65 research outputs found

    Identification of Insertion Deletion Mutations from Deep Targeted Resequencing

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    Taking advantage of the deep targeted sequencing capabilities of next generation sequencers, we have developed a novel two step insertion deletion (indel) detection algorithm (IDA) that can determine indels from single read sequences with high computational efficiency and sensitivity when indels are fractionally less compared to wild type reference sequence. First, it identifies candidate indel positions utilizing specific sequence alignment artifacts produced by rapid alignment programs. Second, it confirms the location of the candidate indel by using the Smith-Waterman (SW) algorithm on a restricted subset of Sequence reads. We demonstrate that IDA is applicable to indels of varying sizes from deep targeted sequencing data at low fractions where the indel is diluted by wild type sequence. Our algorithm is useful in detecting indel variants present at variable allelic frequencies such as may occur in heterozygotes and mixed normal-tumor tissue

    Allele-Specific Copy Number Profiling by Next-Generation DNA Sequencing

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    The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, Falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. Falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, Falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by Falcon allows us to draw detailed conclusions regarding the clonal history of the individual\u27s colon cancer

    Tumor-associated microbiome features of metastatic colorectal cancer and clinical implications

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    BackgroundColon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) and prognosis. We analyzed 16S rRNA sequencing data from tumor samples of patients with metastatic CRC and determined the clinical implications.Materials and methodsWe enrolled 133 patients with metastatic CRC at St. Vincent Hospital in Korea. The V3-V4 regions of the 16S rRNA gene from the tumor DNA were amplified, sequenced on an Illumina MiSeq, and analyzed using the DADA2 package.ResultsAfter excluding samples that retained <5% of the total reads after merging, 120 samples were analyzed. The median age of patients was 63 years (range, 34–82 years), and 76 patients (63.3%) were male. The primary cancer sites were the right colon (27.5%), left colon (30.8%), and rectum (41.7%). All subjects received 5-fluouracil-based systemic chemotherapy. After removing genera with <1% of the total reads in each patient, 523 genera were identified. Rectal origin, high CEA level (≥10 ng/mL), and presence of lung metastasis showed higher richness. Survival analysis revealed that the presence of Prevotella (p = 0.052), Fusobacterium (p = 0.002), Selenomonas (p<0.001), Fretibacterium (p = 0.001), Porphyromonas (p = 0.007), Peptostreptococcus (p = 0.002), and Leptotrichia (p = 0.003) were associated with short overall survival (OS, <24 months), while the presence of Sphingomonas was associated with long OS (p = 0.070). From the multivariate analysis, the presence of Selenomonas (hazard ratio [HR], 6.35; 95% confidence interval [CI], 2.38–16.97; p<0.001) was associated with poor prognosis along with high CEA level.ConclusionTumor microbiome features may be useful prognostic biomarkers for metastatic CRC

    Emergence of Hemagglutinin Mutations during the Course of Influenza Infection

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    Influenza remains a significant cause of disease mortality. The ongoing threat of influenza infection is partly attributable to the emergence of new mutations in the influenza genome. Among the influenza viral gene products, the hemagglutinin (HA) glycoprotein plays a critical role in influenza pathogenesis, is the target for vaccines and accumulates new mutations that may alter the efficacy of immunization. To study the emergence of HA mutations during the course of infection, we employed a deep-targeted sequencing method. We used samples from 17 patients with active H1N1 or H3N2 influenza infections. These patients were not treated with antivirals. In addition, we had samples from five patients who were analyzed longitudinally. Thus, we determined the quantitative changes in the fractional representation of HA mutations during the course of infection. Across individuals in the study, a series of novel HA mutations directly altered the HA coding sequence were identified. Serial viral sampling revealed HA mutations that either were stable, expanded or were reduced in representation during the course of the infection. Overall, we demonstrated the emergence of unique mutations specific to an infected individual and temporal genetic variation during infection

    Ultrasensitive detection of rare mutations using next-generation targeted resequencing

