Next Article in Journal
The Potential Role of Serum and Exhaled Breath Condensate miRNAs in Diagnosis and Predicting Exacerbations in Pediatric Asthma
Next Article in Special Issue
Synthesis, In Vitro Biological Evaluation of Antiproliferative and Neuroprotective Effects and In Silico Studies of Novel 16E-Arylidene-5α,6α-epoxyepiandrosterone Derivatives
Previous Article in Journal
Implementation, Dosimetric Assessment, and Treatment Validation of Knowledge-Based Planning (KBP) Models in VMAT Head and Neck Radiation Oncology
Previous Article in Special Issue
Computational and Preclinical Analysis of 2-(4-Methyl)benzylidene-4,7-dimethyl Indan-1-one (IPX-18): A Novel Arylidene Indanone Small Molecule with Anti-Inflammatory Activity via NF-κB and Nrf2 Signaling
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients

by
Tomas Januskevicius
1,
Rasa Sabaliauskaite
2,
Daiva Dabkeviciene
3,
Ieva Vaicekauskaite
2,4,
Ilona Kulikiene
2,
Agne Sestokaite
2,4,
Asta Vidrinskaite
5,
Arnas Bakavicius
1,6,
Feliksas Jankevicius
1,6,
Albertas Ulys
7 and
Sonata Jarmalaite
4,*
1
Clinic of Gastroenterology, Nephro-Urology and Surgery, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, M. K. Ciurlionio st. 21/27, LT-03101 Vilnius, Lithuania
2
Laboratory of Genetic Diagnostic, National Cancer Institute, Santariskiu st. 1, LT-08406 Vilnius, Lithuania
3
Biobank, National Cancer Institute, Santariskiu st. 1, LT-08406 Vilnius, Lithuania
4
Division of Human Genome Research Centre, Institute of Biosciences, Life Sciences Center, Vilnius University, Sauletekio Ave. 7, LT-10257 Vilnius, Lithuania
5
Nuclear Medicine Department, National Cancer Institute, Santariskiu st. 1, LT-08660 Vilnius, Lithuania
6
Urology Centre, Vilnius University Hospital Santaros Klinikos, Santariskiu st. 2, LT-08661 Vilnius, Lithuania
7
Oncourology Department, National Cancer Institute, Santariskiu st. 1, LT-08660 Vilnius, Lithuania
*
Author to whom correspondence should be addressed.
Biomedicines 2023, 11(3), 761; https://doi.org/10.3390/biomedicines11030761
Submission received: 12 January 2023 / Revised: 23 February 2023 / Accepted: 28 February 2023 / Published: 2 March 2023

Abstract

:
(1) Background: DNA damage response (DDR) pathway gene mutations are detectable in a significant number of patients with metastatic castration-resistant prostate cancer (mCRPC). The study aimed at identification of germline and/or somatic DDR mutations in blood and urine samples from patients with mCRPC for correlation with responses to entire sequence of systemic treatment and survival outcomes. (2) Methods: DDR gene mutations were assessed prospectively in DNA samples from leukocytes and urine sediments from 149 mCRPC patients using five-gene panel targeted sequencing. The impact of DDR status on progression-free survival, as well as treatment-specific and overall survival, was evaluated using Kaplan–Meier curves and Cox regression. (3) Results: DDR mutations were detected in 16.6% of urine and 15.4% of blood samples. BRCA1, BRCA2, CHEK2, ATM and NBN mutations were associated with significantly shorter PFS in response to conventional androgen deprivation therapy and first-line mCRPC therapy with abiraterone acetate. Additionally, BRCA1 and BRCA2 mutation-bearing patients had a significantly worse response to radium-223. However, DDR mutation status was predictive for the favourable effect of second-line abiraterone acetate after previous taxane-based chemotherapy. (4) Conclusions: Our data confirm the benefit of non-invasive urine-based genetic testing for timely identification of high-risk prostate cancer cases for treatment personalization.

1. Introduction

Prostate cancer (PCa), the second most frequent cancer in men, has a wide variety of clinical behaviours, ranging from latent to rapidly progressing disease [1]. Age, family history, racial and ethnic background are the main risk factors for PCa [2,3]. It is assumed that about 60% of individual variation in PCa risk can be attributed to genetic factors [4]. Recent data suggest that up to 17.2% of PCa patients may harbour germline mutations in non-androgen receptor-related pathways [5,6,7]. In PCa, heritable mutations predominantly occur in BRCA1, BRCA2, ATM and CHEK2 genes responsible for DNA damage repair (DDR) pathway responses and the genomic integrity of cells. Inherited mutations in DDR genes increase the risk of a more aggressive form of PCa, and germline BRCA1/BRCA2 mutations are confirmed biomarkers of poor prognosis [8]. Moreover, somatic DDR pathway mutations are frequent in tumour cells, especially in metastatic disease, making them an attractive target for personalized therapy [8].
Nowadays, germline testing of BRCA1/BRCA2 and other DDR genes is recommended in the early stages of PCa by various guidelines, including the NCCN, ESMO and EAU, for heritable disease identification, while tumour (somatic) mutation testing is mainly advocated for metastatic castration-resistant PCa (mCRPC) in relation to poly (ADP-ribose) polymerase (PARP) inhibitor treatment selection [9,10]. Since tumour testing in mCRPC is not always feasible, liquid biopsies can serve as non-invasive alternative sources of diagnostic material.
Liquid biopsy is an innovative tumour-specific mutation detection tool that can be applied to various body fluids such as saliva, blood, urine, and other clinical biosamples. DNA originating from cell-free circulating tumour DNA (cfDNA) or circulating tumour cells (CTC) possesses the same mutation profile as primary tumour or metastases and can represent wide heterogeneity of cancer loci and clonal evolution leading to mCRPC [11]. Additionally, compared to tissue biopsies, liquid biopsy studies allow a more accurate assessment of molecular changes beyond the tumour, including the possibility of detecting both germline and somatic mutations. Urine, as a non-invasive form of liquid biopsy, is an ideal type of biosample: it can be collected frequently in large quantities without causing discomfort, thus ensuring early detection of relapse, resistance to the prescribed treatment or even metastasis. Larger amounts of prostate-specific cells and cfDNA can be collected after prostate massage, but due to the unpleasant procedure, it is increasingly replaced by the use of plain voided urine [12]. First-void urine can be easily separated by centrifugation into a pellet enriched in cells and proteins and supernatant containing cell-free DNA and exosomes.
The discovery and characterization of DDR mutations in PCa accelerated the development of novel personalised treatment options, and two PARP inhibitors, olaparib and rucaparib, were recently approved for systemic mCRPC treatment [13]. Accumulating data also suggest the impact of inherited DDR defects on PCa response to conventional therapies, such as next-generation hormonal therapy (abiraterone acetate (AA), enzalutamide) [14], radium-223 [15] and platinum-based chemotherapy [16,17,18], but such observations need further validation.
The present study aimed at evaluating the prevalence of germline and somatic mutations in five DDR pathway genes (BRCA1, BRCA2, CHEK2, ATM, and NBN) in blood and urine samples of mCRPC patients from a Lithuanian cohort. For predictive value validation, clinical response to a whole spectrum of systemic treatments, from androgen deprivation therapy in a hormone-sensitive setting to radium-223 in cases with bone metastasis, and survival outcomes were evaluated with respect to DDR mutation status.

2. Materials and Methods

2.1. Patient Cohort

In total, 149 consecutive patients with histologically confirmed mCRPC treated and followed at the National Cancer Institute between 2017 and 2018 were included in the study. mCRPC was defined as a metastatic PCa with castration level of serum testosterone (<1.7 nmol/L), as well as biochemical and/or radiological progression of the disease. The study was approved by the Regional Bioethics Committee (No.: 158200-17-874-411), and written informed consent was obtained from all participants.
All patients were followed with monthly clinical examination, PSA and alkaline phosphatase (ALP) assessment every 2 to 3 months, and radiological examination (bone-scan and body CT) at least every 6 months. Progression-free survival (PFS) after different types of therapy was defined as the time elapsed between treatment initiation and disease progression or death from any cause, whichever occurred first. Disease progression was confirmed when at least two of three progression criteria (PSA progression, radiographic progression and clinical deterioration) were fulfilled. Overall survival was defined as the time from PCa diagnosis to death from any cause.

2.2. Sample Collection and DNA Extraction

Blood and first-void urine samples were collected prospectively into EDTA blood collection tubes and urine collection containers according to the standardized procedures. Urine samples were processed within 30 min according to the following protocol: the cellular content of the urine sample was pelleted by centrifugation at 2000× g for 15 min, and the supernatant was removed. The cell pellets were washed with PBS and precipitated. Afterwards, the supernatant was removed, and the cell pellets were resuspended in 2 mL PBS and stored at −80 °C until use. Leukocyte DNA extraction was performed by a fully automated robotic QIAcube system workstation by using QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany). Urine samples were processed within 30 min after the samples were taken, using Viral RNA Mini Kit (Qiagen, Hilden, Germany) according to manufacturer instructions. DNA concentration and purity were determined using the NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and stored at −20 °C until use.

2.3. Quantitative PCR

For the detection of the predominant DNA response pathway gene mutations in genomic DNA, custom TaqMan™ SNP Genotyping Assays (Applied Biosystems (AB) Thermo Fisher Scientific (TFS), Paisley, UK) were designed: 6 for BRCA1/BRCA2 (rs80359112, rs80356898, rs397507246, rs80357711, rs28897672A_C, rs80359604_GT), three for CHEK2 (rs555607708, rs17879961, rs121908698) and one for NBN (rs587776650) gene. Quantitative PCR (qPCR) reactions were performed according to the manufacturer’s protocol. All qPCR reactions were performed in duplicates following the manufacturer’s protocol and using a 7500 Real-Time PCR System (AB, TFS, Foster, CA, USA).

2.4. Targeted Next-Generation Sequencing

Germline DNA from DDR mutation-negative cases in qPCR screening and all urine samples (n = 133 and n = 139, respectively) was sequenced using a targeted five-gene panel: BRCA1, BRCA2, CHEK2, ATM and NBN. The BRCA Germline I Reference Standard gDNA (Horizon Discovery, Cambridge, UK) was used as a positive control. Genomic DNA concentration was determined by using Qubit™ dsDNA BR Assay Kit on a Qubit™ 2.0 Fluorimeter (Invitrogen, TFS, Eugene, OR, USA). For library preparation, Ion AmpliSeq™ Library Kit 2.0 and custom On-Demand Panel (from Life Technologies (LT), Carlsbad, CA, USA) were used under conditions provided by the manufacturer’s protocol. Library concentrations were determined by using the Ion Library TaqMan™ Quantification Kit (AB, TFS, Vilnius, Lithuania). Sequencing was performed on the Ion Torrent™ Ion S5™ system. Average read length after sequencing was 209 bp: ≥93% on target and ≥98% uniformity. Data analysis was performed with Ion Reporter 5.10 tool (LT, Carlsbad, CA, USA). Sequence reads were aligned to human reference genome—hg19. The frequency of pathogenic and likely pathogenic mutations was estimated for each gene and confirmed according to the ClinVar database also using the Integrative Genomics Viewer 2.4.8 tool to eliminate false positive cases and to confirm detected mutant reads in both sequence directions.

2.5. Statistical Analysis

Associations between categorical variables were evaluated by using two-sided Chi-square test or Fisher’s exact test, as appropriate. Normal distribution was tested using Shapiro–Wilk W test. Two independent samples were analysed by Mann–Whitney U test. Outliers were defined as cases exceeding three interquartile ranges for PFS—study patients that discontinued regular follow-up protocol—and removed from the analysis. Kaplan–Meier curves and Cox regression were used for survival analyses. Regarding multivariate Cox regression, covariates with p levels up to 0.2 were selected for the analysis. Differences were considered statistically significant when p-value was <0.050. The data were analysed using R x64 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria), RStudio 1.4.1717 (Posit, PBC, Boston, MA, USA) and IBM SPSS Statistics 21 (IBM Corp., Armonk, NY, USA) software.

