Cancers

2024

Jump to: 2023, 2022

15 pages, 4666 KiB

Open AccessArticle

Exploring The Prognostic Significance of SET-Domain Containing 2 (SETD2) Expression in Advanced and Castrate-Resistant Prostate Cancer

by Yaser Gamallat, Joema Felipe Lima, Sima Seyedi, Qiaowang Li, Jon George Rokne, Reda Alhajj, Sunita Ghosh and Tarek A. Bismar

Cancers 2024, 16(7), 1436; https://doi.org/10.3390/cancers16071436 - 8 Apr 2024

Viewed by 1608

Abstract

SET-domain containing 2 (SETD2) is a histone methyltransferase and an epigenetic modifier with oncogenic functionality. In the current study, we investigated the potential prognostic role of SETD2 in prostate cancer. A cohort of 202 patients’ samples was assembled on tissue microarrays (TMAs) containing [...] Read more.

SET-domain containing 2 (SETD2) is a histone methyltransferase and an epigenetic modifier with oncogenic functionality. In the current study, we investigated the potential prognostic role of SETD2 in prostate cancer. A cohort of 202 patients’ samples was assembled on tissue microarrays (TMAs) containing incidental, advanced, and castrate-resistant CRPCa cases. Our data showed significant elevated SETD2 expression in advanced and castrate-resistant disease (CRPCa) compared to incidental cases (2.53 ± 0.58 and 2.21 ± 0.63 vs. 1.9 ± 0.68; p < 0.001, respectively). Interestingly, the mean intensity of SETD2 expression in deceased vs. alive patients was also significantly different (2.31 ± 0.66 vs. 2 ± 0.68; p = 0.003, respectively). Overall, high SETD2 expression was found to be considered high risk and was significantly associated with poor prognosis and worse overall survival (OS) (HR 1.80; 95% CI: 1.28–2.53, p = 0.001) and lower cause specific survival (CSS) (HR 3.14; 95% CI: 1.94–5.08, p < 0.0001). Moreover, combining high-intensity SETD2 with PTEN loss resulted in lower OS (HR 2.12; 95% CI: 1.22–3.69, p = 0.008) and unfavorable CSS (HR 3.74; 95% CI: 1.67–8.34, p = 0.001). Additionally, high SETD2 intensity with ERG positive expression showed worse prognosis for both OS (HR 1.99, 95% CI 0.87–4.59; p = 0.015) and CSS (HR 2.14, 95% CI 0.98–4.68, p = 0.058). We also investigated the protein expression database TCPA, and our results showed that high SETD2 expression is associated with a poor prognosis. Finally, we performed TCGA PRAD gene set enrichment analysis (GSEA) data for SETD2 overexpression, and our data revealed a potential association with pathways involved in tumor progression such as the AMPK signaling pathway, the cAMP signaling pathway, and the PI3K-Akt signaling pathway, which are potentially associated with tumor progression, chemoresistance, and a poor prognosis. Full article

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2023

Jump to: 2024, 2022

19 pages, 805 KiB

Open AccessArticle

Prostate Region-Wise Imaging Biomarker Profiles for Risk Stratification and Biochemical Recurrence Prediction

by Ángel Sánchez Iglesias, Virginia Morillo Macías, Alfonso Picó Peris, Almudena Fuster-Matanzo, Anna Nogué Infante, Rodrigo Muelas Soria, Fuensanta Bellvís Bataller, Marcos Domingo Pomar, Carlos Casillas Meléndez, Raúl Yébana Huertas and Carlos Ferrer Albiach

Cancers 2023, 15(16), 4163; https://doi.org/10.3390/cancers15164163 - 18 Aug 2023

Cited by 3 | Viewed by 2324

Abstract

Background: Identifying prostate cancer (PCa) patients with a worse prognosis and a higher risk of biochemical recurrence (BCR) is essential to guide treatment choices. Here, we aimed to identify possible imaging biomarker (perfusion/diffusion + radiomic features) profiles extracted from MRIs that were able [...] Read more.

