiar Clinical and Biological Features

Author

Bomben, Riccardo, primary, Dal-Bo, Michele, primary, Benedetti, Dania, primary, Capello, Daniela, primary, Forconi, Francesco, primary, Marconi, Daniela, primary, Bertoni, Francesco, primary, Maffei, Rossana, primary, Laurenti, Luca, primary, Rossi, Davide, primary, Del Principe, Maria Ilaria, primary, Luciano, Fabrizio, primary, Sozzi, Elisa, primary, Cattarossi, Ilaria, primary, Zucchetto, Antonella, primary, Rossi, Francesca Maria, primary, Bulian, Pietro, primary, Zucca, Emanuele, primary, Nicoloso, Milena S., primary, Degan, Massimo, primary, Marasca, Roberto, primary, Efremov, Dimitar G., primary, Del Poeta, Giovanni, primary, Gaidano, Gianluca, primary, and Gattei, Valter, primary

Published
2023
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15. Supplementary Table 1 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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16. Data from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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17. Supplementary Table 2 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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18. Supplementary Figures 2-5 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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19. Supplementary Figure 1 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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20. Supplementary Methods and Materials, Figure Legends 1-5 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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21. Supplementary Tables 3-4 from CD38/CD31, the CCL3 and CCL4 Chemokines, and CD49d/Vascular Cell Adhesion Molecule-1 Are Interchained by Sequential Events Sustaining Chronic Lymphocytic Leukemia Cell Survival

Author

Zucchetto, Antonella, primary, Benedetti, Dania, primary, Tripodo, Claudio, primary, Bomben, Riccardo, primary, Dal Bo, Michele, primary, Marconi, Daniela, primary, Bossi, Fleur, primary, Lorenzon, Debora, primary, Degan, Massimo, primary, Rossi, Francesca Maria, primary, Rossi, Davide, primary, Bulian, Pietro, primary, Franco, Vito, primary, Del Poeta, Giovanni, primary, Deaglio, Silvia, primary, Gaidano, Gianluca, primary, Tedesco, Francesco, primary, Malavasi, Fabio, primary, and Gattei, Valter, primary

Published
2023
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22. Machine Learning Application Identifies Germline Markers of Hypertension in Patients With Ovarian Cancer Treated With Carboplatin, Taxane, and Bevacizumab.

Author

Polano, Maurizio, Bedon, Luca, Dal Bo, Michele, Sorio, Roberto, Bartoletti, Michele, De Mattia, Elena, Cecchin, Erika, Pisano, Carmela, Lorusso, Domenica, Lissoni, Andrea Alberto, De Censi, Andrea, Cecere, Sabrina Chiara, Scollo, Paolo, Marchini, Sergio, Arenare, Laura, De Giorgi, Ugo, Califano, Daniela, Biagioli, Elena, Chiodini, Paolo, and Perrone, Francesco

Subjects
OVARIAN cancer, CANCER patients, MACHINE learning, HYPERTENSION, BEVACIZUMAB, GENETIC variation, PRECISION farming
Abstract

Pharmacogenomics studies how genes influence a person's response to treatment. When complex phenotypes are influenced by multiple genetic variations with little effect, a single piece of genetic information is often insufficient to explain this variability. The application of machine learning (ML) in pharmacogenomics holds great potential — namely, it can be used to unravel complicated genetic relationships that could explain response to therapy. In this study, ML techniques were used to investigate the relationship between genetic variations affecting more than 60 candidate genes and carboplatin‐induced, taxane‐induced, and bevacizumab‐induced toxicities in 171 patients with ovarian cancer enrolled in the MITO‐16A/MaNGO‐OV2A trial. Single‐nucleotide variation (SNV, formerly SNP) profiles were examined using ML to find and prioritize those associated with drug‐induced toxicities, specifically hypertension, hematological toxicity, nonhematological toxicity, and proteinuria. The Boruta algorithm was used in cross‐validation to determine the significance of SNVs in predicting toxicities. Important SNVs were then used to train eXtreme gradient boosting models. During cross‐validation, the models achieved reliable performance with a Matthews correlation coefficient ranging from 0.375 to 0.410. A total of 43 SNVs critical for predicting toxicity were identified. For each toxicity, key SNVs were used to create a polygenic toxicity risk score that effectively divided individuals into high‐risk and low‐risk categories. In particular, compared with low‐risk individuals, high‐risk patients were 28‐fold more likely to develop hypertension. The proposed method provided insightful data to improve precision medicine for patients with ovarian cancer, which may be useful for reducing toxicities and improving toxicity management. [ABSTRACT FROM AUTHOR]

Published
2023
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34. B-cell chronic lymphocytic leukemia

Author

Bertoni, Francesco, primary, Forconi, Francesco, additional, Dal-Bo, Michele, additional, Zucchetto, Antonella, additional, Bomben, Riccardo, additional, Poeta, Giovanni Del, additional, and Gattei, Valter, additional

Published
2013
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37. The Dual Role of the Liver in Nanomedicine as an Actor in the Elimination of Nanostructures or a Therapeutic Target

Author

Baboci, Lorena, Capolla, Sara, Di Cintio, Federica, Colombo, Federico, Mauro, Prisca, Dal Bo, Michele, Argenziano, Monica, Cavalli, Roberta, Toffoli, Giuseppe, and Macor, Paolo

