Abstract
Background and objective:
The rs4680 single-nucleotide polymorphism (SNP) of the COMT gene leads to a reduction in dopamine clearance, resulting in better mood and a decrease in symptoms in noncancer populations, but its influence on quality of life (QOL) during cancer treatment is undefined. We hypothesized that in comparison to wildtype (WT) COMT, the rs4680 SNP is associated with better QOL among men with metastatic hormone-sensitive prostate cancer receiving androgen deprivation therapy ± docetaxel (ADT ± D).
Methods:
In this post hoc analysis, we tested the association between COMT rs4680 status and Functional Assessment of Cancer Therapy-Prostate (overall QOL), Functional Assessment of Chronic Illness Therapy-Fatigue, and Brief Pain Inventory scores at baseline and at 3, 6, 9, and 12 mo using Fisher’s exact test and the Wilcoxon rank-sum test. Blood samples for genotyping were collected before treatment initiation.
Key findings and limitations:
COMT SNP data were available for 550/790 men. Across the overall cohort, 3-mo pain severity was lower for rs4680 versus WT COMT (0.5 vs 1.25; p = 0.04). In the ADT arm, rs4680 versus WT COMT was associated with better overall QOL at 6 mo (128.9 vs 118.5; p = 0.04), less pain at 3 mo (no pain: 70.4% vs 41.5%; p = 0.01), and less pain interference at 3 mo (no interference: 76% vs 51.3%; p = 0.03), 6 mo (75% vs 48.7%; p = 0.02), and 9 mo (83.3% vs 52%; p = 0.02), with similar fatigue scores. Patients in the ADT + D arm had similar QOL regardless of COMT status.
Conclusions and clinical implications:
Patients with the COMT rs4680 SNP experienced less pain and better global QOL after starting ADT alone. This is the first study to show that inherited genetic traits may influence treatment tolerability in men with prostate cancer.
Keywords: COMT gene, Prostate cancer, Quality of life, Androgen deprivation therapy, Single-nucleotide polymorphism
1. Introduction
Patient-reported quality of life (QOL) and clinician-assigned adverse events (AEs) are complementary measures in assessing treatment tolerability for patients receiving cancer therapies. Both QOL and AEs depend on the patient’s experience of symptoms, which is partly governed by neurotransmitter signaling in the brain. Single-nucleotide polymorphisms (SNPs) of genes associated with neurotransmitter metabolism have been linked to patients’ perception of treatment-related symptoms [1]. The largest body of evidence describes the effect of the rs4680 SNP in the COMT gene, which results in a V158M substitution (GG → GA) that leads to a threefold to fourfold reduction in the clearance of dopamine. This promotes higher dopamine levels in the prefrontal cortex and has been associated with better mood and decreased symptoms in a variety of noncancer populations [2–4]. Some studies have even linked rs4680 to the ‘‘placebo effect’’ whereby patients perceive an improvement in symptoms despite not receiving a therapeutic intervention [1,5,6]. The minor allele of rs4680 has been identified in approximately half of individuals of Caucasian ancestry and a quarter of those of African ancestry, and 20% of the general population overall is homozygous for the less active COMT variant (AA genotype) [7]. Other SNPs associated with the risk of developing AEs during cancer treatment have been identified [8–12]. However, it is unknown whether there is a relationship between these germline variants and QOL in patients receiving cancer treatment.
The ECOG-ACRIN E3805 CHAARTED trial demonstrated a survival benefit with addition of docetaxel to androgen deprivation therapy (ADT + D) over ADT alone in patients with metastatic hormone-sensitive prostate cancer (mHSPC) [13]. Patient-reported outcomes were collected during the trial and demonstrated improved QOL at 12 mo in patients receiving ADT + D in comparison to ADT alone [14]. The objective of this analysis was to investigate the influence of genetic COMT polymorphisms on QOL and symptoms related to cancer treatment. We hypothesized that COMT rs4680 would be associated with better QOL outcomes than COMT wildtype (WT) in patients with mHSPC receiving ADT ± docetaxel.
