Mutational signatures of colorectal cancers according to distinct computational workflows
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB61897 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR13361401_1.fastq.gz | Fastqsanger.gz | |||
| ERR13361401_2.fastq.gz | Fastqsanger.gz | |||
| ERR13361801_1.fastq.gz | Fastqsanger.gz | |||
| ERR13361801_2.fastq.gz | Fastqsanger.gz | |||
| ERR13358210_1.fastq.gz | Fastqsanger.gz |
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Project description:Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures.
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Project description:Molecular profiling of breast cancer has achieved great depth in defining the mutational landscapes and molecular profiles of primary tumors, though little is still known regarding cancer evolution into a recurrence. Proteogenomic workflows are particularly useful in defining the multi-layered biology of complex diseases by combining genomic, transcriptomic, and proteomic technologies so to inform not only on mutational processes, but also on their repercussion at the effector level, proteins. We employed our recently developed proteogenomic workflow to analyze a cohort of 27 primary breast cancers and their matched loco-regional recurrences by whole genome sequencing, RNA sequencing, and mass spectrometry.
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Project description:BackgroundIncidence of testicular cancer is highest among young adults and has been increasing dramatically for men born since 1945. This study aimed to elucidate the factors driving this trend by investigating differences in mutational signatures by age of onset.MethodsWe retrieved somatic variant and clinical data pertaining to 135 testicular tumors from The Cancer Genome Atlas. We compared mutational load, prevalence of specific mutated genes, mutation types, and mutational signatures between age of onset groups (< 30 years, 30-39 years, ≥ 40 years) after adjusting for subtype. A recursively partitioned mixture model was utilized to characterize combinations of signatures among the young-onset cases.ResultsMutational load was significantly higher among older-onset tumors (p < 0.05). There were no highly prevalent driver mutations among young-onset tumors. Mutated genes and types of nucleotide mutations were not significantly different by age group (p > 0.05). Signatures 1, 8 and 29 were more common among young-onset tumors, while signatures 11 and 16 had higher prevalence among older-onset tumors (p < 0.05). Among young-onset tumors, clustering of signatures resulted in four distinct tumor classes.ConclusionsSignature contributions differ by age with signatures 1, 8 and 29 were more common among younger-onset tumors. While these signatures are connected with endogenous deamination of 5-methylcytosine, late replication errors and chewing tobacco, respectively, additional research is needed to further elucidate the etiology of young-onset testicular cancer. Large studies of mutational signatures among young-onset patients are required to understand epidemiologic trends as well as inform targeted prevention and treatment strategies.
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Project description:Aristolochic acids (AAs) are potent mutagens commonly found in herbal plant-based remedies widely used throughout Asian countries. To understand whether AA is involved in the tumorigenesis of the oro-gastrointestinal tract, we used whole-exome sequencing to profile 54 cases of four distinct types of oro-gastrointestinal tract cancer (OGITC) from Taiwan. A diverse landscape of mutational signatures including those from DNA mismatch repair and reactive oxygen species was observed. APOBEC mutational signatures were observed in 60% of oral squamous cell carcinomas. Only one sample harbored AA mutational signatures, contradictory to prior reports of cancers from Taiwan. The metabolism of AA in the liver and urinary tract, transient exposure time, and high cell turnover rates at OGITC sites may explain our findings. AA signatures in OGITCs are rare and unlikely to be a major contributing factor in oro-gastrointestinal tract tumorigenesis.
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