2021 06 17 11 56                                                                              Angelo and his group                   

We at CERM mourn the premature decease of Dr. Angelo Di Leo. Di Leo (58 years old) passed away on Sunday 13 June 2021, after a long illness.

Angelo Di Leo was one of the world's leading experts in the field of medical oncology of breast cancer and one of the first to appreciate the impact that metabolomics could have in precision oncology. In this framework, aimed at ensuring the right treatment for the right patient at the right time, a strong collaboration with the metabolomic research group at CERM started more than a decade ago. This collaboration proved to be particularly solid and scientifically fruitful and set the foundation for the applications of metabolomics in the clinical oncology of breast cancer.

Angelo was successfully committed to oncology since his graduation in medicine at the University of Palermo in 1988. Since September 2003, after 6 years in Brussels, Dr. Di Leo held the position of director of the Oncology Department at the "Santo Stefano" Hospital in Prato. In Prato, he managed to create a specialized laboratory for oncological translational research. Angelo authored many scientific articles published in international journals and participated as a speaker at numerous national and international conferences. In 2019, the international scientific community awarded Di Leo the Esmo (European Society for Medical Oncology) prize for “Having significantly contributed to the development of personalized therapies for breast cancer”. He was the first Italian to receive this prestigious award.

Angelo's main research field was breast cancer. He was involved in the coordination of numerous international phase III trials, with the aim of evaluating the effectiveness of new drugs. He has been very active in the evaluation of molecular markers with potentially predictive value for the diagnosis, prognosis and treatment of patients with breast cancer. Indeed, because every tumour is different, the knowledge of its molecular profile is important to propose the most suitable treatment for each individual. To do this, it is necessary to take into account the metabolism and the specific biological characteristics of both the tumour and of the host.

With Angelo we have lost an extraordinary and visionary scientist, for whom we have developed over the years a profound esteem, which was flanked by an equally profound friendship. In one of our first collaborative papers, published in Annals of Oncology in 2011, we demonstrated how it is possible to use the metabolic fingerprint present in serum samples of women with breast cancer to discriminate early patients from metastatic. This opened interesting perspectives for prognosis. In fact, in a significant number of patients at an early stage and who have benefited from the surgical removal of the tumour, there can be a recurrence of the disease in the following years (up to 10). This relapse is supposed to be due to not identifiable micro-metastases. Metabolomics could permit the development of an accurate "risk of metastasis development", by comparing the metabolic profile of a patient with the previously identified typical profiles of early and metastatic patients. The more the profile is similar to that of metastatic disease, the more the risk of recurrence for the patient is high. This hypothesis was verified in a subsequent study published in Molecular Oncology in 2015. Retrospectively analysing serum samples collected from women operated for an early breast cancer, it was possible to predict with a high accuracy (above 80%), the women who subsequently had a relapse. These data, obtained on a limited number of patients (about 100), were further validated by a further study (Clinical Cancer Research, 2017) on a large multicentre cohort of about 700 patients, reinforcing the idea of the predictive and prognostic power of serum metabolomics. This discovery can pave the way for a rapid translation of metabolomics into the clinical oncology practice, contributing to targeted and optimal therapeutic choices for patients.

All CERMians express sympathy and condolence to his wife and colleague, Dr. Laura Biganzoli, the new director of the Oncology Unit in Prato, and to his daughter, Federica.

Di Leos’s joint publications with CERMians

1.    Di Donato S, Vignoli A, Biagioni C, Malorni L, Mori E, Tenori L, Calamai V, Parnofiello A, Di Pierro G, Migliaccio I, Cantafio S, Baraghini M, Mottino G, Becheri D, Del Monte F, Miceli E, McCartney A, Di Leo A, Luchinat C, Biganzoli L. A serum metabolomics classifier derived from elderly patients with metastatic colorectal cancer predicts relapse in the adjuvant setting. Cancers 2021;13(11).

2.     McCartney A, Vignoli A, Tenori L, Fornier M, Rossi L, Risi E, Luchinat C, Biganzoli L, Di Leo A. Metabolomic analysis of serum may refine 21-gene expression assay risk recurrence stratification. NPJ Breast Cancer 2019;5(1).

3.     McCartney A, Vignoli A, Biganzoli L, Love R, Tenori L, Luchinat C, Di Leo A. Metabolomics in breast cancer: A decade in review. Cancer Treat Rev 2018;67:88-96.

4.    McCartney A, Vignoli A, Hart C, Tenori L, Luchinat C, Biganzoli L, Di Leo A. De-escalating and escalating treatment beyond endocrine therapy in patients with luminal breast cancer. Breast 2017;34:S13-8.

5.    Hart CD, Vignoli A, Tenori L, Uy GL, Van To T, Adebamowo C, Hossain SM, Biganzoli L, Risi E, Love RR, Luchinat C, Di Leo A. Serum metabolomic profiles identify ER-positive early breast cancer patients at increased risk of disease recurrence in a multicenter population. Clin Cancer Res 2017;23(6):1422-31.

6.    Hart CD, Tenori L, Luchinat C, Di Leo A. Metabolomics in breast cancer: Current status and perspectives. Adv Exp Med Biol 2016;882:217-34.

7.    Tenori L, Oakman C, Morris PG, Gralka E, Turner N, Cappadona S, Fornier M, Hudis C, Norton L, Luchinat C, Di Leo A. Serum metabolomic profiles evaluated after surgery may identify patients with oestrogen receptor negative early breast cancer at increased risk of disease recurrence. results from a retrospective study. Mol Oncol 2015;9(1):128-39.

8.    Oakman C, Tenori L, Silvia CS, Luchinat C, Bertini I, Di Leo A. Targeting metabolomics in breast cancer. Curr Breast Cancer Rep 2012;4(4):249-56.

9.    Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC, Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: A pilot study. Mol Oncol 2012;6(4):437-44.

10.   Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E, Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Ann Oncol 2011;22(6):1295-301.

11.   Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011;43(7):1010-20.

12.   Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: Available results, current research projects in breast cancer, and future applications. J Clin Oncol 2007;25(19):2840-6.

13.  Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol 2007;18 Suppl 12:xii8-14.