Genetic determinants of aromatase inhibitor-related arthralgia: the B-ABLE cohort study

Musculoskeletal symptoms associated with aromatase inhibitors in the treatment of early breast cancer: A scoping review of risk factors and outcomes

PURPOSE

Aromatase inhibitor-associated musculoskeletal symptoms (AIMSS) are the most common adverse effects experienced by breast cancer patients. This scoping review aimed to systematically synthesize the predictors/risk factors and outcomes of AIMSS in patients with early-stage breast cancer.

METHODS

A systematic search was conducted in PubMed, Web of Science, EMBASE, CINAHL, and the China National Knowledge Internet (CNKI) from inception to December 2024 following the scoping review framework proposed by Arksey and O'Malley (2005).

RESULTS

A total of 5,008 studies were identified, and 98 were included in this review. The risk factors for AIMSS included psychosocial and demographic factors (e.g., age, BMI, menstrual status, and anxiety), clinical factors (e.g., history of chemotherapy, preexisting pain, and musculoskeletal diseases) and gene polymorphisms (e.g., ESR1, OPG, RANKL, TCL1A, and CYP19A1). The outcomes of AIMSS encompassed physical, psychological, behavioral, and survival-related impacts.

CONCLUSION

This scoping review synthesized the available evidence on predictors, risk factors, and outcomes of AIMSS, providing a foundation for developing risk prediction models and enhancing symptom management strategies.

Adverse Event Profiles of the Third-Generation Aromatase Inhibitors: Analysis of Spontaneous Reports Submitted to FAERS

The third-generation aromatase inhibitors (AIs), represented by letrozole, anastrozole, and exemestane, have been used as a standard first-line adjuvant therapy for postmenopausal breast cancer patients with positive hormone receptor. However, their safety in the real world has not been systematically analyzed. We used the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) to investigate adverse event (AE) profiles of the three AIs, covering the period from Q1 2004 to Q3 2023. The time-to-event onset profiles and cumulative incidence were analyzed by Weibull shape parameter test and Kaplan-Meier method, respectively. The disproportionality analysis was utilized to assess drug toxicity risk. Based on the FAERS database, 18,035, 8242, and 7011 reports listing letrozole, anastrozole, and exemestane as primary suspected drugs were extracted, respectively. AEs associated with anastrozole displayed the latest onset (p < 0.0001); meanwhile, WSP test showed that all three AIs had early failure-type profiles. At the preferred term level, we acquired 95, 59, and 42 significant signals associated with letrozole, anastrozole, and exemestane, which involved 18, 13, and 15 system organ classes, respectively. The three AIs all reported that their strongest AE signal was trigger finger. Neutropenia was the most frequent AE for letrozole, while the highest occurrences of anastrozole and exemestane were arthralgia. We also found that interstitial lung disease, a rare but serious AE, showed strong signal intensity in all three AIs. Additionally, letrozole was also associated with lots of other rare but serious AEs in hematologic, respiratory, and hepatic systems, which were not recorded in the instructions. Our analysis of safety warning signals of the third-generation AIs from the FAERS database provided reference for clinical safe and rational drug use.

A Cohort Study to Evaluate Genetic Predictors of Aromatase Inhibitor Musculoskeletal Symptoms: Results from ECOG-ACRIN E1Z11

PURPOSE

Aromatase inhibitor (AI)-associated musculoskeletal symptoms (AIMSS) are common and frequently lead to AI discontinuation. SNPs in candidate genes have been associated with AIMSS and AI discontinuation. E1Z11 is a prospective cohort study designed to validate the association between 10 SNPs and AI discontinuation due to AIMSS.

PATIENTS AND METHODS

Postmenopausal women with stage I to III hormone receptor-positive breast cancer received anastrozole 1 mg daily and completed patient-reported outcome measures to assess AIMSS (Stanford Health Assessment Questionnaire) at baseline, 3, 6, 9, and 12 months. We estimated that 40% of participants would develop AIMSS and 25% would discontinue AI treatment within 12 months. Enrollment of 1,000 women with a fixed number per racial stratum provided 80% power to detect an effect size of 1.5 to 4. SNPs were found in ESR1 (rs2234693, rs2347868, and rs9340835), CYP19A1 (rs1062033 and rs4646), TCL1A (rs11849538, rs2369049, rs7158782, and rs7159713), and HTR2A (rs2296972).

RESULTS

Of the 970 evaluable women, 43% developed AIMSS and 12% discontinued AI therapy within 12 months. Although more Black and Asian women developed AIMSS than White women (49% vs. 39%, P = 0.017; 50% vs. 39%, P = 0.004, respectively), the AI discontinuation rates were similar across groups. None of the SNPs were significantly associated with AIMSS or AI discontinuation in the overall population or in distinct cohorts. The OR for rs2296972 (HTR2A) approached significance for developing AIMSS.

CONCLUSIONS

We were unable to prospectively validate candidate SNPs previously associated with AI discontinuation due to AIMSS. Future analyses will explore additional genetic markers, patient-reported outcome predictors of AIMSS, and differences by race.

Current and future advances in practice: aromatase inhibitor-induced arthralgia

Aromatase inhibitors (AIs) have shown great success as adjuvant therapy for post-menopausal women with hormone receptor-positive breast cancers. AI-induced arthralgia (AIA) is a frequent AI toxicity contributing to non-adherence and discontinuation. This review aims to understand current knowledge of AIA. The mean incidence of AIA was 39.1% and the mean discontinuation of AI therapy due to AIA was 9.3%. Most of the AIAs were non-inflammatory. A shorter time since the last menstrual period and pre-existing joint pain were risk factors. Vitamin D3 supplementation may be a preventative measure and treatment with duloxetine, acupuncture and/or exercise is supported by large randomized controlled trials. There was consistent improvement in AIAs with switching to an alternate AI, and this could additionally allow continuation of cancer treatment with AI. Further research is needed to identify predictive biomarkers, better characterize AIA subcategories and study more reliable therapeutic options.

Incorporation of emergent symptoms and genetic covariates improves prediction of aromatase inhibitor therapy discontinuation

Objectives

Early discontinuation is common among breast cancer patients taking aromatase inhibitors (AIs). Although several predictors have been identified, it is unclear how to simultaneously consider multiple risk factors for an individual. We sought to develop a tool for prediction of AI discontinuation and to explore how predictive value of risk factors changes with time.

Materials and Methods

Survival machine learning was used to predict time-to-discontinuation of AIs in 181 women who enrolled in a prospective cohort. Models were evaluated via time-dependent area under the curve (AUC), c-index, and integrated Brier score. Feature importance was analysis was conducted via Shapley Additive Explanations (SHAP) and time-dependence of their predictive value was analyzed by time-dependent AUC. Personalized survival curves were constructed for risk communication.

Results

The best-performing model incorporated genetic risk factors and changes in patient-reported outcomes, achieving mean time-dependent AUC of 0.66, and AUC of 0.72 and 0.67 at 6- and 12-month cutoffs, respectively. The most significant features included variants in ESR1 and emergent symptoms. Predictive value of genetic risk factors was highest in the first year of treatment. Decrease in physical function was the strongest independent predictor at follow-up.

Discussion and Conclusion

Incorporation of genomic and 3-month follow-up data improved the ability of the models to identify the individuals at risk of AI discontinuation. Genetic risk factors were particularly important for predicting early discontinuers. This study provides insight into the complex nature of AI discontinuation and highlights the importance of incorporating genetic risk factors and emergent symptoms into prediction models.

Genome-wide association study of aromatase inhibitor discontinuation due to musculoskeletal symptoms

OBJECTIVE

Aromatase inhibitors (AIs) are commonly used to treat hormone receptor positive (HR +) breast cancer. AI-induced musculoskeletal syndrome (AIMSS) is a common toxicity that causes AI treatment discontinuation. The objective of this genome-wide association study (GWAS) was to identify genetic variants associated with discontinuation of AI therapy due to AIMSS and attempt to replicate previously reported associations.

METHODS

In the Exemestane and Letrozole Pharmacogenetics (ELPh) study, postmenopausal patients with HR + non-metastatic breast cancer were randomized to letrozole or exemestane. Genome-wide genotyping of germline DNA was conducted followed by imputation. Each imputed variant was tested for association with time-to-treatment discontinuation due to AIMSS using a Cox proportional hazards model assuming additive genetic effects and adjusting for age, baseline pain score, prior taxane treatment, and AI arm. Secondary analyses were conducted within each AI arm and analyses of candidate variants previously reported to be associated with AIMSS risk.

RESULTS

Four hundred ELPh participants were included in the combined analysis. Two variants surpassed the genome-wide significance level in the primary analysis (p value < 5 × 10-8), an intronic variant (rs79048288) within CCDC148 (HR = 4.42, 95% CI: 2.67-7.33) and an intergenic variant (rs912571) upstream of PPP1R14C (HR = 0.30, 95% CI: 0.20-0.47). In the secondary analysis, rs74418677, which is known to be associated with expression of SUPT20H, was significantly associated with discontinuation of letrozole therapy due to AIMSS (HR = 5.91, 95% CI: 3.16-11.06). We were able to replicate associations for candidate variants previously reported to be associated with AIMSS in this cohort, but were not able to replicate associations for any other variants previously reported in other patient cohorts.

CONCLUSIONS

Our GWAS findings identify several candidate variants that may be associated with AIMSS risk from AI generally or letrozole specifically. Validation of these associations in independent cohorts is needed before translating these findings into clinical practice to improve treatment outcomes in patients with HR + breast cancer.

Further Evidence That OPG rs2073618 Is Associated With Increased Risk of Musculoskeletal Symptoms in Patients Receiving Aromatase Inhibitors for Early Breast Cancer

Background

Aromatase inhibitors (AI) reduce recurrence and death in patients with early-stage hormone receptor-positive (HR +) breast cancer. Treatment-related toxicities, including AI-induced musculoskeletal symptoms (AIMSS), are common and may lead to early AI discontinuation. The objective of this study was to replicate previously reported associations for candidate germline genetic polymorphisms with AIMSS.

Methods

Women with stage 0-III HR + breast cancer initiating adjuvant AI were enrolled in a prospective clinic-based observational cohort. AIMSS were assessed by patient-reported outcomes (PRO) including the PROMIS pain interference and physical function measures plus the FACT-ES joint pain question at baseline and after 3 and 6 months. For the primary analysis, AIMSS were defined as ≥ 4-point increase in the pain interference T-score from baseline. Secondary AIMSS endpoints were defined as ≥ 4-point decrease in the physical function T-score from baseline and as ≥ 1-point increase on the FACT-ES joint pain question from baseline. The primary hypothesis was that TCL1A rs11849538 would be associated with AIMSS. Twelve other germline variants in CYP19A1, VDR, PIRC66, OPG, ESR1, CYP27B1, CYP17A1, and RANKL were also analyzed assuming a dominant genetic effect and prespecified direction of effect on AIMSS using univariate logistic regression with an unadjusted α = 0.05. Significant univariate associations in the expected direction were adjusted for age, race, body mass index (BMI), prior taxane, and the type of AI using multivariable logistic regression.

Results

A total of 143 participants with PRO and genetic data were included in this analysis, most of whom were treated with anastrozole (78%) or letrozole (20%). On primary analysis, participants carrying TCL1A rs11849538 were not more likely to develop AIMSS (odds ratio = 1.29, 95% confidence interval: 0.55-3.07, p = 0.56). In the statistically uncorrected secondary analysis, OPG rs2073618 was associated with AIMSS defined by worsening on the FACT-ES joint pain question (OR = 3.33, p = 0.004), and this association maintained significance after covariate adjustment (OR = 3.98, p = 0.003).