2. Patients and methods
2.1. Study design and population
E3805 CHAARTED was a multicenter randomized clinical trial comparing survival for patients with mHSPC treated with ADT + D versus ADT alone [15]. Enrolled patients had a pathologic or clinical diagnosis of advanced prostate adenocarcinoma, adequate performance status, no organ dysfunction, and no ADT use in the previous 12 mo. Patients were randomized 1:1 to ADT with docetaxel (75 mg/m2 every 3 wk for up to 6 cycles) or ADT alone. Blood samples were collected before treatment initiation for genotyping using Affymetrix GeneChip microarrays. COMT rs4680 was the only SNP investigated for this analysis. Approximately 5% of samples were randomly selected for duplicate genotyping for quality control. The concordance rate for duplicate genotyping was 100%. Samples were excluded if the sample-level call rate was <98%.
2.2. Study instruments
QOL domains were assessed via patient-reported outcome measures (PROMs), with scoring and important differences as previously reported [14,16]. The Functional Assessment of Cancer Therapy-Prostate (FACT-P) reflects disease-specific QOL (important difference 6–10 points, range 0–156) and higher scores indicate better QOL. The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) measures fatigue (important difference 3 points, range 0–160); higher scores reflect less fatigue. The Brief Pain Inventory (BPI) measures pain levels (important difference is a change of 2 points, range 0–10), with higher scores indicating worse pain for two dimensions, pain severity (pain score) and pain interference in daily activities (interference). PROMs were administered at baseline and at 3, 6, 9, and 12 mo after treatment initiation.
2.3. Statistical analysis
Descriptive statistics were calculated to summarize demographic and clinical characteristics by COMT status and treatment arm. FACT-P, BPI, and FACIT-F score distributions were compared between the COMT groups over time and by treatment arm using the Wilcoxon rank-sum test and Fisher’s exact test. All figures were created using R v4.4.1 [17].
3. Results
Of 790 men in the E3805 CHAARTED trial, 550 had SNP data available (284 in the ADT + D arm and 266 in the ADT alone arm). The distribution of clinical and demographic variables overall was balanced across the COMT WT (GG homozygous and GA heterozygous) and rs4680 (AA homozygous) genotypes (Table 1). PROM completion rates steadily decreased over the 12-mo period but remained above 70% (Supplementary Table 1).
Table 1 – Patient demographics and clinical characteristics by COMT status and treatment arm.
|
COMT rs4680 (AA genotype) |
Wildtype COMT (GG or GA genotype) |
|||
|---|---|---|---|---|
| ADT + D (n = 70) | ADT alone (n = 53) | ADT + D (n = 214) | ADT alone (n = 213) | |
| Age (yr) | ||||
| Mean (standard deviation) | 63.9 (7.37) | 62.7 (9.21) | 63.0 (8.68) | 62.5 (8.94) |
| Median (range) | 63.5 (47–79) | 63.0 (44–84) | 64.0 (42–88) | 63.0 (39–91) |
| ECOG PS, n (%) | ||||
| 0 | 51 (72.9%) | 39 (73.6%) | 154 (72.0%) | 155 (73.1%) |
| 1–2 | 19 (27.1%) | 14 (26.4%) | 60 (28.0%) | 57 (26.9%) |
| Data missing | 0 | 0 | 0 | 1 |
| Metastasis volume, n (%) | ||||
| High | 45 (64.3%) | 32 (60.4%) | 143 (66.8%) | 135 (63.4%) |
| Low | 25 (35.7%) | 21 (39.6%) | 71 (33.2%) | 78 (36.6%) |
| Gleason score, n (%) | ||||
| ≤7 | 20 (33.3%) | 15 (31.9%) | 64 (32.2%) | 61 (32.1%) |
| 8–10 | 40 (66.7%) | 32 (68.1%) | 135 (67.8%) | 129 (64.8%) |
| Data missing | 10 | 6 | 15 | 23 |
| Prior local treatment, n (%) | ||||
| No | 51 (72.9%) | 34 (64.2%) | 152 (71.0%) | 146 (68.9%) |
| Yes | 19 (27.1%) | 19 (35.8%) | 62 (29.0%) | 66 (31.1%) |
| Data missing | 0 | 0 | 0 | 1 |
ADT = androgen deprivation therapy; + D = with docetaxel; ECOG PS = Eastern Cooperative Oncology Group performance status.
Across all patients, an association between COMT polymorphism and PROM scores during the first 12 mo was only seen for pain severity at 3 mo: the median BPI score was 0.5 in the rs4680 group versus 1.25 in the COMT WT group (p = 0.04; Table 2). Analysis by treatment arm revealed that in the ADT alone arm, patients with had higher FACT-P scores at 6 mo were higher in the rs4680 versus the COMT WT group (128.9 vs 118.5; p = 0.04), meeting the threshold for a clinically important difference. At the other time points, there was a trend for higher FACT-P scores in the rs4680 versus the COMT WT group, except at 12 mo, when overall QOL scores were similar (Fig. 1). Moreover, the rs4680 group in the ADT alone arm had less pain at 3 mo (no pain: 70.4% vs 41.5%; p = 0.01) and a trend towards less pain 6-mo (63.6% vs 41.9%; p = 0.07) and 9-mo (63.6% vs 39.0%; p = 0.06) time points in comparison to the COMT WT group. Similarly, there was less pain-related interference at 3 mo (no interference: 76.0% vs 51.3%; p = 0.03), 6 mo (75.0% vs 48.7%; p = 0.02), and 9 mo (83.3% vs 52.0%; p = 0.02) in the rs4680 versus the COMT WT group in the ADT alone arm (Fig. 2). While there were no statistically significant differences in FACIT-F scores between the rs4680 and COMT WT groups in the ADT alone arm during the first 12 mo, scores were consistently higher in the rs4680 group (Fig. 3). Analysis of the top and bottom quartiles for FACT-P and BPI scores (ie, least and most symptomatic) in the first 3 mo of ADT treatment revealed no new interactions by rs4680 status, although these subgroups were small (data not shown). In contrast to the associations between COMT rs4680 and PROM scores in the ADT alone arm, no such associations were observed for any PROM in the ADT + D arm.
Table 2 –
Association between COMT status and median FACT-P, BPI, and FACIT-F scores
| Instrument and category | Median score (interquartile range) |
||||
|---|---|---|---|---|---|
| Baseline | 3 mo | 6 mo | 9 mo | 12 mo | |
| FACT-P | |||||
| COMT rs4680 | 125 (29.2) | 119 (30.4) | 123 (26.6) | 124 (29.9) | 123 (31) |
| COMT wildtype | 124 (26) | 122 (25.8) | 121 (28) | 123 (29) | 122 (28) |
| p value | 0.98 | 0.84 | 0.45 | 0.68 | 0.68 |
| BPI severity | |||||
| COMT rs4680 | 0.75 (2) | 0.5 (2) | 1 (2.5) | 1 (2.75) | 1.5 (2.75) |
| COMT wildtype | 1 (2.5) | 1.25 (2.81) | 1.25 (3) | 1.25 (3.25) | 1.5 (2.75) |
| p value | 0.34 | 0.04 | 0.33 | 0.26 | 0.28 |
| BPI interference | |||||
| COMT rs4680 | 0.43 (1.64) | 0.14 (2.39) | 0.71 (2.89) | 0.64 (2.39) | 0.93 (2.57) |
| COMT wildtype | 0.43 (2) | 0.71 (2.71) | 0.71 (3.14) | 0.86 (3.11) | 0.86 (3) |
| p value | 0.64 | 0.08 | 0.57 | 0.42 | 0.65 |
| FACIT-F | |||||
| COMT rs4680 | 45 (10.9) | 41 (14) | 42 (15) | 43 (12) | 41.4 (14) |
| COMT wildtype | 44 (12) | 41 (15.1) | 43 (14) | 43 (13) | 42 (16) |
| p value | 0.50 | 0.58 | 0.69 | 0.84 | 0.88 |
BPI = Brief Pain Inventory; FACIT-F = Functional Assessment of Chronic Illness Therapy-Fatigue; FACT-P = Functional Assessment of Cancer Therapy-Prostate.
