scholarly journals Whole exome sequencing of multiple meningiomas with varying histopathological presentation in one patient revealed distinctive somatic mutation burden and independent clonal origins

2019 ◽  
Vol Volume 11 ◽  
pp. 4085-4095 ◽  
Author(s):  
Han-Song Sheng ◽  
Fang Shen ◽  
Nu Zhang ◽  
Li-Sheng Yu ◽  
Xiang-Qi Lu ◽  
...  
2018 ◽  
Author(s):  
Talita Aguiar ◽  
Tatiane Rodrigues ◽  
Cecília Maria Lima da Costa ◽  
Isabela Werneck ◽  
Monica Cypriano ◽  
...  

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Liuxing Feng ◽  
Shifu Hong ◽  
Jin Gao ◽  
Jiayi Li

Purpose. Liver metastasis remains the leading cause of cancer-related mortality in colorectal cancer. The mechanism of occurrence and development of liver metastasis from colorectal cancer is unclear. Methods. The primary tumor tissues and blood samples of 8 patients with liver metastasis of colorectal cancer were collected, followed by nucleic acid extraction and library construction. Whole-exome sequencing was performed to detect the genomic variations. Bioinformatics was used to comprehensively analyze the sequencing data of these samples, including the differences of tumor mutation burden, the characteristics of gene mutations, and signaling pathways. Results. The results showed that the top three genes with the highest mutation frequency were TP53, APC, and KRAS. Tumor mutation burden of this study, with a median of 8.34 mutations per MB, was significantly different with The Cancer Genome Atlas databases. Analysis of molecular function and signaling pathways showed that the mutated genes could be classified into five major categories and 39 signaling pathways, involving in Wnt, angiogenesis, P53, Alzheimer disease-presenilin pathway, notch, and cadherin signaling pathway. Conclusions. In conclusion, we identified the extensive landscape of altered genes and pathways in colorectal cancer liver metastasis, which will be useful to design clinical therapy for personalized medicine.


2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Kenji Watanabe ◽  
Shigeru Yamamoto ◽  
Syuiti Sakaguti ◽  
Keishiro Isayama ◽  
Masaaki Oka ◽  
...  

Author(s):  
Firda Aminy Maruf ◽  
Rian Pratama ◽  
Giltae Song

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.


Leukemia ◽  
2014 ◽  
Vol 28 (4) ◽  
pp. 935-938 ◽  
Author(s):  
L Wang ◽  
S I Swierczek ◽  
J Drummond ◽  
K Hickman ◽  
SJ Kim ◽  
...  

2017 ◽  
Vol 6 (7) ◽  
pp. 540-548 ◽  
Author(s):  
Benjamin G Challis ◽  
Andrew S Powlson ◽  
Ruth T Casey ◽  
Carla Pearson ◽  
Brian Y Lam ◽  
...  

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.


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