Hotspot propensity across mutational processes Arnedo-Pac, Claudia; Muiños, Ferran; Gonzalez-Perez, Abel ...
Molecular systems biology,
01/2024, Letnik:
20, Številka:
1
Journal Article
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The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of ...mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5–78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94–95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80–100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.
Synopsis
The propensity of mutational signatures to leave mutational hotspots serves as an estimate of the variability in their mutational probability at single-nucleotide resolution. Using known influences of the mutation rate at different scales allowed to closely model the observed hotspot propensity of signature 1.
The variability in the mutational probabilities at single-nucleotide resolution of different mutational processes (represented by signatures) can be estimated through their propensity to form hotspots across tumours.
Mutational signatures 1 and 17 show several-fold higher variability of their mutational probabilities at single-nucleotide resolution than other common somatic mutational processes.
The hotspot propensity of signature 17 (and others) cannot be fully explained through the variability of genomic features known to influence the mutation rate at small and large scales.
The hotspot propensity of signature 1 can be closely explained through the distribution of mutations at 10 Kbp resolution and methylated CpG sites along the genome.
The propensity of mutational signatures to leave mutational hotspots serves as an estimate of the variability in their mutational probability at single-nucleotide resolution. Using known influences of the mutation rate at different scales allowed to closely model the observed hotspot propensity of signature 1.
Adult T cell acute lymphoblastic leukemia (T-ALL) is a rare disease that affects less than 10 individuals in one million. It has been less studied than its cognate pediatric malignancy, which is more ...prevalent. A higher percentage of the adult patients relapse, compared to children. It is thus essential to study the mechanisms of relapse of adult T-ALL cases.
We profile whole-genome somatic mutations of 19 primary T-ALLs from adult patients and the corresponding relapse malignancies and analyze their evolution upon treatment in comparison with 238 pediatric and young adult ALL cases. We compare the mutational processes and driver mutations active in primary and relapse adult T-ALLs with those of pediatric patients. A precise estimation of clock-like mutations in leukemic cells shows that the emergence of the relapse clone occurs several months before the diagnosis of the primary T-ALL. Specifically, through the doubling time of the leukemic population, we find that in at least 14 out of the 19 patients, the population of relapse leukemia present at the moment of diagnosis comprises more than one but fewer than 10
blasts. Using simulations, we show that in all patients the relapse appears to be driven by genetic mutations.
The early appearance of a population of leukemic cells with genetic mechanisms of resistance across adult T-ALL cases constitutes a challenge for treatment. Improving early detection of the malignancy is thus key to prevent its relapse.
Pediatric cancers are rare diseases, and children without known germline predisposing conditions who develop a second malignancy during developmental ages are extremely rare. We present four such ...clinical cases and, through whole-genome and error-correcting ultra-deep duplex sequencing of tumor and normal samples, we explored the origin of the second malignancy in four children, uncovering different routes of development. The exposure to cytotoxic therapies was linked to the emergence of a secondary acute myeloid leukemia. A common somatic mutation acquired early during embryonic development was the driver of two solid malignancies in another child. In two cases, the two tumors developed from completely independent clones diverging during embryogenesis. Importantly, we demonstrate that platinum-based therapies contributed at least one order of magnitude more mutations per day of exposure than aging to normal tissues in these children.
Using whole-genome and error-correcting ultra-deep duplex sequencing, we uncover different origins for second neoplasms in four children. We also uncover the presence of platinum-related mutations across 10 normal tissues of exposed individuals, highlighting the impact that the use of cytotoxic therapies may have on cancer survivors. See related commentary by Pacyna and Nangalia, p. 900. This article is featured in Selected Articles from This Issue, p. 897.
E3 ligases and degrons, the sequences they recognize in target proteins, are key parts of the ubiquitin-mediated proteolysis system. There are several examples of alterations of these two components ...of the system that have a role in cancer. Here we uncover the landscape of the contribution of such alterations to tumorigenesis across cancer types. We first systematically identified new instances of degrons across the human proteome by using a random forest classifier and validated the functionality of a dozen of them, exploiting somatic mutations across >7,000 tumors. We detected signals of positive selection across known and new degron instances. Our results reveal that several oncogenes are frequently targeted by mutations that affect the sequence of their degrons or their cognate E3 ubiquitin ligases, causing an abnormal increase in their protein abundance. Overall, an important number of driver mutations across primary tumors affect either degrons or E3-ubiquitin ligases.
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