Chrome Extension
WeChat Mini Program
Use on ChatGLM

Prognostic Value of NF-κB Interacting Long Non-Coding RNA Expression in Lung Adenocarcinoma and Lung Squamous Cell Cancer: a Study Based on the Cancer Genome Atlas Datasets

Translational cancer research(2018)

Cited 0|Views34
No score
Abstract
Background: It has been reported that NF-kappa B interacting long non-coding RNA (NKILA) expression is aberrant in several types of cancers, but its expression level and prognostic value in lung adenocarcinoma (LUAD) and lung squamous cell cancer (LUSC) remain unclear. Therefore, in this study, we aimed to evaluate the prognostic value of NKILA expression in LUAD and LUSC based on publicly available data. Methods: The expression data of NKILA and clinical information concerning LUAD and LUSC were downloaded from the Cancer Genome Atlas (TCGA) datasets. Student's t-test was utilized to analyze the significance of differences between 2 groups, and a one-way ANOVA was performed to test the significance of differences among 3 or more groups. Kaplan-Meier survival curves were implemented to assess the relationship between NKILA expression and overall survival (OS)/5-year survival in cancer patients. P<0.05 was considered to reveal a statistically significant difference. Results: NKILA was upregulated in LUAD cancer tissues compared with matched normal tissues, and there was a significant difference (1.833 +/- 0.440 vs. 0.612 +/- 0.028, P=0.007). The same tendency was observed in LUSC, but there was no significant difference (0.863 +/- 0.158 vs. 0.563 +/- 0.028, P=0.089). Moreover, high NKILA expression was correlated with poor OS in LUAD (log-rank, P=0.008). Conclusions: Our study observed the distinctive expression of NKILA between LUAD and LUSC, suggesting that NKILA may be a biomarker for identifying LUAD and predicting the prognosis of LUAD patients.
More
Translated text
Key words
NF-kappa B interacting long non-coding RNA (NKILA),non-small cell lung cancer (NSCLC),lung adenocarcinoma (LUAD),lung squamous cell cancer (LUSC),prognosis
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined