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Cancers
Special Issues
Prognostic and Predictive Biomarkers of Prostate Cancer
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Prognostic and Predictive Biomarkers of Prostate Cancer

A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 13495

Special Issue Editors

Dr. Pierre Jean Lamy

E-Mail Website
Guest Editor
Genomic Institute Imagenome, Montpellier, France
Interests: Oncogenetics; cancer biomarkers; tumor markers; companion diagnostic tests; prostate and breast cancers
Prof. Christophe Hennequin

E-Mail Website
Guest Editor
Saint-Louis Hospital, Assistance Publique – Hôpitaux de Paris, Paris, France
Interests: prostate cancer; bladder cancer; breast cancer; oncology-radiotherapy
Dr. Mathieu Roumiguie

E-Mail Website
Guest Editor
Department of urology, CHU IUCT, Toulouse, France
Interests: Bladder cancer; prostate cancer
Dr. Xavier Rebillard

E-Mail Website
Guest Editor
Urology unit, Clinique Beau Soleil, Montpellier, France
Interests: urologic cancer; oncology; prostate cancer screening

Special Issue Information

Dear Colleagues, 

Prostate cancer is the most common cancer in men. The median age of diagnosis is just before the age of 70, and the five-year survival rate is 94%. Prostate cancer generally presents a good prognosis, and it can, thus, be discussed with the patient of whether to avoid a diagnostic biopsy in certain clinical situations of suspected prostate cancer. In the case of a positive biopsy, there are different options to consider, such as active surveillance, watchful waiting, or the initiation of local treatment. To guide the patient’s choice between these options, it is necessary to determine the prognosis of the disease and define the stage of the cancer. Prostate cancer staging is based on the tumor extent using TNM categories, the PSA level and the Gleason score (Grade group). Risk groups, based on PSA, digital rectal examination, and biopsy, from very low to very high are used to determine treatment options, but they are not perfect indicators of the risk. There are ongoing efforts to develop new biomarkers, based on blood or tissue testing, that can aid clinicians in determining which cancers are supposed to be aggressive and need specific treatment.

Biomarkers could also be used to improve the early detection of prostate cancer, to avoid negative biopsies and other diagnoses, to avoid repeated biopsies, and to reduce the number of different diagnostic procedures (MRI, biopsy, other biomarkers, etc.). Recently, targeted therapies have been developed to treat metastatic prostate cancers, and biomarkers predictive of response or resistance to these treatments could be used for the management of these patients. There is currently a need to technically and clinically validate these biomarkers. This Special Issue will focus on the evaluation of the use of new biomarkers in different clinical settings to improve prostate cancer management.

Dr. Pierre Jean Lamy
Prof. Christophe Hennequin
Dr. Mathieu Roumiguie
Dr. Xavier Rebillard
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • prostate cancer
  • biomarkers
  • diagnostic test
  • screening
  • prognosis
  • active surveillance
  • watchful waiting
  • risk groups
  • targeted therapy
  • companion diagnostic test

Published Papers (5 papers)

