scholarly journals Designing PCR Primers for Detecting Clinically Actionable Single Nucleotide Variation for Non-Small Cell Lung Cancer

2020 ◽  
Vol 2 (2) ◽  
pp. 17-21
Author(s):  
Jamie H. Kwon
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Pcr Primers ◽  
Small Cell ◽  
Nucleotide Variation ◽  
Single Nucleotide Variation ◽  
Small Cell Lung ◽  
Single Nucleotide

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 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 Biopsy of palliative lesions following radiotherapy

BJR|Open ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 20180025
Author(s):  
Shiro Fujita ◽  
Katsuhiro Masago ◽  
Yasushi Yatabe
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Driver Mutations ◽  
Small Cell Lung ◽  
Single Nucleotide ◽  
Course Of Disease ◽  
Definitive Radiotherapy ◽  
Post Therapy

Objective: Definite radiotherapy and/or chemoradiotherapy is often conducted for the treatment of non-small cell lung cancer. However, there is a potential concern regarding the mutagenic effects on tumor cells derived from the therapies, and genomic information regarding cancer cells that survived definitive radiotherapy/chemoradiotherapy is lacking. To evaluate the mutagenic effect of radiotherapy/chemoradiotherapy, we compared genomic signatures of recurrent non-small cell lung cancer tissue with those of pre-treatment. Methods: We evaluated seven specimens from three patients who developed disease recurrence after definite radiotherapy/chemoradiotherapy, and we ranked the mutations according to the Combined Annotation-Dependent Depletion score. Results: Some mutations remained in the post-therapy state, and others, including driver mutations, either newly occurred or disappeared during the course of disease. Of the four specimens obtained in the post-radiation period, 21 variants were detected. Compared with single nucleotide substitution (5, 23.8%), substantial number of deletions (16, 76.2%) was observed in specimens obtained after definite radiotherapy/chemoradiotherapy. Conclusion: Radiotherapy/chemoradiotherapy effects on tumor cells have a wide spectrum, and resequencing of a recurrent lesion is always recommended to discuss the best course of therapy for recurrent non-small cell lung cancer after definitive radiotherapy/chemoradiotherapy. Advances in knowledge: With regard to cancer cells that survived definitive radiotherapy/chemoradiotherapy, some mutations remained in the post-therapy state, and others, including driver mutations, either newly occurred or disappeared during the course of disease. Compared with single nucleotide substitution, substantial number of deletions was observed in specimens obtained after definite radiotherapy/chemoradiotherapy.

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