LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database

LI Menghan; XIAO Qiong; GAO Peng; FU Yu; SUN Chenrui; SONG Yongxi

doi:10.3971/j.issn.1000-8578.2022.21.1159

Cancer Research on Prevention and Treatment > 2022 > 49(6): 606-611. > DOI: 10.3971/j.issn.1000-8578.2022.21.1159

LI Menghan, XIAO Qiong, GAO Peng, FU Yu, SUN Chenrui, SONG Yongxi. LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database[J]. Cancer Research on Prevention and Treatment, 2022, 49(6): 606-611. DOI: 10.3971/j.issn.1000-8578.2022.21.1159

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LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database

Department of Surgical Oncology and General Surgery, The First Hospital of China Medical University; Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors (China Medical University), Ministry of Education, Shenyang 110001, China

Funding:

Major Research and Development Program of Liaoning, China 2019020176-JH1/103

Xingliao Talent Program of Liaoning, China XLYC1807164

Young People Scientific and Technological Innovation Talent Support Program of Shenyang, Liaoning RC190202

More Information

Corresponding author:
SONG Yongxi, E-mail: songyongxi840309@126.com
Received Date: October 13, 2021
Revised Date: February 28, 2022
Available Online: January 12, 2024

Graphical Abstract

Abstract

Abstract

Objective
To establish a lncRNA prognostic risk model for gastrointestinal tumors based on the TCGA database and evaluate the prognosis of patients.
Methods
We collected the data of patients with esophageal cancer, gastric cancer, colon cancer and rectal cancer in the TCGA database. Univariate Cox analysis, Lasso and multivariate Cox analysis were performed to construct the prognostic risk scoring model. The model was validated and tested for independence. Time-dependent ROC curve analysis was performed to evaluate the clinical application value of the model.
Results
We established a prognostic risk model based on 13 lncRNAs. The three-year AUC of the training set and the validation set were 0.746 and 0.704, respectively. The pan-cancer data set was divided into high- and low-risk groups for survival analysis. The 5-year survival rate of the low-risk group was significantly higher than that of the high-risk group; among all cancer types, the five-year survival rates of the low-risk group were higher than those of the high-risk group. Multivariate Cox analysis showed that the risk score could be an independent indicator of prognosis.
Conclusion
The 13-gene prognostic risk score model is constructed successfully. The risk score obtained by this model can be used as an independent prognostic predictor of the patients with gastrointestinal cancer.
- Gastrointestinal neoplasms,
- TCGA database,
- Prognosis,
- Lasso regression

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References (19)

References

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LncRNA Prognostic Risk Scoring Model for Gastrointestinal Tumors Based on TCGA Database