Naslov
Exploring the epigenomic context of mutational processes

Autori
Karlić, Rosa

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Advances in Biomedical Research IV Book of Abstracts / - , 2021, 34-34

Skup
Advances in Biomedical Research IV

Mjesto i datum
Split, Croatia, 04.10.2021. - 09.10.2021

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Podatak o recenziji nije dostupan

Ključne riječi
cancer genomics ; epigenomics ; cell-of-origin

Sažetak
One of the main challenges in cancer biology is the identification of the cell-of-origin (COO) in cancer. We previously demonstrated that the landscape of somatic mutations in cancer is associated with the chromatin marks of the cell- of-origin and developed a novel approach, based on machine learning methods, that can successfully identify COO by utilizing different epigenetic features of the cell-of-origin and somatic mutations found in the cancer genome (Polak et al., 2015). We further extended our analysis and showed that this principle is generalizable to common cancer types and subtypes (Kübler et al., 2019). The prediction accuracy of models used to predict the COO varies across cancer types, potentially caused by the fact that somatic mutations in human cancers can be generated by various underlying mutational processes. Different mutational processes give rise to characteristic mutational patterns, called mutational signatures, which can be identified using various mathematical pproaches. It was recently shown that mutations generated by distinct mutational processes are differentially enriched in active/inactive chromatin domains (Akdemir et al., 2020), implying that they are differentially related to the epigenomic context of the cell-of- origin and that the inclusion of mutational signature information might positively impact the accuracy of predicting the COO. We tested this hypothesis by exploring the impact of genomic regions with high APOBEC mutational signature on the outcome of the models for predicting the cell-of-origin in different subtypes of breast cancer, frequently enriched in APOBEC-mediated somatic mutations. We were able to show that the inclusion/exclusion of APOBEC mutations does influence the prediction accuracy of our models, highlighting the crucial role of the specific cell type of origin and mutational process in shaping the mutational landscape and early tumor evolution.

Izvorni jezik
Engleski

Znanstvena područja
Biologija

POVEZANOST RADA