Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach.

Stratification of metastatic melanoma patients based on mutational signatures / Alfano, Caterina; Farina, Lorenzo; Petti, Manuela. - (2023), pp. 2798-2802. (Intervento presentato al convegno 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) tenutosi a Istanbul; Turkiye) [10.1109/BIBM58861.2023.10385763].

Stratification of metastatic melanoma patients based on mutational signatures

Caterina Alfano
Primo
;
Lorenzo Farina
Secondo
;
Manuela Petti
Ultimo
2023

Abstract

Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach.
2023
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
mutational signatures; metastatic melanoma; genomics; precision oncology; computational medicine; patient stratification
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Stratification of metastatic melanoma patients based on mutational signatures / Alfano, Caterina; Farina, Lorenzo; Petti, Manuela. - (2023), pp. 2798-2802. (Intervento presentato al convegno 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) tenutosi a Istanbul; Turkiye) [10.1109/BIBM58861.2023.10385763].
File allegati a questo prodotto
File Dimensione Formato  
Alfano_postprint_Stratification_2023.pdf

accesso aperto

Note: DOI: 10.1109/BIBM58861.2023.10385763
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 798.36 kB
Formato Adobe PDF
798.36 kB Adobe PDF
Alfano_Stratification_2023.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.52 MB
Formato Adobe PDF
1.52 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1700848
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact