Dataset Information

Individualized transcriptomic changes in malignant and benign prostate identify markers of disease recurrence

ABSTRACT: More accurate methods for early prediction of cancer aggressiveness are essential for enhanced prostate cancer (PC) treatment. In this study, the transcriptome profiles from malignant and adjacent benign prostate tissue samples were compared in 41 patients who underwent radical prostatectomy. Hierarchical clustering clearly separated benign and malignant tissues and included expected transcriptional changes associated with carcinogenesis. Using reproducibility-optimized statistical testing (ROTS), we identified 45 genes whose expression differed between paired malignant and benign prostate tissue from the same patient (FDR < 0.05) in patients with and without biochemical recurrence (BCR). Within this individualized approach, two interconnected regulatory pathways underlying the pathogenesis were identified: one centered on FOS, NR4A, and EGR family transcription factors, with strong involvement of TNFα signaling, and another, a less dense network, centered on IL6. Expression of the 45 identified transcripts was also higher in the more aggressive Luminal B-type PC than in Luminal A- and Basal-type PC, further underscoring their association with PC aggressiveness. A machine learning method (SIVS) was then used to further define five transcripts, BPIFB2, C11orf96, DUSP5, NR4A2, and NR4A3, whose individualized malignant to benign expression differences were most strongly associated with an increased risk of BCR, and thus, providing novel information on their potential involvement in processes increasing the PC aggressiveness.

ORGANISM(S): Homo sapiens

PROVIDER: GSE316750 | GEO | 2026/05/26

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Aldo-keto reductase (AKR) 1C family member 3 (AKR1C3), one of four identified human AKR enzymes, catalyzes steroid, prostaglandin, and xenobiotic metabolism. In the prostate, AKR1C3 is up-regulated in localized and advanced prostate adenocarcinoma, and is associated with prostate cancer (PCa) aggressiveness. Here we provide initial evidence for potential roles of AKR1C3 in PCa progression. Methods: Spatial distribution of AKR1C3 was analyzed using immunohistochemical staining in prostate adenocarcinoma tissue array. Human PCa PC-3 cells were stably transfected with AKR1C3 cDNA to establish PC3-AKR1C3 transfectants. Microarray and bioinformatics analyses were performed to identify pathways that are activated by elevated AKR1C3 expression in PCa cells. Functional confirmation of microarray and bioinformatics results was performed by immunoblot analysis and an in vitro Matrigel angiogenesis assay. Results: Elevated AKR1C3 expression was specifically limited to human prostate adenocarcinoma. Microarray and bioinformatics analysis suggested that elevated AKR1C3 expression in PC-3 cells modulates estradiol and androgen metabolism and activates insulin growth factor (IGF)-1 and Akt signaling pathways. Immunoblots confirmed that phosphorylated levels of IGF-1 receptor (IGF-1R) and Akt are significantly up-regulated in PC3-AKR1C3 as compared to mock transfectants. PC3-AKR1C3 transfectants promoted endothelial cell tube formation in Matrigel as compared to parental PC-3 cells and mock transfectants. Conclusion: Microarray and bioinformatics data followed by biological analyses suggest that elevated AKR1C3 expression in PC-3 cells promotes PCa angiogenesis and aggressiveness. These results suggest AKR1C3 can promote the aggressiveness of PCa through modulating estrogen and androgen metabolism with subsequent activation of growth factor IGF-1 and cytoplasmic Akt signaling pathways. Total RNA from mock- and ACR1C3 transfected PC-3 cells was isolated, with 2 or 3 biological replicates each. Gene expression data from AKR1C3 transfected PC-3 cells were compared with mock-transfected data.

Dataset Information

Individualized transcriptomic changes in malignant and benign prostate identify markers of disease recurrence

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets