Adabbo, Bruno (2024) A Spatially Resolved Multi-Omics Analysis of Glioblastoma at Single Cell Resolution. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: A Spatially Resolved Multi-Omics Analysis of Glioblastoma at Single Cell Resolution
Autori:
Autore
Email
Adabbo, Bruno
bruno.adabbo@unina.it
Data: 11 Dicembre 2024
Numero di pagine: 128
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Dottorato: Computational and quantitative biology
Ciclo di dottorato: 37
Coordinatore del Corso di dottorato:
nome
email
Ceccarelli, Michele
michele.ceccarelli@unina.it
Tutor:
nome
email
Ceccarelli, Michele
[non definito]
Data: 11 Dicembre 2024
Numero di pagine: 128
Parole chiave: Spatial Transcriptomics, Glioblastoma
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni
Depositato il: 18 Nov 2025 11:54
Ultima modifica: 12 Ago 2026 05:38
URI: https://www.fedoa.unina.it/id/eprint/16472

Abstract

Tumor heterogeneity fueled by plasticity of tumor cells is key to therapy failure in cancer, but the factors driving transitions between cell states and whether the spatial organization of malignant cells drives plasticity remain elusive. We combined spatial transcriptomics at single cell resolution, proteomics and neighborhood analytics to define the role of proximal communications of malignant and non-malignant cells in glioblastoma plasticity. We found that tumor cell state coherence was maximal in cells organized in homotypic clusters with defined relationships with non-malignant cells, whereas randomly dispersed cells downregulated the original state, acquired alternative phenotypes and exhibited changes in the microenvironment. These findings, validated using an independent cohort of glioblastoma samples profiled by 10x Visium, highlight the critical influence of spatial organization on tumor cell identity and suggest that disrupting homotypic clustering could serve as a potential strategy to induce phenotypic shifts in tumor cells, thereby influencing therapeutic outcomes.

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