This master’s thesis represents a preliminary exploration of the development of Rhabdomyosarcoma in subjects suffering from Duchenne Muscular Dystrophy following case reports of concomitant physiopathology. The clinical question, which arose from neurological studies, was approached with computational systems biology methodologies. The objective is to understand underlying physiopathological processes that, involving the modification of genomic expression, give rise to such scenarios. The assessment of the expression of genes through the quantitative evaluation of their transcriptome and the comparison between healthy, control subjects, and pathologic samples is therefore crucial. Through over-representation and functional class scoring enrichment analyses, a sarcoma signature was identified in dystrophic subjects. Pseudotime trajectory inference on bulk RNA data highlighted a gene set correlated to the development of RMS in a dystrophic context. Subsequent enrichment analysis identified the result as SMARCA2 signatures. The exploration of these signatures was performed through correlation, differential expression, and enrichment analyses in human and murine data from both pathologies. In conclusion, this work uncovered signatures with a possible crucial role in determining the development of RMS in dystrophic patients, suggesting the direction of further studies.
Questa tesi magistrale rappresenta un’esplorazione iniziale dello sviluppo di Rhabdomiosarcoma (RMS) in soggetti affetti da Distrofia Muscolare di Duchenne a seguito di casi di studio in cui le due patologie sono state identificate nei medesimi soggetti. Il quesito clinico, nato da studi neurologici, è stato affrontato con metodologie computazionali di biologia dei sistemi. L’obiettivo è di comprendere i processi fisiopatologici che sottostanno a questo quadro clinico attraverso le modifiche dell‘espressione genomica. Di conseguenza, la valutazione dell’espressione genica attraverso un’analisi quantitativa del trascrittoma e il paragone tra soggetti sani di controllo e soggetti patologici è fondamentale. Attraverso analisi di arricchimento in dati di pazienti distrofici è emersa come significativa una signature di sarcoma. L’inferenza di una traiettoria nello pseudotempo ha evidenziato un set di geni correlati allo sviluppo nel tempo di RMS in soggetti con distrofia. Da un’analisi di arricchimento il set di geni è emerso appartenere alle signature di Shen SMARCA2 targets. L’esplorazione di queste signature è stata svolta in dati umani e murini di Rhabdomiosarcoma e Distrofia con studi di correlazione, di espressione differenziale e di arricchimento. In conclusione questo lavoro ha svelato delle signature potenzialmente rilevanti per lo sviluppo di RMS in pazienti con Distrofia Muscolare di Duchenne, suggerendo una direzione di ricerca per studi futuri.
Investigating the relationship between Duchenne Muscular Dystrophy and Rhabdomyosarcoma: a computational systems biology approach
CARLESSO, SUSANNA
2022/2023
Abstract
This master’s thesis represents a preliminary exploration of the development of Rhabdomyosarcoma in subjects suffering from Duchenne Muscular Dystrophy following case reports of concomitant physiopathology. The clinical question, which arose from neurological studies, was approached with computational systems biology methodologies. The objective is to understand underlying physiopathological processes that, involving the modification of genomic expression, give rise to such scenarios. The assessment of the expression of genes through the quantitative evaluation of their transcriptome and the comparison between healthy, control subjects, and pathologic samples is therefore crucial. Through over-representation and functional class scoring enrichment analyses, a sarcoma signature was identified in dystrophic subjects. Pseudotime trajectory inference on bulk RNA data highlighted a gene set correlated to the development of RMS in a dystrophic context. Subsequent enrichment analysis identified the result as SMARCA2 signatures. The exploration of these signatures was performed through correlation, differential expression, and enrichment analyses in human and murine data from both pathologies. In conclusion, this work uncovered signatures with a possible crucial role in determining the development of RMS in dystrophic patients, suggesting the direction of further studies.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/218905