3. Results

3.1. DDR Mutations in Blood and Urine of mCRPC Patients

In a cohort of 149 mCRPC cases, 23 patients (15.4%) were identified with germline mutations of selected DDR genes in the blood cells: 16 with qPCR and seven using NGS. According to mutation type, six insertion/deletion and 17 missense mutations were detected. In the blood samples from the patients, BRCA1 mutation was detected in two (1.3%), BRCA2 in three (2.0%), CHEK2 in 12 (8.1%), ATM in five (3.4%), and NBN in one (0.7%). The most frequently mutated gene was CHEK2: 11 patients harboured CHEK2 mutation c.470T > C and one had the c.1100delC mutation. Three variants of unclear clinical significance according to the ClinVar database were detected (Table 1) in leukocytes.
For the mutation analysis, urine samples from 139 mCRPC patients were available (six samples were missing and four were low in NGS library quantity). In total, 26 pathogenic mutations were detected in 23 out of 139 cases (16.6%; Figure 1). All germline mutations detected in leukocytes (19 in total) from these patients were also identified in urine samples. However, seven somatic mutations (2—BRCA1, 2—BRCA2, 1—CHEK2 and 2—ATM) were additionally identified in the urine of five patients (5/139; 3.6%), where the majority (116/139; 83%) were negative for germline alterations in the blood analysis.
Multiple mutations were detected in the urine of three patients (2.2%; 3/139), where concomitant somatic alterations in BRCA1 and ATM genes were detected in one case (0.7%; 1/139) and a combination of BRCA2 and CHEK2 mutations was identified in two patients (1.4%; 2/139; somatic-somatic and somatic-germline).

3.2. Urinary DDR Mutations and Clinical Response

Due to the more complete presentation of both somatic and germline types of mutations, an oncoprint of urinary samples was used for further analysis. The patients with and without detected pathogenic mutations in urine were divided into mutation-positive DDR(+) and mutation-negative DDR(−) groups, respectively. Although there were 23 cases with at least one mutation detected in urine, two cases (PN029, PN038) were classified as outliers and not included in the analysis. Additionally, one patient (PN072) was evaluated as DDR(−) due to the unknown pathogenic variant of ATM mutation (Table 1). Finally, the patients with BRCA1, BRCA2, CHEK2 (c.1100delC only), ATM and NBN were classified as DDR(+)A group (12 patients), omitting the cases with less pathogenic [4] CHEK2 mutation c.470T > C (eight patients). Therefore, the analysis was performed by comparing the DDR(+) with the DDR(−) group, and the DDR(+)A with the DDR(−) group. Baseline clinical and demographic characteristics of DDR(+) and DDR(−) cohorts are provided in Table 2.
Mean response time to androgen deprivation therapy (ADT) in a hormone-sensitive setting (HSPC) was 4.5 (95% CI: 3.9–5.1) years. For DDR(+)A patients, the mean response time was 1.8 times shorter, as compared to DDR(−) patients (Figure 2B, p = 0.022). In multivariate regression analysis, mutations of the DDR(+)A cohort (p = 0.019) and higher cISUP grade group (p = 0.001) were the main predictors for the shorter response to conventional ADT (Table 3).
After disease progression to mCRPC, the mean PFS for the first-line therapy was 1.3 (95% CI: 1.1–1.5) years. DDR(+) was associated with significantly shorter PFS (Figure 2C, p = 0.003). In addition, significantly worse outcomes were registered in the DDR(+)A group vs. DDR(−) (Figure 2D, p = 0.005). The same response was evaluated in multifactorial analysis (Table 3).
Regarding AA as the first-line drug for mCRPC, DDR(+) and DDR(+)A groups were associated with significantly shorter response times, as compared to DDR(−) patients (Figure 2E–F, p = 0.003 and p = 0.025, respectively). Likewise, adjusted HR was significantly higher for DDR(+) vs. DDR(−) (Table 3, p = 0.011), when a tendency was demonstrated by the DDR(+)A mutation group (Table 3, p = 0.076). No statistically significant differences in PFS for the first-line therapy were observed when docetaxel was administered as the first-line drug.
Eight DDR(+) and 23 DDR(−) patients received AA after disease progression on prior docetaxel therapy. The mean PFS for the AA as the second-line drug was 1.5 (95% CI: 0.9–2.1) years, while mean PFS for DDR(+) and DDR(−) patients was 1.7 (95% CI: 0.8–2.6) and 1.4 (95% CI: 0.8–2.1) years, respectively. Contrary to the first-line treatment with AA, DDR(+) status was not a significant predictor of poor response to the second-line treatment with AA (HR = 0.9 95% CI: 0.4–2.0, p = 0.78).
Radium-223 dichloride therapy was administered to 16 patients in the DDR(−) group and seven patients in the DDR(+) group. Regarding DDR(+) status, two patients with two CHEK2 mutations and five patients with BRCA1/BRCA2 mutations underwent radium-223 dichloride therapy. After three or six cycles of bone-specific therapy, the median levels of ALP were comparable in all groups with particular DDR status. However, the DDR(+)A group showed a tendency toward a worse response on bone scintigraphy at the end of radium-223 therapy than the DDR(−) group (p = 0.11). In more detail, only two of five DDR(+)A patients showed a positive response, while 81% (13 of 16) of DDR(−) and 57% (4 of 7) of DDR(+) patients had a positive response.

3.3. Survival and Urinary DDR Mutations

The mean overall survival for mCRPC patients was 11.2 (95% CI: 10.2–12.2) years, where the DDR(+)A group was characterized by reduced survival rates, as the mean survival was 9.5 (95% CI: 7.1–11.9) vs. 11.4 (95% CI: 10.3–12.4) in the DDR(−) group (Figure 2H, p = 0.05). Although multivariate analysis identified the cISUP grade group and radical therapy as independent prognostic factors for overall survival (Table 3, p < 0.001 and p = 0.001, respectively), gene alterations in the DDR(+)A group (HR = 2.0, 95% CI: 1.0–4.2, p = 0.058) also demonstrated a remarkably deleterious impact on overall survival in mCRPC patients (Table 3).

4. Discussion

CRPC is a clinically heterogenous disease with various treatment possibilities approved for the therapeutic armamentarium. However, for the selection of the most appropriate treatment strategies and further drug sequencing, scientific evidence is still scarce, especially in the most aggressive and lethal form of the disease—mCRPC, including DDR-mutated cases.
According to the recent literature, the percentage of patients with germline mutations in DDR genes ranged from 1.4–2.1% in low-risk [7,18] to 11.8% in metastatic [7] disease, while it could be as high as 15.4% in mCRPC patients, as detected in our study. In comparison, the median prevalence rates of somatic mutations vary from 10.7% in PCa in general to 13.2% in the metastatic disease [19]. In our study, 16,6% cases were identified with germline or somatic DDR pathway mutations using urine samples as liquid biopsies.
Pathogenic germline BRCA1, BRCA2 and ATM mutations in blood leukocytes were detected in 3.4% of mCRPC patients each, while the CHEK2 mutation was the most common (8.1%), though CHEK2 c.1100delC was detected in only 0.7% of patients. Other authors have reported comparable rates, where BRCA1, BRCA2 and ATM mutations were detected in 4.1% and 1.9% of mCRPC patients, respectively [19]. Importantly, all inherited DDR mutations detected in blood samples were also identified in urine, where a significant number of additional somatic alterations were also detected.
The high diagnostic potential of liquid biopsy tests has been previously shown in a blood plasma study by Annala et al., where 65 mCRPC patient germline and cfDNA sample pair sequencing showed high concordance in allele fractions and somatic mutation status [20]. Moreover, liquid biopsy is more suitable for patient monitoring, metastasis detection, and disease heterogeneity analysis, since multiple prostate biopsies are not recommended for mCRPC patients [21]. While the mutation analysis in urine already has been suggested as a diagnostic test for PCa [22], comprehensive data are lacking on the amount of germline and/or somatic mutations in urine of mCRPC cases. In our study, in addition to germline mutations detected both in blood leukocytes and urine DNA, an additional seven somatic mutations were identified on NGS in urine samples.
It is generally accepted that PCa patients harbouring DDR mutations have a more aggressive form of the disease and are associated with poor survival outcomes [23,24]. Emerging evidence suggests that DDR mutation carriers demonstrate an inferior response to androgen pathway-targeted therapy [25], while based on the synthetic lethality phenomenon, they may benefit from poly-ADP ribose polymerase (PARP) inhibitors [26,27,28]. From this point of view, patients with DDR mutations may also obtain a greater clinical benefit from DNA-damaging therapies, such as platinum-based chemotherapy [16,17,18] or bone-targeted radium-223 therapy [15,29]. Regrettably, these studies analysing clinical response in DDR mutated PCa cases typically cover only some fragments of the disease with specific clinical characteristics and provide hardly comparable controversial results.
CTC and cfDNA continue to be extensively researched in the liquid biopsy field. Identification of total CTC and other CTC-derived biomarkers, such as androgen receptor splice variant 7 (AR-V 7), in advanced PCa patients, might predict the disease prognosis and treatment response, as shown by various studies [30,31,32]. Further investigation into DDR mutation-positive PCa and CTC-related biomarkers may lead to a better understanding of the disease resistance and the development of personalized treatment options.
Our study provides a comprehensive analysis of clinical responses to various PCa therapies in all stages of the disease, from ADT in HSPC to bone-targeted therapy in mCRPC, and represents a complete natural history of disease progression for DDR mutation carriers. According to our data, DDR(+)A mutation carriers demonstrated significantly shorter response to conventional ADT in HSPC that consequently was followed by significantly shorter PFS for AA in the mCRPC setting, and similar results were also reported by Annala et al. [25]. All of these findings, including relatively rapid disease progression in DDR mutated cases, provide a rationale for germline and somatic mutation testing for timely identification of the most aggressive forms of PCa. Moreover, our study demonstrated a superior response of DDR mutation carriers to AA when it was administered after docetaxel, while the first-line treatment with docetaxel also showed sufficient response in these patients. Consistent with our finding, Castro et al. reported comparable response rates between patients with and without DDR mutations treated with taxane therapy [19]. A favourable response to platinum-based chemotherapy in DDR mutation carriers with mCRPC is also known from other studies [16,17,18], supporting the idea that targeting different cellular pathways (cell cycle, apoptosis, DNA repair) might be beneficial for improved response in PCa patients with DDR deficiency. In fact, DDR(+)A patients responded poorly to a set of administered therapies, and multivariate analysis revealed DDR(+)A mutations as remarkably hazardous to overall survival after adjustment to cISUP grade and radical therapy. Shorter time to progression in various treatment regimens observed for DDR(+) patients in our and previous studies [15,25] suggest the need to review the whole sequence of systemic treatment in DDR mutation-positive mCRPC.
This was a prospective study with well-balanced baseline clinical and demographic characteristics and a full overview of the natural history of PCa disease, but the shortcoming of an insufficient power of statistical testing should be noted, as a small number of patients with specific DDR mutations could affect the statistical analysis, especially when a tendency was observed in the results. Notwithstanding this limitation, the study demonstrated a significant predictive value of non-invasive urinary DDR testing in all stages of PCa, which, in turn, could suggest personalized therapy to obtain the best possible clinical outcomes.

5. Conclusions

Our data reveal the clinical value of non-invasive urine-based genetic testing in mCRPC patients for treatment individualization. DDR mutation testing along with the routine screening for familial or precocious PCa should be suggested for the selection of the most appropriate treatment strategy not only in mCRPC but also in earlier stages of PCa.

Author Contributions

Conceptualization, S.J., F.J.; formal analysis, D.D., I.V.; investigation, R.S., I.K., A.S., I.V.; data curation, T.J., R.S., A.B., A.V., A.U.; writing—original draft preparation, T.J., R.S., D.D., I.V., A.B.; visualization, R.S., I.V., D.D.; supervision, S.J., F.J.; funding acquisition, S.J., F.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Research Council of Lithuania grant No. SEN-09/2016.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Regional Bioethics Committee No.: 158200-17-874-411 (7 February 2017).

Informed Consent Statement

Written informed consent was obtained from all participants involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We would like to thank the Science Foundation from National Cancer Institute of Lithuania and the UAB Sanofi-Aventis Lietuva for the unrestricted grant for partly supporting this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bray, F.; Ferlay, J.; Soerjomataram, I. Global Cancer Statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef]
  2. Castro, E.; Eeles, R. The role of BRCA1 and BRCA2 in prostate cancer. Asian J. Androl. 2012, 14, 409–414. [Google Scholar] [CrossRef]
  3. Dias, A.; Kote-Jarai, Z.; Mikropoulos, C.; Eeles, R. Prostate Cancer Germline Variations and Implications for Screening and Treatment. Cold Spring Harb. Perspect. Med. 2018, 8, a030379. [Google Scholar] [CrossRef]
  4. Rantapero, T.; Wahlfors, T.; Kähler, A.; Hultman, C.; Lindberg, J.; Tammela, T.L.J.; Nykter, M.; Schleutker, J.; Wiklund, F. Inherited DNA Repair Gene Mutations in Men with Lethal Prostate Cancer. Genes 2020, 11, 314. [Google Scholar] [CrossRef]
  5. Nicolosi, P.; Ledet, E.; Yang, S.; Michalski, S.; Freschi, B.; O’Leary, E.; Esplin, E.D.; Nussbaum, R.L.; Sartor, O. Prevalence of Germline Variants in Prostate Cancer and Implications for Current Genetic Testing Guidelines. JAMA Oncol. 2019, 5, 523–528. [Google Scholar] [CrossRef]
  6. Leongamornlert, D.; Saunders, E.; Dadaev, T.; Tymrakiewicz, M.; Goh, C.; Jugurnauth-Little, S.; Kozarewa, I.; Fenwick, K.; Assiotis, I.; Barrowdale, D.; et al. Frequent germline deleterious mutations in DNA repair genes in familial prostate cancer cases are associated with advanced Disease. Br. J. Cancer 2014, 110, 1663–1672. [Google Scholar] [CrossRef]
  7. Pritchard, C.C.; Mateo, J.; Walsh, M.F.; de Sarkar, N.; Abida, W.; Beltran, H.; Garofalo, A.; Gulati, R.; Carreira, S.; Eeles, R.; et al. Inherited DNA-Repair Gene Mutations in Men with Metastatic Prostate Cancer. N. Engl. J. Med. 2016, 375, 443–453. [Google Scholar] [CrossRef]
  8. Morgado, P.C.; Mateo, J. Clinical implications of homologous recombination repair mutations in prostate cancer. Prostate 2022, 82, 45–59. [Google Scholar] [CrossRef]
  9. NCCN Guidelines: Prostate Cancer Early Detection | National Comprehensive Cancer Network. Available online: https://www.nccn.org/ (accessed on 24 September 2021).
  10. EAU Guidelines: Prostate Cancer|Uroweb. Available online: https://uroweb.org/guideline/prostate-cancer/ (accessed on 24 September 2021).
  11. Russano, M.; Napolitano, A.; Ribelli, G.; Iuliani, M.; Simonetti, S.; Citarella, F.; Pantano, F.; Dell’aquila, E.; Anesi, C.; Silvestris, N.; et al. Liquid biopsy and tumor heterogeneity in metastatic solid tumors: The potentiality of blood samples. J. Exp. Clin. Cancer Res. 2020, 39, 95. [Google Scholar] [CrossRef]
  12. Eskra, J.N.; Rabizadeh, D.; Pavlovich, C.P.; Catalona, W.J.; Luo, J. Approaches to urinary detection of prostate cancer. Prostate Cancer Prostatic Dis. 2019, 22, 362–381. [Google Scholar] [CrossRef]
  13. Markowski, M.C.; Antonarakis, E.S. Germline genetic testing in prostate cancer—Further enrichment in variant histologies? Oncoscience 2018, 5, 62–64. [Google Scholar] [CrossRef]
  14. Antonarakis, E.S.; Lu, C.; Luber, B.; Liang, C.; Wang, H.; Chen, Y.; Silberstein, J.L.; Piana, D.; Lai, Z.; Chen, Y.; et al. Germline DNA-repair Gene Mutations and Outcomes in Men with Metastatic Castration-resistant Prostate Cancer Receiving First-Line Abiraterone and Enzalutamide. Eur. Urol. Oncol. 2018, 74, 218–225. [Google Scholar] [CrossRef]
  15. Isaacsson Velho, P.; Qazi, F.; Hassan, S.; Carducci, M.A.; Denmeade, S.R.; Markowski, M.C.; Thorek, D.L.; DeWeese, T.L.; Song, D.Y.; Tran, P.T.; et al. Efficacy of Radium-223 in Bone-metastatic Castration-resistant Prostate Cancer with and without Homologous Repair Gene Defects. Eur. Urol. 2019, 76, 170–176. [Google Scholar] [CrossRef] [PubMed]
  16. Cheng, H.H.; Pritchard, C.C.; Boyd, T.; Nelson, P.S.; Montgomery, B. Biallelic Inactivation of BRCA2 in Platinum-sensitive Metastatic Castration-resistant Prostate Cancer. Eur. Urol. 2016, 69, 992–995. [Google Scholar] [CrossRef] [PubMed]
  17. Pomerantz, M.M.; Spisák, S.; Jia, L.; Cronin, A.M.; Csabai, I.; Ledet, E.; Sartor, A.O.; Rainville, I.; O’Connor, E.P.; Herbert, Z.T.; et al. The association between germline BRCA2 variants and sensitivity to platinum-based chemotherapy among men with metastatic prostate cancer. Cancer 2017, 123, 3532–3539. [Google Scholar] [CrossRef] [PubMed]
  18. Zafeiriou, Z.; Bianchini, D.; Chandler, R.; Rescigno, P.; Yuan, W.; Carreira, S.; Barrero, M.; Petremolo, A.; Miranda, S.; Riisnaes, R.; et al. Genomic Analysis of Three Metastatic Prostate Cancer Patients with Exceptional Responses to Carboplatin Indicating Different Types of DNA Repair Deficiency. Eur. Urol. 2019, 75, 184–192. [Google Scholar] [CrossRef]
  19. Castro, E.; Romero-Laorden, N.; del Pozo, A.; Lozano, R.; Medina, A.; Puente, J.; Piulats, J.M.; Lorente, D.; Saez, M.I.; Morales-Barrera, R.; et al. Prorepair-B: A Prospective Cohort Study of the Impact of Germline DNA Repair Mutations on the Outcomes of Patients with Metastatic Castration-Resistant Prostate Cancer. J. Clin. Oncol. 2019, 37, 490–503. [Google Scholar] [CrossRef] [PubMed]
  20. Annala, M.; Vandekerkhove, G.; Khalaf, D.; Taavitsainen, S.; Beja, K.; Warner, E.W.; Sunderland, K.; Kollmannsberger, C.; Eigl, B.J.; Finch, D.; et al. Circulating Tumor DNA Genomics Correlate with Resistance to Abiraterone and Enzalutamide in Prostate Cancer. Cancer Discov. 2018, 8, 444–457. [Google Scholar] [CrossRef] [PubMed]
  21. Ramesh, N.; Sei, E.; Tsai, P.C.; Bai, S.; Zhao, Y.; Troncoso, P.; Corn, P.G.; Logothetis, C.; Zurita, A.J.; Navin, N.E. Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing. Genome Biol. 2020, 21, 162. [Google Scholar] [CrossRef]
  22. Kavalci, E.; Onder, A.U.; Brusgaard, K.; Bostanci, A.; Selhanoglu, M.Y.; Serakinci, N. Identification of genetic biomarkers in urine for early detection of prostate cancer. Curr. Probl. Cancer 2021, 45, 100616. [Google Scholar] [CrossRef]
  23. Bancroft, E.K.; Page, E.C.; Castro, E.; Lilja, H.; Vickers, A.; Sjoberg, D.; Assel, M.; Foster, C.S.; Mitchell, G.; Drew, K.; et al. Targeted prostate cancer screening in BRCA1 and BRCA2 mutation carriers: Results from the initial screening round of the IMPACT Study. Eur. Urol. 2014, 66, 489–499. [Google Scholar] [CrossRef] [PubMed]
  24. Na, R.; Zheng, S.L.; Han, M.; Yu, H.; Jiang, D.; Shah, S.; Ewing, C.M.; Zhang, L.; Novakovic, K.; Petkewicz, J.; et al. Germline Mutations in ATM and BRCA1/2 Distinguish Risk for Lethal and Indolent Prostate Cancer and are Associated with Early Age at Death. Eur. Urol. 2017, 71, 740–747. [Google Scholar] [CrossRef] [PubMed]
  25. Annala, M.; Struss, W.J.; Warner, E.W.; Beja, K.; Vandekerkhove, G.; Wong, A.; Khalaf, D.; Seppälä, I.L.; So, A.; Lo, G.; et al. Treatment Outcomes and Tumor Loss of Heterozygosity in Germline DNA Repair–deficient Prostate Cancer. Eur. Urol. 2017, 72, 34–42. [Google Scholar] [CrossRef] [PubMed]
  26. Lang, S.H.; Swift, S.L.; White, H.; Misso, K.; Kleijnen, J.; Quek, R.G.W. A systematic review of the prevalence of DNA damage response gene mutations in prostate cancer. Int. J. Oncol. 2019, 55, 597–616. [Google Scholar] [CrossRef] [PubMed]
  27. Mateo, J.; Carreira, S.; Sandhu, S.; Miranda, S.; Mossop, H.; Perez-Lopez, R.; Nava Rodrigues, D.; Robinson, D.; Omlin, A.; Tunariu, N.; et al. DNA-Repair Defects and Olaparib in Metastatic Prostate Cancer. N. Engl. J. Med. 2015, 373, 1697–1708. [Google Scholar] [CrossRef] [PubMed]
  28. de Bono, J.; Mateo, J.; Fizazi, K.; Saad, F.; Shore, N.; Sandhu, S.; Chi, K.N.; Sartor, O.; Agarwal, N.; Olmos, D.; et al. Olaparib for Metastatic Castration-Resistant Prostate Cancer. N. Engl. J. Med. 2020, 382, 2091–2102. [Google Scholar] [CrossRef] [PubMed]
  29. Teply, B.A.; Antonarakis, E.S. Treatment strategies for DNA repair-deficient prostate cancer. Expert Rev. Clin. Pharmacol. 2017, 10, 889–898. [Google Scholar] [CrossRef]
  30. Di Lorenzo, G.; Zappavigna, S.; Crocetto, F.; Giuliano, M.; Ribera, D.; Morra, R.; Scafuri, L.; Verde, A.; Bruzzese, D.; Iaccarino, S.; et al. Assessment of Total, PTEN-, and AR-V7+ Circulating Tumor Cell Count by Flow Cytometry in Patients with Metastatic Castration-Resistant Prostate Cancer Receiving Enzalutamide. Clin. Genitourin. Cancer 2021, 19, e286–e298. [Google Scholar] [CrossRef]
  31. Armstrong, A.J.; Luo, J.; Nanus, D.M.; Giannakakou, P.; Szmulewitz, R.Z.; Danila, D.C.; Healy, P.; Anand, M.; Berry, W.R.; Zhang, T.; et al. Prospective Multicenter Study of Circulating Tumor Cell AR-V7 and Taxane Versus Hormonal Treatment Outcomes in Metastatic Castration-Resistant Prostate Cancer. JCO Precis. Oncol. 2020, 28, 1285–1301. [Google Scholar] [CrossRef]
  32. Scher, H.I.; Lu, D.; Schreiber, N.A.; Louw, J.; Graf, R.P.; Vargas, H.A.; Johnson, A.; Jendrisak, A.; Bambury, R.; Danila, D.; et al. Association of AR-V7 on circulating tumor cells as a treatment-specific biomarker with outcomes and survival in castration-resistant prostate cancer. JAMA Oncol. 2016, 2, 1441–1449. [Google Scholar] [CrossRef]