Fig. 1 – Association between COMT polymorphism status and Functional Assessment of Cancer Therapy-Prostate (FACT-P) scores by treatment arm. ADT = androgen deprivation therapy; ADT + D = ADT + docetaxel.
Fig. 2 – Association between COMT polymorphism status and Brief Pain Inventory (BPI) scores for (A) pain severity and (B) pain interference by treatment arm. ADT = androgen deprivation therapy; ADT + D = ADT + docetaxel.
Fig. 3 – Association between COMT polymorphism status and Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) scores by treatment arm. ADT = androgen deprivation therapy; ADT + D = ADT + docetaxel.
4. Discussion
In this post hoc analysis of the E3805 CHAARTED trial, we found an association between COMT rs4680 and better QOL outcomes in patients with mHSPC. While patients with rs4680 appeared to only experience lower pain at 3 mo compared to WT across a number of PROMs, stratifying by treatment arm revealed that patients treated with ADT had higher overall QOL at 6 months, as well as decreased pain severity at 3 months and decreased interference due to pain at 3, 6, and 9 months. Importantly, these differences in symptom perception were not present prior to treatment initiation, which suggests that a subset of patients have better tolerability of ADT and/or derive greater symptomatic benefit. Since PROMs measure a combination of disease-specific and treatment-related symptoms, it is hard to tease apart whether our findings indicate that patients with rs4680 have improvements in disease-related symptoms or rather lower treatment-related symptoms. Notably, patients who additionally received docetaxel did not have differences in symptom burden regardless of their rs4680 status, reflecting that the potent QOL-altering effects of chemotherapy may increase symptom burden even in patients who may be genetically predisposed to experience fewer symptoms. Overall, our results suggest an important, if largely understudied, role that germline genetic variance in neurotransmitter metabolism may play in the patient experience during cancer treatment.
The side-effect profile of ADT is well known and extensive, with the onset of fatigue, vasomotor symptoms, muscle wasting, and loss of libido occurring soon after testosterone loss, as well as metabolic changes that can have pervasive effects on cardiovascular and bone health [18–20]. As patients with advanced prostate cancer face lifelong testosterone suppression, it is crucial to identify predictive factors for patients at risk of more severe side effects and offer tailored, patient-centered recommendations regarding supportive care [21]. Our findings suggest that COMT rs4680 could be a genetic biomarker associated with lower symptom burden and ultimately may affect an individual’s likelihood of adhering to hormonal treatment. Additional planned analyses of PROM data and AE rates in CHAARTED and other cohorts could validate the potential predictive role of COMT polymorphisms.
In contrast to the relatively low number of analyses in cancer populations, the association between COMT rs4680 and symptomatic responses to treatment has been widely studied in noncancer populations. Owing to the role of COMT in neurotransmitter metabolism, the majority of pharmacogenomic studies have focused on differential responses to antidepressant and antipsychotic agents, with more rapid and deeper responses identified among patients with rs4680 [22,23]. The potential role of rs4680 has been examined in cancer populations to a lesser extent, with a focus on pain and fatigue. An early Norwegian study on the effect of COMT status on opioid tolerance among patients with cancer-related pain identified lower morphine requirements for those with rs4680 in comparison to COMT WT [24]. Furthermore, a recently published Chinese study found lower oxycodone requirements for cancer pain among patients with rs4680 [25]. While both studies included heterogeneous patient populations, with ∼10% suffering from urological cancers, there seems to be a consistent signal that rs4680 portends lower pain medication requirements and thus patients with this polymorphism may experience less subjective suffering from their disease. By contrast, a Spanish study in patients with early-stage breast cancer actually found higher fatigue assessed using the Piper Fatigue Scale among those with rs4680, although this population had received both chemotherapy and radiation treatment [26]. In our cohort, chemotherapy negated the QOL benefits of rs4680 observed in the ADT alone arm, but we saw no difference in fatigue scores.