Conclusion

Carriers of OPG rs2073618 may be at increased risk of AIMSS. If confirmed in other cohorts, OPG genotyping can be used to identify individuals with HR + early breast cancer in whom alternate endocrine therapy or interventions to enhance symptom detection and implement strategies to reduce musculoskeletal symptoms may be needed.

Aromatase and CDK4/6 Inhibitor-Induced Musculoskeletal Symptoms: A Systematic Review

BACKGROUND

Treatment with aromatase inhibitors (AIs) is fundamental in women with hormone receptor-positive breast cancer in the adjuvant as well as the metastatic setting. Even though it is considered to be a well-tolerated therapy, aromatase inhibitor-associated musculoskeletal syndrome (AIMSS) is the most common adverse event encountered by breast cancer patients. CDK4/6 inhibitors have emerged as a new treatment strategy in metastatic hormone receptor-positive breast cancer. However, the impact of CDK4/6 inhibitors on musculoskeletal symptoms caused by AIs is not well-defined.

OBJECTIVES

This systematic review aims to identify the frequency of joint symptoms induced by treatment with AIs and CDK4/6 inhibitors in the metastatic setting.

SEARCH STRATEGY

Eligible articles were identified by a search of existing literature for the period 2005/01/01-2021/01/01; The algorithm consisted of a predefined combination of the following keywords "breast", "cancer", "aromatase inhibitors", "CDK4/6", "phase III".

SELECTION CRITERIA

This study was performed in accordance with PRISMA guidelines. All randomized controlled Phase III trials (RCTs) evaluating the administration of third-generation aromatase inhibitors (AIs) and CDK4/6 inhibitors in postmenopausal women in the metastatic setting were considered eligible for this review.

DATA COLLECTION

Overall, 16 randomized control trials (RCTs) were retrieved, of which nine studies explored the administration of AIs in the metastatic setting and seven studies investigated the combination of CDK4/6 inhibitors and AIs. Arthralgia was reported in 1-47% of patients treated with AIs and 5.8-33.3% of patients treated with CDK4/6 inhibitors. Myalgias occurred in 2-23.7% of patients receiving AIs compared with 4.8-11.9% of patients treated with CDK4/6 inhibitors. The incidence of back pain was 7-32.9% vs. 2.9-8.5% in postmenopausal women with metastatic disease treated with AIs and CDK4/6 inhibitors, respectively. Bone pain was reported in 7-32.9% of postmenopausal women treated with AIs and 2.9-8.5% of women treated with CDK4/6 inhibitors.

CONCLUSIONS

AI treatment-induced musculoskeletal syndrome is an adverse event affecting over one-third (20-47%) of postmenopausal patients treated with AIs that often leads to treatment discontinuation. Data from RCTs provide evidence that the incidence of musculoskeletal symptoms is relatively decreased upon CDK4/6 inhibitor administration. CDK4/6 inhibitors may provide a protective role against AIMSS development.

Aromatase Inhibitor-Associated Musculoskeletal Syndrome: Understanding Mechanisms and Management

Aromatase inhibitors (AIs) are a key component in the chemoprevention and treatment of hormone receptor-positive (HR+) breast cancer. While the addition of AI therapy has improved cancer-related outcomes in the management of HR+ breast cancer, AIs are associated with musculoskeletal adverse effects known as the aromatase inhibitor-associated musculoskeletal syndrome (AIMSS) that limit its tolerability and use. AIMSS is mainly comprised of AI-associated bone loss and arthralgias that affect up to half of women on AI therapy and detrimentally impact patient quality of life and treatment adherence. The pathophysiology of AIMSS is not fully understood though has been proposed to be related to estrogen deprivation within the musculoskeletal and nervous systems. This review aims to characterize the prevalence, risk factors, and clinical features of AIMSS, and explore the syndrome's underlying mechanisms and management strategies.

Aromatase Inhibitors-Induced Musculoskeletal Disorders: Current Knowledge on Clinical and Molecular Aspects

Aromatase inhibitors (AIs) have radically changed the prognosis of hormone receptor positive breast cancer (BC) in post-menopausal women, and are a mainstay of the adjuvant therapy for BC after surgery in place of, or following, Tamoxifen. However, AIs aren't side effect-free; frequent adverse events involve the musculoskeletal system, in the form of bone loss, AI-associated arthralgia (AIA) syndrome and autoimmune rheumatic diseases. In this narrative review, we reported the main clinical features of these three detrimental conditions, their influence on therapy adherence, the possible underlying molecular mechanisms and the available pharmacological and non-pharmacological treatments. The best-known form is the AIs-induced osteoporosis, whose molecular pathway and therapeutic possibilities were extensively investigated in the last decade. AIA syndrome is a high prevalent joint pain disorder which often determines a premature discontinuation of the therapy. Several points still need to be clarified, as a universally accepted diagnostic definition, the pathogenetic mechanisms and satisfactory management strategies. The association of AIs therapy with autoimmune diseases is of the utmost interest. The related literature has been recently expanded, but many issues remain to be explored, the first being the molecular mechanisms.

Genetic and clinical predictors of arthralgia during letrozole or anastrozole therapy in breast cancer patients

PURPOSE

Female patients with breast cancer frequently develop arthralgia when treated with aromatase inhibitors (AI). Although the mechanism of AI-induced arthralgia is unknown, potential biomarkers have been identified. The purpose of this study was to investigate the clinical and genetic predictors of AI-induced arthralgia in a prospective cohort of patients with estrogen receptor-positive breast cancer.

METHODS

One hundred and ninety-six patients were enrolled at initiation of AI therapy with either letrozole or anastrozole. Patients completed two validated self-report questionnaires assessing pain, stiffness, and physical function at baseline, and repeated the questionnaires at two and at six months after the initiation of treatment with an AI. Germline DNA of all patients was genotyped for seven single-nucleotide polymorphisms (SNPs) previously identified by genetic screens and genome-wide association studies as associated with AI-induced arthralgia.

RESULTS

More than 50% of the study group experienced arthralgia symptoms. Genetic analysis revealed that four SNPs, in CYP19A1 (rs4775936) and ESR1 (rs9322336, rs2234693, rs9340799), were associated with the development of arthralgia (adjusted P = 0.016, 0.018, 0.017, 0.047). High body mass index (BMI) was also associated with the development of arthralgia symptoms (adjusted P = 0.001). Patients prescribed letrozole were significantly more likely to develop arthralgia than patients on anastrozole (P = 0.018), and also more likely to discontinue AI therapy due to arthralgia. The CYP19A1 (rs4775936) SNP was significantly associated with discontinuation of therapy due to intolerable arthralgia.

CONCLUSIONS

Our results suggested that BMI and AI drug (letrozole versus anastrozole) were clinical predictors of arthralgia, while genetic variants rs4775936, rs9322336, rs2234693, and rs9340799 were genetic predictors of AI-induced arthralgia. Significantly, rs4775936 was also a predictor of discontinuation of therapy.

Association of CYP19A1 gene variations with adjuvant letrozole-induced adverse events in South Indian postmenopausal breast cancer cohort expressing hormone-receptor positivity

PURPOSE

Musculoskeletal adverse events (MS-AEs) and vasomotor symptoms (VMSs) are the major side-effects of newer generation non-steroidal aromatase inhibitor (AI), letrozole. Single-nucleotide polymorphisms (SNPs) in CYP19A1 gene coding for the enzyme aromatase are related to AI treatment-associated adverse drug reactions. Therefore, we aimed to determine whether SNPs in the CYP19A1 gene are associated with adjuvant letrozole-induced 'specific' AEs in postmenopausal hormone receptor-positive (HR+) breast cancer patients.

METHODS

Genomic DNA was isolated from 198 HR+ breast cancer patients by the phenol-chloroform method, and eleven SNPs in the CYP19A1 gene were genotyped by TaqMan genotyping assays on the qRT-PCR system. Toxicity was assessed according to the National Cancer Institute Common Terminology Criteria for Adverse Events version 3.0, and the data were analyzed using SPSS v19.0 and Haploview v4.2 statistical software.

RESULTS

Subjects carrying the genetic variants of CYP19A1 gene SNP rs700519 had significantly higher odds (OR 2.33; 95% CI [1.29-4.20], P = 0.0057) of MS-AEs under dominant statistical effect. The frequency of the two distinct haplotypes that include the variant allele 'T' at rs700519 locus, H5-GCTATCTGGCG (P = 0.042) and H11-GCTATTGCACG (P = 0.013) were significantly higher in patients with musculoskeletal toxicity than in those without MS-AEs and thus predisposing to MS-AEs. Similarly, H6-GCCAGCTGGCG (P = 0.037) haplotype exhibited higher frequencies in patients presented with VMSs. However, no such association was observed between CYP19A1 genotypes and VMSs.

CONCLUSIONS

To the best of our knowledge, this is the first study assessing the impact of CYP19A1 genetic variations with adjuvant letrozole treatment-associated AEs in Indian women. Genetic variations in the CYP19A1 gene is associated with letrozole-induced AEs and warrants further investigation in larger cohorts to validate this finding.

Single Nucleotide Polymorphisms in 25-Hydroxyvitamin D3 1-Alpha-Hydroxylase (CYP27B1) Gene: The Risk of Malignant Tumors and Other Chronic Diseases

: Vitamin D is widely known for its roles in the promotion of apoptosis and differentiation, with simultaneous inhibition of proliferation, inflammation, angiogenesis, invasion, and metastasis. Modern literature lacks complete information on polymorphisms in CYP27B1, the only enzyme capable of vitamin D activation. This review presents gathered data that relate to genetic variants in CYP27B1 gene in correlation to multiple diseases, mostly concerning colorectal, prostate, breast, lung, and pancreatic cancers, as well as on other pathologies, such as non-Hodgkin's lymphoma, oral lichen planus, or multiple sclerosis.

Genetic Underpinnings of Musculoskeletal Pain During Treatment With Aromatase Inhibitors for Breast Cancer: A Biological Pathway Analysis

BACKGROUND

Musculoskeletal pain (MSKP) is the most reported symptom during treatment with aromatase inhibitors (AIs) for breast cancer. The mechanisms underlying MSKP are multidimensional and not well understood. The goals of this biological pathway analysis were to (1) gain an understanding of the genetic variation and biological mechanisms underlying MSKP with AI therapy and (2) identify plausible biological pathways and candidate genes for future investigation.

METHOD

Genes associated with MSKP during AI therapy or genes involved in drug metabolism of and response to AIs were identified from the literature. Studies published through February 2019 were queried in PubMed®. The genes identified from the literature were entered into QIAGEN's Ingenuity® Pathway Analysis (IPA) software to generate canonical pathways, upstream regulators, and networks through a core analysis.

RESULTS

The 17 genes identified were ABCB1, ABCG1, CYP17A1, CYP19A1, CYP27B1, CYP2A6, CYP3A4, CYP3A5, ESR1, OATP1B1, OPG, RANKL, SLCO3A1, TCL1A, UGT2A1, UGT2B17, and VDR. These genes are involved in encoding bone-remodeling regulators, drug-metabolizing enzymes (cytochrome P450 family, UDP-glucuronosyltransferases family), or drug transporters (ATP-binding cassette transporters, organic anion transporters). Multiple plausible biological pathways (e.g., nicotine degradation, melatonin degradation) and candidate genes (e.g., NFKB, HSP90, AKT, ERK1/2, FOXA2) are proposed for future investigation based on the IPA results.

CONCLUSION

Multiple genes and molecular-level etiologies may contribute to MSKP with AI therapy in women with breast cancer. Our innovative combination of gene identification from the literature plus biological pathway analysis allowed for the emergence of novel candidate genes and biological pathways for future investigations.

