scholarly journals Integrated Analysis of Germline and Tumor DNA Identifies New Candidate Genes Involved in Familial Colorectal Cancer

Cancers ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 362 ◽  
Author(s):  
Marcos Díaz-Gay ◽  
Sebastià Franch-Expósito ◽  
Coral Arnau-Collell ◽  
Solip Park ◽  
Fran Supek ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Candidate Genes ◽  
Copy Number Variants ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Functional Studies ◽  
Mutational Profiling ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Colorectal cancer (CRC) shows aggregation in some families but no alterations in the known hereditary CRC genes. We aimed to identify new candidate genes which are potentially involved in germline predisposition to familial CRC. An integrated analysis of germline and tumor whole-exome sequencing data was performed in 18 unrelated CRC families. Deleterious single nucleotide variants (SNV), short insertions and deletions (indels), copy number variants (CNVs) and loss of heterozygosity (LOH) were assessed as candidates for first germline or second somatic hits. Candidate tumor suppressor genes were selected when alterations were detected in both germline and somatic DNA, fulfilling Knudson’s two-hit hypothesis. Somatic mutational profiling and signature analysis were also performed. A series of germline-somatic variant pairs were detected. In all cases, the first hit was presented as a rare SNV/indel, whereas the second hit was either a different SNV (3 genes) or LOH affecting the same gene (141 genes). BRCA2, BLM, ERCC2, RECQL, REV3L and RIF1 were among the most promising candidate genes for germline CRC predisposition. The identification of new candidate genes involved in familial CRC could be achieved by our integrated analysis. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.

scholarly journals MAGOS: Discovering Subclones in Tumors Sequenced at Standard Depths

2019 ◽  
Author(s):  
Navid Ahmadinejad ◽  
Shayna Troftgruben ◽  
Carlo Maley ◽  
Junwen Wang ◽  
Li Liu
Keyword(s):  
Copy Number Variants ◽  
R Package ◽  
Computational Method ◽  
Intratumor Heterogeneity ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Real World Data ◽  
Computation Efficiency ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

ABSTRACTUnderstanding intratumor heterogeneity is critical to designing personalized treatments and improving clinical outcomes of cancers. Such investigations require accurate delineation of the subclonal composition of a tumor, which to date can only be reliably inferred from deep-sequencing data (>300x depth). To enable accurate subclonal discovery in tumors sequenced at standard depths (30-50x), we develop a novel computational method that incorporates an adaptive error model into statistical decomposition of mixed populations, which corrects the mean-variance dependency of sequencing data at the subclonal level. Tested on extensive computer simulations and real-world data, this new method, named model-based adaptive grouping of subclones (MAGOS), consistently outperforms existing methods on minimum sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports subclone analysis using single nucleotide variants and copy number variants from one or more samples of an individual tumor. Applications of MAGOS to whole-exome sequencing data of 331 liver cancer samples discovered a significant association between subclonal diversity and patient overall survival. MAGOS is freely available as an R package at github (https://github.com/liliulab/magos).

scholarly journals SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences from Reference Genomes

2019 ◽  
Author(s):  
Yue Xing ◽  
Alan R. Dabney ◽  
Xiao Li ◽  
Guosong Wang ◽  
Clare A. Gill ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Software Applications ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

AbstractCopy number variants are insertions and deletions of 1 kb or larger in a genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.

scholarly journals CANOES: detecting rare copy number variants from whole exome sequencing data

2014 ◽  
Vol 42 (12) ◽  
pp. e97-e97 ◽  
Author(s):  
Daniel Backenroth ◽  
Jason Homsy ◽  
Laura R. Murillo ◽  
Joe Glessner ◽  
Edwin Lin ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

scholarly journals EXCAVATOR: detecting copy number variants from whole-exome sequencing data

2013 ◽  
Vol 14 (10) ◽  
pp. R120 ◽  
Author(s):  
Alberto Magi ◽  
Lorenzo Tattini ◽  
Ingrid Cifola ◽  
Romina D’Aurizio ◽  
Matteo Benelli ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Constitutive mismatch repair defect syndrome: New insights from whole exome sequencing data and functional studies

