A cellular senescence-related gene prognostic index for biochemical recurrence and drug resistance in patients with prostate cancer

Abstract

In this study, we aimed to establish a novel cellular senescence-related gene prognostic index (CSG PI) to predict biochemical recurrence (BCR) and drug resistance in patients with prostate cancer (PCa) undergoing radical radiotherapy or prostatectomy. We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcription factors and competing endogenous RNAs. Three cellular senescence-related genes were used to establish the CSGPI. We observed that CSGPI was an independent risk factor for BCR in PCa patients (HR: 2.62; 95% CI: 1.55-4.44), consistent with the results of external validation (HR: 1.88; 95% CI: 1.12-3.14). The CSGPI had a moderate diagnostic effect on drug resistance (AUC: 0.812, 95% CI: 0.586-1.000). The lncRNA PART1 was significantly associated with BCR (HR: 0.46; 95% CI: 0.27-0.77), and might modulate the mRNA expression of definitive genes through interactions with 57 miRNAs. Gene set enrichment analysis indicated that CSGPI was closely related to ECM receptor interaction, focal adhesion, TGF beta signaling pathway, pathway in cancer, regulation of actin cytoskeleton, and so on. Immune checkpoint analysis showed that PDCD1LG2 and CD96 were significantly higher in the BCR group compared to non-BCR group, and patients with higher expression of CD96 were more prone to BCR than their counterparts (HR: 1.79; 95% CI: 1.06-3.03). In addition, the CSGPI score was significantly associated with the mRNA expression of HAVCR2, CD96, and CD47. Analysis of mismatch repair and methyltransferase genes showed that DNMT3B was more highly expressed in the BCR group and that patients with higher expression of DNMT3B experienced a higher risk of BCR (HR: 2.08; 95% CI: 1.23-3.52). We observed that M1 macrophage, CD8+ T cells, stromal score, immune score, and ESTIMATE score were higher in the BCR group. In contrast, tumor purity was less scored in the BCR group. Spearman analysis revealed a positive relationship between CSGPI and M1 macrophages, CD4+ T cells, dendritic cells, stromal score, immune score, and ESTIMATE score. In conclusion, we found that the CSGPI might serve as a biomarker to predict BCR and drug resistance in PCa patients. Moreover, CD96 and DNMT3B might be potential treatment targets, and immune evasion might contribute to the BCR process of PCa.

Keywords: Cellular senescence; biochemical recurrence; immune checkpoint; methyltransferase; prostate cancer; tumor immune microenvironment.

Figure 1

The detailed flowchart in this study. WGCNA = weighted gene coexpression network analysis; GO = gene ontology; KEGG = Kyoto Encyclopedia of Genes and Genome; GSEA = gene set enrichment analysis; TF = transcription factor; CSGPI = cellular senescence-related gene prognostic index; mRNA = message RNA; long noncoding RNA = lncRNA.

Figure 2

Process of screening definitive genes and clinical values. A. Volcano plot showing the mRNA expression of definitive genes between tumor and normal tissues; B. Modules and phenotype showing the tumor-related modules; C. Venn plot showing DEGs associated with tumor and cellular senescence; D. Gene screening through Lasso regression; E. Genes associated with BCR-free survival in PCa using univariate and multivariate COX analysis after Lasso regression; F. Examining the clinical values of CSGPI score using univariate and multivariate COX analysis for BCR free survival; G. Plot of risk factor showing the distribution of high- and low-risk patients; H. Correlation between CSGPI score and PSA; I. Time dependent ROC curve of CSGPI score discriminating BCR from no BCR; J. Kaplan-Meier curve showing survival differences between high- and low-risk patients for BCR free survival; K. Kaplan-Meier curve showing survival differences between high- and low-risk patients for metastasis free survival; L. External validation of CSGPI score through Kaplan-Meier curve showing survival differences between high- and low-risk patients for BCR free survival in TCGA dataset; M. Time dependent ROC curve of CSGPI score discriminating BCR from no BCR in TCGA dataset; N. ROC curve showing the diagnostic ability of CSGPI for drug chemoresistance; O. Protein-protein network of ACACA, CTSB, and SERPINB5; P. TF-ceRNA network of ACACA, CTSB, and SERPINB5. CSGPI = cellular senescence-related gene prognostic index; ROC = receiver operating characteristic; BCR = biochemical recurrence; PSA = prostate specific antigen; TF = transcription factor; ceRNA = competing endogenous RNA; PCa = prostate cancer.

Figure 3

Gene ontology analysis of candidate genes. A. BP analysis; B. CC analysis; C. MF analysis; D. KEGG analysis; KEGG = Kyoto Encyclopedia of Genes and Genome; BP = biological process; CC = cell composition; MF = molecular function.

Figure 4

GSEA analysis of high- and low-risk patients with prostate cancer. A. GSEA C2 analysis; B. GSEA hallmark analysis; GSEA = gene set enrichment analysis. Prostate cancer patients were divided into high- and low-risk groups according to the median value of the cellular senescence-related gene prognostic index.

Figure 5

TME, drug, and cell line analysis. A. Comparison between BCR and no BCR group for immune checkpoints; B. Kaplan-Meier curve showing survival differences of high- and low-expression of CD96 for BCR free survival; C. Radar plot showing correlation between immune checkpoints and CSGPI score; D. Comparison between BCR and no BCR group for mismatch repair and methyltransferase genes; E. Kaplan-Meier curve showing survival differences of high- and low-expression of DNMT3B for BCR free survival; F. Comparison between BCR and no BCR group for TME cells; G. Comparison between BCR and no BCR group for TME score; H. Radar plot showing correlation TME parameters and CSGPI score; I. Venn plot showing common sensitive drugs of ACACA, CTSB, and SERPINB5 through the CTRP database; J. Plot showing the top 30 potential drugs for ACACA, CTSB, and SERPINB5 through the CTRP database; K. Venn plot showing common cell lines of ACACA, CTSB, and SERPINB5 in prostate cancer. TME = tumor immune microenvironment; CSGPI = cellular senescence-related gene prognostic index; BCR = biochemical recurrence; CTRP = the cancer therapeutics response portal.