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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

Publication: Journal of Clinical Oncology

Abstract

Purpose

Germline mutations in DNA damage repair (DDR) genes are identified in a significant proportion of patients with metastatic prostate cancer, but the clinical implications of these genes remain unclear. This prospective multicenter cohort study evaluated the prevalence and effect of germline DDR (gDDR) mutations on metastatic castration-resistance prostate cancer (mCRPC) outcomes.

Patients and Methods

Unselected patients were enrolled at diagnosis of mCRPC and were screened for gDDR mutations in 107 genes. The primary aim was to assess the impact of ATM/BRCA1/BRCA2/PALB2 germline mutations on cause-specific survival (CSS) from diagnosis of mCRPC. Secondary aims included the association of gDDR subgroups with response outcomes for mCRPC treatments. Combined progression-free survival from the first systemic therapy (PFS) until progression on the second systemic therapy (PFS2) was also explored.

Results

We identified 68 carriers (16.2%) of 419 eligible patients, including 14 with BRCA2, eight with ATM, four with BRCA1, and none with PALB2 mutations. The study did not reach its primary end point, because the difference in CSS between ATM/BRCA1/BRCA2/PALB2 carriers and noncarriers was not statistically significant (23.3 v 33.2 months; P = .264). CSS was halved in germline BRCA2 (gBRCA2) carriers (17.4 v 33.2 months; P = .027), and gBRCA2 mutations were identified as an independent prognostic factor for CCS (hazard ratio [HR], 2.11; P = .033). Significant interactions between gBRCA2 status and treatment type (androgen signaling inhibitor v taxane therapy) were observed (CSS adjusted P = .014; PFS2 adjusted P = .005). CSS (24.0 v 17.0 months) and PFS2 (18.9 v 8.6 months) were greater in gBRCA2 carriers treated in first line with abiraterone or enzalutamide compared with taxanes. Clinical outcomes did not differ by treatment type in noncarriers.

Conclusion

gBRCA2 mutations have a deleterious impact on mCRPC outcomes that may be affected by the first line of treatment used. Determination of gBRCA2 status may be of assistance for the selection of the initial treatment in mCRPC. Nonetheless, confirmatory studies are required before these results can support a change in clinical practice.

Introduction

Inherited mutations in several genes involved in DNA damage repair (DDR) have been reported to predispose men to prostate cancer1-4; these include mutations in BRCA2, the genetic event that confers the greatest risk of the disease.5 Recent next-generation sequencing studies have revealed that germline deleterious mutations in DDR genes are present in 8% to 12% of patients with metastatic prostate cancer.6-8 In a retrospective multi-institutional pooled analysis by Pritchard et al,7 the most frequently mutated genes were BRCA2 (5.3%), CHEK2 (2%), ATM (1.6%), and BRCA1 (0.9%). Mutations in the other 16 genes analyzed accounted for less than 0.5% of cases. A prevalence of 12% is significantly higher than that reported in localized prostate cancer (5%) or in the general population (3%),7,9 which suggests an association with aggressive disease. In fact, germline mutations in BRCA2 seem to be an independent poor prognostic factor for localized disease associated with shorter metastasis-free survival and cause-specific survival (CSS).10,11 On the basis of this evidence, updated National Comprehensive Cancer Network (NCCN) guidelines now recommend germline BRCA1/BRCA2 testing in all patients with metastatic prostate cancer.12 The prognostic implications of non-BRCA2 DDR defects are less well established. Nonetheless, both germline and somatic DDR defects have been identified as potential predictive biomarkers for platinum-based chemotherapy and poly-ADP ribose polymerase (PARP) inhibitors.13-15 Despite promising results with these drugs, resistance eventually occurs,16,17 and the data about the impact of DDR defects on the response to currently approved therapies for metastatic castration resistant prostate cancer (mCRPC) are limited and conflicting.8,18-23
As a result of the recommendation for germline screening and the implementation of sequencing panels in clinical practice to seek actionable genetic aberrations, the number of patients with germline DNA repair defects is likely to increase in the near future, so there is a pressing need for a better understanding of the implications of DDR defects on the prognosis and treatment of patients with mCRPC.

Patients and Methods

Study Design and Patients

PROREPAIR-B (ClinicalTrials.gov identifier: NCT03075735) is a multicenter prospective cohort study that involved 38 sites (Appendix, online only). Its primary aim was to assess the impact of BRCA1, BRCA2, ATM, and PALB2 germline mutations on CSS from diagnosis of mCRPC and to estimate the prevalence of germline DDR mutations (gDDR) in this population. Secondary end points included the analysis of the impact of gDDR mutations according to three groups—ATM/BRCA1/BRAC2/PALB2; BRCA2 only; and all gDDR carriers—on CSS, time to PSA progression (TTPP), progression-free survival (PFS), prostate-specific antigen (PSA), and radiographic response rates according to treatment line and by treatment type (androgen signaling inhibitor [ASI] or taxane). The study was granted approval by the Spanish regulatory authorities and by local institutional review boards at the participating sites.
Patients with histologically confirmed prostate cancer and unknown mutational status were enrolled at the time of metastatic castration-resistant diagnosis and observed until death. Patients had to be eligible to start a firstline treatment with a survival-prolonging therapy (SPT) within 6 months of castration resistance. The Appendix (online only) provides a complete list of inclusion and exclusion criteria. All patients provided informed consent at study entry.

Study Procedures

A baseline imaging (computed tomography [CT]/magnetic resonance imaging, and bone scan) evaluation within 6 weeks and a complete full blood count and biochemistry, including PSA and testosterone within 2 weeks of study entry, were required. A 5-mL blood sample was drawn at study entry for germline DNA extraction. All treatments were at the discretion of the treating physicians and were not dictated by the study. Responses and progression were evaluated according to the Prostate Cancer Clinical Trials Working Group 2 (PCWG2)24 or defined by protocol (Appendix).

Germline Variants Analyses

Sequencing libraries were generated from germline DNA using a custom NimbleGen SeqCap XL Target Enrichment (Roche, Pleasanton, CA) panel and read using an Illumina NexSEquation 500 platform (Illumina, San Diego, CA). On average 2 to 3 million 100-bp reads with a mean coverage of greater than ×150 for each sample were obtained. Then, sequencing files were processed according to the best practices proposed by the Genome Analysis Toolkit (GATK) and then filtered and annotated using ANNOVAR25 and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) records. A review panel blinded to patient information classified pathogenic variants using ClinVar annotations and the guidelines of the American College of Medical Genetics and Genomics.26 The Exome Aggregation Consortium (ExAC)27 noncancer data (n = 53,105) and CIBERER Spanish Variant Server (CSVS; http://csvs.babelomics.org/; n = 1,551) populations were filtered and reviewed using the same criteria to establish the frequency of pathogenic variants in the noncancer population for the analyzed DDR genes in the study. All variants identified as pathogenic were validated using multicapillary electrophoresis, polymerase chain reaction, Multiplex Ligation-dependent Probe Amplification (MLPA), and/or the BROCA panel (University of Washington Laboratory of Medicine, Seattle, WA; http://tests.labmed.washington.edu/BROCA).

