Highlights
- •There were 143 metabolic gens that differentially expressed in the survival group comparing with the dead group.
- •SVM classifier based on 21 feature metabolic genes have a good performance in samples classifying.
- •RS prognostic prediction model constructed by 10 metabolic genes have great potential in prognostic prediction.
- •GSEA showed complement and coagulation cascades, PPAR signaling pathway and hematopoietic cell lineage were activated in high risk group.
- •High risk group had obviously lower counts of b cell naive and t cell CD4+ memory resting, while higher counts of b cell plasma and macrophage M2.
Abstract
Objectives
Our study aimed to reveal the metabolic-related gene signatures for survival prediction
and immune cell subtypes associated with IHCC prognosis.
Methods
Differentially expressed metabolic genes were identified between survival group and
dead group which were divided according to survival at discharge. Recursive feature
elimination (RFE) and randomForest (RF) algorithms were applied to optimize the combination
of feature metabolic genes, which were used to generate SVM classifier. Performance
of SVM classifier was evaluated by receiver operating characteristic (ROC) curves.
Gene set enrichment analysis (GSEA) was conducted to uncover the activated pathways
in high risk group, and differences in immune cell distributions were revealed.
Results
There were 143 differentially expressed metabolic gens. RFE and RF identified 21 overlapping
differentially expressed metabolic genes, and the constructed SVM classifier had excellent
accuracy in training and validation dataset. RS survival prediction model was consisted
of 10 metabolic genes. RS model had reliable predictive capability in the training
and validation dataset. GSEA revealed 15 significant KEGG pathways that were relatively
activated in the high risk group. High risk group had obviously lower counts of B
cell naive and T cell CD4+ memory resting, while higher counts of B cell plasma and
macrophage M2.
Conclusion
Prognostic prediction model of 10 metabolic genes could accurately predict the prognosis
of IHCC patients.
Keywords
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Article info
Publication history
Published online: April 12, 2023
Accepted:
April 11,
2023
Received in revised form:
March 26,
2023
Received:
February 15,
2023
Identification
Copyright
© 2023 Elsevier Inc. All rights reserved.