Clinical and genetic risk factors for aromatase inhibitor-associated arthralgia in breast cancer survivors

BACKGROUND

Arthralgia is a common and debilitating toxicity of aromatase inhibitors (AI) that leads to premature drug discontinuation. We sought to evaluate the clinical and genetic risk factors associated with AI-associated arthralgia (AIAA).

METHODS

We performed a cross-sectional study among postmenopausal women with stage 0-III breast cancer who were prescribed a third-generation AI for adjuvant therapy. The primary outcome was patient-reported AIAA occurrence. We extracted and assayed germline DNA for single nucleotide polymorphisms (SNPs) of genes implicated in estrogen and inflammation pathways. Multivariable logistic regression models examined the association between demographic, clinical, and genetic factors and AIAA. Analyses were restricted to White participants.

RESULTS

Among 1049 White participants, 543 (52%) reported AIAA. In multivariable analyses, women who had a college education [Adjusted Odds Ratio (AOR) 1.49, 95% Confidence Interval (CI) 1.00-2.20], had a more recent transition into menopause (<10 years) (5-10 years AOR 1.55, 95% CI 1.09-2.22; <5 years AOR 1.78, 95% CI 1.18-2.67), were within one year of starting AIs (AOR 1.61, 95% CI 1.08-2.40), and those who received chemotherapy (AOR 1.38, 95% CI 1.02-1.88) were significantly more likely to report AIAA. Additionally, SNP rs11648233 (HSD17B2) was significantly associated with higher odds of AIAA (AOR 2.21, 95% CI 1.55-3.16).

CONCLUSIONS

Time since menopause and start of AIs, prior chemotherapy, and SNP rs11648233 within the HSD17B2 gene in the estrogen pathway were significantly associated with patient-reported AIAA. These findings suggest that clinical and genetic factors involved in estrogen withdrawal increase the risk of AIAA in postmenopausal breast cancer survivors.

Genome-wide enriched pathway analysis of acute post-radiotherapy pain in breast cancer patients: a prospective cohort study

BACKGROUND

Adjuvant radiotherapy (RT) can increase the risk of developing pain; however, the molecular mechanisms of RT-related pain remain unclear. The current study aimed to identify susceptibility loci and enriched pathways for clinically relevant acute post-RT pain, defined as having moderate to severe pain (pain score ≥ 4) at the completion of RT.

METHODS

We conducted a genome-wide association study (GWAS) with 1,344,832 single-nucleotide polymorphisms (SNPs), a gene-based analysis using PLINK set-based tests of 19,621 genes, and a functional enrichment analysis of a gene list of 875 genes with p < 0.05 using NIH DAVID functional annotation module with KEGG pathways and GO terms (n = 380) among 1112 breast cancer patients.

RESULTS

About 29% of patients reported acute post-RT pain. None of SNPs nor genes reached genome-wide significant level. Four SNPs showed suggestive associations with post-RT pain; rs16970540 in RFFL or near the LIG3 gene (p = 1.7 × 10-6), rs4584690, and rs7335912 in ABCC4/MPR4 gene (p = 5.5 × 10-6 and p = 7.8 × 10-6, respectively), and rs73633565 in EGFL6 gene (p = 8.1 × 10-6). Gene-based analysis suggested the potential involvement of neurotransmitters, olfactory receptors, and cytochrome P450 in post-RT pain, whereas functional analysis showed glucuronidation (FDR-adjusted p value = 9.46 × 10-7) and olfactory receptor activities (FDR-adjusted p value = 0.032) as the most significantly enriched biological features.

CONCLUSIONS

This is the first GWAS suggesting that post-RT pain is a complex polygenic trait influenced by many biological processes and functions such as glucuronidation and olfactory receptor activities. If validated in larger populations, the results can provide biological targets for pain management to improve cancer patients' quality of life. Additionally, these genes can be further tested as predictive biomarkers for personalized pain management.

Genetic Variants Associated with Cancer Pain and Response to Opioid Analgesics: Implications for Precision Pain Management

OBJECTIVE

To review the current knowledge on the association of genetic variants with cancer pain.

DATA SOURCES

Data-based publications and review articles retrieved from PubMed, CINAHL, and Web of Science, as well as an additional search in Google Scholar.

CONCLUSION

Genetic variability can influence differential pain perception and response to opioids in cancer patients, which will have implications in the optimal personalized treatment of cancer pain. More studies are warranted to replicate findings.

IMPLICATIONS FOR NURSING PRACTICE

Nurses are poised to educate patients on biomarker testing and interpretation and to use precision pain management strategies based on this information.

The Roles of Common Variation and Somatic Mutation in Cancer Pharmacogenomics

Cancer pharmacogenomics is the science concerned with understanding genetic alterations and its effects on the pharmacokinetics and pharmacodynamics of anti-cancer drugs, with the aim to provide cancer patients with the precise medication that will achieve a good response and cause low/no incidence of adverse events. Advances in biotechnology and bioinformatics have enabled genomic research to evolve from the evaluation of alterations at the single-gene level to studies on the whole-genome scale using large-scale genotyping and next generation sequencing techniques. International collaborative efforts have resulted in the construction of databases to curate the identified genetic alterations that are clinically significant, and these are currently utilized in clinical sequencing and liquid biopsy screening/monitoring. Furthermore, countless clinical studies have accumulated sufficient evidence to match cancer patients to therapies by utilizing the information of clinical-relevant alterations. In this review we summarize the importance of germline alterations that act as predictive biomarkers for drug-induced toxicity and drug response as well as somatic mutations in cancer cells that function as drug targets. The integration of genomics into the medical field has transformed the era of cancer therapy from one-size-fits-all to cancer precision medicine.

Systematic review of genetic polymorphisms associated with psychoneurological symptoms in breast cancer survivors

PURPOSE

Psychoneurological (PN) symptoms, such as anxiety, cognitive impairment, depression, fatigue, sleep disturbances, and pain, are highly prevalent in breast cancer patients undergoing cancer treatment. Emerging evidence suggests that genetic polymorphisms may contribute to differential symptom susceptibility. We aimed to systematically review associations between genetic polymorphisms and PN symptoms during or after cancer treatment for early-stage breast cancer.

