Targeting the glucocorticoid receptor signature gene Mono Amine Oxidase-A enhances the efficacy of chemo- and anti-androgen therapy in advanced prostate cancer

Puhr, Martin; Eigentler, Andrea; Handle, Florian; Hackl, Hubert; Ploner, Christian; Heidegger, Isabel; Schaefer, Georg; Brandt, Maximilian Peter; Hoefer, Julia; Pluijm, Gabri van der; Klocker, Helmut

doi:10.1038/s41388-021-01754-0

Cited by 22 publications

(28 citation statements)

References 40 publications

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“…With the rapid development of genomics, a large number of genomic data were obtained from the microarray chip and high-throughput sequencing, which helped us to better understand the tumor heterogeneity and guide future clinical decision-making ( Miyamoto et al, 2018 ; Labrecque et al, 2019 ; Puhr et al, 2021 ; Ylitalo et al, 2021 ). For example, the SPP1 gene was identified as an extracellular matrix signature, which was remarkably up-regulated in mCRPC and may be a novel therapeutic target for mCRPC patients ( Pang et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Shi

et al. 2022

Front. Genet.

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Background: The emergence of castration resistance is fatal for patients with prostate cancer (PCa); however, there is still a lack of effective means to detect the early progression. In this study, a novel combined nomogram was established to predict the risk of progression related to castration resistance.Methods: The castration-resistant prostate cancer (CRPC)-related differentially expressed genes (DEGs) were identified by R packages “limma” and “WGCNA” in GSE35988-GPL6480 and GSE70768-GPL10558, respectively. Relationships between DEGs and progression-free interval (PFI) were analyzed using the Kaplan–Meier method in TCGA PCa patients. A multigene signature was built by lasso-penalized Cox regression analysis, and assessed by the receiver operator characteristic (ROC) curve and Kaplan–Meier curve. Finally, the univariate and multivariate Cox regression analyses were used to establish a combined nomogram. The prognostic value of the nomogram was validated by concordance index (C-index), calibration plots, ROC curve, and decision curve analysis (DCA).Results: 15 CRPC-related DEGs were identified finally, of which 13 genes were significantly associated with PFI and used as the candidate genes for modeling. A two-gene (KIFC2 and BCAS1) signature was built to predict the risk of progression. The ROC curve indicated that 5-year area under curve (AUC) in the training, testing, and whole TCGA dataset was 0.722, 0.739, and 0.731, respectively. Patients with high-risk scores were significantly associated with poorer PFI (p < 0.0001). A novel combined nomogram was successfully established for individualized prediction integrating with T stage, Gleason score, and risk score. While the 1-year, 3-year, and 5-year AUC were 0.76, 0.761, and 0.762, respectively, the good prognostic value of the nomogram was also validated by the C-index (0.734), calibration plots, and DCA.Conclusion: The combined nomogram can be used to predict the individualized risk of progression related to castration resistance for PCa patients and has been preliminarily verified to have good predictive ability.

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Section: Introductionmentioning

confidence: 99%

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Shi

et al. 2022

Front. Genet.

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“…In prostate cancer, the glucocorticoid receptor (GR) is a prime suspect for acquired therapy resistance, as resistance to the antiandrogen enzalutamide (Enz) can occur through bypass of androgen receptor (AR) blockade by the glucocorticoid receptor (GR)[ 70 ]. Prostate cancer (PCa) cells are able to increase GR signaling during anti-androgen therapy and thereby circumvent androgen receptor (AR) blockade and cell death [ 71 , 72 ]. In 2014, Dago et al [ 70 ] analyzed the whole-genome CNV variation of peripheral blood CTCs in patients with castration-resistant prostate cancer at four treatment time points, before chemotherapy, before treatment with abiraterone, when symptoms were significantly relieved, and when symptoms worsened.…”

Section: Single Cell Sequencing Of Circulating Tumor Cellsmentioning

confidence: 99%

“…GR expression is silenced in prostate cancer by a combination of AR binding and EZH2-mediated repression at the GR locus but is restored in advanced prostate cancers upon reversion of both repressive signals. Puhr et al [ 72 ] identified MAO-A as a directly upregulated mutual epithelial and stromal GR target, which is induced after GC treatment and during PCa progression. Their findings demonstrate that targeting MAO-A represents an innovative therapeutic strategy to synergistically block GR- and AR-dependent PCa cell growth and thereby overcome therapy resistance.…”

Section: Single Cell Sequencing Of Circulating Tumor Cellsmentioning

confidence: 99%

Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

Liao

et al. 2021

Mol Cancer

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Circulating tumor cells are tumor cells with high vitality and high metastatic potential that invade and shed into the peripheral blood from primary solid tumors or metastatic foci. Due to the heterogeneity of tumors, it is difficult for high-throughput sequencing analysis of tumor tissues to find the genomic characteristics of low-abundance tumor stem cells. Single-cell sequencing of circulating tumor cells avoids interference from tumor heterogeneity by comparing the differences between single-cell genomes, transcriptomes, and epigenetic groups among circulating tumor cells, primary and metastatic tumors, and metastatic lymph nodes in patients' peripheral blood, providing a new perspective for understanding the biological process of tumors. This article describes the identification, biological characteristics, and single-cell genome-wide variation in circulating tumor cells and summarizes the application of single-cell sequencing technology to tumor typing, metastasis analysis, progression detection, and adjuvant therapy.

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“…Moreover, a significant difference was observed in the chemotherapy response to the other 83 drugs, although they are not yet approved for the treatment of PRAD. Despite the advances in PRAD treatment, therapeutic options for PRAD remain limited [ 124 , 125 ]. These 83 drugs can be considered a pool when looking for novel therapies.…”

Section: Discussionmentioning

confidence: 99%

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils the Characteristics of the Immune Microenvironment and Prognosis Signature in Prostate Cancer

Wang

Xiao

Pan

et al. 2022

Journal of Oncology

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The immune microenvironment is a culmination of the collaborative effort of immune cells and is important in cancer development. The underlying mechanisms of the tumor immune microenvironment in regulating prostate cancer (PRAD) are unclear. In the current study, 144 natural killer cell-related genes were identified using differential expression, single-sample gene set enrichment analysis, and weighted gene coexpression network analysis. Furthermore, VCL, ACTA2, MYL9, MYLK, MYH11, TPM1, ACTG2, TAGLN, and FLNC were selected as hub genes via the protein-protein interaction network. Based on the expression patterns of the hub genes, endothelial, epithelial, and tissue stem cells were identified as key cell subpopulations, which could regulate PRAD via immune response, extracellular signaling, and protein formation. Moreover, 27 genes were identified as prognostic signatures and used to construct the risk score model. Receiver operating characteristic curves revealed the good performance of the risk score model in both the training and testing datasets. Different chemotherapeutic responses were observed between the low- and high-risk groups. Additionally, a nomogram based on the risk score and other clinical features was established to predict the 1-, 3-, and 5-year progression-free interval of patients with PRAD. This study provides novel insights into the molecular mechanisms of the immune microenvironment and its role in the pathogenesis of PARD. The identification of key cell subpopulations has a potential therapeutic and prognostic use in PRAD.

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Targeting the glucocorticoid receptor signature gene Mono Amine Oxidase-A enhances the efficacy of chemo- and anti-androgen therapy in advanced prostate cancer

Cited by 22 publications

References 40 publications

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils the Characteristics of the Immune Microenvironment and Prognosis Signature in Prostate Cancer

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