Sample Size Calculation and Statistical Analyses

The study statistical design was based on PROREPAIR-B primary endpoint, which was based on our previous report of the association of BRCA1 and BRCA2 mutations with higher metastatic spread and shorter CSS.10 Sample size was calculated using the method proposed by Rubinstein et al28 and assumed a prevalence of germline mutations in ATM, BRCA1, BRCA2, and PALB2 of 5% or greater in patients with mCRPC; a median CSS of 30 months in the noncarriers group, and a hazard ratio (HR) for CSS from mCRPC of 3.0 or greater in ATM/BRCA1/BRCA2/PALB2 carriers versus noncarriers. To demonstrate our hypothesis, with an α of .05 and a β of .20, the study required enrollment of at least 408 patients to observe 171 or more prostate cancer–related deaths over an enrollment period of 30 months and a minimum follow-up of 8 months.
Response rates, including PSA decline of 50% or greater (PSA50) and objective radiographic responses (ORRs), in addition to time-to-event end points (ie, CSS, TTPP, and PFS) were defined by protocol or PCWG224 criteria (Appendix). All times to events were assessed by means of the Kaplan-Meier method, and the survival curves were compared using a log-rank test. Univariable and multivariable HRs were calculated using Cox proportional hazards models. All P values were two sided. Statistical Package for the Social Sciences for Windows version 19 (SPSS, Chicago, IL) and R version 3.3.3 programs were used for the statistical analysis. Data collection cutoff for these analyses was October 31, 2017, when the median follow-up from mCRPC was 40 months and 253 prostate cancer–related deaths had occurred.

Results

Between January 2013 and April 2016, 419 eligible patients from 38 institutions were included (Fig 1). Of them, 98% were white with Spanish ancestry. At prostate cancer diagnosis median age of participants was 66.2 years (range 40.8 to 92.1) and half of them (48.2%) already had metastatic disease. (Table 1).
Fig 1. Diagram to illustrate the participants’ flow in the PROREPAIR-B (ClinicalTrials.gov identifier: NCT03075735) study. DDR, DNA damage repair.
Table 1. Patient Characteristics at the Time of Metastatic Castration-Resistant Diagnosis and Summary of the Treatments Administered for mCRPC to the Patients in the Different Carrier Groups.

Germline DNA-Repair Gene Mutations and Familial Cancer History

Twenty-six patients (6.2%) carried a deleterious germline mutation in BRCA2 (n = 14), ATM (n = 8), or BRCA1 (n = 4). No mutations in PALB2 were identified. When all 107 DDR genes screened were considered (Fig 2A), 16.2% of patients harbored a pathogenic or likely pathogenic mutation (Fig 2B; Appendix Table A2, online only; Fig A1).
Fig 2. Prevalence of pathogenic variants in DNA damage repair (DDR) genes in unselected patients with metastatic castration-resistant prostate cancer (mCRPC). (A) Full list of the DDR genes screened in the PROREPAIR-B (ClinicalTrials.gov identifier: NCT03075735) study. (B) Distribution of the pathogenic/likely pathogenic mutations identified in the study. (C) Prevalence of deleterious germline mutations in the DDR genes analyzed in metastatic prostate cancer compared with noncancer populations—the Exome Aggregation Consortium (ExAC) and the CIBERER Spanish Variant Server (CSVS) populations. (*) ATM, ATR, BAP1, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, FAM175A, GEN1, MLH1, MRE11A, MSH2, MSH6, NBN, PALB2, PMS2, RAD51C, RAD51D, XRCC2. OR, odds ratio; SNV, single-nucleotide variant.
The prevalence of ATM/BRCA1/BRCA2/PALB2 mutations was significantly higher in mCRPC than in CSVS (6.2% v 0.7%; P < .001) and ExAC (6.2% v 0.9%; P < .001) populations. The odds ratios (ORs) for carrier status in mCRPC compared with Spanish and global noncancer populations were substantially increased for several DDR genes (Fig 2C; Appendix Table A2), including ATM, BRCA1, BRCA2, and MRE11A. The ORs for germline mutations in DDR genes in mCRPC compared with ExAC and CSVS were 1.4 (95% CI, 1.1 to 1.8; P = .021) and 3.2 (95% CI, 2.3 to 4.5; P < .001), respectively.
At study entry, 96 patients (22.9%) reported a family history of cancer that was significantly more common in gDDR carriers than in noncarriers (60.3% v 16.0%; P < .001; Appendix Fig A2, online only). Of all carriers, those with BRCA2 mutations had the greatest association with a family history of cancer (85.7% v 20.7%; P < .001). Breast and ovarian were the most frequent tumor types among the relatives of gDDR-carrier patients (28.0%). Thirty-nine patients reported a first- or second-degree relative with prostate cancer (17.6% of gDDR carriers v 7.7% of noncarriers; P = .019).

Characteristics of Carriers and Noncarriers at Diagnosis of mCRPC

The median time from the initiation of continuous androgen-deprivation therapy for recurrent or metastatic disease to castration resistance was significantly shorter for gDDR carriers than noncarriers (22.8 v 28.4 months; P = .007), particularly for BRCA2 carriers versus noncarriers (22.8 v 13.2 months; P = .048). Progression to mCRPC in the ATM/BRCA1/BRCA2/PALB2 group was frequently accompanied by radiographic progression (61.5%; P = .015 v noncarriers), particularly in BRCA2 carriers (71.4%; P = .011 v noncarriers). Other baseline characteristics at mCRPC were similar in the carriers and noncarriers groups (Table 1). No differences in the exposure to treatments were observed between groups. Remarkably, only 7.4% of carriers and 5.4% noncarriers received platinum-based chemotherapy (P = .567). Just four patients (1.1%), all of them noncarriers, received a PARP inhibitor in the context of clinical trials.

CSS From mCRPC

Median CSS was 10 months shorter in ATM/BRCA1/BRCA2/PALB2 carriers than in noncarriers (Fig 3A), yet the difference was not significant (23.3 v 33.2 months; P = .264; HR, 1.32; 95% CI, 0.81 to 2.17), and the study did not meet the prespecified primary end point. Likewise, there were no differences in CSS when all gDDR carrier patients were analyzed (P = .646; Fig 3C). Conversely, BRCA2 carriers showed a CSS that was approximately halved compared with noncarriers, which reached statistical significance (median, 17.4 v 33.2 months; P = .027; HR, 2.10; 95% CI, 1.07 to 4.10; Fig 3B). The difference in CSS was also significant when BRCA2 carriers were compared with other non-BRCA2 gDDR carriers (median, 33.8 months; P = .048). Multivariable analyses identified BRCA2 as an independent prognostic factor for CSS in mCRPC (HR, 2.11; 95% CI, 1.06 to 4.18.
Fig 3. Cause-specific survival (CSS) from diagnosis of metastatic castration-resistant prostate cancer (mCRPC). Kaplan-Meier curves for CSS: (A) ATM/BRCA1/BRCA2/PALB2 versus noncarriers; (B) BRCA2 versus noncarriers; (C) All germline DNA damage repair positive (gDDR+) versus noncarriers. (D) Forest plot of univariable hazard ratios (HRs) for CSS. ALP, alkaline phosphatase; ECOG, Eastern Cooperative Oncology Group; LDH, lactate dehydrogenase; PCa, prostate cancer; PSA, prostate-specific antigen.

Outcomes From First ASI and First Taxane

At the time of data cutoff, 365 patients had received at least one ASI, most of them as first (59.5%) or second (32.6%) SPT. A taxane was given to 326 patients in this setting, mostly as first SPT (60.4%), and docetaxel was the taxane of choice for 96.3%. Overall, nonsignificant differences in PSA50 responses, ORR, TTTP, PFS, and CSS were observed between ATM/BRCA1/BRCA2/PALB2, gDDR carrier, and noncarrier groups when treated either with the first ASI or the first taxane. However, shorter median CSS after the first taxane (12.8 v 23.3 months; P = .015; HR, 2.23; 95% CI, 1.13 to 4.38), but not after the first ASI (23.3 v 26.2 months; P = .215; HR, 1.63; 95% CI, 0.76 to 3.48), was observed in BRCA2 carriers compared with noncarriers (Table 2). The differences between these two groups in PSA50, ORR, TTPP, and PFS were not significant (Table 2).
Table 2. Outcomes of Patients by Carrier Group After Treatment With the First Taxane or the First ASI Given for mCRPC.