Background: Identifying prostate cancer (PCa) patients with a worse prognosis and a higher risk of biochemical recurrence (BCR) is essential to guide treatment choices. Here, we aimed to identify possible imaging biomarker (perfusion/diffusion + radiomic features) profiles extracted from MRIs that were able to discriminate patients according to their risk or the occurrence of BCR 10 years after diagnosis, as well as to evaluate their predictive value with or without clinical data. Methods: Patients with localized PCa receiving neoadjuvant androgen deprivation therapy and radiotherapy were retrospectively evaluated. Imaging features were extracted from MRIs for each prostate region or for the whole gland. Univariate and multivariate analyses were conducted. Results: 128 patients (mean [range] age, 71 [50–83] years) were included. Prostate region-wise imaging biomarker profiles mainly composed of radiomic features allowed discriminating risk groups and patients experiencing BCR. Heterogeneity-related radiomic features were increased in patients with worse prognosis and with BCR. Overall, imaging biomarkers profiles retained good predictive ability (AUC values superior to 0.725 in most cases), which generally improved when clinical data were included (particularly evident for the prediction of the BCR, with AUC values ranging from 0.841 to 0.877 for combined models and sensitivity values above 0.960) and when models were built per prostate region vs. the whole gland. Conclusions: Prostate region-aware imaging profiles enable identification of patients with worse prognosis and with a higher risk of BCR, retaining higher predictive values when combined with clinical variables. Full article

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14 pages, 1131 KiB

Open AccessArticle

MRI-Guided Targeted and Systematic Prostate Biopsies as Prognostic Indicators for Prostate Cancer Treatment Decisions

by Furat Abd Ali, Karl-Dietrich Sievert, Michel Eisenblaetter, Barbara Titze, Torsten Hansen, Peter J. Barth and Ulf Titze

Cancers 2023, 15(15), 3915; https://doi.org/10.3390/cancers15153915 - 1 Aug 2023

Cited by 3 | Viewed by 1514

Abstract

The standard procedure for the diagnosis of prostate carcinoma involves the collection of 10–12 systematic biopsies (SBx) from both lobes. MRI-guided targeted biopsies (TBx) from suspicious foci increase the detection rates of clinically significant (cs) PCa. We investigated the extent to which the [...] Read more.

The standard procedure for the diagnosis of prostate carcinoma involves the collection of 10–12 systematic biopsies (SBx) from both lobes. MRI-guided targeted biopsies (TBx) from suspicious foci increase the detection rates of clinically significant (cs) PCa. We investigated the extent to which the results of the TBx predicted the tumor board treatment decisions. SBx and TBx were acquired from 150 patients. Risk stratifications and recommendations for interventional therapy (prostatectomy and radiotherapy) or active surveillance were established by interdisciplinary tumor boards. We analyzed how often TBx alone were enough to correctly classify the tumors as well as to indicate interventional therapy and how often the findings of SBx were crucial for therapy decisions. A total of 28/39 (72%) favorable risk tumors were detected in TBx, of which 11/26 (42%) very-low-risk tumors were not detected and 8/13 (62%) low-risk tumors were undergraded. A total of 36/44 (82%) intermediate-risk PCa were present in TBx, of which 4 (9%) were underdiagnosed as a favorable risk tumor. A total of 12/13 (92%) high-risk carcinomas were detected and correctly grouped in TBx. The majority of csPCa were identified by the sampling of TBx alone. The tumor size was underestimated in a proportion of ISUP grade 1 tumors. Systematic biopsy sampling is therefore indicated for the next AS follow-up in these cases. Full article

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12 pages, 931 KiB

Open AccessArticle

Prediction of Prostate Cancer Biochemical and Clinical Recurrence Is Improved by IHC-Assisted Grading Using Appl1, Sortilin and Syndecan-1

by Jessica M. Logan, Ashley M. Hopkins, Carmela Martini, Alexandra Sorvina, Prerna Tewari, Sarita Prabhakaran, Chelsea Huzzell, Ian R. D. Johnson, Shane M. Hickey, Ben S.-Y. Ung, Joanna Lazniewska, Robert D. Brooks, Courtney R. Moore, Maria C. Caruso, Litsa Karageorgos, Cara M. Martin, Sharon O’Toole, Laura Bogue Edgerton, Mark P. Ward, Mark Bates, Stavros Selemidis, Adrian Esterman, Sheena Heffernan, Helen Keegan, Sarah Ní Mhaolcatha, Roisin O’Connor, Victoria Malone, Marguerite Carter, Katie Ryan, Andres Clarke, Nathan Brady, Sonja Klebe, Hemamali Samaratunga, Brett Delahunt, Michael J. Sorich, Kim Moretti, Lisa M. Butler, John J. O’Leary and Douglas A. Brooks Show full author list Hide full author list

Cancers 2023, 15(12), 3215; https://doi.org/10.3390/cancers15123215 - 16 Jun 2023

Cited by 8 | Viewed by 5204

Abstract

Gleason scoring is used within a five-tier risk stratification system to guide therapeutic decisions for patients with prostate cancer. This study aimed to compare the predictive performance of routine H&E or biomarker-assisted ISUP (International Society of Urological Pathology) grade grouping for assessing the [...] Read more.

Gleason scoring is used within a five-tier risk stratification system to guide therapeutic decisions for patients with prostate cancer. This study aimed to compare the predictive performance of routine H&E or biomarker-assisted ISUP (International Society of Urological Pathology) grade grouping for assessing the risk of biochemical recurrence (BCR) and clinical recurrence (CR) in patients with prostate cancer. This retrospective study was an assessment of 114 men with prostate cancer who provided radical prostatectomy samples to the Australian Prostate Cancer Bioresource between 2006 and 2014. The prediction of CR was the primary outcome (median time to CR 79.8 months), and BCR was assessed as a secondary outcome (median time to BCR 41.7 months). The associations of (1) H&E ISUP grade groups and (2) modified ISUP grade groups informed by the Appl1, Sortilin and Syndecan-1 immunohistochemistry (IHC) labelling were modelled with BCR and CR using Cox proportional hazard approaches. IHC-assisted grading was more predictive than H&E for BCR (C-statistic 0.63 vs. 0.59) and CR (C-statistic 0.71 vs. 0.66). On adjusted analysis, IHC-assisted ISUP grading was independently associated with both outcome measures. IHC-assisted ISUP grading using the biomarker panel was an independent predictor of individual BCR and CR. Prospective studies are needed to further validate this biomarker technology and to define BCR and CR associations in real-world cohorts. Full article

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14 pages, 3371 KiB

Open AccessReview

GNL3 and PA2G4 as Prognostic Biomarkers in Prostate Cancer

by Shashank Kumar, Mohd Shuaib, Abdullah F. AlAsmari, Faleh Alqahtani and Sanjay Gupta

Cancers 2023, 15(10), 2723; https://doi.org/10.3390/cancers15102723 - 11 May 2023

Cited by 2 | Viewed by 2243

Abstract

Prostate cancer is a multifocal and heterogeneous disease common in males and remains the fifth leading cause of cancer-related deaths worldwide. The prognosis of prostate cancer is variable and based on the degree of cancer and its stage at the time of diagnosis. [...] Read more.

Prostate cancer is a multifocal and heterogeneous disease common in males and remains the fifth leading cause of cancer-related deaths worldwide. The prognosis of prostate cancer is variable and based on the degree of cancer and its stage at the time of diagnosis. Existing biomarkers for the prognosis of prostate cancer are unreliable and lacks specificity and sensitivity in guiding clinical decision. There is need to search for novel biomarkers having prognostic and predictive capabilities in guiding clinical outcomes. Using a bioinformatics approach, we predicted GNL3 and PA2G4 as biomarkers of prognostic significance in prostate cancer. A progressive increase in the expression of GNL3 and PA2G4 was observed during cancer progression having significant association with poor survival in prostate cancer patients. The Receiver Operating Characteristics of both genes showed improved area under the curve against sensitivity versus specificity in the pooled samples from three different GSE datasets. Overall, our analysis predicted GNL3 and PA2G4 as prognostic biomarkers of clinical significance in prostate cancer. Full article

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11 pages, 1570 KiB

Open AccessArticle

Identification of F-Box/SPRY Domain-Containing Protein 1 (FBXO45) as a Prognostic Biomarker for TMPRSS2–ERG-Positive Primary Prostate Cancers

by Marthe von Danwitz, Niklas Klümper, Marit Bernhardt, Alexander Cox, Philipp Krausewitz, Abdullah Alajati, Glen Kristiansen, Manuel Ritter, Jörg Ellinger and Johannes Stein

Cancers 2023, 15(6), 1890; https://doi.org/10.3390/cancers15061890 - 21 Mar 2023

Cited by 2 | Viewed by 2015

Abstract

Background: F-box/SPRY domain-containing protein 1 (FBXO45) plays a crucial role in the regulation of apoptosis via the ubiquitylation and degradation of specific targets. Recent studies indicate the prognostic potential of FBXO45 in several cancers. However, its specific role in prostate carcinoma remains unclear. [...] Read more.

Background: F-box/SPRY domain-containing protein 1 (FBXO45) plays a crucial role in the regulation of apoptosis via the ubiquitylation and degradation of specific targets. Recent studies indicate the prognostic potential of FBXO45 in several cancers. However, its specific role in prostate carcinoma remains unclear. Methods: A systematic analysis of FBXO45 mRNA expression in PCA was performed using The Cancer Genome Atlas database and a publicly available Gene Expression Omnibus progression PCA cohort. Subsequently, FBXO45 protein expression was assessed via immunohistochemical analysis of a comprehensive tissue microarray cohort. The expression data were correlated with the clinicopathological parameters and biochemical-free survival. The immunohistochemical analyses were stratified according to the TMPRSS2–ERG rearrangement status. To assess the impact of FBXO45 knockdown on the tumour proliferation capacity of cells and metastatic potential, transfection with antisense-oligonucleotides was conducted within a cell culture model. Results: FBXO45 mRNA expression was associated with adverse clinicopathological parameters in the TCGA cohort and was enhanced throughout progression to distant metastasis. FBXO45 was associated with shortened biochemical-free survival, which was pronounced for the TMPRSS2–ERG-positive tumours. In vitro, FBXO45 knockdown led to a significant reduction in migration capacity in the PC3, DU145 and LNCaP cell cultures. Conclusions: Comprehensive expression analysis and functional data suggest FBXO45 as a prognostic biomarker in PCA. Full article

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24 pages, 1054 KiB

Open AccessReview

Emerging Role of IGF-1 in Prostate Cancer: A Promising Biomarker and Therapeutic Target

by Guoqiang Liu, Minggang Zhu, Mingrui Zhang and Feng Pan

Cancers 2023, 15(4), 1287; https://doi.org/10.3390/cancers15041287 - 17 Feb 2023

Cited by 18 | Viewed by 3315

Abstract

Prostate cancer (PCa) is a highly heterogeneous disease driven by gene alterations and microenvironmental influences. Not only enhanced serum IGF-1 but also the activation of IGF-1R and its downstream signaling components has been increasingly recognized to have a vital driving role in the [...] Read more.

Prostate cancer (PCa) is a highly heterogeneous disease driven by gene alterations and microenvironmental influences. Not only enhanced serum IGF-1 but also the activation of IGF-1R and its downstream signaling components has been increasingly recognized to have a vital driving role in the development of PCa. A better understanding of IGF-1/IGF-1R activity and regulation has therefore emerged as an important subject of PCa research. IGF-1/IGF-1R signaling affects diverse biological processes in cancer cells, including promoting survival and renewal, inducing migration and spread, and promoting resistance to radiation and castration. Consequently, inhibitory reagents targeting IGF-1/IGF-1R have been developed to limit cancer development. Multiple agents targeting IGF-1/IGF-1R signaling have shown effects against tumor growth in tumor xenograft models, but further verification of their effectiveness in PCa patients in clinical trials is still needed. Combining androgen deprivation therapy or cytotoxic chemotherapeutics with IGF-1R antagonists based on reliable predictive biomarkers and developing and applying novel agents may provide more desirable outcomes. This review will summarize the contribution of IGF-1 signaling to the development of PCa and highlight the relevance of this signaling axis in potential strategies for cancer therapy. Full article

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14 pages, 1365 KiB

Open AccessFeature PaperReview

Aquaporins as Prognostic Biomarker in Prostate Cancer

by Prem Prakash Kushwaha, Shiv Verma and Sanjay Gupta

Cancers 2023, 15(2), 331; https://doi.org/10.3390/cancers15020331 - 4 Jan 2023

Cited by 6 | Viewed by 2448

Abstract

Prostate cancer is a complex heterogeneous disease that affects millions of males worldwide. Despite rapid advances in molecular biology and innovation in technology, few biomarkers have been forthcoming in prostate cancer. The currently available biomarkers for the prognosis of prostate cancer are inadequate [...] Read more.

Prostate cancer is a complex heterogeneous disease that affects millions of males worldwide. Despite rapid advances in molecular biology and innovation in technology, few biomarkers have been forthcoming in prostate cancer. The currently available biomarkers for the prognosis of prostate cancer are inadequate and face challenges, thus having limited clinical utility. To date, there are a number of prognostic and predictive biomarkers identified for prostate cancer but lack specificity and sensitivity to guide clinical decision making. There is still tremendous scope for specific biomarkers to understand the natural history and complex biology of this heterogeneous disease, and to identify early treatment responses. Accumulative studies indicate that aquaporins (AQPs) a family of membrane water channels may serve as a prognostic biomarker for prostate cancer in monitoring disease advancement. In the present review, we discuss the existing prostate cancer biomarkers, their limitations, and aquaporins as a prospective biomarker of prognostic significance in prostate cancer. Full article

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2022

Jump to: 2024, 2023

15 pages, 803 KiB

Open AccessArticle

The CAPRA&PDE4D5/7/9 Prognostic Model Is Significantly Associated with Adverse Post-Surgical Pathology Outcomes

by Chloe Gulliver, Sebastian Huss, Axel Semjonow, George S. Baillie and Ralf Hoffmann

Cancers 2023, 15(1), 262; https://doi.org/10.3390/cancers15010262 - 30 Dec 2022

Cited by 1 | Viewed by 1724

Abstract

Objectives: To investigate the association of the prognostic risk score CAPRA&PDE4D5/7/9 as measured on pre-surgical diagnostic needle biopsy tissue with pathological outcomes after radical prostatectomies in a clinically low–intermediate-risk patient cohort. Patients and Methods: RNA was extracted from biopsy punches of diagnostic needle [...] Read more.

Objectives: To investigate the association of the prognostic risk score CAPRA&PDE4D5/7/9 as measured on pre-surgical diagnostic needle biopsy tissue with pathological outcomes after radical prostatectomies in a clinically low–intermediate-risk patient cohort. Patients and Methods: RNA was extracted from biopsy punches of diagnostic needle biopsies. The patient cohort comprises n = 151 patients; of those n = 84 had low–intermediate clinical risk based on the CAPRA score and DRE clinical stage <cT3. This cohort (n = 84) was investigated for pathology outcomes in this study. RT-qPCR was performed to determine PDE4D5, PDE4D7 and PDE4D9 transcript scores in the cohorts. The CAPRA score was inferred from the relevant clinical data (patient age, PSA, cT, biopsy Gleason, and percentage tumor positive biopsy cores). Logistic regression was used to combine the PDE4D5, PDE4D7 and PDE4D9 scores to build a PDE4D5/7/9_BCR regression model. The CAPRA&PDE4D5/7/9_BCR risk score used was same as previously published. Results: We investigated three post-surgical outcomes in this study: (i) Adverse Pathology (any ISUP pathological Gleason grade >2, or pathological pT stage > pT3a, or tumor penetrated prostate capsular status, or pN1 disease); (ii) any ISUP pathological Gleason >2; (iii) any ISUP pathological Gleason >1. In the n = 84 patients with low to intermediate clinical risk profiles, the clinical-genomics CAPRA&PDE4D5/7/9_BCR risk score was significantly lower in patients with favorable vs. unfavorable outcomes. In univariable logistic regression modeling the genomics PDE4D5/7/9_BCR as well as the clinical-genomics CAPRA&PDE4D5/7/9_BCR combination model were significantly associated with all three post-surgical pathology outcomes (p = 0.02, p = 0.0004, p = 0.04; and p = 0.01, p = 0.0002, p = 0.01, respectively). The clinically used PRIAS criteria for the selection of low-risk candidate patients for active surveillance (AS) were not significantly associated with any of the three tested post-operative pathology outcomes (p = 0.3, p = 0.1, p = 0.1, respectively). In multivariable analysis adjusted for the CAPRA score, the genomics PDE4D5/7/9_BCR risk score remained significant for the outcomes of adverse pathology (p = 0.04) and ISUP pathological Gleason >2 (p = 0.004). The negative predictive value of the CAPRA&PDE4D5/7/9_BCR risk score using the low-risk cut-off (0.1) for the three pathological endpoints was 82.0%, 100%, and 59.1%, respectively for a selected low-risk cohort of n = 22 patients (26.2% of the entire cohort) compared to 72.1%, 94.4%, and 55.6% for n = 18 low-risk patients (21.4% of the total cohort) selected based on the PRIAS inclusion criteria. Conclusion: In this study, we have shown that the previously reported clinical-genomics prostate cancer risk model CAPRA&PDE4D5/7/9_BCR which was developed to predict biological outcomes after surgery of primary prostate cancer is also significantly associated with post-surgical pathology outcomes. The risk score predicts adverse pathology independent of the clinical risk metrics. Compared to clinically used active surveillance inclusion criteria, the clinical-genomics CAPRA&PDE4D5/7/9_BCR risk model selects 22% (n = 8) more low-risk patients with higher negative predictive value to experience unfavorable post-operative pathology outcomes. Full article

