SPOP Mutations as a Predictive Biomarker for Androgen Receptor Axis–Targeted Therapy in De Novo Metastatic Castration-Sensitive Prostate Cancer

Over the past 7 years, the therapeutic landscape for advanced prostate cancer has expanded significantly with the introduction of several novel agents and moving of agents typically given in the castration-resistant stage to earlier settings due to significant improvements in survival (1–5). Multiple phase III randomized trials have established the benefit of intensification of androgen deprivation therapy (ADT) with the addition of docetaxel or androgen receptor axis–targeted therapies (ARAT) such as abiraterone, enzalutamide, and apalutamide in improving survival outcomes for patients with metastatic castration-sensitive prostate cancer (mCSPC), and are now the new standard of care (1–7). However, we currently lack biomarkers to identify which patients benefit most from ADT intensification with ARAT or docetaxel.

A lack of prospective clinical trials in prostate cancer focusing on pathogenic alterations other than those belonging to the homologous recombination repair pathway has been recognized as a knowledge gap (8). While prostate cancer is generally viewed as a disease driven by androgen receptor (AR) signaling, multiple reports have identified several unique molecular subtypes (9). One of these subgroups is characterized by recurrent inactivating point mutations in the SPOP gene (9–12). SPOP, “speckle type BTB/POZ protein,” is an adaptor protein of the CUL3-RBX1 E3 ubiquitin ligase complex involved in the binding of multiple oncogenic proteins for ubiquitination and subsequent proteasomal degradation (13). Several studies indicate that loss-of-function SPOP mutations are an early event associated with prostate tumorigenesis, resulting in stabilized AR protein and increased AR signaling. Prior reports suggest that SPOP mutation may be associated with improved survival outcomes in patients with mCSPC treated with ADT, or metastatic castration-resistant prostate cancer treated with an ARAT (14–16). However, the predictive potential of SPOP mutations has not been studied, nor has its ability to influence taxane therapy benefit.

Because of greater dependency of SPOP-altered prostate cancer on androgen signaling, we hypothesized that ADT intensification with ARAT, but not with docetaxel, will be associated with improved outcomes in patients with de novo (dn)-mCSPC harboring SPOP mutations.

The study cohort comprised patients with a confirmed diagnosis of de novo mCSPC included in the U.S.-wide Flatiron Health (FH)-Foundation Medicine (FMI) deidentified mCSPC clinico-genomic database (CGDB) between January 2011 and December 2021 who underwent genomic testing using Foundation Medicine comprehensive genomic profiling (CGP) assays.

The deidentified data originated from approximately 280 U.S. cancer clinics (∼800 sites of care). Retrospective longitudinal clinical data were derived from electronic health record (EHR) data, comprising patient-level structured and unstructured data, curated via technology-enabled abstraction of clinical notes and radiology/pathology reports and were linked to CGP data by deidentified, deterministic matching (17). FH database mortality information is a composite derived from three sources: documents within the EHR, Social Security Death Index, and a commercial death dataset mining data from obituaries and funeral homes. This mortality information has been externally validated in comparison to the National Death Index with greater than 90% accuracy (18). The CGDB has previously supported replications of biomarker associations with survival observed in clinical trials (17, 19, 20). Abstracted clinical data included demographics, clinical features, therapy exposure (with start and stop dates for each therapy line), and survival.

Patient inclusion criteria were as follows: diagnosis of metastatic disease within 30 days of original prostate cancer diagnosis (to ensure de novo metastatic diagnosis), tissue biopsy collected within 90 days of original diagnosis to better reflect phenotype/genotype characteristics at the time of treatment decisions, and start of ARAT or docetaxel therapy within 120 days of initial diagnosis to improve homogeneity of the population (Fig. 1A and B for flowchart).

The FoundationOne or FoundationOneCDx hybrid capture-based next-generation sequencing assays were performed on tumor biopsies in a Clinical Laboratory Improvement Amendments–certified, College of American Pathologists–accredited laboratory (Foundation Medicine). Samples were evaluated for alterations as described previously (21). SPOP mutations were included if characterized as known pathogenic by existing literature, reflecting the documented hotspot alterations (missense changes, small in-frame insertions/deletions) within the MATH domain (amino acids 38–163). Patient specimens not containing a known pathogenic SPOP mutation are referred to as “SPOP wild-type.”

For larger genomic database analyses in supplementary, tissue biopsies from prostate acinar adenocarcinoma were profiled using FoundationOne (N = 4,200) and FoundationeOneCDx (N = 13,550), and liquid biopsies from patients with prostate cancer were profiled using FoundationOneLiquid CDx (N = 5,629). Approval for this study, including a waiver of informed consent and a Health Insurance Portability and Accountability Act waiver of authorization, was obtained from the WIRB-Copernicus Group Institutional Review Board (protocol no. 20152817).

A prespecified statistical analysis plan (SAP) was developed. Consistent with ISPOR guidelines (22), inclusion and exclusion criteria, potential biases, primary outcome measures, exploratory outcome measures, handling of missing data, and all methods described below were defined prior to analysis execution unless noted. The prespecified primary outcome analysis compared the effectiveness of ARAT, and separately docetaxel, in patients with dn-mCSPC with either mutated SPOP (mutSPOP) or wild-type SPOP (wtSPOP), evaluating both time to castration-resistant prostate cancer (TTCRPC) and overall survival (OS) in concert. Exploratory outcomes included effectiveness of ARAT, and separately docetaxel, in patients with dn-mCSPC harboring TMPRSS2-ERG gene fusions; as well as a comparison of ARAT versus docetaxel subgroup analyses adjusted for baseline prognostic features.

χ² tests and Wilcoxon rank-sum tests were used to assess differences between cohorts of categorical and continuous variables, respectively. Missing values were imputed with the expected values based upon observed covariates using random forests with R package “missForest,” with imputed values treated identically to measured values in subsequent analysis. TTCRPC was calculated from dates of metastatic diagnosis to castration resistance, as assessed by the clinician, or last clinic visit if not yet castration resistant. Patients were right censored if not yet reached CRPC. OS was calculated from metastatic diagnosis to death from any cause, and patients with no record of mortality were right censored at the date of the last clinic visit. Because patients cannot enter the database until a CGP report is delivered, OS risk intervals were left truncated (delayed entry) to the date of the CGP report to account for immortal time (23, 24).

Differences in time-to-event outcomes were assessed with the log-rank test and Cox proportional hazards (PH) models. Multiple comparison adjustments were not performed; P values are reported to quantify the strength of association between biomarker and each respective outcome, not for null hypothesis significance testing. Results were interpreted considering outcome measures collectively (TTCRPC, OS) rather than outcome measures standing on their own.

Biomarker treatment interaction tests (P_interaction; ref. 25) made use of multivariable Cox PH regression models containing the following variables: drug class (ARAT or docetaxel), biomarker (mutSPOP vs. wtSPOP), and the interaction term between drug class and biomarker, adjusted for risk of CRPC or death.

Pretherapy prognostic features [Eastern Cooperative Oncology Group (ECOG) score, Gleason score, PSA, age, alkaline phosphatase, albumin, hemoglobin] associated with risk of CRPC or OS were combined into multivariable models (Supplementary Table S1) and resulting sum of coefficients used as a risk score for adjustment in all Cox PH models, as described previously (26, 27). Risk adjustment was not declared in SAP.

R version 3.6.3 software was used for all statistical analyses.

The data supporting the findings of this study originated from Flatiron Health, Inc. and Foundation Medicine, Inc. These deidentified data may be made available upon request, and are subject to a license agreement with FH and FMI; interested researchers should contact <[email protected]> and <[email protected]> to determine licensing terms.

Of 4,417 profiled prostate cancer tissue specimens available, 1,497 were obtained within 90 days of original prostate cancer diagnosis, and were thus considered to reflect hormone-sensitive specimens (Fig. 1A). mutSPOP was detected in 152/1,497 (10.2% prevalence; Supplementary Table S2). Of these, 447 unique patients met the eligibility criteria additionally inclusive of metastatic disease diagnosed within 30 days of original diagnosis, and ARAT or docetaxel treatment beginning within 120 days of original diagnosis (Fig. 1A and B), treated with either ARAT (n = 223) or docetaxel (n = 214). mutSPOP was detected in 20/223 (8.6%) and 18/214 (8.4%) patients in the ARAT and docetaxel cohorts, respectively (Fig. 1A; Table 1). Mutations clustered in the MATH domain, with hotspots at residues F102, F133, and W131 (Fig. 2A). Compared with wtSPOP samples, SPOP-mutant samples were mutually exclusive with those harboring TMPRSS2-ERG fusions, were enriched for coalterations in Wnt pathway genes (particularly APC), and were depleted for concurrent alterations in TP53, PTEN, and RB1 (Fig. 2B). As a supplementary analysis, we sought to determine whether similar frequencies of specific MATH domain alterations detected between liquid biopsy and tissue profiling assays were similar. To do this, we made use of the broader Foundation Medicine database (see Materials and Methods) without clinical or outcome associations. Evaluating 17,750 tissue specimens and 5,629 liquid biopsy specimens, the most common hotspots in descending order for tissue profiling and liquid profiling were both F133, F102, and W131 (Supplementary Fig. S1), also mirroring the outcome analysis cohort.

