Association of single nucleotide autophagy‐related protein 5 gene polymorphism rs2245214 with susceptibility to non–small cell lung cancer

2018 ◽  
Vol 120 (2) ◽  
pp. 1924-1931 ◽  
Author(s):  
Mohsen Nikseresht ◽  
Maryam Shahverdi ◽  
Mehdi Dehghani ◽  
Hassan Abidi ◽  
Reza Mahmoudi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Gene Polymorphism ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Related Protein ◽  
Small Cell Lung ◽  
Single Nucleotide

scholarly journals Investigation of Caspase 9 Gene Polymorphism in Patients With Non-small Cell Lung Cancer

2019 ◽  
Vol 39 (5) ◽  
pp. 2437-2441 ◽  
Author(s):  
SINA ERCAN ◽  
SIBEL ARINC ◽  
SEDA GULEC YILMAZ ◽  
CIGDEM ALTUNOK ◽  
FERIDE YAMAN ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Gene Polymorphism ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Caspase 9

scholarly journals Computational Prediction of Probable Single Nucleotide Polymorphism-Cancer Relationships

2020 ◽  
Vol 19 ◽  
pp. 117693512094221
Author(s):  
Shahab Bakhtiari ◽  
Sadegh Sulaimany ◽  
Mehrdad Talebi ◽  
Kabmiz Kalhor
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Link Prediction ◽  
Molecular Mechanisms ◽  
Preferential Attachment ◽  
Small Cell ◽  
Bipartite Network ◽  
Small Cell Lung ◽  
Single Nucleotide

Genetic variations such as single nucleotide polymorphisms (SNPs) can cause susceptibility to cancer. Although thousands of genetic variants have been identified to be associated with different cancers, the molecular mechanisms of cancer remain unknown. There is not a particular dataset of relationships between cancer and SNPs, as a bipartite network, for computational analysis and prediction. Link prediction as a computational graph analysis method can help us to gain new insight into the network. In this article, after creating a network between cancer and SNPs using SNPedia and Cancer Research UK databases, we evaluated the computational link prediction methods to foresee new SNP-Cancer relationships. Results show that among the popular scoring methods based on network topology, for relation prediction, the preferential attachment (PA) algorithm is the most robust method according to computational and experimental evidence, and some of its computational predictions are corroborated in recent publications. According to the PA predictions, rs1801394-Non-small cell lung cancer, rs4880-Non-small cell lung cancer, and rs1805794-Colorectal cancer are some of the best probable SNP-Cancer associations that have not yet been mentioned in any published article, and they are the most probable candidates for additional laboratory and validation studies. Also, it is feasible to improve the predicting algorithms to produce new predictions in the future.

scholarly journals MicroRNA-451 functions as a tumor suppressor in human non-small cell lung cancer by targeting ras-related protein 14 (RAB14)

Oncogene ◽  
2011 ◽  
Vol 30 (23) ◽  
pp. 2644-2658 ◽  
Author(s):  
R Wang ◽  
Z-X Wang ◽  
J-S Yang ◽  
X Pan ◽  
W De ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Suppressor ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Related Protein ◽  
Small Cell Lung
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