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Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis

  • Authors:
    • Tian Lan
    • Zunqiang Xiao
    • Hua Luo
    • Kunlun Su
    • Ouou Yang
    • Chengni Zhan
    • Yunyan Lu
  • View Affiliations / Copyright

    Affiliations: Department of Breast Surgery, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang 310007, P.R. China, The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, P.R. China, Department of Cardiology, The First People's Hospital of Xiaoshan, Hangzhou, Zhejiang 311201, P.R. China
    Copyright: © Lan et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 1434-1442
    |
    Published online on: December 11, 2019
       https://doi.org/10.3892/ol.2019.11208
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Abstract

Esophageal cancer (ESCA) carries a poor prognosis among gastrointestinal malignancies. The present study developed a signature based on mRNAs and long non‑coding RNAs (lncRNAs) to predict prognosis in ESCA by using The Cancer Genome Atlas database. By using least absolute shrinkage and selection operator penalized regression, a set of RNAs (three mRNAs and two lncRNAs) was identified and used to build a risk score system of ESCA prognosis, which was used to stratify patients having considerable diverse survival in the training set [hazard ratio (HR), 3.932; 95% CI, 1.555‑9.944; P<0.002] into high‑ and low‑risk groups. The authentication of the results was achieved through the test set (HR, 3.150; 95% CI, 1.113‑8.918; P<0.02) and the entire set (HR, 3.181; 95% CI, 1.686‑6.006; P<0.0002). The results from multivariate Cox proportional hazard regression analysis in the entire set suggested that the prognostic significance of this signature may be independent of patients' clinicopathological characteristics. Furthermore, this signature was associated with several molecular signaling pathways of cancer according to Gene Set Enrichment Analysis. In addition, a nomogram was built and the risk score and TNM stage were integrated to estimate the 1‑ and 3‑year overall survival rates. The results from the present study demonstrated that the integrated mRNA‑lncRNA signature may be considered as a novel biomarker for the prognosis of ESCA.
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Copy and paste a formatted citation
Spandidos Publications style
Lan T, Xiao Z, Luo H, Su K, Yang O, Zhan C and Lu Y: Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis. Oncol Lett 19: 1434-1442, 2020.
APA
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., & Lu, Y. (2020). Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis. Oncology Letters, 19, 1434-1442. https://doi.org/10.3892/ol.2019.11208
MLA
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., Lu, Y."Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis". Oncology Letters 19.2 (2020): 1434-1442.
Chicago
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., Lu, Y."Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis". Oncology Letters 19, no. 2 (2020): 1434-1442. https://doi.org/10.3892/ol.2019.11208
Copy and paste a formatted citation
x
Spandidos Publications style
Lan T, Xiao Z, Luo H, Su K, Yang O, Zhan C and Lu Y: Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis. Oncol Lett 19: 1434-1442, 2020.
APA
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., & Lu, Y. (2020). Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis. Oncology Letters, 19, 1434-1442. https://doi.org/10.3892/ol.2019.11208
MLA
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., Lu, Y."Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis". Oncology Letters 19.2 (2020): 1434-1442.
Chicago
Lan, T., Xiao, Z., Luo, H., Su, K., Yang, O., Zhan, C., Lu, Y."Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis". Oncology Letters 19, no. 2 (2020): 1434-1442. https://doi.org/10.3892/ol.2019.11208
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