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 |
Items per page: 5 1 - 5 of 98 |
Similar Datasets
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.
| S-EPMC11116831 | biostudies-literature
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.
2023-02-03 | PXD032266 | Pride
Project description:Copy number analyses of regionally separated intratumoral biopsies of prostate cancers. Intratumoral heterogeneity (ITH) leads to regional biases of the mutational landscape in a single tumor and may influence the single biopsy-based clinical diagnosis and treatment decision. To evaluate the extent of ITH in unifocal prostate cancers (PCAs) that had not been sought, we analyzed multiple regional biopsies from three PCAs using DNA copy number analyses. DNA copy number showed ITH including regional biases in the presentation of a well-known driver of TMPRSS2-ERG fusion. Our analyses identified a substantial level of genetic ITH in unifocal PCAs at the genomic levels, which should be taken into account for the curation of biomarkers in the clinical setting. Four intratumoral biopsies were obtained per tumor for three prostate cancers. Radical prostatectomy tissue from three patients with prostate cancers were obtained. Board-certified pathologists reviewed the hematoxylin&eosin stained sections and identified tumor-rich regions (> 80% purity). We selected four different areas for biopsy that were at least 5mm apart and were comprised of the most common Gleason pattern (the most common histologic patterns with minimal histologic differences). Copy number profiling was performed using Agilent 180K platform according to the manufacturer's protocol.
2014-01-18 | E-GEOD-54185 | biostudies-arrayexpress
Project description:Computational Genomics of Preeclampsia
| PRJNA809816 | ENA
Project description:Computational Genomics of Preeclampsia
| PRJNA809817 | ENA
Project description:Computational map of colon polyps
| PRJNA929038 | ENA
Project description:Transcript abundance was measured in whole-body virgin male Drosophila serrata from 41 inbred lines that had diverged through 27 generations of mutation accumulation. Pleiotropic mutations are the ultimate source of genetic variation in complex traits, including many human diseases. However, the nature and extent of mutational pleiotropy remain largely unknown. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation lines of Drosophila serrata, which had diverged for 27 generations. We detected significant mutational variance in 4.6% of ESTs, but 70% of ESTs were invariant among lines, allowing us to reject a null hypothesis of phenome-wide universal pleiotropy. Mutational covariance among ESTs was detected at a frequency of only 1 in 193 random pairs of variable EST, bu t was detected among random combinations of five ESTs in 1 in 5 cases, revealing that mutational covariance among multiple ESTs was common. The observed frequency of significant multivariate covariance among random ESTs implied that a substantial number of ESTs (>70) must be pleiotropically affected by at least some mutations. We measured gene expression of male Drosophila serrata from 41 mutation accumulation lines (whole-body). Data from two replicates for each line are presented.
2013-09-01 | E-GEOD-49815 | biostudies-arrayexpress
Project description:Colibactin, a potent genotoxin of Escherichia coli, causes DNA double strand breaks (DSBs). We investigated if colibactin creates a particular DNA damage signature in infected human cells. Genomic contexts of colibactin-induced DSBs were enriched for a distinct AT-rich hexameric sequence motif. A survey of somatic mutations at the colibactin target sites of several thousand cancer genomes revealed significant enrichment of the motif in colorectal cancers. Moreover, the exact break point location corresponded with mutational hot spots in these cancers corresponding to a distinct trinucleotide signature. This work provides evidence for a role of colibactin in the etiology of human cancer.
2020-04-22 | GSE145594 | GEO
Project description:Immune checkpoint inhibitors are used to restore or augment antitumor immune response and show great promise in treatment of melanoma and other types of cancers. However, only a relatively small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development and resistance mechanisms, as well as tumor heterogeneity in individual patients. Here, we use a proteogenomic approach to characterize the mutational landscape of samples derived from four clinical melanoma patients at the genomic, proteomic and phosphoproteomic level. Integration of datasets enabled identification and quantification of an extensive number of sample-specific amino acid variants, among them many were not previously reported in melanoma. We detected a disproportional number of alternate peptides between treated and untreated (naïve) samples with a high potential to influence signal transduction. This is one of the first proteogenomic study designed to study the mutational landscape of patient-derived melanoma tissue samples in response to immunotherapy.
2022-02-16 | PXD028700 | Pride