Differential Effect of gDDR Carrier Status in Patients Who Received Taxane or ASI as Firstline Treatment

We performed interaction analyses to assess whether the impact of carrier status on CSS was influenced by the first SPT administered. A significant interaction for CSS from firstline treatment between BRCA2 status and treatment type was observed in the unadjusted Cox-regression model (P = .015), which remained significant (P = .014) in an adjusted model that accounted for age; ECOG performance status; PSA; time to mCRPC from androgen-deprivation therapy initiation; and levels of lactate dehydrogenase, alkaline phosphatase, albumin, and hemoglobin (Fig 4). Conversely, nonsignificant interactions for CSS were observed between ATM/BRCA1/BRCA2/PALB2 (unadjusted P = .786; adjusted P = .772) or gDDR carriers (unadjusted P = .498; adjusted P = .909) and treatment type. Likewise, nonsignificant interactions for PSA50, ORR, TTPP, and PFS were identified between any carrier group and treatment type. When we analyzed the second SPT, a significant interaction between germline BRCA2 (gBRCA2) status and treatment was observed (unadjusted P = .006; adjusted P = .032; Appendix Fig A3, online only).
Fig 4. Cause-specific survival (CSS) since firstline survival-prolonging therapy (SPT) and interaction analysis between carrier status and treatment type. Kaplan-Meier analysis in 415 patients—218 treated with androgen signaling inhibitor (ASI) and 197 treated with taxanes (n = 4 received Ra-223 and were excluded), separated according to carrier subgroups: (A) germline BRCA2 mutant versus non-BRCA2 carriers; a positive interaction between BRCA2 carrier status and treatment type was observed (adjusted P = .014). No significant interactions were observed between treatment type and the following: (B) germline ATM/BRCA1/BRCA2 mutant versus non- ATM/BRCA1/BRCA2 carriers (adjusted P = .772) and (C) all germline DNA damage repair (gDDR)–mutant versus non–gDDR carriers (adjusted P = .909). Factors included together with the carrier status in the adjusted interaction Cox regression model were those significantly associated with CSS: median time to metastatic castration-resistant prostate cancer (mCRPC) since androgen-deprivation therapy (ADT), median prostate-specific antigen (PSA), ECOG performance status, albumin, lactate dehydrogenase (LDH), and alkaline phosphatase. HR, hazard ratio.

Impact of Treatment Sequence in BRCA2 Carriers

The interactions described above suggested a worse survival for those BRCA2 carriers who received a taxane as first-SPT and/or an ASI as second-SPT. We then conducted a post hoc analysis to compare CSS and PFS from initiation of the first-SPT to progression to the second-SPT or death (PFS2) according to BRCA2 status and SPT sequence: ASI-taxane or taxane-ASI. A total of 348 patients were eligible for this analysis, 190 (including 7 BRCA2) and 158 (including 7 BRCA2) in the ASI-taxane and taxane-ASI sequence, respectively. Patients in the taxane-ASI group were younger (P < .0001), with worse ECOG (P = .0023), higher PSA (P = .0071), and elevated lactate dehydrogenase (P = .0002) and alkaline phosphatase (P = .0102) than patients in the ASI-taxane group (Appendix Table A3, online only).
We first performed unadjusted interaction analyses between BRCA2 and treatment sequence that were significant for both CSS (P = .020) and PFS2 (P = .001). CSS and PFS2 did not differ between BRCA2 carriers and noncarriers treated with the ASI-taxane sequence (Figs 5A, 5C, 5E). Conversely, BRCA2 carriers treated with the taxane-ASI sequence had significantly worse CSS (median, 28.4 v 10.7 months; P < .001; HR, 4.16; 95% CI, 1.80 to 9.62) and PFS2 (median, 17.1 v 8.6 months; P < .001; HR, 8.16; 95% CI, 3.60 to 18.49) than noncarriers who received the same treatment (Figs 5B, 5D, and 5F). Subsequent Cox regression interaction analysis adjusted for variants that differed between both treatment sequences and other significant prognostic factors (Appendix Table A3) were also significant for both CSS (adjusted P = .015) and PFS2 (adjusted P = .005). BRCA2 was identified as an independent prognostic factor for CSS (HR, 2.95; 95% CI, 1.22 to 7.15) and PFS2 (HR, 5.50; 95% CI, 2.35 to 12.89) in patients treated with the taxane-ASI sequence (Appendix Table A4, online only).
Fig 5. Cause-specific survival (CSS) and progression-free survival (PFS) from initiation of the first survival-prolonging therapy (SPT) to progression to the second SPT (PFS2) in BRCA2 carriers and non–BRCA2 carriers by treatment sequence. Kaplan-Meier curves for CSS: (A) patients treated with an androgen signaling inhibitor (ASI) followed by a taxane; and (B) patients treated with a taxane followed by an ASI. Forest plot of univariable hazard ratios (HRs) for CSS: (C) ASI-taxane sequence; and (D) taxane-ASI sequence. Kaplan-Meier curves for PFS2: (E) ASI-taxane sequence; and (F) taxane-ASI sequence. ALP, alkaline phosphate; ECOG, Eastern Cooperative Oncology Group; LDH, lactate dehydrogenase; M1, metastases; mCRPC, metastatic castration-resistant prostate cancer; PCa, prostate cancer; PSA, prostate-specific antigen.

