Ricerca Gruppi di ricerca e contributi alla ricercaThe Section of BiochemistryGruppo Benelli

Gruppo Benelli

 Cancer Omics Laboratory

CAOS Lab

 

Coordinator

Name: Matteo Benelli

Position: Associate Professor of Biochemistry

e-mail: matteo.benelli@unifi.it

phone: +39 055 2751238

 

Brief Biographical sketch of the Coordinator

 

Matteo Benelli earned a Master's degree in Physics from the University of Florence and completed his Ph.D. in Non-linear Dynamics and Complex Systems at the same institution, focusing on developing computational methods in genomics. He then joined the Laboratory of Computational and Functional Oncology at the University of Trento as a postdoc fellow, investigating the genomics and epigenetics of advanced prostate cancer under the supervision of Prof. Francesca Demichelis. In 2017, Dr. Benelli became a group leader at the Oncology Department of the Hospital of Prato, led by Dr. Angelo Di Leo. There, he established a new research group dedicated to breast cancer omics and their translational applications. In 2021, Dr. Benelli was appointed as co-Principal Investigator and coordinator of the Data Analysis Committee of the multi-national AURORA-EU program, dedicated to molecular characterization of metastatic breast cancer. In 2024, Matteo Benelli assumed the role of Associate Professor of Biochemistry at the University of Florence.

 

Member of the following Boards

• Member of the Steering Committee and Coordinator of the Data Analysis Committee of the AURORA-EU program (NCT02102165)

 

Research Team

The Cancer Omics lab is composed of members with diverse backgrounds, encompassing both computational and wet-lab expertise.

 

• Francesco Santaniello - PhD, Senior bioinformatician, francesco.santaniello@unifi.it
• Dario Romagnoli - PhD, Post-doctoral fellow, dario.romagnoli@unifi.it
• Simone Romagnoli – PhD, Post-doctoral fellow, simone.romagnoli@unifi.it
• Marta Paoli, MSc - PhD Student (in collaboration with Prof. Francesca Demichelis), marta.paoli@unitn.it
• Sara Malinconi – MSc,  Research fellow, sara.malinconi@unifi.it
• Tommaso Orioli – MSc, Research fellow, tommaso.orioli@unifi.it
• Michela Palma – Meng, Research fellow (in collaboration with Fondazione Sandro Pitigliani per la lotta contro i tumori ONLUS), michela.palma@uslcentro.toscana.it

Current research interest

The Cancer Omics Laboratory (CAOS lab) conducts research in cancer omics to address fundamental questions in oncology concerning cancer origin, evolution, progression and resistance to treatment. The CAOS lab performs integrative analyses of multi-omics data, develops new computational approaches and experimental strategies, with a particular emphasis on translational applications, especially liquid biopsy, and with the final goal of identifying new prognostic and predictive molecular and/or imaging biomarkers. A summary of current research interests is reported below.

 

Cancer epigenetics and translational applications. Cancer cells exhibit DNA methylation alterations, which lead to dysregulation in gene expression and may impact genome integrity. These epigenetic changes play a crucial role in the initiation and progression of cancer. Our laboratory investigates the significance of these epigenetic alterations, focusing on their utility as biomarkers to inform about molecular phenotypes, to elucidate altered pathways and their application in liquid biopsy techniques.

 

Integrative analysis of multi-omics cancer data. Cancer is a multifaceted disease originating from alterations of diverse biological mechanisms. Using bioinformatics and machine learning approaches, integrative analysis of multi-omics data enables a comprehensive view of the intricate interactions and dysregulations affecting cancer cells. Our laboratory is involved in AURORA-EU, a large collaborative multi-national project coordinated by Breast International Group (BIG) aimed at improving the understanding of metastatic breast cancer through extensive, multi-omics profiling of paired primary tumors and metastatic biopsy samples.

 

Computational radiomics. Radiomics refers to the process of extracting and analyzing data from clinical imaging such as CT, MRI, PET and Mammography. The extension of radiomics through its association with molecular omics, referred to as radiogenomics, has shown promising applications, such as informing about relevant genomic alterations, predicting gene expressions patterns and genomic heterogeneity. Our laboratory works on the development of new computational methods for the analysis of radiomics datasets and applies machine learning methods for the development of radiomics-based predictors of patients’ outcome and/or cancer phenotypes.

 

Key words

CANCER, ONCOLOGY, GENOMICS, EPIGENETICS, OMICS, COMPUTATIONAL BIOLOGY, BIOINFORMATICS, DATA ANALYSIS, DATA SCIENCE, MACHINE LEARNING, RADIOMICS, BREAST CANCER, TREATMENT RESISTANCE, BIOMARKERS, LIQUID BIOPSY, TRANSLATIONAL RESEARCH

 

Current/recent sources of funding

 

• Dipartimento di Eccellenza (Gender Medicine and single-cell omics) 2024, Principal Investigator
• AIRC Investigator Grant (IG) 2022-2027, Principal Investigator
• Fondazione CR Firenze 2020-2023, Principal Investigator
• Breast International Group (BIG) 2020-current, Principal Investigator
• Ministero della Salute - Ricerca Finalizzata 2019-2025, Collaborator
• Ministero della Salute - Ricerca Finalizzata 2018-2024, Principal Investigator
• Fondazione CR Firenze 2017-2020, Principal Investigator

 

10 best publications (years 2018-2023)

 

1. Romagnoli D, Nardone A, Galardi F, Paoli M, De Luca F, Biagioni C, Franceschini GM, Pestrin M, Sanna G, Moretti E, Demichelis F, Migliaccio I, Biganzoli L, Malorni L, Benelli M. MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples. Briefings in Bioinformatics 2023 24(2): bbad015.
2. Migliaccio I, Paoli M, Risi E, Biagioni C, Biganzoli L, Benelli M^#, Malorni L^#. PIK3CA co-occurring mutations and copy-number gain in hormone receptor positive and HER2 negative breast cancer. NPJ breast cancer 2022 8 (1), 1-10. # co-senior authorship
3. Benelli M*, Franceschini GM*, Magi A, Romagnoli D, Biagioni C, Migliaccio I, Malorni L, Demichelis F. Charting differentially methylated regions in cancer with Rocker-meth. Commun Biol. 2021. *co-first authorship
4. Aftimos P, Oliveira M, Irrthum A, Fumagalli D, Sotiriou C, Nili Gal-Yam E, Robson ME, Ndozeng J, Di Leo A, Ciruelos EM, de Azambuja E, Viale G, Scheepers ED, Curigliano G, Bliss JM, Reis-Filho JS, Colleoni M, Balic M, Cardoso F, Albanell J, Duhem C, Marreaud S, Romagnoli D, Rojas B, Gombos A, Wildiers H, Guerrero-Zotano A, Hall P, Bonetti A, Larsson KF, Degiorgis M, Khodaverdi S, Greil R, Sverrisdottir A, Paoli M, Seyll E, Loibl S, Linderholm B, Zoppoli G, Davidson NE, Johannsson OT, Bedard PL, Loi S, Knox S, Cameron DA, Harbeck N, Lasa Montoya M, Brandão M, Vingiani A, Caballero C, Hilbers FS, Yates LR, Benelli M, Venet D, Piccart MJ. Genomic and transcriptomic analyses of breast cancer primaries and matched metastases in AURORA, the Breast International Group (BIG) molecular screening initiative. Cancer Discov. 2021 Jun 28:candisc.1647.2020.
5. Benelli M, Barucci A, Zoppetti N, Calusi S, Redapi L, Della Gala G, Piffer S, Bernardi L, Fusi F, Pallotta S. Comprehensive Analysis of Radiomic Datasets by RadAR. Cancer Res. 2020 Aug 1;80(15):3170-3174.
6. Galardi F, Luca F, Romagnoli D, Biagioni C, Moretti E, Biganzoli L, Di Leo A, Migliaccio I, Malorni L, Benelli M. Cell-Free DNA-Methylation-Based Methods and Applications in Oncology. Biomolecules. 2020 Dec 15;10(12):1677.
7. Beltran H, Romanel A, Conteduca V, Casiraghi N, Sigouros M, Franceschini GM, Orlando F, Fedrizzi T, Ku SY, Dann E, Alonso A, Mosquera JM, Sboner A, Xiang J, Elemento O, Nanus DM, Tagawa ST, Benelli M, Demichelis F. Circulating tumor DNA profile recognizes transformation to castration-resistant neuroendocrine prostate cancer. J Clin Invest. 2020 Apr 1;130(4):1653-1668.
8. Abida W, Cyrta J, Heller G, Prandi D, Armenia J, Coleman I, Cieslik M, Benelli M, Robinson D, Van Allen EM, Sboner A, Fedrizzi T, Mosquera JM, Robinson BD, De Sarkar N, Kunju LP, Tomlins S, Wu YM, Nava Rodrigues D, Loda M, Gopalan A, Reuter VE, Pritchard CC, Mateo J, Bianchini D, Miranda S, Carreira S, Rescigno P, Filipenko J, Vinson J, Montgomery RB, Beltran H, Heath EI, Scher HI, Kantoff PW, Taplin ME, Schultz N, deBono JS, Demichelis F, Nelson PS, Rubin MA, Chinnaiyan AM, Sawyers CL. Genomic correlates of clinical outcome in advanced prostate cancer. Proc Natl Acad Sci U S A. 2019 Jun 4;116(23):11428-11436.
9. Pietrantonio F, Randon G, Romagnoli D, Di Donato S, Benelli M, de Braud F. Biomarker-guided implementation of the old drug temozolomide as a novel treatment option for patients with metastatic colorectal cancer. Cancer Treat Rev. 2020 Jan;82:101935.
10. Benelli M, Romagnoli D, Demichelis F. Tumor purity quantification by clonal DNA methylation signatures. Bioinformatics. 2018 May 15;34(10):1642-1649.

 

 

Collaborations

 

• AURORA-EU consortium (60 institutes across 14 European countries)
• Philippe Aftimos (Institut Jules Bordet, Brussels, Belgium)
• Francesca Demichelis (University of Trento, Trento, Italy)
• Silvia Giordano (IRCCS Candiolo Cancer Institute, Torino, Italy)
• Roberta Maestro (IRCCS Centro di Riferimento Oncologico di Aviano, Italy)
• Luca Malorni (Hospital of Prato, Azienda USL Toscana Centro, Prato, Italy)
• Ping Mu (UT Southwestern, Dallas, TX, US)
• Filippo Pietrantonio (IRCCS Istituto Nazionale dei Tumori, Milano, Italy)
• Sandro Pasquali (IRCCS Istituto Nazionale dei Tumori, Milano, Italy)