| 1. |
- Larsson, Rikard, et al.
(author)
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Clinical Trial Update and Novel Therapeutic Approaches for Metastatic Prostate Cancer.
- 2011
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In: Current Medicinal Chemistry. - 0929-8673. ; 18, s. 4440-4453
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Journal article (peer-reviewed)abstract
- Recurrent prostate cancer (PCa) remains a major clinical challenge. Invasive and metastatic PCa lesions often exhibit a partial and time-limited response to therapy before the cancer progresses and the patient succumbs to the disease. Despite recent advances in early diagnosis and treatment, approximately one-third of treated patients will relapse and become resistant to currently available treatments. In this review we evaluate current treatment practices and recent advances in therapy for localized prostate malignancy and advanced, metastatic prostate cancer. Some of the promising new drugs for PCa treatment include MDV3100, an androgen receptor (AR) antagonist that prevents androgens from binding to the AR and nuclear translocation and co-activator recruitment of the ligand-receptor complex; abiraterone, an orally administered drug that irreversibly inhibits a rate-limiting enzyme in androgen biosynthesis, CYP17; and several newer cytotoxic drugs (epothilones, satraplatin). Key new insights are that cancer stem cells play a role in PCa and that PCa cells are dependent on the AR for proliferation, even in the hormone refractory state of the disease. We also discuss potential molecular targets for new drug candidates for the treatment of metastatic PCa.
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| 4. |
- Guo, Jinan, et al.
(author)
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A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
- 2024
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In: Prostate Cancer and Prostatic Diseases. - : Nature Publishing Group. - 1365-7852 .- 1476-5608.
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Journal article (peer-reviewed)abstract
- Background: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. Methods: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. Results: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. Conclusions: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.
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| 5. |
- Guo, Jinan, et al.
(author)
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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
- 2021
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In: Frontiers in Medicine. - : Frontiers Media S.A.. - 2296-858X. ; 8
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Journal article (peer-reviewed)abstract
- Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups.Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.
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| 6. |
- Johnson, Heather, et al.
(author)
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Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up
- 2020
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In: BMC Medicine. - : BioMed Central. - 1741-7015. ; 18
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Journal article (peer-reviewed)abstract
- Background: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. Methods: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRTPCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. Results: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963–0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929–0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956–0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980–0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947–0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. Conclusions: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.
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| 7. |
- Sarwar, Martuza, et al.
(author)
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Protein kinase A (PKA) pathway is functionally linked to androgen receptor (AR) in the progression of prostate cancer
- 2014
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In: Urologic Oncology. - : Elsevier. - 1078-1439 .- 1873-2496. ; 32:1, s. 25.e1-25.e12
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Journal article (peer-reviewed)abstract
- OBJECTIVES: In the present study, we investigated whether the cyclic adenosine monophosphate (cAMP)-activated protein kinase A (PKA) pathway may regulate the expression of AR and prostate-specific antigen (PSA) and whether there is a correlation between the expression of cAMP/PKA-associated genes and androgen receptor (AR) in patients with prostate cancer (CaP).MATERIALS AND METHODS: The functional studies were performed in LNCaP and PC3 cell lines. Data on the mRNA expression of sets of genes in human clinical samples, including prostate tissues from organ donors, prostate primary cancer, and metastatic cancer, were extracted from the National Center for Biotechnology Informations Gene Expression Omnibus (GEO) database. Statistical tests were applied.RESULTS: We showed that elevated levels of cAMP/PKA pathways induced an increased expression of AR and PSA proteins in LNCaP cells in the absence of androgen. A cAMP-associated phosphodiesterase-4 (PDE4) inhibitor, rolipram induced an up-regulation in AR expression, whereas a cAMP enhancer, forskolin increased PSA level without affecting AR expression. Forskolin treatment increased the level of PKA R1α in LNCaP cells, but remarkably inhibited R1α expression in aggressive PC3 cells. In patients with CaP, we found that the expression of genes encoding R1α and phosphodiesterase-4B was statistically significantly lower in the metastatic specimens than that in the primary CaP specimens or in the normal prostate tissues (P<0.01) and was reversely correlated with AR expression. Conversely, AR and PRKAR2B mRNA expressions were significantly higher in metastatic lesions than those in the primary CaP specimens or in the normal prostate tissues (P<0.01).CONCLUSION: Our study revealed a novel mechanism to precisely define the functional and clinical interrelationship between the cAMP/PKA pathway and AR signaling in the development of androgen-independent growth of CaPs and metastasis progression.
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| 8. |
- Sarwar, Martuza, et al.
(author)
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Targeted suppression of AR-V7 using PIP5K1 alpha inhibitor overcomes enzalutamide resistance in prostate cancer cells
- 2016
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In: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:39, s. 63065-63081
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Journal article (peer-reviewed)abstract
- One mechanism of resistance of prostate cancer (PCa) to enzalutamide (MDV3100) treatment is the increased expression of AR variants lacking the ligand binding-domain, the best characterized of which is AR-V7. We have previously reported that Phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5K alpha), is a lipid kinase that links to CDK1 and AR pathways. The discovery of PIP5K alpha inhibitor highlight the potential of PIP5K1 alpha as a drug target in PCa. In this study, we show that AR-V7 expression positively correlates with PIP5K1 alpha in tumor specimens from PCa patients. Overexpression of AR-V7 increases PIP5K1 alpha, promotes rapid growth of PCa in xenograft mice, whereas inhibition of PIP5K1 alpha by its inhibitor ISA-2011B suppresses the growth and invasiveness of xenograft tumors overexpressing AR-V7. PIP5K1 alpha is a key co-factor for both AR-V7 and AR, which are present as protein-protein complexes predominantly in the nucleus of PCa cells. In addition, PIP5K1 alpha and CDK1 influence AR-V7 expression also through AKT-associated mechanism dependent on PTEN-status. ISA-2011B disrupts protein stabilization of AR-V7 which is dependent on PIP5K1 alpha, leading to suppression of invasive growth of AR-V7-high tumors in xenograft mice. Our study suggests that combination of enzalutamide and PIP5K1 alpha may have a significant impact on refining therapeutic strategies to circumvent resistance to antiandrogen therapies.
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| 9. |
- Sarwar, Martuza, et al.
(author)
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Targeted suppression of AR-V7 using PIP5K1α inhibitor overcomes enzalutamide resistance in prostate cancer cells
- 2016
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In: Oncotarget. - : Impact Journals. - 1949-2553. ; 7:39, s. 63065-63081
-
Journal article (peer-reviewed)abstract
- One mechanism of resistance of prostate cancer (PCa) to enzalutamide (MDV3100) treatment is the increased expression of AR variants lacking the ligand binding-domain, the best characterized of which is AR-V7. We have previously reported that Phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5Kα), is a lipid kinase that links to CDK1 and AR pathways. The discovery of PIP5Kα inhibitor highlight the potential of PIP5K1α as a drug target in PCa. In this study, we show that AR-V7 expression positively correlates with PIP5K1α in tumor specimens from PCa patients. Overexpression of AR-V7 increases PIP5K1α, promotes rapid growth of PCa in xenograft mice, whereas inhibition of PIP5K1α by its inhibitor ISA-2011B suppresses the growth and invasiveness of xenograft tumors overexpressing AR-V7. PIP5K1α is a key co-factor for both AR-V7 and AR, which are present as protein-protein complexes predominantly in the nucleus of PCa cells. In addition, PIP5K1α and CDK1 influence AR-V7 expression also through AKT-associated mechanism dependent on PTEN-status. ISA-2011B disrupts protein stabilization of AR-V7 which is dependent on PIP5K1α, leading to suppression of invasive growth of AR-V7-high tumors in xenograft mice. Our study suggests that combination of enzalutamide and PIP5K1α may have a significant impact on refining therapeutic strategies to circumvent resistance to antiandrogen therapies
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