the General Program of National Natural Science Foundation of China(81871896);the General Program of National Natural Science Foundation of China(81672316)
Menglei CHEN, Shuai YUAN, Meiyu ZHOU, et al. Expression of long non-coding RNA SFTA1P in lung adenocarcinoma and its predictive value for prognosis[J]. Journal of Third Military Medical University, 2020, 42(21): 2075-2080, 2215.
DOI:
Menglei CHEN, Shuai YUAN, Meiyu ZHOU, et al. Expression of long non-coding RNA SFTA1P in lung adenocarcinoma and its predictive value for prognosis[J]. Journal of Third Military Medical University, 2020, 42(21): 2075-2080, 2215. DOI: 10.16016/j.1000-5404.202005271.
Expression of long non-coding RNA SFTA1P in lung adenocarcinoma and its predictive value for prognosis
To investigate the expression of long non-coding (lnc) RNA SFTA1P in lung adenocarcinoma
and its association with clinical prognosis in order to construct and evaluate a prognostic prediction model based on SFTA1P.
Methods
2
Real-time fluorescence quantitative PCR was used to detect the expression of SFTA1P in 62 pairs of non-small-cell lung cancer (NSCLC) tissues and corresponding normal lung tissues adjacent to the cancer for the association between SFTA1P expression level and clinical prognosis. The data sets of patients diagnosed with lung adenocarcinoma were downloaded from TCGA database
the required variable data were extracted
and the clinical parameter information and SFTA1P expression of the 471 patients with lung adenocarcinoma were sorted out. Subsequently
variables were screened using univariate and multivariate Cox proportion risk regression models
and a nomogram model was constructed based on the final prognostic prediction model. For the internal validation of the prediction model
Bootstrap resampling method was adopted
and concordance index (C-index) and calibration curve were used respectively to evaluate the discrimination and calibration of the prediction model.
Results
2
The S
FTA1P expression was significantly decreased in the lung cancer tissues than the para-cancerous tissues (0.692±0.103
vs
1.765±0.149
P
<
0.05). There were totally 3 selected independent clinical variables correlating to survival rates in the patients
that is
pathological stage
radiotherapy and SFTA1P expression. In the nomogram model
the calibration curves of 1-year and 3-year survival rates showed that the predicted values had good consistency with the actual values
with a C-index of 0.69 and 95% confidence interval of 0.63~0.75.
Conclusion
2
The expression of lnc RNA SFTA1P can be used as an independent prognostic factor for lung adenocarcinoma. The nomogram model constructed from the above independent variables (including age) can predict the survival rate of the patients.
关键词
Keywords
references
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