Single base substitution mutational signatures in pediatric acute myeloid leukemia based on whole genome sequencing.
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ABSTRACT:
SUBMITTER: Gunnarsson R
PROVIDER: S-EPMC8102186 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Whole-genome sequencing (WGS) permits comprehensive cancer genome analyses, revealing mutational signatures, imprints of DNA damage and repair processes that have arisen in each patient's cancer. We performed mutational signature analyses on 12,222 WGS tumor-normal matched pairs, from patients recruited via the UK National Health Service. We contrasted our results to two independent cancer WGS datasets, the International Cancer Genome Consortium (ICGC) and Hartwig Foundation, involving 18,640 WGS cancers in total. Our analyses add 40 single and 18 double substitution signatures to the current mutational signature tally. Critically, we show for each organ, that cancers have a limited number of 'common' signatures and a long tail of 'rare' signatures. We provide a practical solution for utilizing this concept of common versus rare signatures in future analyses.
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Project description:Genomic alterations underlying chemotherapy resistance remains poorly characterized in pediatric acute myeloid leukemia (AML). In this study, we used whole exome sequencing to identify gene mutations associated with chemo-resistance in 44 pediatric AML patients. We identified previously unreported mutations involving epigenetic regulators such as KDM5C, SRIT6, CHD4, and PRPF6 in pediatric AML patients. Despite low prevalence in general pediatric AML, mutations involving epigenetic regulators including splicing factors, were collectively enriched as a group in primary chemo-resistance AML patients. In addition, clonal evolution analysis of secondary chemo-resistance AML patients reveals dominant clone at diagnosis could survive several course of intensified chemotherapy. And gain of new mutations in genes such as MVP, TCF3, SS18, and BCL10, may contribute to chemo-resistance at relapse. These results provide novel insights into the genetic basis of treatment failure in pediatric AML.
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Project description:BackgroundPrevious studies have shown that leukemogenic chromosomal translocations, including fusions between Break point Cluster Region (BCR) and Abelson (ABL) are present in the peripheral blood of healthy individuals. The aim of this study was to gain insights into the genetic alterations other than BCR-Abl translocation in molecular level, which cause chronic myeloid leukemia (CML).MethodsWe performed whole-exome sequencing on four cases representative of BCR-ABL positive CML in chronic phase of the disease.ResultsWe did not identify any pathogenic mutation in all known genes involved in CML or other cancers in our subjects. Nevertheless, we identified polymorphisms in related genes.ConclusionIt is the first report of exome sequencing in Philadelphia chromosome positive CML patients. We did not identify any pathogenic mutation in known cancer genes in our patients who can be due to CML pathogenesis or technical limitations.
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Project description:BACKGROUND:Acute lymphoblastic leukemia (ALL), the most common childhood malignancy, is characterized by recurring structural chromosomal alterations and genetic alterations, whose detection is critical in diagnosis, risk stratification and prognostication. However, the genetic mechanisms that give rise to ALL remain poorly understood. METHODS:Using next-generation sequencing (NGS) in matched germline and tumor samples from 140 pediatric Chinese patients with ALL, we landscaped the gene mutations and estimated the mutation frequencies in this disease. RESULTS:Our results showed that the top driver oncogenes having a mutation prevalence over 5% in childhood ALL included KRAS (8.76%), NRAS (6.4%), FLT3 (5.7%) and KMT2D (5.0%). While the most frequently mutated genes were KRAS, NRAS and FLT3 in B cell ALL (B-ALL), the most common mutations were enriched in NOTCH1 (23.1%), FBXW7 (23.1%) and PHF6 (11.5%) in T cell ALL (T-ALL). These mutant genes are involved in key molecular processes, including the Ras pathway, the Notch pathway, epigenetic modification, and cell-cycle regulation. Strikingly, more than 50% of mutations occurred in the high-hyperdiploid (HeH) ALL existed in Ras pathway, especially FLT3 (20%). We also found that the epigenetic regulator gene KMT2D, which is frequently mutated in ALL, may be involved in driving leukemia transformation, as evidenced by an in vitro functional assay. CONCLUSION:Overall, this study provides further insights into the genetic basis of ALL and shows that Ras mutations are predominant in childhood ALL, especially in the high-hyperdiploid subtype in our research.
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Project description:Primary plasma cell leukemia (pPCL) is a rare and aggressive form of plasma cell dyscrasia and may represent a valid model for high-risk multiple myeloma (MM). To provide novel information concerning the mutational profile of this disease, we performed the whole-exome sequencing of a prospective series of 12 pPCL cases included in a Phase II multicenter clinical trial and previously characterized at clinical and molecular levels. We identified 1, 928 coding somatic non-silent variants on 1, 643 genes, with a mean of 166 variants per sample, and only few variants and genes recurrent in two or more samples. An excess of C > T transitions and the presence of two main mutational signatures (related to APOBEC over-activity and aging) occurring in different translocation groups were observed. We identified 14 candidate cancer driver genes, mainly involved in cell-matrix adhesion, cell cycle, genome stability, RNA metabolism and protein folding. Furthermore, integration of mutation data with copy number alteration profiles evidenced biallelically disrupted genes with potential tumor suppressor functions. Globally, cadherin/Wnt signaling, extracellular matrix and cell cycle checkpoint resulted the most affected functional pathways. Sequencing results were finally combined with gene expression data to better elucidate the biological relevance of mutated genes. This study represents the first whole-exome sequencing screen of pPCL and evidenced a remarkable genetic heterogeneity of mutational patterns. This may provide a contribution to the comprehension of the pathogenetic mechanisms associated with this aggressive form of PC dyscrasia and potentially with high-risk MM.