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Research

16 pages, 3747 KiB  
Article
Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion
by Tzu-Hao Wang, Cheng-Yang Lee, Tzong-Yi Lee, Hsien-Da Huang, Justin Bo-Kai Hsu and Tzu-Hao Chang
Cancers 2021, 13(11), 2528; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13112528 - 21 May 2021
Cited by 30 | Viewed by 3624
Abstract
This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and [...] Read more.
This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and similarity network fusion. Then, multiomics panels were constructed according to the intersected omics biomarkers identified from the two models. Six intersected omics biomarkers, TELO2, ZMYND19, miR-143, miR-378a, cg00687383 (MED4), and cg02318866 (JMJD6; METTL23), were collected for multiomics panel construction. The difference between the Kaplan–Meier curves of high and low recurrence-risk groups generated from the multiomics panel achieved p-value = 5.33 × 10−9, which is better than the former study (p-value = 5 × 10−7). Additionally, when evaluating the selected multiomics biomarkers with clinical information (Gleason score, age, and cancer stage), a high-performance prediction model was generated with C-index = 0.713, p-value = 2.97 × 10−15, and AUC = 0.789. The risk score generated from the selected multiomics biomarkers worked as an effective indicator for the prediction of PRAD recurrence. This study helps us to understand the etiology and pathways of PRAD and further benefits both patients and physicians with potential prognostic biomarkers when making clinical decisions after surgical treatment. Full article
(This article belongs to the Special Issue Prognostic and Predictive Biomarkers of Prostate Cancer)
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13 pages, 4178 KiB  
Article
The Significance of Prostate Specific Antigen Persistence in Prostate Cancer Risk Groups on Long-Term Oncological Outcomes
by Daimantas Milonas, Zilvinas Venclovas, Gustas Sasnauskas and Tomas Ruzgas
Cancers 2021, 13(10), 2453; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13102453 - 18 May 2021
Cited by 6 | Viewed by 2137
Abstract
Objective: To assess the significance of prostate-specific antigen (PSA) persistence at the first measurement after radical prostatectomy (RP) on long-term outcomes in different prostate cancer risk groups. Methods: Persistent PSA was defined as ≥0.1 ng/mL at 4–8 weeks after RP. Patients were stratified [...] Read more.
Objective: To assess the significance of prostate-specific antigen (PSA) persistence at the first measurement after radical prostatectomy (RP) on long-term outcomes in different prostate cancer risk groups. Methods: Persistent PSA was defined as ≥0.1 ng/mL at 4–8 weeks after RP. Patients were stratified into low-, intermediate- and high-risk groups, according to the preoperative PSA, pathological stage, grade group and lymph nodes status. The ten-year cumulative incidence of biochemical recurrence (BCR), metastases, cancer-specific mortality (CSM) and overall mortality (OM) were calculated in patients with undetectable and persistent PSA in different PCa-risk groups. Multivariate regression analyses depicted the significance of PSA persistence on each study endpoint. Results: Of all 1225 men, in 246 (20.1%), PSA persistence was detected. These men had an increased risk of BCR (hazard ratio (HR) 4.2, p < 0.0001), metastases (HR: 2.7, p = 0.002), CRM (HR: 5.5, p = 0.002) and OM (HR: 1.8, p = 0.01) compared to the men with undetectable PSA. The same significance of PSA persistence on each study endpoint was found in the high-risk group (HR: 2.5 to 6.2, p = 0.02 to p < 0.0001). In the intermediate-risk group, PSA persistence was found as a predictor of BCR (HR: 3.9, p < 0.0001), while, in the low-risk group, PSA persistence was not detected as a significant predictor of outcomes after RP. Conclusions: Persistent PSA could be used as an independent predictor of worse long-term outcomes in high-risk PCa patients, while, in intermediate-risk patients, this parameter significantly predicts only biochemical recurrence and has no impact on the outcomes in low-risk PCa patients. Full article
(This article belongs to the Special Issue Prognostic and Predictive Biomarkers of Prostate Cancer)
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12 pages, 606 KiB  
Article
Prostate Cancer Mortality Associated with Aggregate Polymorphisms in Androgen-Regulating Genes: The Atherosclerosis Risk in the Communities (ARIC) Study
by Anna E. Prizment, Sean McSweeney, Nathan Pankratz, Corinne E. Joshu, Justin H. Hwang, Elizabeth A. Platz and Charles J. Ryan
Cancers 2021, 13(8), 1958; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13081958 - 19 Apr 2021
Cited by 7 | Viewed by 2247
Abstract
Genetic variations in androgen metabolism may influence prostate cancer (PC) prognosis. Clinical studies consistently linked PC prognosis with four single nucleotide polymorphisms (SNPs) in the critical androgen-regulating genes: 3-beta-hydroxysteroid dehydrogenase (HSD3B1) rs1047303, 5-alpha-reductase 2 (SRD5A2) rs523349, and solute carrier [...] Read more.
