scholarly journals In search of non-coding driver mutations by deep sequencing of regulatory elements in colorectal cancer

2018 ◽  
Author(s):  
Rebecca C Poulos ◽  
Dilmi Perera ◽  
Deborah Packham ◽  
Anushi Shah ◽  
Caroline Janitz ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Deep Sequencing ◽  
Regulatory Elements ◽  
Driver Mutations ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Regulatory Variants ◽  
Target Capture ◽  
Target Capture Sequencing ◽  
Capture Sequencing

AbstractLarge-scale whole cancer-genome sequencing projects have led to the identification of a handful of cis-regulatory driver mutations in cancer genomes. However, recent studies have demonstrated that very large cancer cohorts will be required in order to identify low frequency non-coding drivers. To further this endeavour, in this study, we performed highdepth sequencing across 95 colorectal cancers and matched normal samples using a unique target capture sequencing (TCS) assay focusing on over 35 megabases of gene regulatory elements. We first assessed coverage and variant detection capability from our TCS data, and compared this with a sample that was additionally whole-genome sequenced (WGS). TCS enabled substantially deeper sequencing and thus we detected 51% more somatic single nucleotide variants (n = 2,457) and 144% more somatic insertions and deletions (n = 39) by TCS than WGS. Variants obtained from TCS data were suitable for somatic mutational signature detection, enabling us to define the signatures associated with germline deleterious variants in MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory mutations to find putative drivers by assessing variant recurrence and function, identifying some regulatory variants that may influence oncogenesis. Our study demonstrates TCS to be a sequencing-efficient alternative to traditional WGS, enabling improved coverage and variant detection when seeking to identify variants at specific loci among larger cohorts. Interestingly, we found no candidate variants that have a clear driver function, suggesting that regulatory drivers may be rare in a colorectal cancer cohort of this size.Author SummaryIn recent years, some cancer research focus has turned towards the role of somatic mutations in the 98% of the genome that is non-coding. To investigate such mutations, we performed deep sequencing of regulatory regions and a selection of coding genes across 95 colorectal cancer and matched-normal samples. To determine the ability of our targeted deep sequencing methodology to accurately detect variants, we compared our results with those from a sample that was additionally whole-genome sequenced. We found target capture sequencing to enable greater sequencing depth, allowing the detection of 51% and 144% more somatic single nucleotide and insertion/deletion mutations, respectively. Our study here demonstrates target capture sequencing to be a useful approach for researchers seeking to identify variants at specific loci among larger cohorts. Our results also enabled the generation of mutational signatures, implicating deleterious germline single nucleotide variants in coding exons of MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory elements in search of somatic cancer driver mutations. We identified some regulatory variants that may influence oncogenesis, but found no candidate variants with clear driver function. These findings suggest that regulatory driver mutations may be rare in a colorectal cancer cohort of this size.

scholarly journals Scarcity of Recurrent Regulatory Driver Mutations in Colorectal Cancer Revealed by Targeted Deep Sequencing

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Rebecca C Poulos ◽  
Dilmi Perera ◽  
Deborah Packham ◽  
Anushi Shah ◽  
Caroline Janitz ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Excision Repair ◽  
Regulatory Elements ◽  
Driver Mutations ◽  
Gene Promoters ◽  
Driver Genes ◽  
Panel Testing ◽  
Target Capture ◽  
Target Capture Sequencing ◽  
Capture Sequencing

Abstract Background Genetic testing of cancer samples primarily focuses on protein-coding regions, despite most mutations arising in noncoding DNA. Noncoding mutations can be pathogenic if they disrupt gene regulation, but the benefits of assessing promoter mutations in driver genes by panel testing has not yet been established. This is especially the case in colorectal cancer, for which few putative driver variants at regulatory elements have been reported. Methods We designed a unique target capture sequencing panel of 39 colorectal cancer driver genes and their promoters, together with more than 35 megabases of regulatory elements focusing on gene promoters. Using this panel, we sequenced 95 colorectal cancer and matched normal samples at high depth, averaging 170× and 82× coverage, respectively. Results Our target capture sequencing design enabled improved coverage and variant detection across captured regions. We found cases with hereditary defects in mismatch and base excision repair due to deleterious germline coding variants, and we identified mutational spectra consistent with these repair deficiencies. Focusing on gene promoters and other regulatory regions, we found little evidence for base or region-specific recurrence of functional somatic mutations. Promoter elements, including TERT, harbored few mutations, with none showing strong functional evidence. Recurrent regulatory mutations were rare in our sequenced regions in colorectal cancer, though we highlight some candidate mutations for future functional studies. Conclusions Our study supports recent findings that regulatory driver mutations are rare in many cancer types and suggests that the inclusion of promoter regions into cancer panel testing is currently likely to have limited clinical utility in colorectal cancer.