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12 pages, 765 KiB

Open AccessArticle

Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions

by Caterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, Beniamino Corcioni, Arrigo Cattabriga, Maria Adriana Cocozza, Antonino Palmeri, Francesca Coppola, Francesca Giunchi, Riccardo Schiavina, Michelangelo Fiorentino, Eugenio Brunocilla, Rita Golfieri and Alessandro Bevilacqua

Cancers 2022, 14(24), 6156; https://doi.org/10.3390/cancers14246156 - 14 Dec 2022

Cited by 8 | Viewed by 2214

Abstract

The risk of misclassifying clinically significant prostate cancer (csPCa) by multiparametric magnetic resonance imaging is consistent, also using the updated PIRADS score and although different definitions of csPCa, patients with Gleason Grade group (GG) ≥ 3 have a significantly worse prognosis. This study [...] Read more.

The risk of misclassifying clinically significant prostate cancer (csPCa) by multiparametric magnetic resonance imaging is consistent, also using the updated PIRADS score and although different definitions of csPCa, patients with Gleason Grade group (GG) ≥ 3 have a significantly worse prognosis. This study aims to develop a machine learning model predicting csPCa (i.e., any GG ≥ 3 lesion at target biopsy) by mpMRI radiomic features and analyzing similarities between GG groups. One hundred and two patients with 117 PIRADS ≥ 3 lesions at mpMRI underwent target+systematic biopsy, providing histologic diagnosis of PCa, 61 GG < 3 and 56 GG ≥ 3. Features were generated locally from an apparent diffusion coefficient and selected, using the LASSO method and Wilcoxon rank-sum test (p < 0.001), to achieve only four features. After data augmentation, the features were exploited to train a support vector machine classifier, subsequently validated on a test set. To assess the results, Kruskal–Wallis and Wilcoxon rank-sum tests (p < 0.001) and receiver operating characteristic (ROC)-related metrics were used. GG1 and GG2 were equivalent (p = 0.26), whilst clear separations between either GG[1,2] and GG ≥ 3 exist (p < 10

^{- 6}

). On the test set, the area under the curve = 0.88 (95% CI, 0.68–0.94), with positive and negative predictive values being 84%. The features retain a histological interpretation. Our model hints at GG2 being much more similar to GG1 than GG ≥ 3. Full article

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24 pages, 1483 KiB

Open AccessReview

Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer

by Samaneh Eickelschulte, Anja Lisa Riediger, Arlou Kristina Angeles, Florian Janke, Stefan Duensing, Holger Sültmann and Magdalena Görtz

Cancers 2022, 14(24), 6094; https://doi.org/10.3390/cancers14246094 - 11 Dec 2022

Cited by 8 | Viewed by 3597

Abstract

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification [...] Read more.