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    With next-generation DNA sequencing technologies, one can interrogate a specific genomic region of interest at very high depth of coverage and identify less prevalent, rare mutations in heterogeneous clinical samples. However, the mutation detection levels are limited by the error rate of the sequencing technology as well as by the availability of variant-calling algorithms with high statistical power and low false positive rates. We demonstrate that we can robustly detect mutations at 0.1% fractional representation. This represents accurate detection of one mutant per every 1000 wild-type alleles. To achieve this sensitive level of mutation detection, we integrate a high accuracy indexing strategy and reference replication for estimating sequencing error variance. We employ a statistical model to estimate the error rate at each position of the reference and to quantify the fraction of variant base in the sample. Our method is highly specific (99%) and sensitive (100%) when applied to a known 0.1% sample fraction admixture of two synthetic DNA samples to validate our method. As a clinical application of this method, we analyzed nine clinical samples of H1N1 influenza A and detected an oseltamivir (antiviral therapy) resistance mutation in the H1N1 neuraminidase gene at a sample fraction of 0.18%

    Metastatic Tumor Evolution and Organoid Modeling Implicate TGFBR2 as a Cancer Driver in Diffuse Gastric Cancer

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    Background: Gastric cancer is the second-leading cause of global cancer deaths, with metastatic disease representing the primary cause of mortality. To identify candidate drivers involved in oncogenesis and tumor evolution, we conduct an extensive genome sequencing analysis of metastatic progression in a diffuse gastric cancer. This involves a comparison between a primary tumor from a hereditary diffuse gastric cancer syndrome proband and its recurrence as an ovarian metastasis. Results: Both the primary tumor and ovarian metastasis have common biallelic loss-of-function of both the CDH1 and TP53 tumor suppressors, indicating a common genetic origin. While the primary tumor exhibits amplification of the Fibroblast growth factor receptor 2 (FGFR2) gene, the metastasis notably lacks FGFR2 amplification but rather possesses unique biallelic alterations of Transforming growth factor-beta receptor 2 (TGFBR2), indicating the divergent in vivo evolution of a TGFBR2-mutant metastatic clonal population in this patient. As TGFBR2 mutations have not previously been functionally validated in gastric cancer, we modeled the metastatic potential of TGFBR2 loss in a murine three-dimensional primary gastric organoid culture. The Tgfbr2 shRNA knockdown within Cdh1-/-; Tp53-/- organoids generates invasion in vitro and robust metastatic tumorigenicity in vivo, confirming Tgfbr2 metastasis suppressor activity. Conclusions: We document the metastatic differentiation and genetic heterogeneity of diffuse gastric cancer and reveal the potential metastatic role of TGFBR2 loss-of-function. In support of this study, we apply a murine primary organoid culture method capable of recapitulating in vivo metastatic gastric cancer. Overall, we describe an integrated approach to identify and functionally validate putative cancer drivers involved in metastasi

    Large Cancer Pedigree Involving Multiple Cancer Genes including Likely Digenic MSH2 and MSH6 Lynch Syndrome (LS) and an Instance of Recombinational Rescue from LS

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    Funding Information: This research was funded in part by a Cedars-Sinai Medical Center Precision Health Initiative Award to Megan P. Hitchins and Andrew Hendifar. Publisher Copyright: © 2022 by the authors.Lynch syndrome (LS), caused by heterozygous pathogenic variants affecting one of the mismatch repair (MMR) genes (MSH2, MLH1, MSH6, PMS2), confers moderate to high risks for colorectal, endometrial, and other cancers. We describe a four-generation, 13-branched pedigree in which multiple LS branches carry the MSH2 pathogenic variant c.2006G>T (p.Gly669Val), one branch has this and an additional novel MSH6 variant c.3936_4001+8dup (intronic), and other non-LS branches carry variants within other cancer-relevant genes (NBN, MC1R, PTPRJ). Both MSH2 c.2006G>T and MSH6 c.3936_4001+8dup caused aberrant RNA splicing in carriers, including out-of-frame exon-skipping, providing functional evidence of their pathogenicity. MSH2 and MSH6 are co-located on Chr2p21, but the two variants segregated independently (mapped in trans) within the digenic branch, with carriers of either or both variants. Thus, MSH2 c.2006G>T and MSH6 c.3936_4001+8dup independently confer LS with differing cancer risks among family members in the same branch. Carriers of both variants have near 100% risk of transmitting either one to offspring. Nevertheless, a female carrier of both variants did not transmit either to one son, due to a germline recombination within the intervening region. Genetic diagnosis, risk stratification, and counseling for cancer and inheritance were highly individualized in this family. The finding of multiple cancer-associated variants in this pedigree illustrates a need to consider offering multicancer gene panel testing, as opposed to targeted cascade testing, as additional cancer variants may be uncovered in relatives.Peer reviewe

