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Single cell-derived spheroids capture the self-renewing subpopulations of metastatic ovarian cancer

Academic Article
Publication Date:
2022
Citation:
Single cell-derived spheroids capture the self-renewing subpopulations of metastatic ovarian cancer / T. Velletri, C.E.V.. - In: CELL DEATH AND DIFFERENTIATION. - ISSN 1350-9047. - 29:3(2022 Mar), pp. 614-626. [10.1038/s41418-021-00878-w]
abstract:
High Grade Serous Ovarian cancer (HGSOC) is a major unmet need in oncology, due to its precocious dissemination and the lack of meaningful human models for the investigation of disease pathogenesis in a patient-specific manner. To overcome this roadblock, we present a new method to isolate and grow single cells directly from patients’ metastatic ascites, establishing the conditions for propagating them as 3D cultures that we refer to as single cell-derived metastatic ovarian cancer spheroids (sMOCS). By single cell RNA sequencing (scRNAseq) we define the cellular composition of metastatic ascites and trace its propagation in 2D and 3D culture paradigms, finding that sMOCS retain and amplify key subpopulations from the original patients’ samples and recapitulate features of the original metastasis that do not emerge from classical 2D culture, including retention of individual patients’ specificities. By enabling the enrichment of uniquely informative cell subpopulations from HGSOC metastasis and the clonal interrogation of their diversity at the functional and molecular level, this method provides a powerful instrument for precision oncology in ovarian cancer.
IRIS type:
01 - Articolo su periodico
List of contributors:
T. Velletri, C.E. Villa, D. Cilli, B. Barzaghi, P. Lo Riso, M. Lupia, R. Luongo, A. Lopez-Tobon, M. De Simone, R.J.P. Bonnal, L. Marelli, S. Piccolo, N. Colombo, M. Pagani, U. Cavallaro, S. Minucci, G. Testa
Authors of the University:
MARELLI LUCA ( author )
MINUCCI SAVERIO ( author )
PAGANI MASSIMILIANO ( author )
TESTA GIUSEPPE ( author )
Link to information sheet:
https://air.unimi.it/handle/2434/905568
Full Text:
https://air.unimi.it/retrieve/handle/2434/905568/1975099/Velletri%20et%20al%20CDD%202021.pdf
Project:
Dipartimenti di Eccellenza 2018-2022 - Dipartimento di ONCOLOGIA ED EMATO-ONCOLOGIA
  • Research Areas

Research Areas

Concepts (4)


Settore BIO/11 - Biologia Molecolare

Settore BIO/13 - Biologia Applicata

Settore MED/06 - Oncologia Medica

Settore MED/40 - Ginecologia e Ostetricia
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