dna copy number variation
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Mixed ductal–lobular carcinoma: an analysis of CDH1 DNA copy number variation and mutation

Breast Cancer ◽  
2021 ◽  
Author(s):  
Xiaoyan Tang ◽  
Yoko Nakanishi ◽  
Hiroko Kobayashi ◽  
Haruna Nishimaki ◽  
Yoshiaki Kusumi ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Lobular Carcinoma ◽  
Dna Copy Number ◽  
Dna Copy Number Variation ◽  
Number Variation

Mitochondrial DNA copy number variation – A potential biomarker for early onset preeclampsia

2021 ◽  
Vol 23 ◽  
pp. 1-4
Author(s):  
Deeksha Pandey ◽  
Aarti Yevale ◽  
Ritam Naha ◽  
Raviprasad Kuthethur ◽  
Sanjiban Chakrabarty ◽  
...  
Keyword(s):  
Mitochondrial Dna ◽  
Copy Number Variation ◽  
Early Onset ◽  
Copy Number ◽  
Dna Copy Number ◽  
Dna Copy Number Variation ◽  
Mitochondrial Dna Copy Number ◽  
Potential Biomarker ◽  
Number Variation ◽  
Early Onset Preeclampsia

scholarly journals Multi-omics analysis based on integrated genomics, epigenomics and transcriptomics in pancreatic cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 507-524 ◽  
Author(s):  
Lingming Kong ◽  
Peng Liu ◽  
Mingjun Zheng ◽  
Busheng Xue ◽  
Keke Liang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Copy Number Variation ◽  
Copy Number ◽  
Integrated Analysis ◽  
Molecular Subgroups ◽  
Dna Copy Number ◽  
Dna Copy Number Variation ◽  
New Genes ◽  
Omics Analysis ◽  
Number Variation

Aim: Integrated analysis of genomics, epigenomics, transcriptomics and clinical information contributes to identify specific molecular subgroups and find novel biomarkers for pancreatic cancer. Materials & methods: The DNA copy number variation, the simple nucleotide variation, methylation and mRNA data of pancreatic cancer patients were obtained from The Cancer Genome Atlas. Four molecular subgroups (iC1, iC2, iC3 and iC4) of pancreatic cancer were identified by integrating analysis. Results: The iC1 subgroup harbors better prognosis, higher immune score, lesser DNA copy number variation mutations and better genomic stability compared with iC2, iC3 and iC4 subgroups. Three new genes ( GRAP2, ICAM3 and A2ML1) correlated with prognosis were identified. Conclusion: Integrated multi-omics analysis provides fresh insight into molecular classification of pancreatic cancer, which may help discover new prognostic biomarkers and reveal the underlying mechanism of pancreatic cancer.

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