Abstract 2556: The somatic variant of HLRCC, an unrecognized type of RCC

2021 ◽  
Author(s):  
Maria J. Merino ◽  
Esra Dikoglu ◽  
Sandeep Gurram ◽  
Marston Linehan ◽  
Ramaprasad Srinivasan
Keyword(s):  
Somatic Variant

scholarly journals Novel idiotypic and antigen-binding characteristics in two anti-dinitrophenyl monoclonal antibodies.

1977 ◽  
Vol 146 (1) ◽  
pp. 282-286 ◽  
Author(s):  
N H Sigal
Keyword(s):  
Monoclonal Antibodies ◽  
Germ Line ◽  
Hypervariable Region ◽  
Weight Basis ◽  
Antigen Binding ◽  
The Novel ◽  
Maximum Frequency ◽  
Somatic Variant ◽  
Binding Characteristics ◽  
Cell Pool

Monoclonal anti-dinitrophenyl antibodies generated in the splenic focus system from B cells of adult BALB/c mice were studied for the presence or absence of murine anti-T15 (M anti-T15) reactivity and for their ability to bind phosphorylcholine (PC). Two foci of the 680 clones analyzed bound PC, and one of these antibodies reacted with M anti-T15 and anti-Fab on a 1:1 weight basis. The discovery of a clonotype reactive with M anti-15 but not with rabbit anti-T15 (R anti-T15) serum, the converse of the R anti-T15+, M anti-T15- clonotype identified in the PC-specific repertoire, points to the novel idiotypic relationships which may be found among homogeneous antibodies binding diverse antigens. The R anti-T15-, M anti-T15+ clonotype may represent a distinct set of hypervariable region sequences inserted into the T15 framework or may be a somatic variant of the T15 germ-line sequence. In addition, the maximum frequency with which this clonotype occurs within the B-cell pool is estimated.

scholarly journals Paired analysis of tumor mutation burden for lung adenocarcinoma and associated idiopathic pulmonary fibrosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yasuto Yoneshima ◽  
Eiji Iwama ◽  
Shingo Matsumoto ◽  
Taichi Matsubara ◽  
Testuzo Tagawa ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Lung Adenocarcinoma ◽  
Genetic Alterations ◽  
Driver Mutations ◽  
Somatic Variant ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
And Oxidative Stress

AbstractGenetic alterations underlying the development of lung cancer in individuals with idiopathic pulmonary fibrosis (IPF) have remained unclear. To explore whether genetic alterations in IPF tissue contribute to the development of IPF-associated lung cancer, we here evaluated tumor mutation burden (TMB) and somatic variants in 14 paired IPF and tumor samples from patients with IPF-associated lung adenocarcinoma. We also determined TMB for 22 samples of lung adenocarcinoma from patients without IPF. TMB for IPF-associated lung adenocarcinoma was significantly higher than that for matched IPF tissue (median of 2.94 vs. 1.26 mutations/Mb, P = 0.002). Three and 102 somatic variants were detected in IPF and matched lung adenocarcinoma samples, respectively, with only one pair of specimens sharing one somatic variant. TMB for IPF-associated lung adenocarcinoma was similar to that for lung adenocarcinoma samples with driver mutations (median of 2.94 vs. 2.51 mutations/Mb) and lower than that for lung adenocarcinoma samples without known driver mutations (median of 2.94 vs. 5.03 mutations/Mb, P = 0.130) from patients without IPF. Our findings suggest that not only the accumulation of somatic mutations but other factors such as inflammation and oxidative stress might contribute to the development and progression of lung cancer in patients with IPF.

Specific Inhibitory Effect of H1e Histone Somatic Variant onin VitroDNA-Methylation Process

1996 ◽  
Vol 220 (1) ◽  
pp. 102-107 ◽  
Author(s):  
Giuseppe Zardo ◽  
Raffaella Santoro ◽  
Maria D'Erme ◽  
Anna Reale ◽  
Leo Guidobaldi ◽  
...  
Keyword(s):  
Inhibitory Effect ◽  
Somatic Variant

Performance Comparison of Computational Prediction Methods for the Function and Pathogenicity of Non-coding Variants

2021 ◽  
Author(s):  
Zheng Wang ◽  
Guihu Zhao ◽  
Bin Li ◽  
Zhenghuan Fang ◽  
Qian Chen ◽  
...  
Keyword(s):  
Computational Methods ◽  
Method Development ◽  
De Novo ◽  
Autism Spectrum ◽  
Common Variant ◽  
Tool Selection ◽  
Somatic Variant ◽  
Germline Variant ◽  
Regulatory Variant ◽  
Coding Variants

Non-coding variants in the human genome greatly influence some traits and complex diseases by their own regulation and modification effects. Hence, an increasing number of computational methods are developed to predict the effects of variants in the human non-coding sequences. However, it is difficult for users with insufficient knowledge about the performances of computational methods to select appropriate computational methods from dozens of methods. In order to solve this problem, we assessed 12 performance measures of 24 methods on four independent non-coding variant benchmark datasets: (Ⅰ) rare germline variant from ClinVar, (Ⅱ) rare somatic variant from COSMIC, (Ⅲ) common regulatory variant dataset, and (Ⅳ) disease associated common variant dataset. All 24 tested methods performed differently under various conditions, indicating that these methods have varying strengths and weaknesses under different scenarios. Importantly, the performance of existing methods was acceptable in the rare germline variant from ClinVar with area under curves (AUCs) of 0.4481 - 0.8033 and poor in the rare somatic variant from COSMIC (AUCs: 0.4984 - 0.7131), common regulatory variant dataset (AUCs: 0.4837 - 0.6472), and disease associated common variant dataset (AUCs: 0.4766 -0.5188). We also compared the prediction performance among 24 methods for non-coding de novo mutations in autism spectrum disorder and found that the CADD and CDTS methods showed better performance. Summarily, we assessed the performances of 24 computational methods under diverse scenarios, providing preliminary advice for proper tool selection and new method development in interpreting non-coding variants.

scholarly journals SomaticCombiner: improving the performance of somatic variant calling based on evaluation tests and a consensus approach

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mingyi Wang ◽  
Wen Luo ◽  
Kristine Jones ◽  
Xiaopeng Bian ◽  
Russell Williams ◽  
...  
Keyword(s):  
Variant Calling ◽  
Consensus Approach ◽  
Somatic Variant

scholarly journals Somatic variant analysis of linked-reads sequencing data with Lancet

2020 ◽  
Author(s):  
Rajeeva Musunuri ◽  
Kanika Arora ◽  
André Corvelo ◽  
Minita Shah ◽  
Jennifer Shelton ◽  
...  
Keyword(s):  
Supplementary Information ◽  
De Bruijn Graph ◽  
Haplotype Structure ◽  
Sequencing Data ◽  
Somatic Variant ◽  
Local Assembly ◽  
De Bruijn ◽  
Variant Analysis ◽  
Colored De Bruijn Graph ◽  
Commercial Research

Abstract Summary We present a new version of the popular somatic variant caller, Lancet, that supports the analysis of linked-reads sequencing data. By seamlessly integrating barcodes and haplotype read assignments within the colored De Bruijn graph local-assembly framework, Lancet computes a barcode-aware coverage and identifies variants that disagree with the local haplotype structure. Availability and implementation Lancet is implemented in C++ and available for academic and non-commercial research purposes as an open-source package at https://github.com/nygenome/lancet. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals neoepiscope improves neoepitope prediction with multivariant phasing

2019 ◽  
Vol 36 (3) ◽  
pp. 713-720 ◽  
Author(s):  
Mary A Wood ◽  
Austin Nguyen ◽  
Adam J Struck ◽  
Kyle Ellrott ◽  
Abhinav Nellore ◽  
...  
Keyword(s):  
False Negative ◽  
Supplementary Information ◽  
Supplementary File ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Somatic Variant ◽  
Negative Results ◽  
Multiple Datasets ◽  
False Negative Results

Abstract Motivation The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for the co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false-positive and false-negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels). Results Herein, we illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible and supports several major histocompatibility complex binding affinity prediction tools. Availability and implementation neoepiscope is available on GitHub at https://github.com/pdxgx/neoepiscope under the MIT license. Scripts for reproducing results described in the text are available at https://github.com/pdxgx/neoepiscope-paper under the MIT license. Additional data from this study, including summaries of variant phasing incidence and benchmarking wallclock times, are available in Supplementary Files 1, 2 and 3. Supplementary File 1 contains Supplementary Table 1, Supplementary Figures 1 and 2, and descriptions of Supplementary Tables 2–8. Supplementary File 2 contains Supplementary Tables 2–6 and 8. Supplementary File 3 contains Supplementary Table 7. Raw sequencing data used for the analyses in this manuscript are available from the Sequence Read Archive under accessions PRJNA278450, PRJNA312948, PRJNA307199, PRJNA343789, PRJNA357321, PRJNA293912, PRJNA369259, PRJNA305077, PRJNA306070, PRJNA82745 and PRJNA324705; from the European Genome-phenome Archive under accessions EGAD00001004352 and EGAD00001002731; and by direct request to the authors. Supplementary information Supplementary data are available at Bioinformatics online.

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