Open Access
ARTICLE
SPP1 and the risk score model to improve the survival prediction of patients with hepatocellular carcinoma based on multiple algorithms and back propagation neural networks
WENLI ZENG1, FENG LING2, KAINUO DANG3, QINGJIA CHI3,*
1 Nursing Department, Renmin Hospital of Wuhan University, Wuhan, 430060, China
2 Oncology Department, Renmin Hospital of Wuhan University, Wuhan, 430060, China
3 Department of Engineering Structure and Mechanics, School of Science, Wuhan University of Technology, Wuhan, 430070, China
* Corresponding Author: Qingjia Chi,
(This article belongs to this Special Issue: Bioinformatics Study of Diseases)
BIOCELL 2023, 47(3), 581-592. https://doi.org/10.32604/biocell.2023.025957
Received 08 August 2022; Accepted 04 November 2022; Issue published 03 January 2023
Abstract
Hepatocellular carcinoma (HCC) is associated with poor prognosis and fluctuations in immune status.
Although studies have found that secreted phosphoprotein 1 (SPP1) is involved in HCC progression, its independent
prognostic value and immune-mediated role remain unclear. Using The Cancer Genome Atlas and Gene Expression
Omnibus data, we found that low expression of SPP1 is significantly associated with improved survival of HCC
patients and that SPP1 expression is correlated with clinical characteristics. Univariate and multivariate Cox
regression confirmed that SPP1 is an independent prognostic factor of HCC. Subsequently, we found that T cell CD4
memory-activated monocytes, M0 macrophages, and resting mast cells showed significant differences in penetration
in the high and low SPP1 expression groups. Next, we used the Weighted Gene Co-Expression Network and Least
Absolute Shrinkage Sum Selection Operator algorithms to construct a risk score for the 9-immune-related genes
signature. The risk score showed a good ability to identify high and low-risk patients and improved survival
prediction. We also used multivariate Cox regression to validate that risk score was significantly correlated with SPP1
and overall survival. Lastly, the Back-Propagation Neural Network confirmed the reliability of the results of multiple
algorithms. In conclusion, the findings suggest that SPP1 is an independent marker of HCC survival and immunotherapy.
Keywords
Cite This Article
ZENG, W., LING, F., DANG, K., CHI, Q. (2023). SPP1 and the risk score model to improve the survival prediction of patients with hepatocellular carcinoma based on multiple algorithms and back propagation neural networks.
BIOCELL, 47(3), 581–592.