The prognostic value of an autophagy-related lncRNA signature in hepatocellular carcinoma
Background: lncRNA may be involved in the occurrence, metastasis, and chemical reaction of hepatocellular carcinoma (HCC) through various pathways associated with autophagy. Therefore, it is urgent to reveal more autophagy-related lncRNAs, explore these lncRNAs’ clinical significance, and find new t...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd
2021
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
LEADER | 03618nam a2200649Ia 4500 | ||
---|---|---|---|
001 | 10.1186-s12859-021-04123-6 | ||
008 | 220427s2021 CNT 000 0 und d | ||
020 | |a 14712105 (ISSN) | ||
245 | 1 | 0 | |a The prognostic value of an autophagy-related lncRNA signature in hepatocellular carcinoma |
260 | 0 | |b BioMed Central Ltd |c 2021 | |
856 | |z View Fulltext in Publisher |u https://doi.org/10.1186/s12859-021-04123-6 | ||
520 | 3 | |a Background: lncRNA may be involved in the occurrence, metastasis, and chemical reaction of hepatocellular carcinoma (HCC) through various pathways associated with autophagy. Therefore, it is urgent to reveal more autophagy-related lncRNAs, explore these lncRNAs’ clinical significance, and find new targeted treatment strategies. Methods: The corresponding data of HCC patients and autophagy genes were obtained from the TCGA database, and the human autophagy database respectively. Based on the co-expression and Cox regression analysis to construct prognostic prediction signature. Results: Finally, a signature containing seven autophagy-related lncRNAs (PRRT3-AS1, RP11-479G22.8, RP11-73M18.8, LINC01138, CTD-2510F5.4, CTC-297N7.9, RP11-324I22.4) was constructed. Based on the risk score of signature, Overall survival (OS) curves show that the OS of high-risk patients is significantly lower than that of low-risk patients (P = 2.292e−10), and the prognostic prediction accuracy of risk score (AUC = 0.786) is significantly higher than that of ALBI (0.532), child_pugh (0.573), AFP (0.5751), and AJCC_stage (0.631). Moreover, multivariate Cox analysis and Nomogram of risk score are indicated that the 1-year and 3-year survival rates of patients are obviously accuracy by the combined analysis of the risk score, child_pugh, age, M_stage, and Grade (The AUC of 1- and 3-years are 0.87, and 0.855). Remarkably, the 7 autophagy-related lncRNAs may participate in Spliceosome, Cell cycle, RNA transport, DNA replication, and mRNA surveillance pathway and be related to the biological process of RNA splicing and mRNA splicing. Conclusion: In conclusion, the 7 autophagy-related lncRNAs might be promising prognostic and therapeutic targets for HCC. © 2021, The Author(s). | |
650 | 0 | 4 | |a autophagy |
650 | 0 | 4 | |a Autophagy |
650 | 0 | 4 | |a Autophagy-related lncRNAs |
650 | 0 | 4 | |a Biological process |
650 | 0 | 4 | |a Biomarkers, Tumor |
650 | 0 | 4 | |a Carcinoma, Hepatocellular |
650 | 0 | 4 | |a Cell death |
650 | 0 | 4 | |a Chemical analysis |
650 | 0 | 4 | |a child |
650 | 0 | 4 | |a Child |
650 | 0 | 4 | |a Child, Preschool |
650 | 0 | 4 | |a Combined analysis |
650 | 0 | 4 | |a Cox regression analysis |
650 | 0 | 4 | |a genetics |
650 | 0 | 4 | |a Hepatocellular carcinoma |
650 | 0 | 4 | |a Hepatocellular carcinoma |
650 | 0 | 4 | |a High-risk patients |
650 | 0 | 4 | |a human |
650 | 0 | 4 | |a Humans |
650 | 0 | 4 | |a infant |
650 | 0 | 4 | |a Infant |
650 | 0 | 4 | |a liver cell carcinoma |
650 | 0 | 4 | |a Liver Neoplasms |
650 | 0 | 4 | |a liver tumor |
650 | 0 | 4 | |a long untranslated RNA |
650 | 0 | 4 | |a Multivariant analysis |
650 | 0 | 4 | |a Prediction accuracy |
650 | 0 | 4 | |a preschool child |
650 | 0 | 4 | |a prognosis |
650 | 0 | 4 | |a Prognosis |
650 | 0 | 4 | |a Risk assessment |
650 | 0 | 4 | |a RNA |
650 | 0 | 4 | |a RNA, Long Noncoding |
650 | 0 | 4 | |a Targeted treatment |
650 | 0 | 4 | |a The Risk prediction model |
650 | 0 | 4 | |a Therapeutic targets |
650 | 0 | 4 | |a tumor marker |
700 | 1 | |a Fu, J. |e author | |
700 | 1 | |a Wang, L. |e author | |
700 | 1 | |a Yang, L. |e author | |
700 | 1 | |a Yang, S. |e author | |
700 | 1 | |a Zhang, X. |e author | |
700 | 1 | |a Zhao, X. |e author | |
700 | 1 | |a Zhou, Y. |e author | |
773 | |t BMC Bioinformatics |