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Distinct cell-types in the prostate share an aging signature suggestive of metabolic reprogramming.

ABSTRACT: Age is a significant risk factor for disease of the prostate. However, the mechanisms by which age increases disease risk have not been well described. We previously reported age-related changes within the inflammatory and luminal compartments of the mouse prostate. Old mouse prostates exhibit an expansion of the population of Trop2+ luminal progenitor cells and a reduction in the frequency and functional capacity of Trop2- luminal cells, indicating that different cell-types have distinct responses to aging. Whether distinct cell-types in the prostate share a common signature of aging has not been established. We transcriptionally profiled four distinct cell-types in young adult and old mouse prostates: stromal, basal, Trop2+ luminal progenitor and Trop2- luminal cells. Motif analysis of genes upregulated in old prostate cell-types pointed to transcriptional regulators of inflammatory and hypoxia-related signaling. Glutathione metabolism and the antioxidant response emerged as a common signature of aging across prostatic lineages. Expression of genes implicated in mouse prostate aging, including the antioxidant response gene Hmox1, correlates with age of diagnosis in primary prostate tumors from the TCGA cohort. These findings reveal a common signature shared by distinct cell-types in the old prostate reflective of age-associated metabolic reprogramming.

SUBMITTER: Crowell PD

PROVIDER: S-EPMC7486537 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Distinct cell-types in the prostate share an aging signature suggestive of metabolic reprogramming.

Crowell Preston D PD Giafaglione Jenna M JM Hashimoto Takao T Goldstein Andrew S AS

American journal of clinical and experimental urology 20200815 4

Age is a significant risk factor for disease of the prostate. However, the mechanisms by which age increases disease risk have not been well described. We previously reported age-related changes within the inflammatory and luminal compartments of the mouse prostate. Old mouse prostates exhibit an expansion of the population of Trop2+ luminal progenitor cells and a reduction in the frequency and functional capacity of Trop2- luminal cells, indicating that different cell-types have distinct respon ...[more]

PMID: 32929410

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Project description:BackgroundMetabolism reprogramming is a hallmark that associates tumor growth, metastasis, progressive, and poor prognosis. However, the metabolism-related molecular patterns and mechanism in clear cell renal cell carcinoma (ccRCC) remain unclear. Herein, the purpose of this study was to identify metabolism-related molecular pattern and to investigate the characteristics and prognostic values of the metabolism-related clustering.MethodsWe comprehensively analyzed the differentially expressed genes (DEGs), and metabolism-related genes (MAGs) in ccRCC based on the TCGA database. Consensus clustering was used to construct a metabolism-related molecular pattern. Then, the biological function, molecular characteristics, Estimate/immune/stomal scores, immune cell infiltration, response to immunotherapy, and chemotherapy were analyzed. We also identified the DEGs between subclusters and constructed a poor signature and risk model based on LASSO regression cox analysis and univariable and multivariable cox regression analyses. Then, a predictive nomogram was constructed and validated by calibration curves.ResultsA total of 1942 DEGs (1004 upregulated and 838 downregulated) between ccRCC tumor and normal samples were identified, and 254 MRGs were screened out from those DEGs. Then, 526 ccRCC patients were divided into two subclusters. The 7 metabolism-related pathways enriched in cluster 2. And cluster 2 with high Estimate/immune/stomal scores and poor survival. While, cluster 1 with higher immune cell infiltrating, expression of the immune checkpoint, IFN, HLA, immune activation-related genes, response to anti-CTLA4 treatment, and chemotherapy. Moreover, we identified 295 DEGs between two metabolism-related subclusters and constructed a 15-gene signature and 9 risk factors. Then, a risk score was calculated and the patients into high- and low-risk groups in TCGA-KIRC and E-MTAB-1980 datasets. And the prediction viability of the risk score was validated by ROC curves. Finally, the clinicopathological characteristics (age and stage), risk score, and molecular clustering, were identified as independent prognostic variables, and were used to construct a nomogram for 1-, 3-, 5-year overall survival predicting. The calibration curves were used to verify the performance of the predicted ability of the nomogram.ConclusionOur finding identified two metabolism-related molecular subclusters for ccRCC, which facilitates the estimation of response to immunotherapy and chemotherapy, and prognosis after treatment.

Project description:The opportunistic pathogen Pseudomonas aeruginosa is among the main colonizers of the lungs of cystic fibrosis (CF) patients. We have isolated and sequenced several P. aeruginosa isolates from the sputum of CF patients and compared them with each other and with the model strain PAO1. Phenotypic analysis of CF isolates showed significant variability in colonization and virulence-related traits suggesting different strategies for adaptation to the CF lung. Genomic analysis indicated these strains shared a large set of core genes with the standard laboratory strain PAO1, and identified the genetic basis for some of the observed phenotypic differences. Proteomics revealed that in a conventional laboratory medium PAO1 expressed 827 proteins that were absent in the CF isolates while the CF isolates shared a distinctive signature set of 703 proteins not detected in PAO1. PAO1 expressed many transporters for the uptake of organic nutrients and relatively few biosynthetic pathways. Conversely, the CF isolates expressed a narrower range of transporters and a broader set of metabolic pathways for the biosynthesis of amino acids, carbohydrates, nucleotides and polyamines. The proteomic data suggests that in a common laboratory medium PAO1 may transport a diverse set of "ready-made" nutrients from the rich medium, whereas the CF isolates may only utilize a limited number of nutrients from the medium relying mainly on their own metabolism for synthesis of essential nutrients. These variations indicate significant differences between the metabolism and physiology of P. aeruginosa CF isolates and PAO1 that cannot be detected at the genome level alone. The widening gap between the increasing genomic data and the lack of phenotypic data means that researchers are increasingly reliant on extrapolating from genomic comparisons using experimentally characterized model organisms such as PAO1. While comparative genomics can provide valuable information, our data suggests that such extrapolations may be fraught with peril.

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Distinct cell-types in the prostate share an aging signature suggestive of metabolic reprogramming.

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Distinct cell-types in the prostate share an aging signature suggestive of metabolic reprogramming.

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