METHODS

Twenty-six eligible articles published until October 2017 were identified in PubMed, PsycINFO, Web of Science, and additional records. Information on study characteristics, genetic polymorphisms, and PN symptoms was extracted. Study quality was evaluated by the STrengthening the REporting of Genetic Association (STREGA) guideline. Genes included in the analysis were categorized by biological pathways based on the Reactome database.

RESULTS

A total of 54 single nucleotide polymorphisms and haplotypes that are significantly associated with PN symptoms were identified; half of them were associated with increased severity of PN symptoms, while the other half contributed to the decrease of PN symptoms. Pain has the known highest number of associated genetic polymorphisms reported, followed by fatigue, cognitive impairment, depressive symptoms, sleep disturbances, and anxiety. The majority of genetic polymorphisms were involved in immune system and neuronal system pathways. Most studies were unsuccessful in meeting the STREGA guideline, which requires transparent reporting of methods and results.

CONCLUSIONS

This review provides comprehensive evidence of genetic polymorphisms underlying PN symptoms, which may pave the way for the development of personalized therapeutics targeting these symptoms. More well-designed genome-wide association studies are required to validate and replicate these findings.

Osteoporosis and musculoskeletal complications related to therapy of breast cancer

Aromatase inhibitors (AIs) are the treatment of choice for the majority of postmenopausal women with estrogen receptor (ER) positive breast cancers in early and advanced stage settings. One of most frequent side effects of AIs is bone loss that is of sufficient magnitude to increase risk of osteoporotic fractures. Osteoporosis is primarily a complex genetic disease with few modifiable risk factors. As the lifespan increases, and breast mortality decreases, more women with breast cancer will be at risk of osteoporotic fractures, or falls that result in fractures. The screening, prevention, and treatment of osteoporosis do not differ in women with or without breast cancer. Rather, breast cancer treatments, including AIs, chemotherapy-induced ovarian failure, and gonadotropin-releasing hormone (GnRH) agonists, all decrease estrogen, which causes net bone resorption, leading some women to experience fracture. Occurring in about fifty-percent of women, AI-induced arthralgia is one of the most common side effects, and causes of nonadherence and discontinuation. Registry studies show that nonadherence and discontinuation may contribute to higher breast cancer mortality. Thus, understanding the mechanisms, risk factors, and interventions to mitigate symptoms of AI-induced arthralgia is a high priority.

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm

Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor‐related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm (NAA) to predict AIA using germline single nucleotide polymorphisms (SNP) data obtained before treatment initiation. Systematic chart review of 700 AI‐treated patients with stage I‐III BC identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. SNP clusters that most closely defined AIA risk were discovered using an NAA that sequentially combined statistical filtering and a machine‐learning algorithm. NCBI PhenGenI and Ensemble databases defined gene attribution of the most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Demographics were similar in cases and controls. A cluster of 70 SNPs, correlating to 57 genes, was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally consistent. Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias.

Pharmacogenetics and aromatase inhibitor induced side effects in breast cancer patients

This paper reviews genetic variations mainly related to the onset of adverse events during aromatase inhibitors in early breast cancer. Genetic variability could occur at different steps. The analysis included studies that involved breast cancer patients, treated with an aromatase inhibitor, genotyped for CYP19A1 and/or CYP17A1 and/or CYP27B1 and/or TCLA1, and/or RANK/RANKL/OPG and/or ESR1/ESR2, and assessed for toxicity profile. Twenty-two articles were included for the analysis. Three studies evaluated outcomes and adverse events; 19 studies assessed only side effects. Functional variations may be useful in predicting the onset of toxicities. The identification of polymorphisms at increased risk of toxicity may enable patient management. However, more data are needed to be applied in the individualization of treatment in daily practice.

Germline genetic predictors of aromatase inhibitor concentrations, estrogen suppression and drug efficacy and toxicity in breast cancer patients

The third-generation aromatase inhibitors (AIs), anastrozole, letrozole and exemestane, are highly effective for the treatment of estrogen receptor-positive breast cancer in postmenopausal women. AIs inhibit the aromatase (CYP19A1)-mediated production of estrogens. Most patients taking AIs achieve undetectable blood estrogen concentrations resulting in drug efficacy with tolerable side effects. However, some patients have suboptimal outcomes, which may be due, in part, to inherited germline genetic variants. This review summarizes published germline genetic associations with AI treatment outcomes including systemic AI concentrations, estrogenic response to AIs, AI treatment efficacy and AI treatment toxicities. Significant associations are highlighted with commentary about prioritization for future validation to identify pharmacogenetic predictors of AI treatment outcomes that can be used to inform personalized treatment decisions in patients with estrogen receptor-positive breast cancer.

Molecular basis of aromatase inhibitor associated arthralgia: known and potential candidate genes and associated biomarkers

INTRODUCTION

Aromatase inhibitors (AIs) are routinely used for the adjuvant treatment of women with hormone receptor-positive early breast cancer. AIs are widely prescribed in the postmenopausal setting, as they are effective at preventing recurrence. However, their use is complicated by significant adverse effects, particularly arthralgia, noted in up to 50% of treated patients, and thereby affects quality of life and AI compliance. The mechanism by which AIs cause arthralgia is largely unknown, although there is a growing body of literature which suggests that there may be multiple intersecting mechanisms. Areas covered: This review describes the evidence for the mechanistic basis of AI arthralgia as well as potential pathways that could contribute to the development of AI associated arthralgia. Expert opinion: Interplay of multiple factors, such as interpatient variability in AI metabolism, possibly related to pharmacogenetic factors, the sudden decline of estrogen synthesis, vitamin D status, as well as upregulation of cytokines and inflammation pathways may precipitate or exacerbate muscle and joint pain are linked during AI therapy. However, much more research is needed in this area given the frequency and severity of AI-associated arthralgia.

