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Immune signature driven by ADT-induced immune microenvironment remodeling in prostate cancer is correlated with recurrence-free survival and immune infiltration.

ABSTRACT: Androgen deprivation therapy (ADT) is a cornerstone treatment for locally advanced or metastatic prostate cancer (PCa). However, its potential effects on the tumor immune microenvironment (TIM) of PCa patients and the underlying mechanism remain largely unclear. To explore the effects of ADT on PCa TIM, RNA sequencing was performed on six paired pre-ADT biopsy and post-ADT PCa lesions, and five paired paracancerous benign tissues from patients receiving neoadjuvant ADT with locally advanced PCa. Bioinformatics methods including ESTIMATE and ssGSEA were used to evaluate the stromal immune score and immune cell infiltration in PCa and paracancerous tissues. Weighted correlation network analysis was used to screen hub genes in the ADT-induced immune remodeling process. The results showed differences exist between PCa and paracancerous tissues in response to ADT. Compared with paracancerous tissues, the immune remodeling effect of ADT in PCa was more intense. ZFP36, JUNB, and SOCS3 served as hub genes in the ADT-induced immune remodeling process and were associated with PSA recurrent-free survival in the TCGA and our neoadjuvant ADT cohort. To investigate the joint action of the above three hub genes, an immune signature score was constructed. The results showed that immune signature score-based immune subtypes reveal the heterogeneity of the immune microenvironment of PCa and showed significant differences in patient prognosis, tumor immune infiltration, mutation burden, and landscape.

SUBMITTER: Long X

PROVIDER: S-EPMC7502080 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Immune signature driven by ADT-induced immune microenvironment remodeling in prostate cancer is correlated with recurrence-free survival and immune infiltration.

Long Xingbo X Hou Huimin H Wang Xuan X Liu Shengjie S Diao Tongxiang T Lai Shicong S Hu Maolin M Zhang Shengqi S Liu Ming M Zhang Hong H

Cell death & disease 20200919 9

Androgen deprivation therapy (ADT) is a cornerstone treatment for locally advanced or metastatic prostate cancer (PCa). However, its potential effects on the tumor immune microenvironment (TIM) of PCa patients and the underlying mechanism remain largely unclear. To explore the effects of ADT on PCa TIM, RNA sequencing was performed on six paired pre-ADT biopsy and post-ADT PCa lesions, and five paired paracancerous benign tissues from patients receiving neoadjuvant ADT with locally advanced PCa. ...[more]

PMID: 32951005

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Project description:Background Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establish a ferroptosis-related lncRNA (frlncRNA) signature to predict PCa prognosis. Methods The frlncRNAs were identified by studying their expression by Pearson’s correlation analysis. Differentially expressed prognosis related frlncRNAs were identified by the Wilcoxon test and univariate Cox regression analysis. The LASSO Cox regression model was used to build a model to predict biochemical recurrence (BCR) based on frlncRNAs. The GSEA software (version 4.1.0) was used to explore the enriched pathways in high- and low- risk groups. Patients with PCa were clustered into different subgroups by unsupervised clustering based on the frlncRNAs considered in the prognostic model. Real-time PCR and CCK8 assays were performed to verify the expression and function of frlncRNAs. Results We identified 35 differentially expressed prognosis related frlncRNAs based on data on PCa from TCGA. A risk signature based on five frlncRNAs (AP006284.1, AC132938.1, BCRP3, AL360181.4 and AL135999.1), was confirmed to perform well in predicting BCR. The high-risk group had higher disease grades and a greater number of infiltrating immune cells. Besides this, we found that the five frlncRNAs were connected with typical immune checkpoints. With respect to molecular mechanisms, several metabolic pathways were found to enriched in the low-risk group. Furthermore, patients could be classified into different subtypes with different PSA-free times using the five frlncRNAs. Notably, AP006284.1, AC132938.1, BCRP3 and AL135999.1 were upregulated in PCa cells and tissues, whereas AL360181.4 exhibited the opposite trend. The downregulation of BCRP3 and AP006284.1 impaired the proliferation of 22RV1 cells. Conclusion We generated a prognostic model based on five frlncRNAs, with clinical usefulness, and thus provided a novel strategy for predicting the BCR of patients with PCa. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09876-8.

Project description:ObjectiveNecroptosis, a type of programmed necrotic cell death, has been implicated in cancer biology and therapeutics. Improved risk stratification is required for prostate carcinoma in individuals. In view of the importance of necroptosis, this work proposed a necroptosis-based genetic model for recurrence prediction, and clarified its characteristics.MethodsA least absolute shrinkage and selection operator (LASSO) regression analysis was conducted based upon transcriptome data of necroptosis genes with clinical information in the Cancer Genome Atlas (TCGA) prostate carcinoma samples, which were externally verified in the GSE116918 cohort. Somatic mutation was characterized by Maftools method. The drug sensitivity was estimated via OncoPredict algorithm. T-cell inflammation score and tumor mutational burden (TMB) score were computed for inferring immunotherapy response. CIBERSORT was adopted for scoring the infiltration of immune cell compositions.ResultsThe necroptosis gene model was defined, composed of BCL2, BCL2L11, BNIP3, CASP8, CYLD, HDAC9, IDH2, IPMK, MYC, PLK1, TNF, TNFRSF1A, and TSC1. Considering external verification, this model effectively predicted recurrence-free survival, notably within one year (area under the curve (AUC) = 0.841, 0.706, 0.776, and 0.893 in the discovery, verification, total and external independent sets, respectively). Patients who had a risk score > median value were defined as high risk, while those who had risk score ≤ median value were defined as low risk. Older age, more advanced T, N, M stage, shorter disease-free survival, and more recurred/progressed statuses were found in high-risk patients (all P<0.05). Moreover, the signature independently predicted patient recurrence (P<0.05). High-risk specimens had more frequent somatic mutation, especially of TP53, BSN, APC, TRANK1, DNAH9, and SALL1 (all P<0.05). The heterogeneity in sensitivity to small-molecule compounds was investigated in low- and high-risk patients. Also, high-risk individuals responded better to immunotherapy (P<0.05).ConclusionAltogether, the necroptosis gene signature may effectively predict prostatic carcinoma recurrence and therapeutic responses, but its clinical feasibility must be verified.

Project description:Objective: To identify ferroptosis-related molecular clusters, and to develop and validate a ferroptosis-based molecular signature for predicting biochemical recurrence-free survival (BCRFS) and tumor immune microenvironment of prostate cancer (PCa). Materials and Methods: The clinical data and transcriptome data of PCa were downloaded from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained from FerrDb database. We performed consensus clustering analysis to identify ferroptosis-related molecular subtypes for PCa. Univariate and multivariate Cox regression analysis were used to establish a ferroptosis-based signature for predicting BCRFS. Internal verification, external verification and subgroup survival analysis were then successfully performed. Results: There was a total of 40 differentially expressed FRGs in PCa. We then identified three ferroptosis-related molecular clusters of PCa, which have significantly different immune infiltrating cells, tumor immune microenvironment and PD-L1 expression level. More importantly, a novel ferroptosis-based signature for predicting BCRFS of PCa based on four FRGs (including ASNS, GPT2, NFE2L2, RRM2) was developed. Internal and external verifications were then successfully performed. Patients with high-risk score were associated with significant poor BCRFS compared with those with low-risk score in training cohort, testing cohort and validating cohort, respectively. The area under time-dependent Receiver Operating Characteristic (ROC) curve were 0.755, 0.705 and 0.726 in training cohort, testing cohort and validating cohort, respectively, indicating the great performance of this signature. Independent prognostic analysis indicated that this signature was an independent predictor for BCRFS of PCa. Subgroup analysis revealed that this signature was particularly suitable for younger or stage T III-IV or stage N0 or cluster 1-2 PCa patients. Patients with high-risk score have significantly different tumor immune microenvironment in comparison with those with low-risk score. The results of qRT-PCR successfully verified the mRNA expression levels of ASNS, GPT2, RRM2 and NFE2L2 in DU-145 and RWPE-1 cells while the results of IHC staining exactly verified the relative protein expression levels of ASNS, GPT2, RRM2 and NFE2L2 between PCa and BPH tissues. Conclusions: This study successfully identified three ferroptosis-related molecular clusters. Besides, we developed and validated a novel ferroptosis-based molecular signature, which performed well in predicting BCRFS and tumor immune microenvironment of PCa.

Project description:Lung adenocarcinoma (LUAD), a malignancy with high incidence and mortality rates worldwide, contains multiple genomic and epigenomic abnormalities. And the useful tumor markers associated with these abnormalities need further investigation. Whereas apoptosis is a form of programmed cell death, the expression of apoptosis-related genes in LUAD and its relationship with prognosis is unclear. In the present study, we identified 64 differentially expressed apoptosis-related genes (DEARGs) that were differentially expressed between LUAD tissue and normal lung tissue. Based on these DEARGs, all LUAD cases were classified into two subtypes using The Cancer Genome Atlas (TCGA) cohort to assess the prognostic value of apoptosis-related genes for survival. An 11-gene signature was established by applying the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression method to construct a multigene prediction model and classify all LUAD patients in the TCGA cohort into high or low AS-score groups. Patients in the low AS-score group had significantly higher survival and prognosis than those in the high AS-score group. Taking the median risk score of the AS-score, LUAD patients in the GSE68465 cohort were divided into two risk groups, low and high. The overall survival (OS) time was longer in the low AS-score group. Combined with clinical characteristics, the AS-score was an independent predictor of LUAD patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that the differential genes between the two groups were mainly enriched in cellular immunity. Further analysis revealed higher immune checkpoint protein expression and higher tumor mutational burden (TMB) in the high AS-score group, suggesting better efficacy of immunotherapy in the high AS-score group than the low AS-score group. And the high AS-score group was better in chemotherapy and targeted therapy efficiency. In conclusion, the AS-score constructed based on apoptosis-related genes can predict the prognosis of LUAD patients and provide some guidance for the antitumor treatment of LUAD patients.

Dataset Information

Immune signature driven by ADT-induced immune microenvironment remodeling in prostate cancer is correlated with recurrence-free survival and immune infiltration.

Publications

Immune signature driven by ADT-induced immune microenvironment remodeling in prostate cancer is correlated with recurrence-free survival and immune infiltration.

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