Identification of potential molecular mechanisms of radiation pneumonitis development in non-small-cell lung cancer treatment by data mining
Identification of potential molecular mechanisms of radiation pneumonitis development in non-small-cell lung cancer treatment by data mining
复制标题
通过数据挖掘鉴定非小细胞肺癌治疗中放射性肺炎发生的潜在分子机制
DOI：
10.1051/radiopro/2020048
复制
发表时间：
2020-08-24
期刊：
影响因子：
1.1
通讯作者：
Xu，Y.
中科院分区：
文献类型：
--
作者：
Zhu，L.;Zhang，J.;Xu，Y.
Introduction: Radiation pneumonitis (RP) is the most significant dose-limiting toxicity in patients receiving thoracic radiotherapy. The underlying mechanisms of RP are still inconclusive. Our objective was to determine the genes and molecular pathways associated with RP using computational tools and publicly available data. Methods: RP-associated genes were determined by text mining, and the intersection of the two gene sets was selected for Gene Ontology analysis using the GeneCodis program. Protein-protein interaction network analysis was performed using STRINGdb to identify the final genes. Results: Our analysis identified 256 genes related to RP with text mining. The enriched biological process annotations resulted in 47 sets of annotations containing a total of 156 unique genes. KEGG analysis of the enriched pathways identified 24 pathways containing a total of 41 unique genes. The protein-protein interaction analysis yielded 23 genes (mostly the PI3K family). Conclusion: Gene discovery using in silico text mining and pathway analysis tools can facilitate the identification of the underlying mechanisms of RP.
