Implementation of PSA-based active surveillance in prostate cancer

Characterization of metabolism-associated molecular patterns in prostate cancer

BACKGROUND

Metabolism is a hallmark of cancer and it involves in resistance to antitumor treatment. Therefore, the purposes of this study are to classify metabolism-related molecular pattern and to explore the molecular and tumor microenvironment characteristics for prognosis predicting in prostate cancer.

METHODS

The mRNA expression profiles and the corresponding clinical information for prostate cancer patients from TCGA, cBioPortal, and GEO databases. Samples were classified using unsupervised non-negative matrix factorization (NMF) clustering based on differentially expressed metabolism-related genes (MAGs). The characteristics of disease-free survival (DFS), clinicopathological characteristics, pathways, TME, immune cell infiltration, response to immunotherapy, and sensitivity to chemotherapy between subclusters were explored. A prognostic signature was constructed by LASSO cox regression analysis based on differentially expressed MAGs and followed by the development for prognostic prediction.

RESULTS

A total of 76 MAGs between prostate cancer samples and non-tumorous samples were found, then 489 patients were divided into two metabolism-related subclusters for prostate cancer. The significant differences in clinical characteristics (age, T/N stage, Gleason) and DFS between two subclusters. Cluster 1 was associated with cell cycle and metabolism-related pathways, and epithelial-mesenchymal transition (EMT), etc., involved in cluster 2. Moreover, lower ESTIMATE/immune/stromal scores, lower expression of HLAs and immune checkpoint-related genes, and lower half-maximal inhibitory concentration (IC50) values in cluster 1 compared with cluster 2. The 10 MAG signature was identified and constructed a risk model for DFS predicting. The patients with high-risk scores showed poorer DFS. The area under the curve (AUC) values for 1-, 3-, 5-year DFS were 0.744, 0.731, 0.735 in TCGA-PRAD dataset, and 0.668, 0.712, 0.809 in GSE70768 dataset, 0.763, 0.802, 0.772 in GSE70769 dataset. Besides, risk score and Gleason score were identified as independent factors for DFS predicting, and the AUC values of risk score and Gleason score were respectively 0.743 and 0.738. The nomogram showed a favorable performance in DFS predicting.

CONCLUSION

Our data identified two metabolism-related molecular subclusters for prostate cancer that were distinctly characterized in prostate cancer. Metabolism-related risk profiles were also constructed for prognostic prediction.

miR-192 Is Overexpressed and Promotes Cell Proliferation in Prostate Cancer

OBJECTIVE

Prostate cancer (PCa) is one of the most prevalent types of cancer among men worldwide. The incidence of PCa is increasing in China. Therefore, there is an urgent need to identify novel diagnostic and prognostic markers for PCa to improve the treatment of the disease.

METHODS

The Cancer Genome Atlas (TCGA) and GEO database were used to analyze the expression of miR-192, and the relationship between miR-192 and the clinical features of patients with PCa. Cell cycle and cell proliferation assay were used to detect the functional roles of miR-192 in PCa. Bioinformatic analysis for miR-192-5p was performed using gene ontology and KEGG analysis.

RESULTS

By analyzing the dataset of TCGA, we found that miR-192 was overexpressed in PCa samples compared to normal tissues and was upregulated in high-grade PCa compared to low-grade PCa. We also observed that higher miR-192 expression was associated with a shorter biochemical recurrence-free survival time. Our results also demonstrated that miR-192 promoted PCa cell proliferation and cell cycle progression.

CONCLUSION

These results suggest that miR-192 may be considered for use as a potential diagnostic and therapeutic target of PCa.

Preliminary Case Series of Artemisinin for Prostate Cancer in a Naturopathic Practice

Objective

To determine if oral artemisinin is safe and has a short-term effect on prostate specific antigen (PSA) kinetics in patients with prostate cancer (CaP).

Design

Retrospective case series.

Setting

A private naturopathic urology clinic in Seattle, WA.

Patients

All artemisinin-treated CaP patients were identified retrospectively between 2005 and 2008. A total of 15 patients were identified who had taken artemisinin and included in the study, comprising 5 patients who had previously undergone radical prostatectomy (RP) and were having biochemical recurrences as well as 10 patients with no prior conventional therapy for CaP.

Interventions

High-dose, pulsed oral artemisinin 300-400 mg three times a day every other week for 3-24 months (median 9.5 months, IQR 5-12 months). All patients were treated with an array of other naturopathic therapies.

Outcome measures

The primary outcomes were the PSA doubling time and velocity; secondary outcome measures were signs and symptoms of metastasis and survival.

Results

Of those patients who have previously undergone RP, 2/5 (40%) had improved PSA kinetics after artemisinin therapy. Of those with no prior RP, 5/10 (50%) had improved PSA kinetics. No patient developed signs of metastasis and no patients died. There were no reported adverse effects.

Conclusions

This pilot study provides preliminary evidence to suggest that high-dose, pulsed oral artemisinin therapy may have activity in patients with CaP. A larger controlled trial is warranted to confirm these preliminary beneficial effects.