The implications of genetic variation for the pharmacokinetics and pharmacodynamics of aromatase inhibitors

INTRODUCTION

Breast cancer is the most common female cancer and remains a serious public health concern worldwide. Third-generation aromatase inhibitors (AIs) are widely used in postmenopausal women with estrogen receptor positive breast cancer. However, there is marked interindividual variability in terms of the efficacy and incidence of adverse events following treatment with AIs. Pharmacogenetics has the potential to predict clinical outcomes based on patients' genetic information, paving the way towards personalized treatment.

AREAS COVERED

This article reviews pharmacogenetic studies of AIs, including pharmacokinetic and pharmacodynamic aspects, highlighting those studies where the efficacy and adverse events of AIs have been examined using both candidate gene and genome-wide approaches.

EXPERT OPINION

Pharmacogenetics is a promising approach to develop personalized medicine with AIs. However, the application of pharmacogenetics to predict therapeutic efficacy and adverse events in breast cancer patients is still far from implementation in routine clinical practice. Large, comprehensive, multicenter studies that simultaneously evaluate multiple genes and pathways, including rare variants, are warranted in order to produce reliable and informative results. The ultimate aim is to develop clinically-relevant guidelines for breast cancer therapy.

AI-related BMD variation in actual practice conditions: A prospective cohort study

The aim of the study was to evaluate the progression of bone mineral density (BMD) during 3 years of aromatase inhibitors (AI) therapy in actual practice conditions. This prospective, clinical cohort study of Barcelona-Aromatase induced Bone Loss in Early breast cancer (B-ABLE) assessed BMD changes during 3 years of AI treatment in women with breast cancer. Patients with osteoporosis (T score < -2.5 or T score ≤ -2.0) and a major risk factor and/or prevalent fragility fractures were treated with oral bisphosphonates (BPs). Of 685 women recruited, 179 (26.1%) received BP treatment. By the third year of AI therapy, this group exhibited increased BMD in the lumbar spine (LS; 2.59%) and femoral neck (FN; 2.50%), although the increase was significant only within the first year (LS: 1.99% and FN: 2.04%). Despite BP therapy, however, approximately 15% of these patients lost more than 3% of their baseline bone mass. At 3 years, patients without BP experienced BMD decreases in the LS (-3.10%) and FN (-2.79%). In this group, BMD changes occurred during the first (LS: -1.33% and FN: -1.25%), second (LS: -1.19% and FN: -0.82%), and third (LS: -0.57% and FN: -0.65%) years of AI treatment. Increased BMD (>3%) was observed in just 7.6% and 10.8% of these patients at the LS and FN, respectively. Our data confirm a clinically relevant bone loss associated with AI therapy amongst nonusers of preventative BPs. We further report on the importance of BMD monitoring as well as calcium and 25-hydroxy vitamin D supplementation in these patients.

MAPK1/ERK2 as novel target genes for pain in head and neck cancer patients

Background

Genetic susceptibility plays an important role in the risk of developing pain in individuals with cancer. As a complex trait, multiple genes underlie this susceptibility. We used gene network analyses to identify novel target genes associated with pain in patients newly diagnosed with squamous cell carcinoma of the head and neck (HNSCC).

Results

We first identified 36 cancer pain-related genes (i.e., focus genes) from 36 publications based on a literature search. The Ingenuity Pathway Analysis (IPA) analysis identified additional genes that are functionally related to the 36 focus genes through pathway relationships yielding a total of 82 genes. Subsequently, 800 SNPs within the 82 IPA-selected genes on the Illumina HumanOmniExpress-12v1 platform were selected from a large-scale genotyping effort. Association analyses between the 800 candidate SNPs (covering 82 genes) and pain in a patient cohort of 1368 patients with HNSCC (206 patients with severe pain vs. 1162 with non-severe pain) showed the highest significance for MAPK1/ERK2, a gene belonging to the MAP kinase family (rs8136867, p value = 8.92 × 10⁻⁴; odds ratio [OR] = 1.33, 95 % confidence interval [CI]: 1.13–1.58). Other top genes were PIK3C2G (a member of PI3K [complex], rs10770367, p value = 1.10 × 10⁻³; OR = 1.46, 95 % CI: 1.16–1.82), TCRA (the alpha chain of T-cell receptor, rs6572493, p value = 2.84 × 10⁻³; OR = 0.70, 95 % CI: 0.55–0.88), PDGFC (platelet-derived growth factor C, rs6845322, p value = 4.88 × 10⁻³; OR = 1.32, 95 % CI: 1.09–1.60), and CD247 (a member of CD3, rs2995082, p value = 7.79 × 10⁻³; OR = 0.76, 95 % CI: 0.62–0.93).

Conclusions

Our findings provide novel candidate genes and biological pathways underlying pain in cancer patients. Further study of the variations of these candidate genes could inform clinical decision making when treating cancer pain.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0348-7) contains supplementary material, which is available to authorized users.

Genetic variant in the osteoprotegerin gene is associated with aromatase inhibitor-related musculoskeletal toxicity in breast cancer patients

BACKGROUND

Aromatase inhibitor (AI) therapy is associated with musculoskeletal (MS) toxicity, which adversely affects quality of life and therapy adherence. Our objective was to evaluate whether genetic variants may predict endocrine therapy-related MS pain and hot flashes in a prospective observational cohort study.

PATIENTS & METHODS

254 early breast cancer patients starting AI (n = 159) or tamoxifen therapy (n = 95) were included in this genetic biomarker study. MS and vasomotor symptoms were assessed at baseline and after 3, 6 and 12 months of therapy. AI-induced MS pain was defined as an increase in arthralgia or myalgia relative to baseline. Single nucleotide polymorphisms (SNP) in candidate genes involved in oestrogen signalling or previously associated with AI-related MS pain or oestrogen levels were selected.

RESULTS

Overall, 13 SNPs in CYP19, CYP17, osteoprotegerin (OPG) and oestrogen receptor 1 exhibited an allele frequency >0.05 and were included in the analysis. Patients carrying the G allele of rs2073618 in OPG experienced significantly more AI-induced MS toxicity compared to the wildtype allele, after correction for multiple testing (P = 0.046). Furthermore, this SNP was associated with severity of pain (P = 0.018). No association was found with regard to the other SNPs, both in AI and tamoxifen-treated patients. Neither could an association with vasomotor symptoms be demonstrated.

CONCLUSION

The SNP rs2073618 in OPG is associated with an increased risk of MS symptoms and pain with AI therapy, which has not been reported previously. Validation of this finding in larger cohorts and further functional studies are required.

Effect of age on drug metabolism in women with breast cancer

INTRODUCTION

The aging of the population will increase the number of breast cancer patients requiring treatment in both the adjuvant and metastatic setting. Hormones, chemotherapy and targeted drugs all have a role in treatment. Older patients have been underrepresented in clinical trials making evidence-based decisions difficult. The increase in comorbidity and aging, polypharmacy and changes in function make pharmacotherapy decisions more complicated. Knowledge of the issues is critical in the prescribing of effective and safe therapy. There are factors associated with advancing age that can result in pharmacokinetic and pharmacodynamic variations in processing of hormonal agents, chemotherapy and targeted drugs.

AREAS COVERED

A review of the literature pertaining to pharmacokinetic changes in aging in breast cancer was untaken. Studies are reviewed involving single agents and some combinations.

EXPERT OPINION

Older patients should be considered for standard therapies. Their specific problems need to be evaluated by geriatric-specific assessment including functional status, end organ dysfunction and polypharmacy. There are few instances for age-related changes in pharmacokinetics and when present are usually not clinically significant. When changes are present, they are often the result of comorbidity, drug interactions and drug scheduling issues. The older patients may be more sensitive to certain toxicities such as cardiac toxicity, neuropathy and myelosuppression.

Aromatase inhibitor induced musculoskeletal syndrome: a significant problem with limited treatment options

BACKGROUND

Aromatase inhibitor induced musculoskeletal syndrome is experienced by approximately half of women taking aromatase inhibitors, impairing quality of life and leading some to discontinue treatment. Evidence for effective treatments is lacking. We aimed to understand the manifestations and impact of this syndrome in the Australian breast cancer community, and strategies used for its management.

METHODS

A survey invitation was sent to 2390 members of the Breast Cancer Network Australia Review and Survey Group in April 2014. The online questionnaire included 45 questions covering demographics, aromatase inhibitor use, clinical manifestations and risk factors for the aromatase inhibitor musculoskeletal syndrome, reasons for treatment discontinuation and efficacy of interventions used.

RESULTS

Aromatase inhibitor induced musculoskeletal syndrome was reported by 302 (82 %) of 370 respondents. Twenty-seven percent had discontinued treatment for any reason and of these, 68 % discontinued because of the musculoskeletal syndrome. Eighty-one percent had used at least one intervention from the following three categories to manage the syndrome: doctor prescribed medications, over-the-counter/complementary medicines or alternative/non-drug therapies. Anti-inflammatories, paracetamol (acetaminophen) and yoga were most successful in relieving symptoms in each of the respective categories. Almost a third of respondents reported that one or more interventions helped prevent aromatase inhibitor discontinuation. However, approximately 20 % of respondents found no intervention effective in any category.

CONCLUSION

We conclude that aromatase inhibitor induced musculoskeletal syndrome is a significant issue for Australian women and is an important reason for treatment discontinuation. Women use a variety of interventions to manage this syndrome; however, their efficacy appears limited.

Skeletal adverse effects with aromatase inhibitors in early breast cancer: evidence to date and clinical guidance

Aromatase inhibitors (AIs) are routinely used in the adjuvant treatment of women with hormone receptor-positive early breast cancer. Patients who receive AIs have an increased risk of bone loss and arthralgia compared with those treated with tamoxifen. In addition to the effects of AIs, the population of women with early breast cancer has a high prevalence of 25-hydroxyvitamin D (25(OH)D) insufficiency. In our experience 88% of patients had concentrations lower than 30 ng/ml. Vitamin D supplementation should be adapted to the baseline concentration. Another relevant finding in our research program was the close relationship between 25(OH)D levels and intensity of AI-related arthralgia (AIrA). A target concentration of 40 ng/ml 25(OH)D may prevent development of AIrA. We also demonstrate that AIrA is genetically determined: single nucleotide polymorphisms located in genes encoding key factors for the metabolism of estrogens and vitamin D (CYP17A1, VDR, and CYP27B1) are associated with self-reported arthralgia during AI therapy. We recommend establishing an individualized protocol of bone-health surveillance based on baseline and evolutionary clinical variables.

Symptoms: Aromatase Inhibitor Induced Arthralgias

Recent clinical trials have demonstrated that aromatase inhibitors (AIs) are slightly more effective than tamoxifen at reducing breast cancer recurrences. However, breast cancer patients receiving AIs have a higher incidence of musculoskeletal symptoms, particularly joint pain and stiffness. Musculoskeletal pain and stiffness can lead to noncompliance and increased utilization of health care resources. There is a suggestion that the syndrome is the result of estrogen deprivation and may share components with autoimmune diseases such as Sjögren's syndrome. Several factors may increase the likelihood of developing AI arthralgia, such as prior chemotherapy, prior hormone replacement therapy, and increased weight; there are inconsistencies with regard to the data on genetic predispositions to this syndrome. While several studies have been done to evaluate interventions to treat or prevent AI arthralgia, no clear treatment has emerged as being particularly beneficial. Much of the research has been limited by small sample size, difficulty blinding patients to placebo, inconsistent definitions of the syndrome, multiple patient reported outcomes, lack of objective outcome measures and heterogeneous patient populations. We are at the early stages of research in characterizing, understanding etiology, preventing and treating AI arthralgias; however much work is being done in this area which, hopefully, will ultimately improve the lives of women with breast cancer.