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Immune-related gene index predicts metastasis for prostate cancer patients undergoing radical radiotherapy.

ABSTRACT: In this study, we established a novel immunologic gene prognostic index (IGPI) to predict metastasis and provided new insights into tumor immune microenvironment (TIME) for PCa patients receiving radical radiotherapy. GBP2 and IGF1 were independent factors associated with metastasis-free survival. IGPI score was calculated based on GBP2 and IGF1 and this score was an independent risk factor for PCa patients undergoing radical radiotherapy. Patients with higher IGPI score were at higher risk of metastasis and biochemical recurrence, which were externally validated in the TCGA database and other GEO datasets. IGPI score had demonstrated moderate diagnostic ability of radiation resistance (AUC: 0.889). This score increased with the augment of Gleason score and T stage, as well as biochemical recurrence. Using EPIC, ESTIMATE and immunophenoscore (IPS) algorithms, cancer associated fibroblasts (CAFs), macrophages, stromal score, and estimate score were significantly higher in patients with metastasis group compared to their counterpart. Besides, for CAFs, macrophages, stromal score, and estimate score, patients with higher scores were at higher risk of metastasis, and the HRs were 3.65, 4.01, 4.27, and 3.78, respectively. IGPI score was highly positively associated with stromal score (coefficient: 0.39), immune score (coefficient: 0.43), estimate score (coefficient: 0.45), CAFs (coefficient: 0.42) and macrophages (coefficient: 0.42), while showing the opposite relationship with tumor purity (coefficient: - 0.45). In conclusion, we found that IGPI based on GBP2 and IGF1 might serve as a biomarker predicting metastasis for PCa patients. Besides, the current data further highlight the importance of CAFs in the metastatic process of PCa.

SUBMITTER: Feng D

PROVIDER: S-EPMC9835256 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Immune-related gene index predicts metastasis for prostate cancer patients undergoing radical radiotherapy.

Feng Dechao D Feng Dechao D Zhu Weizhen W Shi Xu X Wang Zhihong Z Wei Wuran W Wei Qiang Q Yang Lu L Han Ping P

Experimental hematology & oncology 20230112 1

In this study, we established a novel immunologic gene prognostic index (IGPI) to predict metastasis and provided new insights into tumor immune microenvironment (TIME) for PCa patients receiving radical radiotherapy. GBP2 and IGF1 were independent factors associated with metastasis-free survival. IGPI score was calculated based on GBP2 and IGF1 and this score was an independent risk factor for PCa patients undergoing radical radiotherapy. Patients with higher IGPI score were at higher risk of m ...[more]

PMID: 36635777

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Project description:Background: Ferroptosis is a new type of programmed cell death which has been reported to be involved in the development of various cancers. In this study, we attempted to explore the possible links between ferroptosis and prostate cancer (PCa), and a novel ferroptosis-related gene prognostic index (FGPI) was constructed to predict biochemical recurrence (BCR) and radiation resistance for PCa patients undergoing radical radiotherapy (RRT). Moreover, the tumor immune microenvironment (TME) of PCa was analyzed. Methods: We merged four GEO datasets by removing batch effects. All analyses were conducted with R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcriptional factor and competing endogenous RNA. Results: We established the FGPI based on ACSL3 and EPAS1. We observed that FGPI was an independent risk factor of BCR for PCa patients (HR: 3.03; 95% CI: 1.68-5.48), consistent with the result of internal validation (HR: 3.44; 95% CI: 1.68-7.05). Furthermore, FGPI showed high ability to identify radiation resistance (AUC: 0.963; 95% CI: 0.882-1.00). LncRNA PART1 was significantly associated with BCR and might modulate the mRNA expression of EPAS1 and ACSL3 through interactions with 60 miRNAs. Gene set enrichment analysis indicated that FGPI was enriched in epithelial-mesenchymal transition, allograft rejection, TGF beta signaling pathway, and ECM receptor interaction. Immune checkpoint and m6A analyses showed that PD-L2, CD96, and METTL14 were differentially expressed between BCR and no BCR groups, among which CD96 was significantly associated with BCR-free survival (HR: 1.79; 95% CI: 1.06-3.03). We observed that cancer-related fibroblasts (CAFs), macrophages, stromal score, immune score, estimate score, and tumor purity were differentially expressed between BCR and no BCR groups and closely related to BCR-free survival (HRs were 2.17, 1.79, 2.20, 1.93, 1.92, and 0.52 for cancer-related fibroblasts, macrophages, stromal score, immune score, estimate score, and tumor purity, respectively). Moreover, cancer-related fibroblasts (coefficient: 0.20), stromal score (coefficient: 0.14), immune score (coefficient: 0.14), estimate score (coefficient: 0.15), and tumor purity (coefficient: -0.15) were significantly related to FGPI, among which higher positive correlation between cancer-related fibroblasts and FGPI was observed. Conclusion: We found that FGPI based on ACSL3 and EPAS1 might be used to predict BCR and radiation resistance for PCa patients. CD96 and PD-L2 might be a possible target for drug action. Besides, we highlighted the importance of immune evasion in the process of BCR.