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification of relevant tissue-based molecular alterations have the potential to improve the clinical decision making and patient outcomes. However, tissue biopsies are invasive and spatially restricted due to tumor heterogeneity. Therefore, there is an urgent need for complementary diagnostic and prognostic options. Liquid biopsy approaches are minimally invasive with potential utility for the early detection, risk stratification, and monitoring of tumors. In this review, we focus on tissue and liquid biopsy biomarkers for early diagnosis and risk stratification of prostate cancer, including modifications on the genomic, epigenomic, transcriptomic, and proteomic levels. High-risk molecular alterations combined with orthogonal clinical parameters can improve the identification of aggressive tumors and increase patient survival. Full article

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Graphical abstract

9 pages, 1011 KiB

Open AccessArticle

Prostate-Specific Antigen Doubling Time Kinetics following Radical Prostatectomy to Guide Need for Treatment Intervention: Validation of Low-Risk Recurrences

by Erica Huang, Joshua Tran, Linda My Huynh, Douglas Skarecky, Robert H. Wilson and Thomas Ahlering

Cancers 2022, 14(17), 4087; https://doi.org/10.3390/cancers14174087 - 24 Aug 2022

Cited by 3 | Viewed by 2210

Abstract

Biochemical recurrence (BCR) following radical prostatectomy (RP) has a limited ability to predict prostate cancer (PC) progression, leading to overtreatment, decreased quality of life, and additional expenses. Previously, we established that one-third of men with BCR in our group experienced low-risk recurrences that [...] Read more.

Biochemical recurrence (BCR) following radical prostatectomy (RP) has a limited ability to predict prostate cancer (PC) progression, leading to overtreatment, decreased quality of life, and additional expenses. Previously, we established that one-third of men with BCR in our group experienced low-risk recurrences that were safely observed without treatment. Our retrospective cohort analysis of 407 BCR patients post RP validates the use of PSA doubling time (DT) kinetics to direct active observation (AO) versus treatment following RP. The primary outcome was no need for treatment according to the predictive value of models of ROC analysis. The secondary outcome was PC-specific mortality (PCSM) according to Kaplan–Meier analysis. A total of 1864 men underwent RP (June 2002–September 2019); 407 experienced BCR (PSA > 0.2 ng/dL, ×2), with a median follow-up of 7.6 years. In adjusted regression analysis, initial PSADT > 12 months and increasing DT were significant predictors for AO (p < 0.001). This model (initial PSADT and DT change) was an excellent predictor of AO in ROC analysis (AUC = 0.83). No patients with initial PSADT > 12 months and increasing DT experienced PCSM. In conclusion, the combination of PSADT > 12 months and increasing DT was an excellent predictor of AO. This is the first demonstration that one-third of BCRs are at low risk of PCSM and can be managed without treatment via DT kinetics. Full article

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10 pages, 887 KiB

Open AccessArticle

Active Observation of Biochemical Recurrence without Treatment following Radical Prostatectomy: Long-Term Analysis of Outcomes

by Erica Huang, Linda My Huynh, Joshua Tran, Adam M. Gordon, Ryan Chandhoke, Blanca Morales, Douglas Skarecky and Thomas E. Ahlering

Cancers 2022, 14(17), 4078; https://doi.org/10.3390/cancers14174078 - 23 Aug 2022

Cited by 2 | Viewed by 2757

Abstract

Biochemical recurrence (BCR) following radical prostatectomy (RP) is an unreliable predictor of prostate cancer (PC) progression. This study was a retrospective cohort analysis of prospectively collected data (407/1895) of men with BCR at a tertiary referral center. Patients were assessed for active observation [...] Read more.

Biochemical recurrence (BCR) following radical prostatectomy (RP) is an unreliable predictor of prostate cancer (PC) progression. This study was a retrospective cohort analysis of prospectively collected data (407/1895) of men with BCR at a tertiary referral center. Patients were assessed for active observation (AO) compared with a treatment group (TG) utilizing doubling time (DT) kinetics. Risk assessment was based on the initial DT (>12 vs. <12 months), then based on the DT pattern (changed over time). Those with unstable, rapidly decreasing DTs received treatment. Those with increasing and slowly decreasing DTs prompted observation. The primary outcome was PC mortality, safety, and efficacy of observations based on DT kinetics. The secondary outcome was BCR patients managed with or without treatment. The median follow-up was 7.5 years (IQR 3.9–10.7). The PCSM in TG and AO was 10.7% and 0%, respectively (p < 0.001). The initial DT was >12 months in 73.6% of AO versus 22.6% of TG (p < 0.001). An increasing DT pattern was observed in 71.5% of AO versus 32.7% of TG (p < 0.001). Utilizing the Cleveland Clinic’s PCSM nomogram, at 10 years, predicted and observed PCSM was 8.6% and 9.5% (p = 0.78), respectively. In conclusion, one-third of patients with BCR post-RP were managed without treatment using DT kinetics, avoiding treatment-related complications, quality-of-life issues, and expenses. Full article