Discussion

To our knowledge, PROREPAIR-B is the first prospective study designed to assess the prevalence and impact of gDDR mutations in the outcomes of patients with mCRPC. It is also likely the last prospective report on the survival and treatment responses of patients with mCRPC who have gDDR mutations but who have not been exposed to PARPis and platinum-based chemotherapy. Although the primary end point of the study (CSS in ATM/BRCA1/BRCA2/PALB2 carriers v noncarriers) was not met (no significant 10-month difference), we were able to identify gBRCA2 mutations as an independent prognostic factor for CSS in the mCRPC setting. The results also suggest that treatment sequence may be relevant for gBRCA2 carriers.
In PROREPAIR-B, we screened unselected patients with mCRPC and identified 16.2% of them as gDDR carriers—a significantly higher prevalence than that in noncancer populations. Despite the general acceptance of ExAC as a control population, the Spanish population remains underrepresented; therefore, we also used CSVS as a control. Still, both are limited by the inclusion of exome-only data and variant calling. Almost half of the carriers harbored a mutation in any of the 18 genes associated to cancer predisposition syndromes that our panel has in common with the 20 analyzed by Pritchard et al,7 who found a prevalence of 11.7% compared with 7.4% in our series. In the series by Pritchard et al,7 Ashkenazi founder mutations BRCA1 c.5266dupC and BRCA2 c.5946delT accounted for 66% and 24% of the mutations identified in BRCA1 and BRCA2, respectively. Similarly, the Eastern European founder mutation CHEK2 p.1100del represented 50% of all mutations in CHEK2. These three mutations, which accounted for 22% of all mutations,7 are very rare in the Spanish population,29,30 and none of our patients carried them. The prevalence of germline mutations is known to vary among populations because of founder mutation effects and other historical and geographic factors.29 BRCA2 remained the most frequently mutated gene in our population, but it had a lower prevalence (3.3%) than that previously reported (5.3%). The second most commonly mutated gene in our series was MUTYH (3.1%). Monoallelic mutations in MUTYH are present in 1% to 2% of the European population, but the association with prostate cancer predisposition remains unclear.31,32 Prevalence of ATM and PALB2 mutations in our series were 1.9% and 0%, respectively. The first was slightly higher, and the second was slightly lower, than those reported by Pritchard et al,7 but both were similar to the prevalence found in Spanish patients with breast cancer.33,34 No founder/recurrent mutations in ATM or PALB2 have been described in our population to date.
Evidence reported to date about the impact of gDDR aberrations on the outcomes of patients with mCRPC treated with the available SPTs is conflicting. In PROREPAIR-B, we observed interactions suggesting that the impact of gBRCA2 on CSS and PFS2 may be modified by treatment type as well as by treatment sequence. Independent of other factors, BRCA2 carriers have worse outcomes when treated with taxanes as the first SPT but not when they received an ASI as first treatment. These observations may contribute to explain the contradictory results reported to date. Annala et al8 analyzed the retrospective data of 176 patients with mCRPC, including 22 gDDR carriers (BRCA2; n = 16) and found that the PFS of gDDR carriers on firstline ASI was significantly shorter than that of noncarriers (3.3 v 6.2 months; P = .01). Importantly, a higher proportion of gDDR carrier patients (45% v 33% of noncarriers) received a taxane followed by an ASI, a sequence that according to our results could negatively affect BRCA2 carriers but not noncarriers. In addition, the poor PFS could be related to the high tumor burden in the patients included, as reflected by the high levels of circulating tumor DNA reported (> 30%). We also note that great heterogeneity was observed in PFS: some gDDR carriers benefited from ASIs for more than 2 years. We also identified some long-time responses among the gDDR carriers in our series, including three BRCA2 carriers who responded for more than 12 months of response; one benefited from enzalutamide for 32 months. These observations are in line with those of Antonarakis et al,22 who recently reported the outcomes of 172 patients with mCRPC treated with an ASI, including 22 gDDR carriers (BRCA1, n = 1; BRCA2, n = 5; and ATM, n = 3). Only 23% of gDDR carriers and noncarriers received chemotherapy before the ASI. In contrast to Annala et al,8 Antonarakis et al22 reported a trend toward a more prolonged PFS in gDDR carriers (13.3 v 10.3 months; P = .107) and ATM/BRCA1/BRCA2 carriers (15 v 10.8 months; P = .090) compared with noncarriers. Interestingly, they also identified previous chemotherapy as a factor associated with worse PFS and CSS but did not analyze whether this affected carriers and noncarriers similarly. Finally, in a retrospective series with 330 noncarriers and 60 gDDR carriers (BRCA2, n = 37), Mateo et al21 found no association between gDDR carrier status and the response to the first ASI or the first taxane. Overall, 73% and 70% of the patients included received a taxane and ASI, respectively, but the treatment sequence was not specified. No differences were observed in CSS between gDDR carriers and noncarriers, (38.4 v 36.0 carriers; P = .73), not even for the BRCA2 subgroup. However, 47% of gDDR carriers received a PARP inhibitor and/or platinum-based chemotherapy, which may have had a confounding effect on survival.
We acknowledge several limitations to this study. First, the prevalence and distribution of gDDR mutations observed in our series may not be extrapolated to other cohorts because of the variability in the prevalence of germline mutations across populations. Additional screening of large cohorts of patients with different genetic backgrounds is required to establish the true frequency of inherited mutations in DDR genes in mCRPC. Second, the evaluation of patient outcomes according to treatment type and sequence is limited by the lack of randomization inherent to an observational study. Because of the small number of carriers treated with each SPT, outliers may have influenced outcomes. Therefore, findings about the impact of treatment sequence in BRCA2 carriers should be considered only hypothesis generating until validated in larger series. Finally, we did not analyze somatic DDR defects that could be present in a substantial proportion of noncarriers6 and could also affect the grade of DDR impairment in gDDR carriers as consequence of the inactivation of the second allele. Neither have we considered other concurrent genomic events35,36 or histologies (ie, intraductal)37 that have been associated with poor prostate cancer outcomes and that may be enriched in gDDR carrier–related tumors.
In conclusion, this study confirms BRCA2 as the most frequently altered DDR gene in unselected patients with mCRPC, although the prevalence and distribution of mutations in DDR genes may vary across populations. Furthermore, we have prospectively demonstrated that gBRCA2 mutations are an independent prognostic factor for survival in mCRPC. Finally, these results suggest that the outcomes associated with gBRCA2 may be modified by the initial treatment type. This observation is based on a small number of patients and requires additional validation before a change in clinical practice is supported. However, if confirmed, gBRCA2 would be the first genetic biomarker to select an ASI instead of taxanes as the first line of treatment for mCRPC.

Acknowledgment

We thank all of the patients, clinicians, and research assistants involved in the PROREPAIR-B study. We would like to acknowledge the teams at the Spanish National Cancer Center (CNIO) and the Institute of Biomedical Research in Málaga (IBIMA), especially Leticia Rivera and Gala Grau (IBIMA) for their dedication as coordinators of the study-monitoring team and logistics, Antonio López and Berta Nasarre (CNIO) for support in the regulatory process and contracts set-up in all participating centers, María Isabel Pacheco and Teresa Garcés for the technical support and sample handling at CNIO Prostate cancer laboratory, and Alicia Barroso, Mercedes Robledo, and Orlando Dominguez (CNIO) for technical support with MLPA and multicapillary sequencing. We also thank the sequencing facility at Instituto de Genética Médica y Molecular, the genomics core facility at CNIO, and the Clinical Molecular Genetics Laboratory at the University of Washington Medical Center.
A complete list of the PROREPAIR-B investigators is provided in the Appendix.

Authors' Disclosures of Potential Conflicts of Interest

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

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/site/ifc.

Elena Castro

Honoraria: Astellas Pharma, Janssen-Cilag, AstraZeneca, Bayer
Consulting or Advisory Role: Bayer, Janssen, Bayer (I), Janssen (I)
Research Funding: AstraZeneca (Inst), Bayer (Inst), Janssen (Inst)
Travel, Accommodations, Expenses: Bayer, Janssen, Roche, Astellas Pharma

Nuria Romero-Laorden

Honoraria: Bayer, Pfizer, Astellas Pharma, Sanofi, Janssen-Cilag, Roche, PharmaMar
Research Funding: Janssen-Cilag (Inst), Bayer (Inst), Astellas Pharma (Inst), Sanofi (Inst)
Travel, Accommodations, Expenses: Pfizer, Janssen-Cilag, Roche

Rebeca Lozano

Speakers' Bureau: Roche, Janssen-Cilag
Travel, Accommodations, Expenses: Roche, Janssen-Cilag

Ana Medina

Honoraria: Janssen-Cilag, Bristol-Myers Squibb, Merck
Consulting or Advisory Role: Bristol-Myers Squibb
Travel, Accommodations, Expenses: Sanofi, Janssen-Cilag, Bristol-Myers Squibb, Roche
Other Relationship: Novartis

Javier Puente

Consulting or Advisory Role: Pfizer, Astellas Pharma, Janssen-Cilag, Merck Sharp & Dohme, Bayer, Roche, Bristol-Myers Squibb, AstraZeneca, Boehringer Ingelheim, Clovis Oncology, Ipsen, Eisai, EUSA Pharma, Sanofi
Speakers' Bureau: Pierre Fabre, Celgene, Kiowa, Novartis, Lilly
Research Funding: Astellas Pharma, Pfizer
Travel, Accommodations, Expenses: Pfizer, Roche, Janssen-Cilag

Josep Maria Piulats

Consulting or Advisory Role: Janssen Oncology, Astellas Pharma, VCN Biosciences, Clovis Oncology, Roche, Genentech, Bristol-Myers Squibb, Merck Sharp & Dohme
Research Funding: Bristol-Myers Squibb, AstraZeneca, MedImmune, Merck Sharp & Dohme, Pfizer, EMD Serono, Incyte, Janssen Oncology
Travel, Accommodations, Expenses: Janssen Oncology, Roche, Bristol-Myers Squibb

David Lorente

Consulting or Advisory Role: Janssen Oncology, Sanofi, Bayer Health
Speakers' Bureau: Janssen Oncology, Bayer Health, Astellas Pharma, Sanofi
Travel, Accommodations, Expenses: Janssen Oncology, Sanofi, Astellas Pharma, Celgene

