scholarly journals MicroRNA expression profiling involved in doxorubicin‑induced cardiotoxicity using high‑throughput deep‑sequencing analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ying Chen ◽  
Yingjie Xu ◽  
Zhoufeng Deng ◽  
Yin Wang ◽  
Ying Zheng ◽  
...  
Keyword(s):  
High Throughput ◽  
Deep Sequencing ◽  
Expression Profiling ◽  
Microrna Expression ◽  
Sequencing Analysis ◽  
Deep Sequencing Analysis

scholarly journals Deep sequencing analysis of microRNA expression in porcine serum-induced hepatic fibrosis rats

2014 ◽  
Vol 13 (4) ◽  
pp. 439-449 ◽  
Author(s):  
Shanfei Ge ◽  
Xiaowei Wang ◽  
Jianping Xie ◽  
Xin Yi ◽  
Fei Liu
Keyword(s):  
Hepatic Fibrosis ◽  
Deep Sequencing ◽  
Microrna Expression ◽  
Sequencing Analysis ◽  
Porcine Serum ◽  
Deep Sequencing Analysis

Deep sequencing analysis of microRNA expression in human melanocyte and melanoma cell lines

Gene ◽  
2015 ◽  
Vol 572 (1) ◽  
pp. 135-145 ◽  
Author(s):  
Nan Ding ◽  
Shaobin Wang ◽  
Qiong Yang ◽  
Yongjun Li ◽  
Hua Cheng ◽  
...  
Keyword(s):  
Cell Lines ◽  
Melanoma Cell ◽  
Deep Sequencing ◽  
Microrna Expression ◽  
Sequencing Analysis ◽  
Human Melanocyte ◽  
Deep Sequencing Analysis ◽  
Melanoma Cell Lines

scholarly journals Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Marta Rodríguez ◽  
Cristina Bajo-Santos ◽  
Nina P. Hessvik ◽  
Susanne Lorenz ◽  
Bastian Fromm ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Sequencing ◽  
Sequencing Analysis ◽  
Non Invasive ◽  
Urinary Exosomes ◽  
Deep Sequencing Analysis

scholarly journals Novel insight into the non-coding repertoire through deep sequencing analysis

2012 ◽  
Vol 40 (11) ◽  
pp. e86-e86 ◽  
Author(s):  
Ofer Isakov ◽  
Roy Ronen ◽  
Judit Kovarsky ◽  
Aviram Gabay ◽  
Ido Gan ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Sequencing Analysis ◽  
Deep Sequencing Analysis ◽  
Insight Into

scholarly journals Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum

2015 ◽  
Vol 31 (13) ◽  
pp. 2141-2150 ◽  
Author(s):  
Ofer Isakov ◽  
Antonio V. Bordería ◽  
David Golan ◽  
Amir Hamenahem ◽  
Gershon Celniker ◽  
...  
Keyword(s):  
Viral Infection ◽  
Deep Sequencing ◽  
Sequencing Analysis ◽  
Detailed Characterization ◽  
Viral Mutant ◽  
Mutant Spectrum ◽  
Deep Sequencing Analysis

scholarly journals Deep Sequencing Analysis Identified a Specific Subset of Mutations Distinctive of Biphasic Malignant Pleural Mesothelioma

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2454
Author(s):  
Federica Torricelli ◽  
Filippo Lococo ◽  
Teresa Severina Di Stefano ◽  
Eugenia Lorenzini ◽  
Simonetta Piana ◽  
...  
Keyword(s):  
Malignant Pleural Mesothelioma ◽  
Deep Sequencing ◽  
Validation Cohort ◽  
Genetic Alterations ◽  
Pleural Mesothelioma ◽  
Sequencing Analysis ◽  
Specific Subset ◽  
Validation Set ◽  
Custom Panel ◽  
Deep Sequencing Analysis

Malignant Pleural Mesothelioma (MPM) is a heterogeneous disease. Morphologically, three different phenotypes are distinguishable: epithelioid (e-), sarcomatoid (s-) and biphasic (biph-) MPM, the latest, being a mixture of e- and s-MPM cells. Being an intermediate entity, management of biph-MPM, remains debatable and controversial, with different guidelines recommending distinct approaches. Identification of biph-MPM associated genetic alterations, through deep sequencing analysis, may provide useful tools to understand these lesions. A retrospective cohort of 69 surgically resected MPMs, 39 biph-MPMs (56.5%) and 30 e-MPMs (43.5%) was selected. A separate set of 16 biph-MPM was used as validation set. Deep sequencing analysis on an MPM-specific custom panel (MPM_geneset) comprising 1041 amplicons spanning 34 genes was performed. A total of 588 variants and 5309 mutational events were detected. In total, 91.3% of MPMs showed at least one mutation and 76.8% showed co-occurrence of more than one alteration. Mutations in MXRA5 (p = 0.05) and NOD2 (p = 0.018) were significantly associated with biph-MPM both in the training and validation cohort and correlated with the extent of the sarcomatoid component. Mutations in NOD2 and XRCC6 correlated with patients’ survival. We demonstrated that biph-MPM are associated with a specific mutation set, and that genetic analysis at diagnosis may improve patients’ risk stratification.

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