A few other SNPs related to the risk of AEs with cancer treatment have been identified, with most of the focus on predicting the risk of chemotherapy-induced neuropathy [9–12]. The studies include a pharmacogenomic analysis for patients with metastatic castration-resistant prostate cancer (mCRPC) in the Alliance/CALGB 90401 trial. This post hoc analysis of genome-wide association data identified VAC14 rs875858 as a predictive SNP for grade ≥3 neuropathy among patients treated with docetaxel. Notably, the analysis involved smaller groups, as the rs875858 minor allele frequency is 0.06, which is notably lower than for rs4680. Nevertheless, the results showed that the risk of severe neuropathy after receiving docetaxel was more than threefold greater for patients with rs875858. This association between rs875858 and neuropathy was not observed in a separate cohort of patients with breast cancer treated with paclitaxel in the same study [8]. Regardless, these findings are particularly relevant to our population of patients with advanced prostate cancer receiving docetaxel. Therefore, in a future analysis we will investigate the role of VAC14 rs875858 in docetaxel-induced neuropathy in this population using AE data and PROMs focused on neuropathy.
Our results add to the body of pharmacogenomic studies and suggest that there may be a time when personalized, genetic-driven patient recommendations will be possible regarding the expected tolerability and side effects of cancer treatment. Clinicians are frequently unable to predict which patients will be at higher or lower risk of toxicity from hormonal therapies and other prostate cancer treatments. However, testing for polymorphisms to predict the risk of toxicity is already common in other scenarios such as gastrointestinal malignancies, for which UGT1A1 and DYPD polymorphisms can predict the likelihood of irinotecan and fluoropyrimidine toxicity, respectively [27,28]. Future studies, using either previously collected genomic data or prospective sequencing in unselected populations, can offer further evidence to validate the role of genetic testing in understanding the effects of cancer treatment on QOL and tailoring individualized counseling and supportive care for prostate cancer survivors.
Our study has several limitations. While this was a hypothesis-driven, a priori analysis of COMT rs4680, the original trial was not powered for this exploratory study. That said, the relatively high rs4680 prevalence meant that there were reasonably large groups for testing of the association between rs4680 and different PROM scores. An interesting future analysis would be to observe the trajectories of patients deemed to be responders versus nonresponders to their assigned treatment, and determine the effect of COMT status on treatment symptoms in these subgroups. In addition, our patient population appeared to have a low symptom burden due to their malignancy at baseline, so the effects of COMT status in patients with higher levels of cancer-associated symptoms in other disease states (eg, bone pain at mCRPC) may be underestimated. Moreover, we did not conduct a multivariable analysis to determine the possible effect of covariates on our findings, although the rs4680 and COMT WT groups had similar clinical characteristics at baseline. Lastly, we did not have sufficient granular information on concomitant medications that patients were receiving during the trial, particularly those that affect serotonin and dopamine pathways, to determine whether they affected QOL in our patients. Controlling for the presence or absence of these medications in subsequent analyses will be important to obtain a clearer picture of the influence of COMT status on symptoms experienced by cancer populations.
5. Conclusions
In comparison to patients with COMT WT status, patients with the rs4680 SNP experienced less pain and better global QOL in the months after starting ADT treatment. This is the first study to show that germline genetic polymorphisms affecting neurotransmitter metabolism can influence QOL in patients with prostate cancer. Further studies are needed to validate these findings in other prostate cancer populations and potentially incorporate COMT genotyping into decision-making regarding a patient’s expected side effects and QOL outcomes.
Supplementary Material
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.org/10.1016/j.euo.2025.04.003.
ADVANCING PRACTICE.
What does this study add?
The study results identify the COMT rs4680 single-nucleotide polymorphism as a promising biomarker for distinct response to androgen deprivation therapy. This is the first study evaluating the potential role of pharmacogenomics in influencing quality of life of men with prostate cancer.
Clinical Relevance
This manuscript describes the potential impact of pharmacogenetics on quality of life and treatment toxocities by using the CHAARTED Trial data. The original approach derives provocative results about the potential impact of inherited genes in the perception of adverse effects deriving from different treatment options and combinations. Associate Editor: Guillaume Ploussard, MD, PhD.
Patient Summary
We found that in a group of men with prostate cancer treated with hormone therapy, those who had a specific variant of the COMT gene had better quality of life and less cancer pain than individuals with the normal COMT gene. This finding suggests that a person’s experience of cancer treatment is partly influenced by their inherited genes.
Funding/Support and role of the sponsor:
This study was conducted by the ECOG-ACRIN Cancer Research Group (co-chairs Peter J. O’Dwyer and Mitchell D. Schnall) and was supported by the National Cancer Institute of the National Institutes of Health under award numbers U10CA180820, U10CA180794, UG1CA189828, UG1CA233180, UG1CA233290, UG1CA233277, UG1CA189859, UG1CA233196, UG1CA233320, UG1CA233234, and UG1CA233320. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional funding was obtained from the Prostate Cancer Foundation (grant 17CHAL04). The funding bodies played no direct role in the study.
Footnotes
Financial disclosures:
Daniel Sentana-Lledo certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Charles J. Ryan reports a consulting or advisory role for Bayer, Oric, Pfizer, and Sanofi. Christopher J. Sweeney reports a consulting or advisory role for Sanofi, Janssen Biotech, Astellas Pharma, Bayer, Genentech/Roche, AstraZeneca, Pfizer, Amgen, Lilly, POINT Biopharma, and Cadence Pharma; research funding from Janssen Biotech, Astellas Pharma, Sanofi, Bayer, Dendreon, and Pfizer; and ownership interests in Leuchemix. David F. Jarrard reports a consulting or advisory role for Gregor Diagnostics. Elizabeth R. Plimack reports a consulting or advisory role for Incyte, Seattle Genetics, Janssen, Flatiron Health, Infinity Pharma, MEI Pharma, Genentech, AstraZeneca, Bristol-Myers Squibb, Merck, and Pfizer; research funding from Peloton and Astellas; and an ownership interest in US patent application 14/588,503 (pending). Benjamin A. Gartrell reports a consulting or advisory role for Bayer, Blue Earth, Bristol-Myers Squibb, Eisai, Immunogen, Janssen, Novartis, Pfizer, and Sanofi. Michael A. Carducci reports a consulting or advisory role for Pfizer, Acrivon Therapeutics, AstraZeneca, and Sanofi; speaker bureau participation for Remedica; and research funding from Pfizer, Arcus Biosciences, Merck, and Celgene/Bristol-Myers Squibb. Maha Hussain reports a consulting or advisory role for Astellas and Bayer; and research funding from Bayer. Jorge A. Garcia reports a consulting or advisory role for Pfizer, AstraZeneca, Ipsen, Aptitude Health, and the US Food and Drug Administration. David Cella reports a consulting or advisory role for AbbVie, Astellas Pharma, Bristol-Myers Squibb, Celcuity, Fulcrum Therapeutics, GlaxoSmithKline, Immunogen, Ipsen, Novartis, and Pfizer; research funding from AbbVie, Bristol-Myers Squibb, Clovis Oncology, Ipsen, Novartis, Pfizer, Pled Pharma, and Regeneron; and ownership interests in FACIT.org. Alicia K. Morgans reports a consulting or advisory role in Advanced Accelerator Applications, Astellas Pharma, AstraZeneca, Bayer, Blue Earth Diagnostics, Exelixis, Janssen, Lantheus Medical Imaging, Merck, Sumitomo Pharma America (formerly Myovant Sciences), Myriad Genetics, Novartis, and Sanofi; speaker bureau participation for Advanced Accelerator Applications, Astellas, AstraZeneca, Bayer, Clovis Oncology, Exelixis, Genentech, Janssen, Janssen Oncology, Merck, Myovant Sciences, Pfizer, and Sanofi; and research funding from Astellas, AstraZeneca, Bayer, Dendreon Pharmaceuticals, Genentech, Sumitomo Pharma America (formerly Myovant Sciences), Sanofi, and Seattle Genetics/Astellas Pharma. The remaining authors have nothing to disclose.
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