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Project description:BackgroundAlterations of 11q23/KMT2A are the most prevalent cytogenetic abnormalities in acute myeloid leukemia (AML) and the prognostic significance of 11q23/KMT2A-rearranged AML based on various translocation partners varies among different studies. However, few studies evaluated the molecular characteristics of 11q23/KMT2A-rearranged pediatric AML. We aim to analyze the mutational landscape of 11q23/KMT2A-rearranged AML and assess their prognostic value in outcomes.MethodsThe mutational landscape and clinical prognosis of 105 children with 11q23/KMT2A-rearranged AML in comparison with 277 children with non-11q23/KMT2A-rearranged AML were analyzed using publicly accessible next-generation sequencing data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) dataset.ResultsPediatric AML patients with 11q23/KMT2A-rearrangements harbored a low number of mutations (Median, 1 mutation/patient, range, 1-22), 58% of which involved in RAS pathway mutations (KRAS, NRAS, and PTPN11) and 10.5% of which comprised of SETD2 mutations. Compared with non-11q23/KMT2A-rearranged AML, the incidence of KRAS (32.4% vs. 10.1%, P〈0.001) and SETD2 (10.5% vs. 1.4%, P=0.001) gene mutations in 11q23/KMT2A-rearranged AML was significantly higher. Both KRAS and SETD2 mutations occurred more often in t(10;11)(p12;q23). KRAS mutations were correlated with worse 5-year event-free survival [EFS] (Plog-rank = 0.001) and 5-year overall survival [OS] (Plog-rank = 0.009) and the presence of SETD2 mutations increases the 5-year relapse rate (PGray = 0.004). Multivariate analyses confirmed KRAS mutations in 11q23/KMT2A-rearranged AML as an independent predictor for poor EFS (hazard ratio [HR] = 2.10, P=0.05) and OS (HR = 2.39, P=0.054).ConclusionOur findings show that pediatric patients with 11q23/KMT2A rearrangements have characteristic mutation patterns and varying clinical outcomes depending on different translocation partners, which could be utilized to develop more accurate risk stratification and tailored therapies.
| S-EPMC9883550 | biostudies-literature
Project description:BackgroundMutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of the lack of a method to identify features of long sequences next to mutation bases, the understanding of how flanking sequences influence mutation signatures is limited.MethodsWe constructed a long short-term memory-self organizing map (LSTM-SOM) unsupervised neural network. By extracting mutated sequence features via LSTM and clustering similar features with the SOM, single-base substitutions in The Cancer Genome Atlas database were clustered according to both their mutation site and flanking sequences. The relationship between mutation sequence signatures and clinical features was then analyzed. Finally, we clustered patients into different classes according to the composition of the mutation sequence signatures by the K-means method and then studied the differences in clinical features and survival between classes.ResultsTen classes of mutant sequence signatures (mutation blots, MBs) were obtained from 2,141,527 single-base substitutions via LSTM-SOM machine learning approach. Different features in mutation bases and flanking sequences were revealed among MBs. MBs reflect both the site and pathological features of cancers. MBs were related to clinical features, including age, sex, and cancer stage. The class of an MB in a given gene was associated with survival. Finally, patients were clustered into 7 classes according to the MB composition. Significant differences in survival and clinical features were observed among different patient classes.ConclusionsWe provided a method for analyzing the characteristics of mutant sequences. Result of this study showed that flanking sequences, together with mutation bases, shape the signatures of SBSs. MBs were shown related to clinical features and survival of cancer patients. Composition of MBs is a feasible predictive factor of clinical prognosis. Further study of the mechanism of MBs related to cancer characteristics is suggested.
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Project description:Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.
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Project description:Mutational signatures accumulate in somatic cells as an admixture of endogenous and exogenous processes that occur during an individual's lifetime. Since dividing cells release cell-free DNA (cfDNA) fragments into the circulation, we hypothesize that plasma cfDNA might reflect mutational signatures. Point mutations in plasma whole genome sequencing (WGS) are challenging to identify through conventional mutation calling due to low sequencing coverage and low mutant allele fractions. In this proof of concept study of plasma WGS at 0.3-1.5x coverage from 215 patients and 227 healthy individuals, we show that both pathological and physiological mutational signatures may be identified in plasma. By applying machine learning to mutation profiles, patients with stage I-IV cancer can be distinguished from healthy individuals with an Area Under the Curve of 0.96. Interrogating mutational processes in plasma may enable earlier cancer detection, and might enable the assessment of cancer risk and etiology.
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