2016 ◽  
Vol 231 ◽  
pp. S12
Author(s):  
Ahmet Okay Caglayan ◽  
Zeynep E. Erson Omay ◽  
Yavuz Koksal ◽  
Suleyman Coskun ◽  
Ekrem Unal ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Mismatch Repair ◽  
Whole Exome Sequencing ◽  
Sequencing Data ◽  
Functional Studies ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Repair Defect

scholarly journals Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2

2016 ◽  
pp. gkw695 ◽  
Author(s):  
Romina D'Aurizio ◽  
Tommaso Pippucci ◽  
Lorenzo Tattini ◽  
Betti Giusti ◽  
Marco Pellegrini ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

scholarly journals TPES: tumor purity estimation from SNVs

2019 ◽  
Vol 35 (21) ◽  
pp. 4433-4435 ◽  
Author(s):  
Alessio Locallo ◽  
Davide Prandi ◽  
Tarcisio Fedrizzi ◽  
Francesca Demichelis
Keyword(s):  
R Package ◽  
Computational Method ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Tumor Purity ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Fraction Distribution ◽  
Tumor Genome

Abstract Motivation Tumor purity (TP) is the proportion of cancer cells in a tumor sample. TP impacts on the accurate assessment of molecular and genomics features as assayed with NGS approaches. State-of-the-art tools mainly rely on somatic copy-number alterations (SCNA) to quantify TP and therefore fail when a tumor genome is nearly euploid, i.e. ‘non-aberrant’ in terms of identifiable SCNAs. Results We introduce a computational method, tumor purity estimation from single-nucleotide variants (SNVs), which derives TP from the allelic fraction distribution of SNVs. On more than 7800 whole-exome sequencing data of TCGA tumor samples, it showed high concordance with a range of TP tools (Spearman’s correlation between 0.68 and 0.82; >9 SNVs) and rescued TP estimates of 1, 194 samples (15%) pan-cancer. Availability and implementation TPES is available as an R package on CRAN and at https://bitbucket.org/l0ka/tpes.git. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Whole exome sequencing identifies genomic alterations in proximal and distal colorectal cancer

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Ryia-Illani Mohd Yunos ◽  
Nurul-Syakima Ab Mutalib ◽  
Sheau Sean Khor ◽  
Sazuita Saidin ◽  
Mohd Ridhwan Abd Razak ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Anatomical Location ◽  
Single Nucleotide Variants ◽  
Functional Studies ◽  
Whole Exome ◽  
Genetic Landscape ◽  
Ion Proton ◽  
Pi3k Signalling

Majority of colorectal cancer (CRC) patients are presented with advanced disease at diagnosis, particularly in cases of proximal CRCs. Little is known about the relationship between the genetic landscape and the anatomical location of the tumour; as well as the prognostication in CRC patients. The objectives of this study were to determine the somatic single nucleotide variants (SNV) and the cellular pathways between the proximal and distal CRCs. Whole exome sequencing was performed on the Ion Proton platform on 10 pairs of normal and CRC samples. The sequencing results were analysed using the Torrent Suite Software and the variants were annotated using ANNOVAR; followed by validation with Sanger sequencing. APC is the most frequently altered gene in both proximal and distal CRCs. KRAS and ATM genes were particularly altered in the proximal CRCs with a frequency of 60% and 40%, respectively. On the other hand, TP53 mutations did not show any CRC anatomical predominance. There were five recurrent novel variants in proximal CRCs and no recurrent variants identified in distal CRC. Wnt signalling pathway was the most frequently altered pathway in both proximal and distal CRCs whereas TGF-? and PI3K signalling pathways were predominantly altered in the proximal CRCs. We found that proximal CRCs presented with more variants and different altered pathways as compared to distal CRCs. However, further study in a larger series of samples coupled with functional studies will be required to confirm the identified variants and determine their roles in the pathogenesis of proximal and distal CRCs.

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