Rafael Morales-Barrera

Consulting or Advisory Role: MSD, Sanofi, AstraZeneca
Speakers' Bureau: MSD Oncology, Asofarma
Travel, Accommodations, Expenses: MSD, Sanofi, Astra Zeneca, Astellas, J&J, Bayer

Enrique Gonzalez-Billalabeitia

Travel, Accommodations, Expenses: Bristol-Myers Squibb, Pfizer, Janssen-Cilag, Astellas Pharma, Sanofi

Iciar García-Carbonero

Consulting or Advisory Role: Janssen Oncology, Astellas Pharma, Bayer, Sanofi
Travel, Accommodations, Expenses: Astellas Pharma, Janssen, Sanofi, Bayer

Pablo Borrega

Consulting or Advisory Role: Bayer, Janssen-Cilag, Astellas Pharma

M. José Mendez Vidal

Consulting or Advisory Role: Janssen-Cilag, Pfizer, Astellas Pharma, Sanofi, Bayer, Bristol-Myers Squibb, Novartis, Roche
Travel, Accommodations, Expenses: Janssen-Cilag, Pfizer, Astellas Pharma, Bristol-Myers Squibb

Alvaro Montesa

Consulting or Advisory Role: Pfizer, Janssen-Cilag, Sanofi, Astellas Pharma, Ipsen, Roche, Bristol-Myers Squibb, Takeda
Travel, Accommodations, Expenses: Pfizer

Aránzazu Gonzalez del Alba

Consulting or Advisory Role: Astellas Pharma, Sanofi, Bayer, Janssen Oncology, Pfizer, Bristol-Myers Squibb, Eisai, Pierre Fabre, EUSA Pharma, Roche, Novartis, Ipsen, Astellas Pharma
Travel, Accommodations, Expenses: Astellas Pharma, Pfizer, Janssen Oncology, Sanofi, Bristol-Myers Squibb, MSD Oncology

Alejo Rodriguez-Vida

Honoraria: Astellas Pharma, AstraZeneca, Bayer, Bristol-Myers Squibb, Janssen, MSD, Roche, Pfizer, Sanofi
Consulting or Advisory Role: Astellas Pharma, Bayer, Bristol-Myers Squibb, Janssen, MSD, Roche, Pfizer
Research Funding: Takeda (Inst), MSD (Inst), Pfizer (Inst)
Travel, Accommodations, Expenses: Bristol-Myers Squibb, Bayer, Janssen, Ipsen, Clovis Oncology, Novartis, Astellas Pharma

Begoña Perez-Valderrama

Honoraria: Pierre Fabre, Astellas Pharma, Novartis, Bristol-Myers Squibb, Ipsen
Consulting or Advisory Role: Astellas Pharma, Novartis, Pfizer, Pierre Fabre, Bayer, Sanofi, Bristol-Myers Squibb, Roche, Ipsen
Travel, Accommodations, Expenses: Janssen-Cilag, Bristol-Myers Squibb

Elena Vallespín

Patents, Royalties, Other Intellectual Property: Royalties from KARYOARRAY-8.512.907. FIBHULP. INGEMM
Expert Testimony: Scienceboard.net
Other Relationship: ENAC (Spanish National Accreditation Body)

Enrique Gallardo

Honoraria: Astellas Pharma, Roche, Bristol-Myers Squibb, Novartis
Consulting or Advisory Role: Pfizer, Bayer Schering Pharma, Janssen Oncology, Astellas Pharma, Roche, Bristol-Myers Squibb, Sanofi, Ipsen, Eisai, Rovi, Daiichi Sankyo, EUSA Pharma
Speakers' Bureau: Rovi, LEO Pharma, Menarini, Bristol-Myers Squibb, Ipsen, Astellas Pharma, Roche, Daiichi Sankyo
Travel, Accommodations, Expenses: Pfizer, Astellas Pharma, Pierre Fabre, Bayer Schering Pharma, Bristol-Myers Squibb, Eisai, Janssen, Roche

Sergio Vazquez

Consulting or Advisory Role: Roche Pharma AG, AstraZeneca Spain, Bayer, Pfizer, Novartis, MSD Oncology, Lilly, Bristol-Myers Squibb, Sanofi, Boehringer Ingelheim
Speakers' Bureau: Roche, AstraZeneca Spain, Novartis, Boehringer Ingelheim, Bayer, Bristol-Myers Squibb
Travel, Accommodations, Expenses: AstraZeneca Spain, Roche Pharma AG

Pablo Lapunzina

Consulting or Advisory Role: Roche, Pfizer
Research Funding: Biomarin
Patents, Royalties, Other Intellectual Property: Intellectual property of a microarray design (KaryoArray)

David Olmos

Honoraria: Bayer, Janssen, Sanofi
Consulting or Advisory Role: Janssen, Bayer, AstraZeneca, Clovis Oncology
Research Funding: AstraZeneca (Inst), Bayer (Inst), Janssen (Inst), Genentech (Inst), Roche (Inst), Pfizer (Inst), Astellas Medivation (Inst), Tokai Pharmaceuticals (Inst)
Travel, Accommodations, Expenses: Bayer, Janssen, Ipsen
No other potential conflicts of interest were reported.

Appendix

The following is a full list of the study sites and principal investigators who have participated in the PROREPAIR-B (ClinicalTrials.gov identifier: NCT03075735) study: Hospital Universitario Quirón, Pozuelo de Alarcon, Almagro, Elena; Hospital General Universitario Gregorio Marañón, Madrid, Arranz, José Ángel; Hospital General Universitario Morales Meseguer, Murcia, Gonzalez-Billalabeitia, Enrique; Hospital San Pedro de Alcántara, Cáceres, Borrega, Pablo; Centro Nacional de Investigaciones Oncológicas, Madrid, Castro, Elena; Hospital Universitario Puerta del Mar, Cádiz, Contreras, José Antonio; Fundació Althaia, Manresa, Domenech, Monserrat; Hospital Universitario de Burgos, Burgos, Escribano, Ricardo; Hospital Universitario de Valme, Sevilla, Fernández-Parra, Eva; Parc Taulí Hospital Universitari, Sabadell, Gallardo, Enrique; Hospital Virgen de la Salud, Toledo, García-Carbonero, Iciar; Hospital Clínico Universitario de Salamanca, Salamanca, García, Rocío; Hospital Arnau de Vilanova, Valencia, Garde, Javier; Hospital Universitario Son Espases, Palma de Mallorca, González del Alba, Arantzazu; Hospital de Son Llatzer, Palma de Mallorca, González, Belén; Onkologikoa, Instituto Oncológico de kutxa, Donostia, Hernández, Amaia; Hospital Universitario Fundación Alcorcón, Alrcorcón, Hernando, Susana; Hospital Universitario de Gran Canaria Doctor Negrín, Las Palmas de Gran Canaria, Jiménez, Pedro; Complejo Hospitalario de Navarra, Pamplona, Laínez, Nuria; Hospital Universitario y Politécnico de La Fe, Valencia, Lorente, David; Complejo Hospitalario Universitario de Granada, Granada, Luque, Raquel; Complejo Hospitalario de Jaén, Jaen, Martínez, Esther; Centro Oncológico de Galicia, A Coruña, Medina, Ana; Hospital Universitario Reina Sofía, Córdoba, Méndez-Vidal, María José; Hospital Regional Universitario Carlos Haya, Málaga, Montesa, Alvaro; Hospital Vall d'Hebron, Barcelona, Morales, Rafael; Centro Nacional de Investigaciones Oncológicas, Madrid, Olmos David; Clínica Universitaria de Navarra, Pamplona, Pérez-Gracia, José Luis; Hospital Univesitario Virgen del Rocío, Sevilla, Pérez-Valderrama, Begoña; Hospital Universitario La Paz, Madrid, Pinto, Álvaro; and Institut Catalá d′Oncologia, Hospital Duran i Reynals, Hospitalet de LLobregat, Piulats, Josep. Hospital Clínico Universitario San Carlos, Madrid, Puente, Javier; Hospital de Mataró, Consorci Sanitari del Maresme, Mataró, Querol, Rosa; Hospital del mar, Barcelona, Rodríguez-Vida, Alejo; Hospital Universitario La Princesa, Madrid, Romero-Laorden, Nuria; Hospital Universitario Virgen de la Victoria, Málaga, Saez, Maria Isabel; Hospital Universitario Lucus Augusti, Lugo, Vazquez, Sergio; Hospital San Pedro, Logroño, Vélez, Edelmira; Hospital General Universitario Ciudad Real, Ciudad Real, Villa-Guzmán, José Carlos; Hospital Costa del Sol, Marbella, Villatoro, Rosa; Hospital Universitario Infanta Sofía, San Sebastián de los Reyes, Zambrana, Francisco.
Supplementary Methods
PROREPAIR-B Eligibility Criteria