Baseline characteristics of both treatment cohorts (ADT plus ARAT, and ADT plus docetaxel) are presented in Table 1. Patients from both cohorts had a similar ECOG, Gleason score, and PSA at metastatic diagnosis. The subgroup of mutSPOP only had similar clinical associations (Supplementary Table S3). It is important to note that docetaxel was approved prior to ARAT in the mCSPC space, with use by year reflected in Table 1, resulting in longer follow-up for the docetaxel cohort. At the time of data analysis, 46.4% of patients in the ARAT and 74.8% patients in the docetaxel cohort had progressed to the castration-resistant stage. In addition, 70.0% and 47.2% patients were alive in the ARAT and docetaxel cohorts, respectively. In the ARAT cohort, abiraterone (61.4%) was the most frequently used intensification agent followed by enzalutamide (30.5%).

Baseline characteristics of patients with mutSPOP and wtSPOP are presented in Supplementary Table S4. Patients with mutSPOP had a significantly higher median PSA than patients with wtSPOP (232.5 vs. 134.5 ng/mL; P = 0.033). Otherwise, no significant differences were observed with regards to year of treatment initiation, age, ECOG, Gleason sum, alkaline phosphatase, or hemoglobin between both groups.

mutSPOP in the ARAT cohort was associated with significantly better TTCRPC compared with wtSPOP [median not reached (NR) vs. 16.7 months, adjusted HR 0.20; 95% confidence interval (CI), 0.06–0.63; P = 0.006; Fig. 3A]. In contrast, more favorable TTCRPC was not observed for patients with mutSPOP versus wtSPOP in the docetaxel cohort [median 18.5 vs. 15.7 months, adjusted HR 0.86 (95% CI, 0.46–1.58; P = 0.62); Fig. 3B].

Similarly, patients with mutSPOP in the ARAT cohort had significantly better OS compared with wtSPOP, [median NR vs. 27.2 months, adjusted HR 0.19 (95% CI, 0.05–0.79; P = 0.022); Fig. 3C]. Again, in the docetaxel cohort, OS was similar between patients with either mutSPOP or wtSPOP [median 30.4 vs. 32.3 months, adjusted HR 1.18 (95% CI, 0.57–2.44; P = 0.66); Fig. 3D].

Treatment interactions were observed between SPOP mutation status (mutant vs. wild-type) and treatment type (ARAT vs. docetaxel) for both TTCRPC (P_interaction = 0.0181) and OS (P_interaction = 0.0279; Fig. 4A and B; Supplementary Table S5). Evaluating subgroups of the cohort, patients with mutSPOP had enrichments for outcomes favoring ARAT versus docetaxel for both TTCRPC and OS (Fig. 4A and B).

TMPRSS2-ERG gene fusions characterize a separate subtype of prostate cancer and are detected in approximately 30%–50% of patients (9). Because TMPRSS2-ERG fusions are generally mutually exclusive with mutSPOP (9, 11, 28) as observed in this study too (Fig. 2B), we conducted an exploratory analysis in ARAT and docetaxel cohorts as a separate control biomarker. TMPRSS2-ERG fusions were associated with more favorable TTCRPC on ARAT (adjusted HR 0.55; 95% CI, 0.34–0.87; P = 0.011) as well as docetaxel (adjusted HR 0.60; 95% CI, 0.42–0.84; P = 0.003) compared with the absence of such a fusion (Supplementary Fig. S2A and S2B). Directionally consistent but weaker associations were seen with OS (Supplementary Fig. S2C and S2D). In contrast to SPOP, tests for treatment interactions with TMPRSS2-ERG status were not significant.