Genetic variations in androgen metabolism may influence prostate cancer (PC) prognosis. Clinical studies consistently linked PC prognosis with four single nucleotide polymorphisms (SNPs) in the critical androgen-regulating genes: 3-beta-hydroxysteroid dehydrogenase (HSD3B1) rs1047303, 5-alpha-reductase 2 (SRD5A2) rs523349, and solute carrier organic ion (SLCO2B1) rs1789693 and rs12422149. We tested the association of four androgen-regulating SNPs, individually and combined, with PC-specific mortality in the ARIC population-based prospective cohort. Men diagnosed with PC (N = 622; 79% White, 21% Black) were followed for death (N = 350) including PC death (N = 74). Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95%CI adjusting for center, age, stage, and grade at diagnosis using separate hazards for races. A priori genetic risk score (GRS) was created as the unweighted sum of risk alleles in the four pre-selected SNPs. The gain-of-function rs1047303C allele was associated PC-specific mortality among men with metastatic PC at diagnosis (HR = 4.89 per risk allele, p = 0.01). Higher GRS was associated with PC-specific mortality (per risk allele: HR = 1.26, p = 0.03). We confirmed that the gain-of-function allele in HSD3B1 rs1047303 is associated with greater PC mortality in men with metastatic disease. Additionally, our findings suggest a cumulative effect of androgen-regulating genes on PC-specific mortality; however, further validation is required. Full article
(This article belongs to the Special Issue Prognostic and Predictive Biomarkers of Prostate Cancer)
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18 pages, 2496 KiB  
Article
Expression of ERBB Family Members as Predictive Markers of Prostate Cancer Progression and Mortality
by Sylvie Clairefond, Véronique Ouellet, Benjamin Péant, Véronique Barrès, Pierre I. Karakiewicz, Anne-Marie Mes-Masson and Fred Saad
Cancers 2021, 13(7), 1688; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13071688 - 02 Apr 2021
Cited by 6 | Viewed by 2080
Abstract
Background: EGFR, ERBB2, ERBB3, and ERBB4 are growth receptors of the ERBB family implicated in the development of epithelial cancers. Studies have suggested a role for EGFR and ERBB3 in the development of prostate cancer (PC), while the involvement of ERBB2 and ERBB4 [...] Read more.
Background: EGFR, ERBB2, ERBB3, and ERBB4 are growth receptors of the ERBB family implicated in the development of epithelial cancers. Studies have suggested a role for EGFR and ERBB3 in the development of prostate cancer (PC), while the involvement of ERBB2 and ERBB4 remains unclear. In this study, we evaluated the expression of all members of the ERBB family in PC tissue from a large cohort and determined their contribution, alone or in combination, as prognostic markers. Methods: Using immunofluorescence coupled with digital image analyses, we quantified the expression of EGFR, ERBB2, ERBB3, and ERBB4 on radical prostatectomy specimens (n = 285) arrayed on six tissue microarrays. By combining EGFR, ERBB2, and ERBB3 protein expression in a decision tree model, we identified an association with biochemical recurrence (log rank = 25.295, p < 0.001), development of bone metastases (log rank = 23.228, p < 0.001), and cancer-specific mortality (log rank = 24.586, p < 0.001). Conclusions: Our study revealed that specific protein expression patterns of ERBB family members are associated with an increased risk of PC progression and mortality. Full article
(This article belongs to the Special Issue Prognostic and Predictive Biomarkers of Prostate Cancer)
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13 pages, 2283 KiB  
Article
Elevated Expression of Glycerol-3-Phosphate Phosphatase as a Biomarker of Poor Prognosis and Aggressive Prostate Cancer
by Mohamed Amine Lounis, Veronique Ouellet, Benjamin Péant, Christine Caron, Zhenhong Li, Anfal Al-Mass, S. R. Murthy Madiraju, Anne-Marie Mes-Masson, Marc Prentki and Fred Saad
Cancers 2021, 13(6), 1273; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13061273 - 13 Mar 2021
Cited by 5 | Viewed by 2408
Abstract
The limitations of the biomarker prostate-specific antigen (PSA) necessitate the pursuit of biomarkers capable of better identifying high-risk prostate cancer (PC) patients in order to improve their therapeutic management and outcomes. Aggressive prostate tumors characteristically exhibit high rates of glycolysis and lipogenesis. Glycerol [...] Read more.
The limitations of the biomarker prostate-specific antigen (PSA) necessitate the pursuit of biomarkers capable of better identifying high-risk prostate cancer (PC) patients in order to improve their therapeutic management and outcomes. Aggressive prostate tumors characteristically exhibit high rates of glycolysis and lipogenesis. Glycerol 3-phosphate phosphatase (G3PP), also known as phosphoglycolate phosphatase (PGP), is a recently identified mammalian enzyme, shown to play a role in the regulation of glucose metabolism, lipogenesis, lipolysis, and cellular nutrient-excess detoxification. We hypothesized that G3PP may relieve metabolic stress in cancer cells and assessed the association of its expression with PC patient prognosis. Using immunohistochemical staining, we assessed the epithelial expression of G3PP in two different radical prostatectomy (RP) cohorts with a total of 1797 patients, for whom information on biochemical recurrence (BCR), metastasis, and mortality was available. The association between biomarker expression, biochemical recurrence (BCR), bone metastasis, and prostate cancer-specific survival was established using log-rank and multivariable Cox regression analyses. High expression of G3PP in PC epithelial cells is associated with an increased risk of BCR, bone metastasis, and PC-specific mortality. Multivariate analysis revealed high G3PP expression in tumors as an independent predictor of BCR and bone metastasis development. High G3PP expression in tumors from patients eligible for prostatectomies is a new and independent prognostic biomarker of poor prognosis and aggressive PC for recurrence, bone metastasis, and mortality. Full article
(This article belongs to the Special Issue Prognostic and Predictive Biomarkers of Prostate Cancer)
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