Ciervo, Erika (2025) Dissecting tumor-immune dynamics through single-nucleus and spatial multi-omics in epigenetic-based immunotherapy for melanoma. [Tesi di dottorato]
![[thumbnail of ciervo_erika_38.pdf]](https://www.fedoa.unina.it/style/images/fileicons/other.png "ciervo_erika_38.pdf") |
Documento PDF
ciervo_erika_38.pdf Visibile a [TBR] Amministratori dell'archivio Download (30MB) |
| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Dissecting tumor-immune dynamics through single-nucleus and spatial multi-omics in epigenetic-based immunotherapy for melanoma |
| Autori: | Autore Email Ciervo, Erika erika.ciervo@unina.it |
| Data: | 10 Dicembre 2025 |
| Numero di pagine: | 166 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Elettrica e delle Tecnologie dell'Informazione |
| Dottorato: | Computational and quantitative biology |
| Ciclo di dottorato: | 38 |
| Coordinatore del Corso di dottorato: | nome email Ceccarelli, Michele michele.ceccarelli@unina.it |
| Tutor: | nome email Ceccarelli, Michele [non definito] Canzoniero, Lorella Maria Teresa [non definito] |
| Data: | 10 Dicembre 2025 |
| Numero di pagine: | 166 |
| Parole chiave: | single-cell multi-omics; spatial transcriptomics; tumor heterogeneity; epigenetic remodeling; transposable elements; metastatic melanoma |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni |
| Informazioni aggiuntive: | Ciclo 38 - XXXVIII |
| Depositato il: | 07 Apr 2026 06:31 |
| Ultima modifica: | 12 Ago 2026 05:37 |
| URI: | https://www.fedoa.unina.it/id/eprint/15923 |
Abstract
Recent advances in single-cell multi-omic and spatial transcriptomic technologies have revolutionized tumor ecosystem research, enabling high-resolution mapping of cellular diversity, regulatory mechanisms, and spatial organization. These approaches have revealed the co-evolution of malignant and surrounding cells during tumor progression and in response to therapy, yet their analysis requires advanced computational frameworks. In this study, computational methods were developed and applied to integrate multi-omic datasets, characterizing tumor heterogeneity and cellular plasticity, and elucidating how epigenetic remodeling, transcriptional reprogramming, and spatial organization shape melanoma progression and therapeutic response. As a case study, metastatic melanoma biopsies obtained from the phase Ib clinical trial NIBIT-M4 were analyzed, where patients received a DNMT1 inhibitor in combination with anti-CTLA-4 immunotherapy. The analysis identified seven tumor metaprograms, including a Wnt/β-catenin–driven differentiated state and a therapy-resistant neural crest-like phenotype. In responder patients, integrative multi-omic profiling revealed reactivation of antigen-presentation and interferon-response programs within immune-rich niches, together with activation of transposable elements. Conversely, in non-responders, homotypic niches favored maintenance of resistant states, with NFATC2 emerging as a key regulator of neural crest-like dedifferentiation and therapy resistance. Overall, this work provides computational methodologies and biological insights into how epi-immunotherapy remodels melanoma ecosystems. By linking chromatin remodeling, transcriptional reprogramming, and spatial dynamics to treatment response, the presented findings highlight β-catenin and NFATC2 as actionable vulnerabilities to overcome resistance.
Downloads
Downloads per month over past year
Actions (login required)
 |
Modifica documento |