Our results suggest that mutSPOP is associated with enriched benefit from ARAT but not docetaxel in the castration-sensitive setting. These results are consistent with our hypothesis, and indicate that SPOP mutations may be the first predictive biomarker for prolonged benefit with ARAT (relative to docetaxel) in patients with dn-mCSPC.

We also observed a statistically significant higher baseline PSA in patients with mutSPOP as compared with patients with wtSPOP. In a prior study evaluating 8,559 patients undergoing radical prostatectomy, mutSPOP was associated with a significantly higher preoperative PSA. This finding was observed consistently across multiple cohorts (29). In normal cells, AR and its coactivators BRD4 and TRIM24 are targeted by SPOP for ubiquitination and proteasomal degradation. In contrast, levels of AR protein and its coactivators increase in prostate cancer cells harboring loss-of-function SPOP mutations due to enhanced protein stability (30, 31). In addition, tumors harboring SPOP and FOXA1 mutations have the highest levels of AR-induced transcripts among various molecularly distinct prostate cancer subtypes (9, 10). SPOP mutations have also been reported to result in increased degradation of 17βHSD4, an essential enzyme in steroid metabolism, resulting in increased testosterone/dihydrotesterone production (32). Taken together, these results further emphasize the increased addiction to AR signaling by prostate cancers harboring pathogenic mutations in the SPOP gene. Therefore, it is perhaps not surprising that deeper blockade of AR signaling by the combination of ADT and ARAT is significantly more effective in patients with mutSPOP-positive dn-mCSPC.

We did not observe differential benefit for mutSPOP-positive patients treated with docetaxel compared with wtSPOP. It is possible this may be due to upregulation of stress granules assembly. Stress granule assembly is a survival mechanism employed by cells under stress, and is upregulated in cancer cells. Caprin1 plays a nucleating role in stress granule assembly and is a target for wtSPOP-mediated ubiquitination and degradation. Prostate cancer cell lines harboring mutSPOP exhibit Caprin1 upregulation, increased stress granule assembly and were associated with increased resistance to docetaxel in one study (33). Alternatively, mutSPOP was recently reported to cause aberrant upregulation of global DNA methylation in cell lines and primary prostate cancer specimens (34). Accordingly, whole methylome analysis revealed hypermethylation and silencing of several tumor suppressor genes such as FOXO3, which may lead to decreased efficacy of docetaxel.

While there are no predictive biomarkers approved to guide treatment selection for patients with mCSPC, our findings indicate that patients with dn-mCSPC harboring mutSPOP will likely derive greater benefit from ARAT and not chemotherapy with docetaxel. Furthermore, there is an urgent need to validate these results in larger databases or completed randomized phase III trials to accelerate translation of mutSPOP as a predictive biomarker in this clinical setting.

The limitations of our study include a nonrandomized retrospective analysis. While biases were considered and known imbalances adjusted, unknown imbalances such as access to subsequent therapies and neuroendocrine differentiation likely remain. Quantified disease burden was not available for adjustment, and while PSA level and ECOG were included in adjustments, along with other factors associating with disease burden and severity, these are incomplete proxies for disease severity and burden. Disease volume has been evaluated as a potential biomarker for docetaxel efficacy: prespecified subgroup analyses of the CHAARTED study reported lack of observed benefit from docetaxel in patients with low volume disease (35). However, a subsequent retrospective analysis of the STAMPEDE trial showed no evidence that docetaxel benefit differed on the basis of metastatic burden (36). It is possible that some patients in the docetaxel cohort in our study had low volume disease and therefore may have derived diminished benefit. On the contrary, it is also possible that patients receiving docetaxel in routine practice settings might be more likely to have aggressive disease at presentation, which might have led to poorer outcomes in the docetaxel cohort. In this context, evaluating docetaxel only cohort for TTCRPC and OS based on SPOP status (Fig. 3,B and D) and ARAT versus docetaxel subgroup analyses after adjusting for available prognostic variables such as ECOG, Gleason score, PSA, age, alkaline phosphatase, albumin, and hemoglobin may mitigate disease severity and burden as a confounder. Co-occurring alterations such as Wnt pathway alterations, TP53, PTEN, and RB1 may also affect treatment responses, and our study did not have the power to examine clinical outcomes according to these coalterations (28). An alternate hypothesis is that CHD1 deletion, which is not assessed by the assays utilized but is highly correlated with SPOP mutations, is the more proximal cause for the increased sensitivity to hormonal therapies (16). Finally, an unanswered question is whether SPOP mutation status can help clinicians decide which patients should receive triplet therapy (ADT plus ARAT plus docetaxel) compared with doublet therapy (ADT plus ARAT) in the dn-mCSPC setting, especially as multi-agent regimens begin to enter the armamentarium.

