期刊
CELL AND BIOSCIENCE
卷 9, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13578-019-0356-1
关键词
TCGA; Lung adenocarcinoma; Transcriptome; Nodal metastasis; Prognosis; RN7SL494P
资金
- National Natural Science Foundation of China [81541153]
- Guangdong Provincial Science and Technology Programs [2016A050503046, 2015A050502048]
- Public Service Platform of South China Sea for R&D Marine Biomedicine Resources [GDMUK201808]
- Fund of Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang) [ZJW-2019-07]
Lymph node metastasis of lung cancer is a serious problem. Therefore, there is a need for a detailed transcriptome study of metastatic lung adenocarcinoma. The lung adenocarcinoma RNA-seq data and the corresponding clinical information available from TCGA were analyzed. Differential expression, gradient changes, and biological pathways were carried out. Potential gene(s) associated with tumor metastasis and survival were validated by Cox regression. A total of 406 and 439 differentially expressed genes were identified for lymph node metastasis and TNM stages, respectively. Of the 296 intersection genes, 112 were associated with nodal metastasis and/or staging. Only 25 of these 112 genes with gradient changes were involved in nodal metastasis, and 13 were involved in staging. Only one gene, RN7SL494P, might be involved in lung adenocarcinoma development and poor outcome. Finally, Cox regression results verified that age, pathology classification, radiotherapy and chemotherapy are all the independent prognostic factors. In particular, RN7SL494P was further verified to be an independent factor affecting lymph node metastasis and patient survival. Furthermore, we verified the RN7SL494P function using simulation data generated by mixing cell lines of the Cancer Cell Line Encyclopedia (CCLE) and obtained consistent results. Our findings suggest a potential clinical application of the RN7SL494P as a promising marker in the evaluation of patients with primary lung adenocarcinoma, not only for predicting nodal metastasis, but also for the prognosis of the outcome.
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