Author

Bruno G. Galuzzi

National Research CouncilORCID 0000-0002-8518-5352Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:statistical model· 4 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Assay:metabolomics· 2 Research Focus:batch correction / integration· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Chiara DamianiiD· 3 shared Daniela GaglioiD· 2 shared Lilia AlberghinaiD· 2 shared Marcella BonanomiiD· 2 shared Marco VanoniiD· 2 shared Alessandro GiammonaiD· 1 shared Alessia Lo DicoiD· 1 shared Alex GraudenziiD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersSystems Biology

Chiara DamianiORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Disrupting Pregnane X Receptor Signaling Overcomes Temozolomide Resistance in Glioblastoma via Succisa pratensis-Derived Metabolites

Francesca Servidio, Fabio Pirovano, Sofia Remedia, Chiara Pellizzer, Martina Nespoli, Bruno G. Galuzzi, Marcella Bonanomi, Sara Mallia, Mauro Commisso, Flavia Guzzo, Clarissa Gervasoni, Daniela Gaglio, Manuela Moriggi, Daniele Capitanio, Gloria Rita Bertoli, , Alessia Lo Dico

This paper shows that Succisa pratensis enhances temozolomide efficacy in glioblastoma by inducing metabolic vulnerability and impairing PXR signaling.

bioRxiv · Jun 26, 2026 · PreprintCancer Biology

Spatial Flux Balance Analysis reveals region-specific cancer metabolic rewiring and metastatic mimicking

Davide Maspero, Giovanni Marteletto, Francesco Lapi, Bruno G. Galuzzi, Irene Ruano, Ben Vandenbosch, Ke Yin, Sabine Tejpar, Alex Graudenzi, Holger Heyn, Anna Pascual‐Reguant, Chiara Damiani

The paper develops spFBA to analyze spatial metabolic differences in cancer, revealing metastatic mimicking and lactate-consuming cells in colorectal tumors.

npj Systems Biology and Applications · Jan 27, 2026Peer-reviewedSystems Biology

Mechanistically Informed Machine Learning Links Non-Canonical TCA Cycle Activity to Warburg Metabolism and Hallmarks of Malignancy

Lihao Lin, Lapi Francesco, Bruno G. Galuzzi, Marco Vanoni, Lilia Alberghina, Chiara Damiani

This study uses a computational framework to analyze non-canonical TCA cycle activity in cancer cell lines, linking it to Warburg metabolism and cancer hallmarks.

bioRxiv · Aug 1, 2025 · PreprintCancer Biology

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

Marzia Di Filippo, Dario Pescini, Bruno G. Galuzzi, Marcella Bonanomi, Daniela Gaglio, Eleonora Mangano, Clarissa Consolandi, Lilia Alberghina, Marco Vanoni, Chiara Damiani

INTEGRATE integrates metabolomics and transcriptomics data to identify metabolic flux regulation at the enzyme expression and metabolic levels in cancer cell lines.

PLoS Computational Biology · Feb 7, 2022Peer-reviewedSystems Biology