Additional prospective-retrospective analyses of outcomes associated with mutSPOP in completed randomized trials will have reduced possibility of unadjusted confounding, improving the precision of anticipated ARAT versus docetaxel benefit in this patient population, and allow for evaluation of subgroups that additionally received both docetaxel and ARAT.

In summary, in this real-world study of patients with dn-mCSPC, the addition of ARAT (but not docetaxel) was associated with significantly longer TTCRPC and OS in patients harboring mutSPOP compared with wtSPOP. These results indicate that mutSPOP likely represents a treatment-selection biomarker in the mCSPC setting.

U. Swami reports personal fees from Astellas, Exelixis, and Seattle Genetics, as well as grants from Janssen, Exelixis, and Astellas/Seattle Genetics outside the submitted work. R.P. Graf reports personal fees from Foundation Medicine, Inc during the conduct of the study, as well as personal fees from Epic Sciences outside the submitted work; in addition, R.P. Graf has a patent pending. V. Fisher reports personal fees from Roche outside the submitted work. H. Tukachinsky reports personal fees from Foundation Medicine Inc. and other support from Roche during the conduct of the study. A.B. Schrock reports personal fees from Foundation Medicine and Roche during the conduct of the study. G. Li reports personal fees from Foundation Medicine and other support from F. Hoffmann-La Roche outside the submitted work. J.S. Ross reports personal fees and other support from Foundation Medicine outside the submitted work. G.R. Oxnard reports personal fees from Foundation Medicine and Roche during the conduct of the study. N. Agarwal reports (lifetime disclosures) consultancy to Astellas, AstraZeneca, Aveo, Bayer, Bristol Myers Squibb, Calithera, Clovis, Eisai, Eli Lilly, EMD Serono, Exelixis, Foundation Medicine, Genentech, Gilead, Janssen, Merck, MEI Pharma, Nektar, Novartis, Pfizer, Pharmacyclics, and Seattle Genetics, as well as research funding to institution from Astellas, AstraZeneca, Bavarian Nordic, Bayer, Bristol Myers Squibb, Calithera, Celldex, Clovis, Eisai, Eli Lilly, EMD Serono, Exelixis, Genentech, Gilead, GlaxoSmithKline, Immunomedics, Janssen, Medivation, Merck, Nektar, New Link Genetics, Novartis, Pfizer, Prometheus, Rexahn, Roche, Sanofi, Seattle Genetics, Takeda, and Tracon. No disclosures were reported by the other authors.

Foundation Medicine, a wholly owned subsidiary of Roche, is a for-profit company and producer of FDA-regulated molecular diagnostics. Authors employed by Foundation Medicine were involved in the design and conduct of the study, analysis, interpretation of the data, preparation, review, and approval of the article.

U. Swami: Conceptualization, writing–original draft, writing–review and editing, final approval of manuscript. R.P. Graf: Conceptualization, formal analysis, writing–original draft, writing–review and editing, final approval of manuscript. R.H. Nussenzveig: Writing–review and editing, final approval of manuscript. V. Fisher: Formal analysis, writing–review and editing, final approval of manuscript. H. Tukachinsky: Writing–review and editing, final approval of manuscript. A.B. Schrock: Writing–review and editing, final approval of manuscript. G. Li: Writing–review and editing, final approval of manuscript. J.S. Ross: Writing–review and editing, final approval of manuscript. N. Sayegh: Writing–review and editing, final approval of manuscript. N. Tripathi: Writing–review and editing, final approval of manuscript. V. Mathew Thomas: Writing–review and editing, final approval of manuscript. G.R. Oxnard: Administrative support, writing–review and editing, final approval of manuscript. E.S. Antonarakis: Conceptualization, formal analysis, writing–review and editing, final approval of manuscript. N. Agarwal: Conceptualization, formal analysis, writing–review and editing, final approval of manuscript.

We thank the patients whose data made this research possible, the clinical and laboratory staff at Foundation Medicine, and the team at Flatiron Health.

This study was supported by Foundation Medicine.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.