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21 pages, 1166 KiB

Open AccessReview

Clinical Applications of Liquid Biopsy in Prostate Cancer: From Screening to Predictive Biomarker

by Filip Ionescu, Jingsong Zhang and Liang Wang

Cancers 2022, 14(7), 1728; https://doi.org/10.3390/cancers14071728 - 29 Mar 2022

Cited by 17 | Viewed by 4003

Abstract

Prostate cancer (PC) remains the most common malignancy and the second most common cause of cancer death in men. As a result of highly variable biological behavior and development of resistance to available agents under therapeutic pressure, optimal management is often unclear. Traditional [...] Read more.

Prostate cancer (PC) remains the most common malignancy and the second most common cause of cancer death in men. As a result of highly variable biological behavior and development of resistance to available agents under therapeutic pressure, optimal management is often unclear. Traditional surgical biopsies, even when augmented by genomic studies, may fail to provide adequate guidance for clinical decisions as these can only provide a snapshot of a dynamic process. Additionally, surgical biopsies are cumbersome to perform repeatedly and often involve risk. Liquid biopsies (LB) are defined as the analysis of either corpuscular (circulating tumor cells, extracellular vesicles) or molecular (circulating DNA or RNA) tumor-derived material. LB could more precisely identify clinically relevant alterations that characterize the metastatic potential of tumors, predict response to specific treatments or actively monitor for the emergence of resistance. These tests can potentially be repeated as often as deemed necessary and can detect real-time response to treatment with minimal inconvenience to the patient. In the current review, we consider common clinical scenarios to describe available LB assays in PC as a platform to explore existing evidence for their use in guiding decision making and to discuss current limitations to their adoption in the clinic. Full article

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13 pages, 2505 KiB

Open AccessArticle

Modeled Early Longitudinal PSA Kinetics Prognostic Value in Rising PSA Prostate Cancer Patients after Local Therapy Treated with ADT +/− Docetaxel

by Aurore Carrot, Reza-Thierry Elaidi, Olivier Colomban, Denis Maillet, Michel Tod, Benoit You and Stéphane Oudard

Cancers 2022, 14(3), 815; https://doi.org/10.3390/cancers14030815 - 5 Feb 2022

Cited by 3 | Viewed by 2403

Abstract

Background: In metastatic prostate cancer (PCa) patients, androgen-deprivation therapy (ADT) combined with chemotherapy or next-generation androgen receptor targeted agents is a new standard treatment. The objective of the present study is to assess longitudinal PSA kinetics during treatment using mathematical modeling, to identify [...] Read more.

Background: In metastatic prostate cancer (PCa) patients, androgen-deprivation therapy (ADT) combined with chemotherapy or next-generation androgen receptor targeted agents is a new standard treatment. The objective of the present study is to assess longitudinal PSA kinetics during treatment using mathematical modeling, to identify the modeled PSA kinetic parameters able to exhibit early prognostic/predictive values. Methods: Phase III clinical trial dataset (NCT00764166) comparing ADT +/− docetaxel in 250 locally treated patients for PCa with rising PSA levels, who were at high risk of metastatic disease was assessed. A kinetic-pharmacodynamic (K-PD) model was used to fit PSA kinetics during the first 100 treatment days, to estimate the modeled PSA production rate K (KPROD) and elimination constant rate K (KELIM). The prognostic value of these parameters, considered as categorized (favorable vs. unfavorable) covariates regarding PSA progression-free survival (PSA-PFS) and overall survival (OS), was assessed using univariate/multivariate analyses. Results: Data from 177/250 patients was assessed. KELIM exhibited a significant prognostic value regarding PSA-PFS and KPROD regarding OS (univariate analysis). In the PSA-PFS final multivariate model, KELIM and the primary therapy type were significant. The OS multivariate model integrated both KPROD and baseline PSA doubling-time. Conclusion: In this first study assessing the modeled PSA kinetics prognostic value in PCa patients treated with systemic treatments, KELIM and KPROD exhibited respective prognostic values regarding PSA-PFS and OS. Full article

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Biomarkers for Detection and Prognosis of Prostate Cancer

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