Inclusion Criteria

1.
Patients must be 18 years or older and provide informed consent.
2.
Histopathology confirmation of prostate cancer diagnosis from diagnostic prostate biopsy, metastasis biopsy, and/or prostatic resection.
3.
Germline mutation carrier status unknown at study entry. Patients should have not undergone genetic testing for DNA damage repair (DDR) genes before they entered the study.
4.
Confirmed serum testosterone levels that corresponded to adequate castration status (< 50 ng/mL) at progression to metastatic castration-resistant prostate cancer (mCRPC).
5.
Patients must meet biochemical and/or radiologic criteria for mCRPC progression (according to the Prostate Cancer Clinical Trials Working Group [PCWG2]), as follows24:
a.
Biochemical progression by prostate-specific antigen (PSA) must be demonstrated with at least three consecutive values that increased greater than the nadir, at least two with a total increase greater than the nadir of more than 2 ng/mL, and a relative increase greater than 50%.
b.
Those patients who have received a classical antiandrogen (bicalutamide, flutamide, nilutamide, or cyproterone acetate) must have a confirming PSA that meets the progression criteria at least 4 weeks after antiandrogen withdrawal.
c.
Those patients who present with new metastases without confirmed PSA progression but with castrate levels of testosterone will be eligible if prostatic origin is demonstrated.
6.
Patients must have bone, visceral, and/or nodal metastasis demonstrated by computed tomography (CT) scan, technetium-99m bone scan, and/or magnetic resonance imaging (MRI) scan. When a patient presents with nodal disease only, at least one node must be located above the bifurcation of iliac arteries and it must be 15 mm or longer in the short axis to be considered metastatic disease.
7.
Eligible patients for this study could meet the criteria for progression to mCRPC (specifically, points 4, 5, and 6 in this list) before consent and initiation of screening as long as the following were met: 6 or fewer months elapsed since mCRPC criteria were met for first time and patients were treatment naïve for mCRPC, with the exception of secondary and/or tertiary hormonal maneuvers. Bisphosphonates or denosumab also were allowed between the diagnosis of mCRPC and study entry. Taxane treatment in a metastatic hormone-sensitive setting was allowed.
8.
Eligible patients must be candidates to start a first-line treatment with an approved survival-prolonging therapy (SPT) for mCRPC (docetaxel, cabazitaxel, enzalutamide, abiraterone, or radium-223 [223Ra]). Treatment should be started within 6 months of study consent.
9.
Eastern Cooperative Oncology Group (ECOG) performance status less than 2 at study entry was required.

Exclusion Criteria

1.
Inadequate documentation of the mCRPC progression criteria and dates of mCRPC diagnosis.
2.
Impossibility to adhere to the study follow -up guidelines for mCRPC or to provide the required essential clinical and/or analytical data for the study.
3.
Prior diagnosis of cancer, except the patients who had the following:
a.
localized malignant tumor treated with radical/curative intention and who have been free of disease for at least 5 years;
b.
diagnosed and treated for a localized skin-cancer (not a melanoma); and
c.
completely resected in situ carcinoma.
4.
Any medical condition which, according to investigator judgment, may interfere with the patient ability to provide informed consent, the adequate recovery of health information, or the execution of the required follow-up evaluations.

Expanded Study Procedures

A baseline imaging evaluation within 6 weeks of study entry (CT/MRI and bone scans) and a complete full blood count and biochemistry, including PSA and testosterone within 2 weeks of study entry, were required. Prognostic data at the time of mCRPC and prior treatment history were also recorded at enrollment. All treatments were by physician choice and were not dictated by the study, but clinical, radiologic, and analytic baseline assessments were mandatory before each treatment line with an SPT was started. A 5-mL blood sample was drawn at study entry for germline DNA extraction.
The start and end dates as well as the doses of each SPT administered were recorded. Patients on active treatment were prospectively observed with regular clinical and PSA evaluations every 3 to 4 weeks and CT/MRI and bone scans every 12 to 16 weeks. Responses and progression were evaluated according to PCWG2.24 Clinical progression was defined by protocol; nonetheless, the final decision to discontinue a treatment and/or to start a new line rested with the treating physician. Patients who permanently discontinued all active treatments were observed for survival at least every 12 weeks until death.

Clinical Progression Criteria

1.
ECOG deterioration by two or more points from treatment baseline because of worsening prostate cancer–related symptoms.
2.
Worsening prostate cancer–related pain, except for bone pain flare related to treatment initiation (first 12 weeks) or transitory223 Ra-related pain after treatment dosing, that meet one of the following:
a.
New pain not controlled with nonsteroidal anti-inflammatory drugs and that requires initiation of opioids (minor/major) for longer than a week;
b.
Previously existing pain that increases in grade for longer than a week and requires increased analgesia to major opioids or to duplicate the dose of major opioids;
c.
Bone pain that requires palliative external irradiation.
3.
Pathologic fracture related to prostate cancer and not attributable to osteoporosis.
4.
Cord compression because of prostate cancer.
5.
Initiation of a new treatment line because of new or worsening prostate cancer–related symptoms.
6.
Any sign or symptom in the patient’s evolution that, according to the judgment of the treating physician, represents an unequivocal sign of clinical progression after treatment.
7.
Death as a result of prostate cancer or attributable to prostate cancer.

Sample collection.

A mandatory 5-mL whole-blood sample was collected in EDTA in all patients to obtain germline DNA. Optional blood samples for plasma and whole-blood RNA isolation were collected in 9-mL Streck (STRECK, Omaha, NE) and 2.5-mL PAXgene (PreAnalytix GmbH, Hombrechtikon, Switzerland) tubes, respectively, at multiple time points, which included the following: baseline for each treatment line, after 8 to 12 weeks of treatment, and at progression for each treatment line. Archived tumor samples were also collected.

DNA extraction and sequencing.

Germline DNA was extracted from EDTA tubes using the Flexigene DNA kit (QIAGEN, Germantown, MD) and the QiaCube platform (Qiagen Crawley, United Kingdom). Quantification of DNA was performed using a Qubit 2.0 fluorometer (Life Technologies, Frederick, MD). Sequencing libraries were generated from 250 ng of germline DNA using the custom panel with NimbleGen SeqCap XL target enrichment (Roche, Pleasanton, CA) and read using an Illumina NexSeq 500 platform (Illumina, San Diego, CA). On average, 2 to 3 million 100-bp reads, with a mean coverage of greater than ×150 for each sample, were obtained. All variants identified as pathogenic and likely pathogenic were validated using multicapillary electrophoresis ABI 3730xls (SegGen, Torance, GA), polymerase chain reaction, or MLPA, as appropriate. An independent validation of some rare variants that involve exon deletions was conducted at the University of Washington using the BROCA panel.

Sequencing data pre-processing and data quality control.