Project description:BackgroundGiven the age relevance of prostate cancer (PCa) and the role of mitochondrial dysfunction (MIDS) in aging, we orchestrated molecular subtypes and identified key genes for PCa from the perspective of MIDS.MethodsCluster analysis, COX regression analysis, function analysis, and tumor immune environment were conducted. We performed all analyses using software R 3.6.3 and its suitable packages.ResultsCXCL14, SFRP4, and CD38 were eventually identified to classify the PCa patients in The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset into two distinct clusters. Patients in the cluster 2 had shorter BCR-free survival than those in the cluster 1 in terms of both TCGA database and GEO dataset. We divided the patients from the TCGA database and the GEO dataset into high- and low-risk groups according to the median of MIDS-related genetic prognostic index. For patients in the TCGA database, the biochemical recurrence (BCR) risk in high-risk group was 2.34 times higher than that in low-risk group. Similarly, for patients in the GEO dataset, the risk of BCR and metastasis in high-risk group was 2.35 and 3.04 times higher than that in low-risk group, respectively. Cluster 2 was closely associated with advanced T stage and higher Gleason score for patients undergoing radical prostatectomy or radiotherapy. For patients undergoing radical prostatectomy, the number of CD8+ T cells was significantly lower in cluster 2 than in cluster 1, while cluster 2 had significantly higher stromal score than cluster 1. For patients undergoing radical radiotherapy, cluster 2 had significantly higher level of CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, but showed lower level of tumor purity than cluster 1.ConclusionsWe proposed distinctly prognosis-related molecular subtypes at genetic level and related formula for PCa patients undergoing radical prostatectomy or radiotherapy, mainly to provide a roadmap for precision medicine.

Project description:BackgroundFerroptosis, an iron-dependent form of programmed cell death, significantly impacts cancer, yet its link to prostate cancer (PCa) prognosis remains underexplored. This study aims to develop and validate a ferroptosis-related gene signature to predict PCa prognosis and immune microenvironment differences, potentially identifying therapeutic targets.MethodsRNA-sequencing data of 478 PCa patients and corresponding clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. We investigated the disease-free survival (DFS) rates of the high- and low-risk groups using the Kaplan-Meier method. Functional differences between the high- and low-risk groups were investigated by a gene set enrichment analysis (GSEA), and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The link between ferroptosis risk score and immune status was examined using CIBERSORT. The expression levels of core prognostic genes in benign prostatic hyperplasia (BPH) and PCa were verified using quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, and immunohistochemistry (IHC).ResultsA novel ferroptosis-related prognostic gene signature was established and tested in the Gene Expression Omnibus (GEO) database based on univariate and multivariate Cox regression analyses. Patients with PCa were classified into high- and low-risk groups based on this ferroptosis signature. Patients in the high-risk group had worse outcomes than those in the low-risk group. The predictive accuracy of the model was demonstrated by a receiver operating characteristic (ROC) analysis. An additional enrichment analysis of TCGA cohort revealed the immune-related pathways were significantly upregulated in the high-risk group, with areas under the curve (AUCs) of 0.85 at 1 year, 0.82 at 3 years, and 0.76 at 5 years. In the GEO cohort, the AUCs reached 0.69 at 1 year, 0.74 at 3 years, and 0.75 at 5 years. An additional enrichment analysis indicated a significant upregulation of cytokine-related pathways, immune receptor activity, and other immune-related pathways in the high-risk group. Furthermore, the analysis revealed that the proportions of mast cells and plasma cells were significantly lower in the high-risk group compared to the low-risk group of PCa patients. Conversely, the proportion of regulatory T cells (Tregs) was significantly higher in the high-risk group than in the low-risk group. According to the qRT-PCR, Western blot, and IHC results, DRD4, SRC, AKR1C2, and AIFM2 expression was significantly higher in PCa than BPH. We also showed that the ferrostatin 1-treated LNCaP cells had higher expression levels of DRD4, SRC, and AKR1C2.ConclusionsA prognostic signature of eight ferroptosis-related genes (FRGs) that may accurately predict PCa patient outcomes was constructed and validated. FRGs may contribute to anti-tumor immunity and serve as therapeutic targets in PCa.

Project description:Background: Nowadays, predictions of biochemical recurrence (BCR) in localized prostate cancer (PCa) patients after radical prostatectomy (RP) are mainly based on clinical parameters with a low predictive accuracy. Given the critical role of apoptosis in PCa occurrence and progression, we aimed to establish a novel predictive model based on apoptosis-related gene signature and clinicopathological parameters that can improve risk stratification for BCR and assist in clinical decision-making. Methods: Expression data and corresponding clinical information were obtained from four public cohorts, one from The Cancer Genome Atlas (TCGA) dataset and three from the Gene Expression Omnibus (GEO) dataset. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate modules closely correlated to BCR, and univariate and multivariate Cox regression analyses were utilized to build the gene signature. Time-dependent receiver operating curve (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic value. Finally, we analyzed the expression of genes in the signature and validated the results using quantitative real-time PCR (qRT-PCR). Results: The novel gene signature we established exhibited a high prognostic value and was able to act as an independent risk factor for BCR [Training set: P < 0.001, hazard ratio (HR) = 7.826; Validation set I: P = 0.006, HR = 2.655; Validation set II: P = 0.003, HR = 4.175; Validation set III: P < 0.001, HR = 3.008]. Nomogram based on the gene signature and clinical parameters was capable of distinguishing high-risk BCR patients. Additionally, functional enrichment analysis showed several enriched pathways and biological processes, which might help reveal the underlying mechanism. The expression results of qRT-PCR were consistent with TCGA results. Conclusion: The apoptosis-related gene signature could serve as a powerful predictor and risk factor for BCR in localized PCa patients after RP.

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Immune-related gene index predicts metastasis for prostate cancer patients undergoing radical radiotherapy.

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Immune-related gene index predicts metastasis for prostate cancer patients undergoing radical radiotherapy.

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