scholarly journals Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Syed H. Zaidi ◽  
Tabitha A. Harrison ◽  
Amanda I. Phipps ◽  
Robert Steinfelder ◽  
Quang M. Trinh ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Impact On Survival

scholarly journals A gain-of-function single nucleotide variant creates a new promoter which acts as an orientation-dependent enhancer-blocker

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yavor K. Bozhilov ◽  
Damien J. Downes ◽  
Jelena Telenius ◽  
A. Marieke Oudelaar ◽  
Emmanuel N. Olivier ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Diseases ◽  
Regulatory Elements ◽  
Base Change ◽  
Dependent Manner ◽  
Globin Genes ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Super Enhancer ◽  
Single Base Change

AbstractMany single nucleotide variants (SNVs) associated with human traits and genetic diseases are thought to alter the activity of existing regulatory elements. Some SNVs may also create entirely new regulatory elements which change gene expression, but the mechanism by which they do so is largely unknown. Here we show that a single base change in an otherwise unremarkable region of the human α-globin cluster creates an entirely new promoter and an associated unidirectional transcript. This SNV downregulates α-globin expression causing α-thalassaemia. Of note, the new promoter lying between the α-globin genes and their associated super-enhancer disrupts their interaction in an orientation-dependent manner. Together these observations show how both the order and orientation of the fundamental elements of the genome determine patterns of gene expression and support the concept that active genes may act to disrupt enhancer-promoter interactions in mammals as in Drosophila. Finally, these findings should prompt others to fully evaluate SNVs lying outside of known regulatory elements as causing changes in gene expression by creating new regulatory elements.

scholarly journals Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
John K. L. Wong ◽  
Christian Aichmüller ◽  
Markus Schulze ◽  
Mario Hlevnjak ◽  
Shaymaa Elgaafary ◽  
...  
Keyword(s):  
Somatic Hypermutation ◽  
Regulatory Elements ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Base Substitution ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Coding Regions ◽  
Mutational Hotspots

AbstractCancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

Whole Exome Sequencing In Relapsed Pediatric T-ALL: Progression Into Relapse Is Characterized By An Increased Number Of Somatic Mutations and a Conservation Of Mutations In Leukemogenic Driver Genes

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 228-228
Author(s):  
Joachim Kunz ◽  
Tobias Rausch ◽  
Obul R Bandapalli ◽  
Martina U. Muckenthaler ◽  
Adrian M Stuetz ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Lymphoblastic Leukemia ◽  
Initial Diagnosis ◽  
Driver Mutations ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Whole Exome ◽  
Recurrent Mutations

Abstract Acute precursor T-lymphoblastic leukemia (T-ALL) remains a serious challenge in pediatric oncology, because relapses carry a particularly poor prognosis with high rates of induction failure and death despite generally excellent treatment responses of the initial disease. It is critical, therefore, to understand the molecular evolution of pediatric T-ALL and to elucidate the mechanisms leading to T-ALL relapse and to understand the differences in treatment response between the two phases of the disease. We have thus subjected DNA from bone marrow samples obtained at the time of initial diagnosis, remission and relapse of 14 patients to whole exome sequencing (WES). Eleven patients suffered from early relapse (duration of remission 6-19 months) and 3 patients from late relapse (duration of remission 29-46 months).The Agilent SureSelect Target Enrichment Kit was used to capture human exons for deep sequencing. The captured fragments were sequenced as 100 bp paired reads using an Illumina HiSeq2000 sequencing instrument. All sequenced DNA reads were preprocessed using Trimmomatic (Lohse et al., Nucl. Acids Res., 2012) to clip adapter contaminations and to trim reads for low quality bases. The remaining reads greater than 36bp were mapped to build hg19 of the human reference genome with Stampy (Lunter & Goodson, Genome Res. 2011), using default parameters. Following such preprocessing, the number of mapped reads was >95% for all samples. Single-nucleotide variants (SNVs) were called using SAMtools mpileup (Li et al., Bioinformatics, 2009). The number of exonic SNVs varied between 23,741 and 31,418 per sample. To facilitate a fast classification and identification of candidate driver mutations, all identified coding SNVs were comprehensively annotated using the ANNOVAR framework (Wang et al., Nat. Rev. Genet., 2010). To identify possible somatic driver mutations, candidate SNVs were filtered for non-synonymous, stopgain or stoploss SNVs, requiring an SNV quality greater or equal to 50, and requiring absence of segmental duplications. Leukemia-specific mutations were identified by filtering against the corresponding remission sample and validated by Sanger sequencing of the genomic DNA following PCR amplification. We identified on average 9.3 somatic single nucleotide variants (SNV) and 0.6 insertions and deletions (indels) per patient sample at the time of initial diagnosis and 21.7 SNVs and 0.3 indels in relapse. On average, 6.3 SNVs were detected both at the time of initial diagnosis and in relapse. These SNVs were thus defined as leukemia specific. Further to SNVs, we have also estimated the frequency of copy number variations (CNV) at low resolution. Apart from the deletions resulting from T-cell receptor rearrangement, we identified on average for each patient 0.7 copy number gains and 2.2 copy number losses at the time of initial diagnosis and 0.5 copy number gains and 2.4 copy number losses in relapse. We detected 24/27 copy number alterations both in initial diagnosis and in relapse. The most common CNV detected was the CDKN2A/B deletion on chromosome 9p. Nine genes were recurrently mutated in 2 or more patients thus indicating the functional leukemogenic potential of these SNVs in T-ALL. These recurrent mutations included known oncogenes (Notch1), tumor suppressor genes (FBXW7, PHF6, WT1) and genes conferring drug resistance (NT5C2). In several patients one gene (such as Notch 1, PHF6, WT1) carried different mutations either at the time of initial diagnosis and or in relapse, indicating that the major leukemic clone had been eradicated by primary treatment, but that a minor clone had persisted and expanded during relapse. The types of mutations did not differ significantly between mutations that were either already present at diagnosis or those that were newly acquired in relapse, indicating that the treatment did not cause specific genomic damage. We will further characterize the clonal evolution of T-ALL into relapse by targeted re-sequencing at high depth of genes with either relapse specific or initial-disease specific mutations. In conclusion, T-ALL relapse differs from primary disease by a higher number of leukemogenic SNVs without gross genomic instability resulting in large CNVs. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Unbiased association and expression studies identify novel genes for tooth development

2017 ◽  
Author(s):  
Meredith A. Williams ◽  
Claudia Biguetti ◽  
Miguel Romero-Bustillos ◽  
Kanwal Maheshwari ◽  
Nuriye Dinckan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tooth Development ◽  
Strong Association ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Independent Dataset ◽  
Expression Studies ◽  
Genome Wide ◽  
Predisposing Genes ◽  
Individual Contributions

AbstractPreviously reported co-occurrence of colorectal cancer (CRC) and tooth agenesis (TA) and the overlap in disease-associated gene variants suggest involvement of similar molecular pathways. In this study, we took an unbiased approach and tested genome-wide significant CRC-associated variants for association with isolated TA. Thirty single nucleotide variants (SNVs) in CRC-predisposing genes/loci were genotyped in a discovery dataset composed of 440 individuals with and without isolated TA. Genome-wide significant associations were found between TA and DUSP10 rs6687758 (P=1.25 × 10−9) and ATF1 rs11169552 (P=4.36 × 10−10), with strong association found with CASC8 rs10505477 (P=8.2 × 10−5). Additional CRC marker haplotypes were also significantly associated with TA (P<0.0002). Genotyping an independent dataset consisting of 52 cases with TA and 427 controls confirmed the association with CASC8.Atf1 and Dusp10 expression was detected in the mouse developing teeth from early bud stages to the formation of the complete tooth, suggesting a potential role for these genes and their encoded proteins in tooth development. Our findings suggest Atf1 and Dusp10 as new tooth development genes, while having a role in colorectal cancer. While their individual contributions in tooth development remain to be elucidated, these genes may be considered additional candidates to be tested in future human genetic studies.

scholarly journals Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

2018 ◽  
Author(s):  
Dimitrios Kleftogiannis ◽  
Marco Punta ◽  
Anuradha Jayaram ◽  
Shahneen Sandhu ◽  
Stephen Q. Wong ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Low Frequency ◽  
Poisson Model ◽  
Real Data ◽  
Analytical Sensitivity ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Deep Sequencing Data ◽  
Targeted Deep Sequencing

AbstractBackgroundTargeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).MethodsTo address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.ResultsOur tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.ConclusionsAmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

scholarly journals Capture Sequencing Is a Useful Method for Comprehensive Clonality Analysis Based on Ig/TCR Gene Rearrangements in Acute Lymphoblastic Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1543-1543
Author(s):  
Dai Nishijima ◽  
Mitsuko Akaihata ◽  
Yuka Iijima-Yamashita ◽  
Tomomi Yamada ◽  
Yuichi Shiraishi ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
T Cell ◽  
High Throughput ◽  
Lymphoblastic Leukemia ◽  
The Other ◽  
Gene Rearrangements ◽  
Clonal Architecture ◽  
Target Capture ◽  
Target Capture Sequencing ◽  
Capture Sequencing

Abstract Introduction Immunoglobulin (Ig)/ T-cell receptor (TCR) gene rearrangements are the most widely used clonal marker to detect residual leukemic cells in patients with Acute Lymphoblastic Leukemia (ALL). Ig/TCR gene rearrangements based molecular minimum residual disease (MRD) monitoring has become one of the most powerful prognostic indicators for patients with ALL. Although the standard method of real-time quantitative PCR (RQ-PCR) provides very good sensitivity in MRD measurement, the workflow is very complicated and time-consuming, requiring expert technique and much work for operation, which limits the number of patients to be examined for MRD monitoring and the number of testable markers per patient. Material and methods To reveal clonal architecture and detect appropriate MRD marker, we designed capture probes covering the coding and recognition signal sequences of V, D, J genes of the Ig/TCR loci. We performed high-throughput target-capture sequencing in 208 pediatric cases with BCP-ALL and 35 pediatric cases with T-cell ALL, including 20 relapsed cases and 14 MRD marker negative cases. Extracted DNA samples were enriched with about 420 capture probes (Agilent Technology) and sequenced by HiSeq2500 platform (Illumina) in order to obtain enough sequence coverage (> 500 mean depth). Sequenced data were analyzed with Ig/TCR recombination analysis tool Vidjil (Giraud et al, 2014) and V(D)J recombination clones were listed according to a number of detected read for each clone. Results Total 2379 clonal Ig/TCR gene rearrangements (median 9 per patient, range 0-82) were detected by capture sequencing among 236 (97%) cases. A clonal IGH sequence with V(D)J recombination was identified in 91% of BCP-ALL cases, followed by TRG (68 %), IGK (67 %), TRA+D (66%), TRD (59 %), TRB (49%), and IGL (15 %), respectively. On the other hand, clonal TRG V(D)J recombination was detected in 74% of T-ALL cases, followed by TRB (69%), TRD (57%), IGH (26%), and TRA+D (6%), respectively. About half of BCP-ALL cases were identified two independent IGH rearrangements. These frequencies agree with previous reports obtained by PCR based experiments. In the cases in this study with well-characterized clonal Ig/TCR gene rearrangements by PCR and Sanger sequencing, our capture sequencing was able to detect all rearrangements used in MRD measurements. Although 8 BCP-ALL cases in this study were marker-negative in standard PCR-MRD diagnostics, clonal Ig/TCR gene rearrangements were identified for 5 out of 8 cases by capture sequencing. Some of the hidden clonal rearrangements showed specific and good quantitative amplification by RQ-PCR and can be used as sensitive PCR-MRD targets. On the other hand, all the MRD marker negative 6 T-ALL cases were not detected clonal Ig/TCR gene rearrangements. Finally, we compared the clonal architecture based on Ig/TCR gene rearrangements between diagnosis and relapse in relapsed B-ALL patients. Changes in the clonal architecture were associated with remission duration. In very early relapse cases, detected Ig/TCR rearrangements and their proportion at relapse are very similar to those at diagnosis. In early to late relapse cases, some major Ig/TCR gene rearrangements were lost at relapse and other minor rearrangements expanded at relapse. Most of the identified Ig/TCR gene rearrangements were different between at diagnosis and at relapse in a case relapsed after more than 10 years. Loss of rearrangements were commonly seen in TRA, TRB, and IgL, while most of the IgK and TRD rearrangements were steady during disease course. Conclusion Introducing target capture sequencing enables to high throughput sample preparation and automated data analysis. Capture sequencing is a useful method for comprehensive detection of Ig/TCR gene rearrangements and contributes to better understanding clonal architecture and detecting appropriate MRD markers in ALL patients. Disclosures No relevant conflicts of interest to declare.

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