First data analysis consisted in transformation of the bcl files from the NextSeq 500 sequencer to fastq files by using the Illumina des-multiplexing tool, bcl2fastq (Illumina, San Diego, CA). Then, the sequences were mapped to the Universiy of California Santa Cruz human reference genome hg19 (version February 2009) with Bowtie2 (Langmead B, et al: Nat Methods 9:357-359, 2012). Duplicate reads were removed using the Picard RemoveDuplicated function (http://broadinstitute.github.io/picard/). Indel realignment and base quality score recalibration were performed afterward (with RealignerTargetCreator and IndelRealigner functions from the suite Genome Analysis Toolkit [GATK]) following the best practices proposed by GATK (McKenna A, et al: Genome Res 20:1297-1303, 2010; DePristo MA, et al: Nat Genet 43:491-498, 2011; Van der Auwera GA, et al: Curr Protoc Bioinformatics 43:1110-1133, 2013). Variant calling was performed over the re-aligned and re-calibrated BAM files. The characterized variants were the result of an in-house consensus between the outputs of the GATK variant callers UnifiedGenotyper and HaplotypeCaller. The condensed vcf files were filtered and annotated with Annovar.25 In addition, the vcf files were enriched with prediction tools of pathogenicity provided by the proxy dbNSFP (release 3.0; Liu X, et al: Hum Mutat 37:235-241, 2016) together with population data [Exac Non-Finnish European data27 and CIBERER Spanish Variant Server (http://csvs.babelomics.org/)], and clinical and genomic information from matched Clinvar (Landrum MJ, et al: Nucleic Acids Res 44:D862-D868, 2016) records.
In parallel to the analysis process, an exhaustive quality control of the sequenced samples was performed. In addition, the samples were crossed out to determine relationships among them. No family relationships were identified, and a sample duplication was detected. The quality of the sequencing procedure was assessed by a range of markers, such as the percentage of mapped reads, the percentage of mapped reads in the region of interest (ROI), the percentage of duplicated reads and the percentage of ROI over a depth of ×20 (ie, horizontal coverage). In addition, the final efficiency of each sample was measured by the ratio of sequences that were eligible for variant determination and the initial number of mapped reads.

Variants classification and review panel.

Germline variants with a minor allele frequency of 0.5% or higher in the Exome Aggregation Consortium (ExAC) database (release 0.3) were discarded.27 From the remaining variants, those classified in ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/; Landrum MJ, et al: Nucleic Acids Res 44:D862-D868, 2016) as pathogenic/likely pathogenic were confirmed and classified as such. The remaining variants were filtered according to ANNOVAR and ClinVar annotations. Those not previously reported, or reported as variants of unknown significance, were review independently by three investigators with training in cancer genetics (E.C., N.R.L., R.L.) blinded to patient outcomes and according to the guidelines of the American College of Medical Genetics and Genomics.26 Then each potentially pathogenic variant according to Clinvar or American College of Medical Genetics and Genomics criteria was discussed and classified by the following study panel: Elena Castro, Medical Oncologist, Cancer Genetics; Nuria Romero-Laorden, Medical Oncologist, Cancer Genetics; Rebeca Lozano, Medical Oncologist, Cancer Genetics; Angela del Pozo, Bioinformaticist; Pablo Lapunzina, Medical Geneticist; Colin C. Pritchard, Molecular Pathologist, Cancer Genetics; and David Olmos, Medical Oncologist, Genomics.

Definition of positive family history of cancer.

Prior family history of cancer was collected on at least three generations for each person in the study. A positive family history of cancer was defined as the occurrence of prostate, breast, ovarian, or other tumor types (excluding nonmelanoma skin tumors) in first- or second-degree relatives.

Frequency of pathogenic variants in ExAC and CSVS populations.

ExAC noncancer data (n = 53,105) and CIBERER Spanish Variant Server (CSVS; http://csvs.babelomics.org/; n = 1,551) populations were filtered and reviewed using the same criteria by four reviewers.

Time-to-event end points definition.

Cause-specific survival (CSS) was prospectively defined and measured. CSS from mCRPC was calculated from the confirmation date of mCRPC (biochemical and/or radiologic progression to mCRPC) or treatment starting date to the date of death. Progression to castration resistance and diagnosis of metastasis for first time may not happen at the same time, so the date of mCRPC diagnosis was the date in which both events were present: progression to castration resistance (biochemical and/or radiologic) and evidence of metastasis in CT/MRI or bone scan.
CSS from any specific treatment line was calculated from treatment starting date (first dose) to the date of death. A death was considered related to prostate cancer if the main cause of death was prostate cancer, complications secondary to the prostate cancer spread, or any complication directly related to the treatment of prostate cancer. When the cause of death was unrelated to prostate cancer, the patient data were censored at the time of death for any CSS analysis.
Those patients who remained alive at the time of database cutoff for this analysis were censored at the last follow-up. Similarly, patients lost to follow-up but who were alive at the last evaluation were censored at the time of the last evaluation.
Time to PSA progression (TTPP) was prospectively defined and measured. TTPP was defined as the time elapsed from initiation of treatment to PSA progression. According to PCWG2 criteria, PSA progression was considered the date that an increase of 25% or more and absolute increase of 2 ng/mL or more from the nadir were documented. For patients who had an initial PSA decline during treatment, this had to be confirmed by a second value more than 3 weeks later.
TTPA was censored at the time of the last regular PSA evaluation in those patients without biochemical progression at the end of the monitoring, at the start of a new line of treatment, and/or at death. Patients with a PSA less than 2 ng/mL at the starting date of any treatment line were not eligible for TTPP.
Progression-free survival (PFS) was prospectively defined and measured. PFS was defined as the time from initiation of treatment to disease progression in bone or soft tissue according to radiographic criteria (PCWG2 and RECIST 1.1) or by symptoms according to clinical criteria (defined by protocol, including death), whichever occurred first.

Additional statistical methods.

All continuous variables were transformed into binomial variables according to standard reference or median values. Patient characteristics were compared between noncarriers and carriers for the pre-planned subgroups (ATM/BRCA1/BRCA2/PALB2; BRCA2; and all gDDR carriers. The association of mutation status with baseline characteristics and family cancer history as well as the comparison of the prevalence of mutations between our patients and the general population were tested using the χ2, Fisher’s exact, or Mann-Whitney U test, as appropriate.
Fig A1. Mutation lolliplot that shows the distribution of the presumed pathogenic mutations identified. BHD, β-hairpin domain; DEAD-2, a conserved and ubiquitous domain within a number of RAD3-like DNA-binding helicases; DRMBL, DNA repair metallo-beta-lactamase domain; FAT, FRAP-ATM- TRRAP domain; FATC, FAT-C-terminal domain; FHA, forkhead-associated domain; HMG, high mobility group; MutS, MutS domain; NUDIX, NUDIX domain; res, restriction enzyme, res subunit; TAN, Tel1/ATM N-terminal motif; WD40, WD domain, G-beta repeat; WGR, WGR domain.
Fig A2. Family history of cancer in first- and second-degree relatives in the carriers and noncarriers groups: (A) all tumors; (B) patients with family history of breast and ovarian cancer; and (C) patients with family history of prostate cancer. (*) ATM, ATR, BAP1, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, FAM175A, GEN1, MLH1, MRE11A, MSH2, MSH6, NBN, PALB2, PMS2, RAD51C, RAD51D, XRCC2. BROCA, University of Washington Laboratory of Medicine panel; DDR, DNA damage repair.
Fig A3. Kaplan-Meier analysis for cause-specific survival (CSS) and interaction between BRCA2 carrier status and treatment type administered as second-line survival-prolonging therapy (SPT). ASI, androgen signaling inhibitor; mCRPC, metastatic castration-resistant prostate cancer.
Table A1. List of Pathogenic/Likely Pathogenic Mutations Identified in the Study
Table A2. Prevalence of Pathogenic Variants in PROREPAIR-B, ExAC, and CSVS
Table A3. Post Hoc Analyses According to Treatment Sequence: Included Patient Baseline Characteristics
Table A4. Post Hoc Analyses According to Treatment Sequence: MVA Models for Each Treatment Sequence

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Information & Authors

Information

Published In

Journal of Clinical Oncology
Pages: 490 - 503
PubMed: 30625039

History

Published online: January 09, 2019
Published in print: February 20, 2019

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Authors

Affiliations

Elena Castro, MD, PhD
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
Hospital Universitario Quiron, Madrid, Spain
Nuria Romero-Laorden, MD, PhD
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
Hospital Universitario La Princesa, Madrid, Spain
Angela del Pozo, PhD
Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, and CIBERER Instituto de Salud Carlos III, Madrid, Spain
Rebeca Lozano, MD
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
CNIO_IBIMA Genitourinary Cancer Research Unit, Institute of Biomedical Research in Málaga, Málaga Spain
Ana Medina, MD
Centro Oncológico de Galicia, Coruña, Spain
Javier Puente, MD, PhD
Hospital Clínico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain
Josep Maria Piulats, MD, PhD
Institut Català d’Oncologia, Bellvitge Biomedical Research Institute, Barcelona, Spain
David Lorente, MD
Hospital Universitario La Fe, Valencia, Spain
Maria Isabel Saez, MD
CNIO_IBIMA Genitourinary Cancer Research Unit, Institute of Biomedical Research in Málaga, Málaga Spain
Hospitales Universitarios Virgen de la Victoria y Regional de Málaga, Málaga, Spain
Rafael Morales-Barrera, MD
Vall d’Hebron Institute of Oncology, Vall d’Hebron University Hospital, Universitat Autònoma de Barcelona, Barcelona, Spain
Enrique Gonzalez-Billalabeitia, MD, PhD
Hospital Morales Messeguer–IMIB, UCAM, Murcia, Spain
Ylenia Cendón, MSc
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
Universidad Autónoma de Madrid, Madrid, Spain
Iciar García-Carbonero, MD
Hospital Virgen de la Salud, Toledo, Spain
Pablo Borrega, MD
Hospital San Pedro de Alcántara, Cáceres, Spain
M. José Mendez Vidal, MD
Hospital Universitario Reina Sofia, Córdoba, Spain
Alvaro Montesa, MD
CNIO_IBIMA Genitourinary Cancer Research Unit, Institute of Biomedical Research in Málaga, Málaga Spain
Hospitales Universitarios Virgen de la Victoria y Regional de Málaga, Málaga, Spain
Paz Nombela, MSc
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
Eva Fernández-Parra, MD
Hospital Universitario de Valme, Seville, Spain
Aránzazu Gonzalez del Alba, MD
Hospital Universitario Son Espases, Palma de Mallorca, Spain
José Carlos Villa-Guzmán, MD
Hospital General Universitario de Ciudad Real, Ciudad Real, Spain
Kristina Ibáñez, PhD
Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, and CIBERER Instituto de Salud Carlos III, Madrid, Spain
Alejo Rodriguez-Vida, MD, PhD
Hospital del Mar, Barcelona, Spain
Lorena Magraner-Pardo, MSc
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
Begoña Perez-Valderrama, MD
Hospital Universitario Virgen del Rocío, Seville, Spain
Elena Vallespín, PhD
Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, and CIBERER Instituto de Salud Carlos III, Madrid, Spain
Enrique Gallardo, MD
Parc Taulí Hospital Universitari, Institut d’Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain.
Sergio Vazquez, MD
Hospital Universitario Lucus Augusti, Lugo, Spain
Colin C. Pritchard, MD, PhD
University of Washington Medical Center, Seattle, WA
Pablo Lapunzina, MD, PhD
Institute of Medical and Molecular Genetics, Hospital Universitario La Paz, and CIBERER Instituto de Salud Carlos III, Madrid, Spain
David Olmos, MD, PhD [email protected]
Prostate Cancer Clinical Unit, Spanish National Cancer Research Center, Madrid, Spain
CNIO_IBIMA Genitourinary Cancer Research Unit, Institute of Biomedical Research in Málaga, Málaga Spain

Notes

David Olmos, MD, PhD, Spanish National Cancer Research Center, 3, Melchor Fernández Almagro, 28029 Madrid, Spain; e-mail: [email protected].
E.C. and N.R.-L. contributed equally to this work.

Author Contributions

Conception and design: Elena Castro, Nuria Romero-Laorden, Angela del Pozo, Elena Vallespín, Pablo Lapunzina, David Olmos
Collection and assembly of data: Elena Castro, Nuria Romero-Laorden, Rebeca Lozano, Ana Medina, Javier Puente, Josep Maria Piulats, David Lorente, Maria Isabel Saez, Rafael Morales-Barrera, Enrique Gonzalez-Billalabeitia, Ylenia Cendón, Iciar García-Carbonero, Pablo Borrega, M. José Méndez Vidal, Alvaro Montesa, Eva Fernández-Parra, Aránzazu González del Alba, José Carlos Villa-Guzmán, Aljo Rodriguez-Vida, Lorena Magraner-Pardo, Begoña Perez-Valderrama, Enrique Gallardo, Sergio Vazquez, Pablo Lapunzina, David Olmos
Provision of study material or patients: All authors
Data analysis and interpretation: Elena Castro, Nuria Romero-Laorden, Angela del Pozo, Rebeca Lozano, David Lorente, Enrique González-Billalabeitia, Ylenia Cendón, Paz Nombela, Kristina Ibañez, Lorena Magraner-Pardo, Colin C. Pritchard, David Olmos
Administrative support: Elena Castro, Nuria Romero-Laorden, Rebeca Lozano, David Olmos
Financial support: Elena Castro, Pablo Lapunzina, David Olmos
Manuscript writing: All authors
Final approval of manuscript: All authors
Accountable for all aspects of the work: All authors

Funding Information

Supported by an unrestricted grant from Fundación Cris contra el cancer; three investigator awards from the Prostate Cancer Foundation (C.C.P. [2013], D.O. [2014], and E.C. [2017]); and three grants from Fondo de Investigación Sanitaria, Instituto de Salud Carlos III (No. PI13/01287 and PI16/01565 to D.O. and No. PI15/01471 to P.L.). During the conduct of this study, E.C., D.O., P.N., and L.M.-P. were supported by grants from Ministerio de Economía, Industria y Competitividad (No. JCI-2014-19129 [E.C.], No. RYC-2015-18625 [D.O.], No. SVP-2013-067937 [P.N.], No. SVP-2014-068895 [L.M.]); D.O. was also funded by a Return fellowship from Fundación Científica de la Asociación Española Contra el Cancer, 2012-2015; N.R.L. and R.L., by grants from Instituto de Salud Carlos III (No. CM14-00200 to N.R.L. and No. CM17-00221 [R.L.]); and Y.C., by a grant from Ministerio de Educación, Cultura y Deportes (No. FPU15/05126). C.C.P. was supported by a congressional-designated medical research program award (No. CMRP-PC131820).

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Elena Castro, Nuria Romero-Laorden, Angela del Pozo, Rebeca Lozano, Ana Medina, Javier Puente, Josep Maria Piulats, David Lorente, Maria Isabel Saez, Rafael Morales-Barrera, Enrique Gonzalez-Billalabeitia, Ylenia Cendón, Iciar García-Carbonero, Pablo Borrega, M. José Mendez Vidal, Alvaro Montesa, Paz Nombela, Eva Fernández-Parra, Aránzazu Gonzalez del Alba, José Carlos Villa-Guzmán, Kristina Ibáñez, Alejo Rodriguez-Vida, Lorena Magraner-Pardo, Begoña Perez-Valderrama, Elena Vallespín, Enrique Gallardo, Sergio Vazquez, Colin C. Pritchard, Pablo Lapunzina, David Olmos
Journal of Clinical Oncology 2019 37:6, 490-503

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