scholarly journals Whole-exome sequencing identifies a novel somatic mutation in MMP8 associated with a t(1;22)-acute megakaryoblastic leukemia

Leukemia ◽  
2013 ◽  
Vol 28 (4) ◽  
pp. 945-948 ◽  
Author(s):  
Y Kim ◽  
V P Schulz ◽  
N Satake ◽  
T A Gruber ◽  
A M Teixeira ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Acute Megakaryoblastic Leukemia ◽  
Megakaryoblastic Leukemia ◽  
Whole Exome

scholarly journals A novel somatic mutation of SIN3A detected in breast cancer by whole-exome sequencing enhances cell proliferation through ERα expression

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Kenji Watanabe ◽  
Shigeru Yamamoto ◽  
Syuiti Sakaguti ◽  
Keishiro Isayama ◽  
Masaaki Oka ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Proliferation ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Whole Exome

scholarly journals DNN-Boost: Somatic mutation identification of tumor-only whole-exome sequencing data using deep neural network and XGBoost

2021 ◽  
Author(s):  
Firda Aminy Maruf ◽  
Rian Pratama ◽  
Giltae Song
Keyword(s):  
Neural Network ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Deep Neural Network ◽  
Somatic Mutations ◽  
Sequencing Data ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Detection of somatic mutation in whole-exome sequencing data can help elucidate the mechanism of tumor progression. Most computational approaches require exome sequencing for both tumor and normal samples. However, it is more common to sequence exomes for tumor samples only without the paired normal samples. To include these types of data for extensive studies on the process of tumorigenesis, it is necessary to develop an approach for identifying somatic mutations using tumor exome sequencing data only. In this study, we designed a machine learning approach using Deep Neural Network (DNN) and XGBoost to identify somatic mutations in tumor-only exome sequencing data and we integrated this into a pipeline called DNN-Boost. The XGBoost algorithm is used to extract the features from the results of variant callers and these features are then fed into the DNN model as input. The XGBoost algorithm resolves issues of missing values and overfitting. We evaluated our proposed model and compared its performance with other existing benchmark methods. We noted that the DNN-Boost classification model outperformed the benchmark method in classifying somatic mutations from paired tumor-normal exome data and tumor-only exome data.

scholarly journals Whole-exome sequencing of polycythemia vera revealed novel driver genes and somatic mutation shared by T cells and granulocytes

Leukemia ◽  
2014 ◽  
Vol 28 (4) ◽  
pp. 935-938 ◽  
Author(s):  
L Wang ◽  
S I Swierczek ◽  
J Drummond ◽  
K Hickman ◽  
SJ Kim ◽  
...  
Keyword(s):  
T Cells ◽  
Polycythemia Vera ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Driver Genes ◽  
Whole Exome

scholarly journals Adult-onset hyperinsulinaemic hypoglycaemia in clinical practice: diagnosis, aetiology and management

2017 ◽  
Vol 6 (7) ◽  
pp. 540-548 ◽  
Author(s):  
Benjamin G Challis ◽  
Andrew S Powlson ◽  
Ruth T Casey ◽  
Carla Pearson ◽  
Brian Y Lam ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Metastatic Disease ◽  
Stage Iv ◽  
Stage I ◽  
Adult Onset ◽  
Hyperinsulinaemic Hypoglycaemia ◽  
Whole Exome ◽  
Glucokinase Mutation

Objective In adults with hyperinsulinaemic hypoglycaemia (HH), in particular those with insulinoma, the optimal diagnostic and management strategies remain uncertain. Here, we sought to characterise the biochemical and radiological assessment, and clinical management of adults with HH at a tertiary centre over a thirteen-year period. Design Clinical, biochemical, radiological and histological data were reviewed from all confirmed cases of adult-onset hyperinsulinaemic hypoglycaemia at our centre between 2003 and 2016. In a subset of patients with stage I insulinoma, whole-exome sequencing of tumour DNA was performed. Results Twenty-nine patients were identified (27 insulinoma, including 6 subjects with metastatic disease; 1 pro-insulin/GLP-1 co-secreting tumour; 1 activating glucokinase mutation). In all cases, hypoglycaemia (glucose ≤2.2 mmol/L) was achieved within 48 h of a supervised fast. At fast termination, subjects with stage IV insulinoma had significantly higher insulin, C-peptide and pro-insulin compared to those with insulinoma staged I–IIIB. Preoperative localisation of insulinoma was most successfully achieved with EUS. In two patients with inoperable, metastatic insulinoma, peptide receptor radionuclide therapy (PRRT) with 177Lu-DOTATATE rapidly restored euglycaemia and lowered fasting insulin. Finally, in a subset of stage I insulinoma, whole-exome sequencing of tumour DNA identified the pathogenic Ying Yang-1 (YY1) somatic mutation (c.C1115G/p.T372R) in one tumour, with all tumours exhibiting a low somatic mutation burden. Conclusion Our study highlights, in particular, the utility of the 48-h fast in the diagnosis of insulinoma, EUS for tumour localisation and the value of PRRT therapy in the treatment of metastatic disease.

scholarly journals Whole-exome sequencing of plasma cell-free DNA portrays the somatic mutation landscape of refractory metastatic colorectal cancer and enables the discovery of mutatedKDR/VEGFR2 receptors as modulators of anti-angiogenic therapies

2017 ◽  
Author(s):  
Rodrigo A. Toledo ◽  
Elena Garralda ◽  
Maria Mitsi ◽  
Tirso Pons ◽  
Jorge Monsech ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Plasma Cell ◽  
Somatic Mutations ◽  
Free Dna ◽  
Whole Exome ◽  
Cancer Mutations

ABSTRACTThe non-invasive detection of cancer mutations is a breakthrough in oncology. Here, we applied whole-exome sequencing of matched germline and basal plasma cell-free DNA samples (WES-cfDNA) on aRAS/BRAF/PIK3CAwild-type metastatic colorectal cancer patient with primary resistance to standard treatment regimens including VEGFR inhibitors. Using WES-cfDNA, we could detect 73% (54/74) of the somatic mutations uncovered by WES-tumor including a variety of mutation types: frameshift (indels), missense, noncoding (splicing), and nonsense mutations. Additionally, WES-cfDNA discovered 14 high-confidence somatic mutations not identified by WES-tumor. Importantly, in the absence of the tumor specimen, WES-cfDNA could identify 68 of the 88 (77.3%) total mutations that could be identified by both techniques. Of tumor biology relevance, we identified the novelKDR/VEGFR2 L840F somatic mutation, which we showed was a clonal mutation event in this tumor. Comprehensivein vitroandin vivofunctional assays confirmed that L840F causes strong resistance to anti-angiogenic drugs, whereas theKDR/VEGFR2 hot-spot mutant R1032Q confers sensitivity to cabozantinib. Moreover, we found a 1-3% of recurrentKDRsomatic mutations across large and non-overlapping cancer sequencing projects, and the majority of these mutations were located in protein residues frequently mutated in other cancer-relevant kinases, such as EGFR, ABL1, and ALK, suggesting a functional role.In summary, the current study highlights the capability of exomic sequencing of cfDNA from plasma of cancer patients as a powerful platform for somatic landscape analysis and discovery of resistance-associated cancer mutations. Because of its advantage to generate results highly concordant to those of tumor sequencing without the hurdle of conventional tumor biopsies, we anticipate that WES-cfDNA will become frequently used in oncology. Moreover, our study identified for the first-timeKDR/VEGFR2 somatic mutations as potential genetic biomarkers of response to anti-angiogenic cancer therapies and will serve as reference for further studies on the topic.

Whole-exome sequencing reveals recurrent somatic mutation networks in cancer

2013 ◽  
Vol 340 (2) ◽  
pp. 270-276 ◽  
Author(s):  
Xiaoping Liu ◽  
Jiguang Wang ◽  
Luonan Chen
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Whole Exome

Abstract A18: Insights into the somatic mutation burden of hepatoblastomas using whole exome sequencing

2018 ◽  
Author(s):  
Talita Aguiar ◽  
Tatiane Rodrigues ◽  
Cecília Maria Lima da Costa ◽  
Isabela Werneck ◽  
Monica Cypriano ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Somatic Mutation ◽  
Whole Exome ◽  
Mutation Burden
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