    Germline variants of ATG7 in familial cholangiocarcinoma alter autophagy and p62

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    Funding Information: The authors recognize and appreciate the patients and families who contributed to the current study. We acknowledge the Icelandic Cancer Registry for assistance in the ascertainment of the Icelandic cancer patients. We thank deCODE genetics for access to data and facilities, assistance with data analysis and helpful discussions. This work was supported by the National Institutes of Health [P01HG000205 to SUG and HPJ, 1U01CA15192001-A1 to HPJ, 1U01CA176299 to HPJ, HG006137-07 to HPJ, R01 CA116468NIH to DAJ, 5K08CA166512 to LDN]; Intermountain Healthcare to SUG, JC and HPJ; a Research Scholar Grant from the American Cancer Society [RSG-13-297-01-TBG to JC and HPJ]; Clayville Foundation to HPJ; Gastric Cancer Foundation to HPJ and LDN; the Samuel Waxman Cancer Research Foundation to DAJ; Oklahoma Center for Adult Stem Cell Research (OCASCR) to DAJ; Oklahoma Medical Research Foundation (OMRF) to DAJ; the Conquer Cancer Foundation (Young Investigator Award) to LDN; the Carl Kawaja Foundation to LDN; the Research Fund of Iceland [130230-0529 to ES and MHO, 184861-052 to ES, 184727-051 to MHO]; and a grant from the Icelandic Cancer Society Research Fund to MHO. Publisher Copyright: © 2022, The Author(s).Autophagy is a housekeeping mechanism tasked with eliminating misfolded proteins and damaged organelles to maintain cellular homeostasis. Autophagy deficiency results in increased oxidative stress, DNA damage and chronic cellular injury. Among the core genes in the autophagy machinery, ATG7 is required for autophagy initiation and autophagosome formation. Based on the analysis of an extended pedigree of familial cholangiocarcinoma, we determined that all affected family members had a novel germline mutation (c.2000C>T p.Arg659* (p.R659*)) in ATG7. Somatic deletions of ATG7 were identified in the tumors of affected individuals. We applied linked-read sequencing to one tumor sample and demonstrated that the ATG7 somatic deletion and germline mutation were located on distinct alleles, resulting in two hits to ATG7. From a parallel population genetic study, we identified a germline polymorphism of ATG7 (c.1591C>G p.Asp522Glu (p.D522E)) associated with increased risk of cholangiocarcinoma. To characterize the impact of these germline ATG7 variants on autophagy activity, we developed an ATG7-null cell line derived from the human bile duct. The mutant p.R659* ATG7 protein lacked the ability to lipidate its LC3 substrate, leading to complete loss of autophagy and increased p62 levels. Our findings indicate that germline ATG7 variants have the potential to impact autophagy function with implications for cholangiocarcinoma development.Peer reviewe

    A Flexible Approach for Highly Multiplexed Candidate Gene Targeted Resequencing

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    We have developed an integrated strategy for targeted resequencing and analysis of gene subsets from the human exome for variants. Our capture technology is geared towards resequencing gene subsets substantially larger than can be done efficiently with simplex or multiplex PCR but smaller in scale than exome sequencing. We describe all the steps from the initial capture assay to single nucleotide variant (SNV) discovery. The capture methodology uses in-solution 80-mer oligonucleotides. To provide optimal flexibility in choosing human gene targets, we designed an in silico set of oligonucleotides, the Human OligoExome, that covers the gene exons annotated by the Consensus Coding Sequencing Project (CCDS). This resource is openly available as an Internet accessible database where one can download capture oligonucleotides sequences for any CCDS gene and design custom capture assays. Using this resource, we demonstrated the flexibility of this assay by custom designing capture assays ranging from 10 to over 100 gene targets with total capture sizes from over 100 Kilobases to nearly one Megabase. We established a method to reduce capture variability and incorporated indexing schemes to increase sample throughput. Our approach has multiple applications that include but are not limited to population targeted resequencing studies of specific gene subsets, validation of variants discovered in whole genome sequencing surveys and possible diagnostic analysis of disease gene subsets. We also present a cost analysis demonstrating its cost-effectiveness for large population studies
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