Figure 1. Oncoprint of selected pathogenic alterations detected in urine and leukocyte samples. Only samples with at least one detected mutation are shown. The percentages correlate to the number of mutations found in all 149 patients analysed in leukocytes and 139 in urine samples.
Figure 1. Oncoprint of selected pathogenic alterations detected in urine and leukocyte samples. Only samples with at least one detected mutation are shown. The percentages correlate to the number of mutations found in all 149 patients analysed in leukocytes and 139 in urine samples.
Biomedicines 11 00761 g001
Figure 2. Progression-free survival for ADT in HSPC, the first-line therapy in mCRPC and overall survival. Graphs are supplied as DDR(+) vs. DDR(−) and DDR(+)A vs. DDR(−) for: ADT in HSPC (A,B), the first-line therapy (C,D), the first-line therapy with abiraterone acetate (E,F) and overall survival (G,H). The 95% confidence intervals are presented in brackets. Abbreviations: ADT—androgen deprivation therapy; HR—hazard ratio; HSPC—hormone-sensitive prostate cancer; PFS—progression-free survival.
Figure 2. Progression-free survival for ADT in HSPC, the first-line therapy in mCRPC and overall survival. Graphs are supplied as DDR(+) vs. DDR(−) and DDR(+)A vs. DDR(−) for: ADT in HSPC (A,B), the first-line therapy (C,D), the first-line therapy with abiraterone acetate (E,F) and overall survival (G,H). The 95% confidence intervals are presented in brackets. Abbreviations: ADT—androgen deprivation therapy; HR—hazard ratio; HSPC—hormone-sensitive prostate cancer; PFS—progression-free survival.
Biomedicines 11 00761 g002
Table 1. Molecular characteristics of variants of pathogenic or unclear clinical significance in mutation-positive patients.
Table 1. Molecular characteristics of variants of pathogenic or unclear clinical significance in mutation-positive patients.
LeukocytesGeneSample IDPathogenic VariantsAmino AciddbSNP, rsMethod
CodingTypeVariantExon
BRCA1PN088; PN179c.4035delAINDELframeshiftdel11p.Glu1346Lysfsrs80357711qPCR
BRCA2PN082c.658_659delGTINDELframeshiftdel8p.Val220Ilefsrs80359604qPCR
PS001c.7879A > TSNVmissense17p.Ile2627Phers80359014NGS
PN050c.3847_3848delGTINDELframeshiftdel11p.Val1283fsrs80359405NGS
CHEK2PN004; PN022; PN034; PN051; PN055; PN073; PN107; PN108; PN125; PN136; PN143c.470T > CSNVmissense4p.Ile157Thrrs17879961qPCR
PN223c.1100delCINDELframeshiftdel11p.Thr367Metfsrs555607708qPCR
NBNPN132c.657_661delACAAAINDELframeshiftdel6p.Lys219fsrs587776650qPCR
ATMPN029; PN175c.8122G > ASNVmissense55p.Asp2708Asnrs587782719NGS
PN044c.1339C > TSNVnonsense10p.Arg447Terrs587779815
PN090; PN206c.5932G > TSNVnonsense40p.Glu1978Terrs587779852
GeneSample IDVariants of Unclear Clinical SignificanceAmino AciddbSNP, rsMethod
CodingTypeVariantExon
BRCA2PN031c.8242_8244delGGTINDELnonframeshiftdel18p.Gly2748delNGS
NBNPN199c.1445G > ASNVmissense11p.Arg482Lysrs775451862
ATMPN048c.4631A > GSNVmissense31p.Tyr1544Cysrs779718362
UrineGeneSample IDPathogenic VariantAmino AciddbSNP, rsMethod
CodingTypeVariantExon
BRCA1PN025c.3268C > TSNVnonsense10p.Gln1090Terrs80357402NGS
PN038c.5574G > ASNVnonsense24p.Trp1858Terrs80356914
PN088; PN179c.4035delAINDELframeshiftdel11p.Glu1346Lysfsrs80357711
BRCA2PN033c.1532C > ASNVnonsense10p.Ser511Terrs1555281935
PN050; PN143c.3847_3848delGTINDELframeshiftdel11p.Val1283fsrs80359405
PN082c.658_659delGTINDELframeshiftdel8p.Val220Ilefsrs80359604
CHEK2PN034 PN051; PN055; PN073; PN107; PN108; PN125; PN136; PN143c.470T > CSNVmissense4p.Ile157Thrrs17879961
PN033; PN223c.1100delCINDELframeshiftdel11p.Thr367Metfsrs555607708
NBNPN132c.657_661delACAAAINDELframeshiftdel6p.Lys219fsrs587776650
ATMPN029; PN175c.8122G > ASNVmissense55p.Asp2708Asnrs587782719
PN044c.1339C > TSNVnonsense10p.Arg447Terrs587779815
PN090c.5932G > TSNVnonsense40p.Glu1978Terrs587779852
PN025c.3663G > ASNVnonsense25p.Trp1221Terrs864622490
PN072c.6006 + 1G > CSNVunknown40p.?rs786202016
Abbreviations: SNV—single nucleotide variant; INDEL—insertion/deletion variant. Grey colour indicates deceased patients.
Table 2. Clinico-pathological and demographic characteristics of study cohort.
Table 2. Clinico-pathological and demographic characteristics of study cohort.
VariableDDR(+)
(n = 20)
DDR(−)
(n = 117)
p Value
Age at PCa diagnosis, years 0.27
Median (IQR)63.5 (57.7–71.5)66.4 (61.5–71.1)
Age at mCRPC diagnosis, years 0.27
Median (IQR)63.5 (57.7–71.5)66.4 (61.5–71.1)
PSA level at PCa diagnosis, ng/mL 0.09
<10; n (%)3 (15.0)36 (30.7)
10–20; n (%)3 (15.0)25 (21.4)
>20; n (%)14 (70.0)53 (45.4)
cISUP grade group 0.71
1; n (%)7 (35.0)48 (41.0)
2; n (%)4 (20.0)18 (15.4)
3; n (%)2 (10.0)14 (12.0)
4; n (%)5 (25.0)16 (13.7)
5; n (%)1 (5.0)12 (10.3)