Subjects
Article Subject
Abstract

The development of nanostructures for therapeutic purpose is rapidly growing, following the results obtained in vivo in animal models and in the clinical trials. Unfortunately, the potential therapeutic efficacy is not completely exploited, yet. This is mainly due to the fast clearance of the nanostructures in the body. Nanoparticles and the liver have a unique interaction because the liver represents one of the major barriers for drug delivery. This interaction becomes even more relevant and complex when the drug delivery strategies employing nanostructures are proposed for the therapy of liver diseases, such as hepatocellular carcinoma (HCC). In this case, the selective delivery of therapeutic nanoparticles to the tumor microenvironment collides with the tendency of nanostructures to be quickly eliminated by the organ. The design of a new therapeutic approach based on nanoparticles to treat HCC has to particularly take into consideration passive and active mechanisms to avoid or delay liver elimination and to specifically address cancer cells or the cancer microenvironment. This review will analyze the different aspects concerning the dual role of the liver, both as an organ carrying out a clearance activity for the nanostructures and as target for therapeutic strategies for HCC treatment.

Published
2020
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41. Machine Learning Application in a Phase I Clinical Trial Allows for the Identification of Clinical‐Biomolecular Markers Significantly Associated With Toxicity.

Author

Bedon, Luca, Cecchin, Erika, Fabbiani, Emanuele, Dal Bo, Michele, Buonadonna, Angela, Polano, Maurizio, and Toffoli, Giuseppe

Subjects
BEVACIZUMAB, ASPARTATE aminotransferase, MACHINE learning, RANDOM forest algorithms, CLINICAL trials, ELECTRONIC health records, BIOCHEMISTRY
Abstract

Machine learning (ML) algorithms have been used to forecast clinical outcomes or drug adverse effects by analyzing different data sets such as electronic health records, diagnostic data, and molecular data. However, ML implementation in phase I clinical trial is still an unexplored strategy that implies challenges such as the selection of the best development strategy when dealing with limited sample size. In the attempt to better define prechemotherapy baseline clinical and biomolecular predictors of drug toxicity, we trained and compared five ML algorithms starting from clinical, blood biochemistry, and genotype data derived from a previous phase Ib study aimed to define the maximum tolerated dose of irinotecan (FOLFIRI (folinic acid, fluorouracil, and irinotecan) plus bevacizumab regimen) in patients with metastatic colorectal cancer. During cross‐validation the Random Forest algorithm achieved the best performance with a mean Matthews correlation coefficient of 0.549 and a mean accuracy of 80.4%; the best predictors of dose‐limiting toxicity at baseline were hemoglobin, serum glutamic oxaloacetic transaminase (SGOT), and albumin. The feasibility of a prediction model prototype was in principle assessed using the two distinct dose escalation cohorts, where in the validation cohort the model scored a Matthews correlation coefficient of 0.59 and an accuracy of 82.0%. Moreover, we found a strong relationship between SGOT and irinotecan pharmacokinetics, suggesting its role as surrogates' estimators of the irinotecan metabolism equilibrium. In conclusion, the potential application of ML techniques to phase I study could provide clinicians with early prediction tools useful both to ameliorate the management of clinical trials and to make more adequate treatment decisions. [ABSTRACT FROM AUTHOR]

Published
2022
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44. SF3B1-mutated chronic lymphocytic leukemia shows evidence of NOTCH1 pathway activation including CD20 downregulation

Author

Pozzo, Federico, primary, Bittolo, Tamara, additional, Tissino, Erika, additional, Vit, Filippo, additional, Vendramini, Elena, additional, Laurenti, Luca, additional, D’Arena, Giovanni, additional, Olivieri, Jacopo, additional, Pozzato, Gabriele, additional, Zaja, Francesco, additional, Chiarenza, Annalisa, additional, Di Raimondo, Francesco, additional, Zucchetto, Antonella, additional, Bomben, Riccardo, additional, Rossi, Francesca Maria, additional, Del Poeta, Giovanni, additional, Dal Bo, Michele, additional, and Gattei, Valter, additional

Published
2020
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46. A Novel Comprehensive Clinical Stratification Model to Refine Prognosis of Glioblastoma Patients Undergoing Surgical Resection

Author

Ius, Tamara, primary, Pignotti, Fabrizio, additional, Della Pepa, Giuseppe Maria, additional, La Rocca, Giuseppe, additional, Somma, Teresa, additional, Isola, Miriam, additional, Battistella, Claudio, additional, Gaudino, Simona, additional, Polano, Maurizio, additional, Dal Bo, Michele, additional, Bagatto, Daniele, additional, Pegolo, Enrico, additional, Chiesa, Silvia, additional, Arcicasa, Mauro, additional, Olivi, Alessandro, additional, Skrap, Miran, additional, and Sabatino, Giovanni, additional

Published
2020
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48. Molecular and clinical features of chronic lymphocytic leukaemia with stereotyped B cell receptors: results from an Italian multicentre study

Author

Bomben, Riccardo, Dal Bo, Michele, Capello, Daniela, Forconi, Francesco, Maffei, Rossana, Laurenti, Luca, Rossi, Davide, Del Principe, Maria Ilaria, Zucchetto, Antonella, Bertoni, Francesco, Rossi, Francesca Maria, Bulian, Pietro, Cattarossi, Ilaria, Ilariucci, Fiorella, Sozzi, Elisa, Spina, Valeria, Zucca, Emanuele, Degan, Massimo, Lauria, Francesco, Del Poeta, Giovanni, Efremov, Dimitar G., Marasca, Roberto, Gaidano, Gianluca, and Gattei, Valter

Published
2009

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