cT stage 0.62
≤T2; n (%)6 (30.0)43 (36.8)
≥T3; n (%)14 (70.0)67 (57.3)
Radical treatment 0.27
Radical prostatectomy; n (%)3 (15.0)9 (7.7)
Radiation therapy; n (%)9 (45.0)42 (35.9)
None; n (%)8 (40.0)66 (6.4)
Abiraterone acetate therapy for mCRPC 0.07
First-line; n (%)11 (55.0)88 (75.2)
Second-line; n (%)8 (40.0)26 (22.2)
Other; n (%)3 (15.0)3 (2.5)
Docetaxel therapy for mCRPC 0.77
First-line; n (%)9 (45.0)28 (23.9)
Second-line; n (%)3 (15.0)13 (11.1)
Other; n (%)3 (15.0)11 (9.4)
Deceased 0.32
Yes; n (%)15 (75.0)73 (62.4)
No; n (%)5 (25.0)44 (37.6)
Abbreviations: cISUP—clinical ISUP group; cT—clinical T staging; DDR—DNA damage response; IQR—interquartile range; ISUP—International Society of Urological Pathology; n—total number of patients; mCRPC—metastatic castration-resistant prostate cancer; PCa—prostate cancer; PSA—prostate-specific antigen.
Table 3. Univariate and multivariate Cox regression analysis to assess significant factors associated with treatment and survival outcomes.
Table 3. Univariate and multivariate Cox regression analysis to assess significant factors associated with treatment and survival outcomes.
Analysed by DDR(+)Analysed by DDR(+)A
Univariate MultivariateUnivariateMultivariate
HR with 95% CIp ValueHR with 95% CIp ValueHR with 95% CIp ValueHR with 95% CIp Value
PFS for ADT
DDR genetic alteration1.04 (0.64–1.71)0.861.18 (0.71–1.96)0.532.11 (1.12–4.01)0.0222.17 (1.14–4.13)0.019
Age1.01 (0.98–1.04)0.34-0.99 (0.97–1.03)0.94-
cISUP 2.07 (1.43–3.00)<0.0012.09 (1.44–3.04)<0.0011.87 (1.28–2.74)0.0011.88 (1.28–2.75)0.001
RT1.00 (0.71–1.43)0.97-1.23 (0.86–1.76)0.26-
PSA0 - -
M vs. L0.95 (0.58–1.56) 0.850.99 (0.60–1.64)0.99
H vs. L1.11 (0.74–1.66) 0.621.14 (0.76–1.73)0.53
PFS for mCRPC first-line treatment
DDR genetic alteration2.17 (1.31–3.59)0.0032.22 (1.34–3.69)0.0022.47 (1.32–4.62)0.0052.53 (1.34–4.77)0.004
Age1.02 (0.99–1.05)0.171.01 (0.98–1.04)0.381.02 (0.99–1.05)0.191.01 (0.99–1.04)0.34
cISUP 1.26 (0.83–1.92)0.27-1.22 (0.79–1.89)0.37-
RT0.77 (0.52–1.15)0.190.84 (0.55–1.29)0.430.77 (0.51–1.17)0.22-
PSA1 1.001 (1.000–1.002)0.0041.001 (1.000–1.002)0.0111.001 (1.000–1.002)0.0051.001 (1.000–1.002)0.004
PFS for mCRPC first-line AA treatment
DDR genetic alteration2.72 (1.39–5.33) 0.0032.43 (1.23–4.83)0.0112.72 (1.14–6.50)0.0252.25 (0.92–5.49)0.076
Age1.03 (0.99–1.06) 0.081.02 (0.99–1.06)0.241.03 (0.99–1.07)0.061.03 (0.99–1.07)0.18
cISUP 1.13 (0.64–2.02) 0.67-1.05 (0.57–1.93)0.88-
RT0.67 (0.41–1.10) 0.110.84 (0.48–1.46)0.530.65 (0.39–1.10)0.110.85 (0.48–1.49)0.57
PSA1 1.001 (1.001–1.002)0.0111.001 (1.000–1.002)0.0071.001 (1.001–1.002)0.0011.001 (1.000–1.002)0.002
Overall survival
DDR genetic alteration1.07 (0.60–1.90) 0.821.62 (0.87–3.02)0.1261.47 (0.73–2.95)0.282.02 (0.98–4.17)0.058
Age1.06 (1.03–1.09) <0.0011.03 (0.99–1.06)0.1281.05 (1.02–1.09)0.0041.02 (0.99–1.06)0.22
cISUP 3.15 (1.97–5.02) <0.0013.16 (1.93–5.15)<0.0012.83 (1.76–4.55)<0.0013.01 (1.83–4.94)<0.001
RT0.34 (0.21–0.54) <0.0010.39 (0.23–0.67)0.0010.39 (0.24–0.63)<0.0010.40 (0.23–0.69)<0.001
PSA1 1.001 (1.000–1.002)0.0221.000 (0.999–1.001)0.6141.001 (1.000–1.002)0.0471.000 (0.99–1,001)0.70
Abbreviations: CI—confidence interval; cISUP—clinical ISUP grade groups 3–5 vs. 1/2; mCRPC—metastatic castration-resistant prostate cancer; HR—hazard ratio; ISUP—International Society of Urological Pathology; PFS—progression-free survival; RT—radical treatment; PSA0—PSA at PCa diagnosis, ng/mL: L—<10, M—10–20, H—>20; PSA1—PSA before first-line mCRPC treatment; Numbers in bold indicate p-values <0.050.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Januskevicius, T.; Sabaliauskaite, R.; Dabkeviciene, D.; Vaicekauskaite, I.; Kulikiene, I.; Sestokaite, A.; Vidrinskaite, A.; Bakavicius, A.; Jankevicius, F.; Ulys, A.; et al. Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients. Biomedicines 2023, 11, 761. https://doi.org/10.3390/biomedicines11030761

AMA Style

Januskevicius T, Sabaliauskaite R, Dabkeviciene D, Vaicekauskaite I, Kulikiene I, Sestokaite A, Vidrinskaite A, Bakavicius A, Jankevicius F, Ulys A, et al. Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients. Biomedicines. 2023; 11(3):761. https://doi.org/10.3390/biomedicines11030761

Chicago/Turabian Style

Januskevicius, Tomas, Rasa Sabaliauskaite, Daiva Dabkeviciene, Ieva Vaicekauskaite, Ilona Kulikiene, Agne Sestokaite, Asta Vidrinskaite, Arnas Bakavicius, Feliksas Jankevicius, Albertas Ulys, and et al. 2023. "Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients" Biomedicines 11, no. 3: 761. https://doi.org/10.3390/biomedicines11030761

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop