Browsing by Author "Stearns, Vered"

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    A Cohort Study to Evaluate Genetic Predictors of Aromatase Inhibitor Musculoskeletal Symptoms: Results from ECOG-ACRIN E1Z11
    (American Association for Cancer Research, 2024) Stearns, Vered; Jegede, Opeyemi A.; Chang, Victor T-S; Skaar, Todd C.; Berenberg, Jeffrey L.; Nand, Ranveer; Shafqat, Atif; Jacobs, Nisha L.; Luginbuhl, William; Gilman, Paul; Benson, Al B., III; Goodman, Judie R.; Buchschacher, Gary L., Jr.; Henry, N. Lynn; Loprinzi, Charles L.; Flynn, Patrick J.; Mitchell, Edith P.; Fisch, Michael J.; Sparano, Joseph A.; Wagner, Lynne I.; Pharmacology and Toxicology, School of Medicine
    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.
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    Association between CYP2D6 genotype and tamoxifen-induced hot flashes in a prospective cohort
    (Springer, 2009-10) Henry, N. Lynn; Rae, James M.; Li, Lang; Azzouz, Faouzi; Skaar, Todd C.; Desta, Zereunesay; Sikora, Matthew J.; Philips, Santosh; Nguyen, Anne T.; Storniolo, Anna Maria; Hayes, Daniel F.; Flockhart, David A.; Stearns, Vered
    Women with reduced CYP2D6 activity have low endoxifen concentrations and likely worse long term benefits from tamoxifen. We investigated the association between CYP2D6 genotype and tamoxifen-induced hot flashes in a prospective cohort. We collected hot flash frequency and severity data over 12 months from 297 women initiating tamoxifen. We performed CYP2D6 genotyping using the AmpliChip CYP450 test and correlated inherited genetic polymorphisms in CYP2D6 and tamoxifen-induced hot flashes. Intermediate metabolizers had greater mean hot flash scores after 4 months of tamoxifen therapy (44.3) compared to poor metabolizers (20.6, P = 0.038) or extensive metabolizers (26.9, P = 0.011). At 4 months, we observed a trend toward fewer severe hot flashes in poor metabolizers compared to intermediate plus extensive metabolizers (P = 0.062). CYP2D6 activity may be a modest predictive factor for tamoxifen-induced hot flashes. The presence or absence of hot flashes should not be used to determine tamoxifen's efficacy.
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    Association of Variants in Candidate Genes with Lipid Profiles in Women with Early Breast Cancer on Adjuvant Aromatase Inhibitor Therapy
    (American Association for Cancer Research, 2016-03-15) Santa-Maria, Cesar A.; Blackford, Amanda; Nguyen, Anne T.; Skaar, Todd C.; Philips, Santosh; Oesterreich, Steffi; Rae, James M.; Desta, Zeruesenay; Robarge, Jason; Henry, Norah Lynn; Storniolo, Anna M.; Hayes, Daniel F.; Blumenthal, Roger S.; Ouyang, Pamela; Post, Wendy S.; Flockhart, David A.; Stearns, Vered; Medicine, School of Medicine
    Purpose: Aromatase inhibitors can exert unfavorable effects on lipid profiles; however, previous studies have reported inconsistent results. We describe the association of single-nucleotide polymorphisms (SNP) in candidate genes with lipid profiles in women treated with adjuvant aromatase inhibitors. Experimental design: We conducted a prospective observational study to test the associations between SNPs in candidate genes in estrogen signaling and aromatase inhibitor metabolism pathways with fasting lipid profiles during the first 3 months of aromatase inhibitor therapy in postmenopausal women with early breast cancer randomized to adjuvant letrozole or exemestane. We performed genetic association analysis and multivariable linear regressions using dominant, recessive, and additive models. Results: A total of 303 women had complete genetic and lipid data and were evaluable for analysis. In letrozole-treated patients, SNPs in CYP19A1, including rs4646, rs10046, rs700518, rs749292, rs2289106, rs3759811, and rs4775936 were significantly associated with decreases in triglycerides by 20.2 mg/dL and 39.3 mg/dL (P < 0.00053), respectively, and with variable changes in high-density lipoprotein (HDL-C) from decreases by 4.2 mg/dL to increases by 9.8 mg/dL (P < 0.00053). Conclusions: Variants in CYP19A1 are associated with decreases in triglycerides and variable changes in HDL-C in postmenopausal women on adjuvant aromatase inhibitors. Future studies are needed to validate these findings, and to identify breast cancer survivors who are at higher risk for cardiovascular disease with aromatase inhibitor therapy.
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    Associations between genetic variants and the effect of letrozole and exemestane on bone mass and bone turnover
    (SpringerLink, 2015-11) Oesterreich, Steffi; Henry, N. Lynn; Kidwell, Kelley M.; Van Poznak, Catherine H.; Skaar, Todd C.; Dantzer, Jessica; Li, Lang; Hangartner, Thomas N.; Peacock, Munro; Nguyen, Anne T.; Rae, James M.; Desta, Zeruesenay; Philips, Santosh; Storniolo, Anna M.; Stearns, Vered; Hayes, Daniel F.; Flockhart, David A.; Medicine, School of Medicine
    Adjuvant therapy for hormone receptor (HR) positive postmenopausal breast cancer patients includes aromatase inhibitors (AI). While both the non-steroidal AI letrozole and the steroidal AI exemestane decrease serum estrogen concentrations, there is evidence that exemestane may be less detrimental to bone. We hypothesized that single nucleotide polymorphisms (SNP) predict effects of AIs on bone turnover. Early stage HR-positive breast cancer patients were enrolled in a randomized trial of exemestane versus letrozole. Effects of AI on bone mineral density (BMD) and bone turnover markers (BTM), and associations between SNPs in 24 candidate genes and changes in BMD or BTM were determined. Of the 503 enrolled patients, paired BMD data were available for 123 and 101 patients treated with letrozole and exemestane, respectively, and paired BTM data were available for 175 and 173 patients, respectively. The mean change in lumbar spine BMD was significantly greater for letrozole-treated (-3.2 %) compared to exemestane-treated patients (-1.0 %) (p = 0.0016). Urine N-telopeptide was significantly increased in patients treated with exemestane (p = 0.001) but not letrozole. Two SNPs (rs4870061 and rs9322335) in ESR1 and one SNP (rs10140457) in ESR2 were associated with decreased BMD in letrozole-treated patients. In the exemestane-treated patients, SNPs in ESR1 (Rs2813543) and CYP19A1 (Rs6493497) were associated with decreased bone density. Exemestane had a less negative impact on bone density compared to letrozole, and the effects of AI therapy on bone may be impacted by genetic variants in the ER pathway.
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    Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow
    (Frontiers, 2022-11-14) Leal, Jeffrey P.; Rowe, Steven P.; Stearns, Vered; Connolly, Roisin M.; Vaklavas, Christos; Liu, Minetta C.; Storniolo, Anna Maria; Wahl, Richard L.; Pomper, Martin G.; Solnes, Lilja B.; Medicine, School of Medicine
    Applications based on artificial intelligence (AI) and deep learning (DL) are rapidly being developed to assist in the detection and characterization of lesions on medical images. In this study, we developed and examined an image-processing workflow that incorporates both traditional image processing with AI technology and utilizes a standards-based approach for disease identification and quantitation to segment and classify tissue within a whole-body [18F]FDG PET/CT study. Methods One hundred thirty baseline PET/CT studies from two multi-institutional preoperative clinical trials in early-stage breast cancer were semi-automatically segmented using techniques based on PERCIST v1.0 thresholds and the individual segmentations classified as to tissue type by an experienced nuclear medicine physician. These classifications were then used to train a convolutional neural network (CNN) to automatically accomplish the same tasks. Results Our CNN-based workflow demonstrated Sensitivity at detecting disease (either primary lesion or lymphadenopathy) of 0.96 (95% CI [0.9, 1.0], 99% CI [0.87,1.00]), Specificity of 1.00 (95% CI [1.0,1.0], 99% CI [1.0,1.0]), DICE score of 0.94 (95% CI [0.89, 0.99], 99% CI [0.86, 1.00]), and Jaccard score of 0.89 (95% CI [0.80, 0.98], 99% CI [0.74, 1.00]). Conclusion This pilot work has demonstrated the ability of AI-based workflow using DL-CNNs to specifically identify breast cancer tissue as determined by [18F]FDG avidity in a PET/CT study. The high sensitivity and specificity of the network supports the idea that AI can be trained to recognize specific tissue signatures, both normal and disease, in molecular imaging studies using radiopharmaceuticals. Future work will explore the applicability of these techniques to other disease types and alternative radiotracers, as well as explore the accuracy of fully automated and quantitative detection and response assessment.
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    Changes in breast density and circulating estrogens in postmenopausal women receiving adjuvant anastrozole
    (AACR, 2011-12) Prowell, Tatiana M.; Blackford, Amanda L.; Byrne, Celia; Khouri, Nagi F.; Dowsett, Mitchell; Folkerd, Elizabeth; Tarpinian, Karineh S.; Powers, Pendleton P.; Wright, Laurie A.; Donehower, Michele G.; Jeter, Stacie C.; Armstrong, Deborah K.; Emens, Leisha A.; Fetting, John H.; Wolff, Antonio C.; Garrett-Mayer, Elizabeth; Skaar, Todd C.; Davidson, Nancy E.; Stearns, Vered
    Factors associated with an increased risk of breast cancer include prior breast cancer, high circulating estrogens, and increased breast density. Adjuvant aromatase inhibitors are associated with a reduction in incidence of contralateral breast cancer. We conducted a prospective, single-arm, single-institution study to determine whether use of anastrozole is associated with changes in contralateral breast density and circulating estrogens. Eligible patients included postmenopausal women with hormone receptor-positive early-stage breast cancer who had completed local therapy, had an intact contralateral breast, and were recommended an aromatase inhibitor as their only systemic therapy. Participants received anastrozole 1 mg daily for 12 months on study. We assessed contralateral breast density and serum estrogens at baseline, 6, and 12 months. The primary endpoint was change in contralateral percent breast density from baseline to 12 months. Secondary endpoints included change in serum estrone sulfate from baseline to 12 months. Fifty-four patients were accrued. At 12 months, compared with baseline, there was a nonstatistically significant reduction in breast density (mean change: -16%, 95% CI: -30 to 2, P = 0.08) and a significant reduction in estrone sulfate (mean change: -93%, 95% CI: -94 to -91, P < 0.001). Eighteen women achieved 20% or greater relative reduction in contralateral percent density at 12 months compared with baseline; however, no measured patient or disease characteristics distinguished these women from the overall population. Large trials are required to provide additional data on the relationship between aromatase inhibitors and breast density and, more importantly, whether observed changes in breast density correlate with meaningful disease-specific outcomes.
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    Composite Functional Genetic and Comedication CYP2D6 Activity Score in Predicting Tamoxifen Drug Exposure Among Breast Cancer Patients
    (Wiley, 2010-04) Borges, Silvana; Desta, Zeruesenay; Jin, Yan; Faouzi, Azzouz; Robarge, Jason D.; Philip, Santosh; Nguyen, Anne; Stearns, Vered; Hayes, Daniel; Rae, James M.; Skaar, Todd C.; Flockhart, David A.; Li, Lang
    Accurate assessment of CYP2D6 phenotypes from genotype is inadequate in patients taking CYP2D6 substrate together with CYP2D6 inhibitors. A novel CYP2D6 scoring system is proposed that incorporates the impact of concomitant medications with the genotype in calculating the CYP2D6 activity score. Training (n = 159) and validation (n = 81) data sets were obtained from a prospective cohort tamoxifen pharmacogenetics registry. Two inhibitor factors were defined: 1 genotype independent and 1 genotype based. Three CYP2D6 gene scoring systems, and their combination with the inhibitor factors, were compared. These 3 scores were based on Zineh, Zanger, and Gaedigk's approaches. Endoxifen/NDM-Tam plasma ratio was used as the phenotype. The overall performance of the 3 gene scoring systems without consideration of CYP2D6-inhibiting medications in predicting CYP2D6 phenotype was poor in both the training set (R(2) = 0.24, 0.22, and 0.18) and the validation set (R(2) = 0.30, 0.24, and 0.15). Once the CYP2D6 genotype-independent inhibitor factor was integrated into the score calculation, the R(2) values in the training and validation data sets were nearly twice as high as the genotype-only scoring model: (0.44, 0.43, 0.38) and (0.53, 0.50, 0.41), respectively. The integration of the inhibitory effect of concomitant medications with the CYP2D6 genotype into the composite CYP2D6 activity score doubled the ability to predict the CYP2D6 phenotype. However, endoxifen phenotypes still varied substantially, even with incorporation of CYD2D6 genotype and inhibiting factors, suggesting that other, as yet unidentified factors must be involved in tamoxifen activation.
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    CYP2D6 Activity in Patients with Metastatic Breast Cancer Treated with Single Agent Tamoxifen: Results from ECOG-ACRIN E3108
    (Springer, 2025) Stearns, Vered; ONeill, Anne; Schneider, Bryan P.; Skaar, Todd C.; Liu, Minetta C.; Lohrisch, Caroline; Goetz, Matthew P.; Vallejos, Carlos S.; Sparano, Joseph A.; Villa, Diego; Silverman, Paula; Cheema, Puneet S.; Moore, Dennis F., Jr.; Sledge, George W., Jr.; Medicine, School of Medicine
    Purpose: In tamoxifen-treated individuals, reduced-function genetic variants in the CYP2D6 gene or inhibition of the enzyme result in low circulating endoxifen concentrations. We assessed the impact of reduced CYP2D6 activity and circulating endoxifen concentrations on breast cancer outcomes. Patients and methods: Patients with locally advanced or stage IV hormone receptor-positive breast cancer were enrolled in this single arm phase II trial and received open label tamoxifen 20 mg PO daily. The primary objective was to assess CYP2D6 poor metabolizer (PM) vs intermediate and normal metabolizer status (IM + NM) with progression-free survival (PFS). CYP2D6 phenotype was determined from whole blood samples (Roche Amplichip), and secondary endpoint evaluated endoxifen concentrations determined from 3 month post registration plasma samples (Quest Diagnostics). Results: From September 2010 to June 2013, 113 of planned 204 patients were registered to the trial and began protocol treatment. Accrual to the trial closed early due to lower-than-expected rate of CYP2D6 poor metabolizers. Median age was 62, 86% (97/113) were white, 33% (30/113) Hispanic, 83% (92/113) postmenopausal. Samples were evaluable for CYP2D6 in 75% (85/113) of patients (2/85 PM, 27/85 IM, and 56/85 NM). Median PFS for PM and IM + NM was 12.9 months and 6.9 months, respectively. Median PFS was 11.1 and 13.8 months respectively for patients with low (≤ 15.5) and high (> 15.5) endoxifen concentrations (ng/ml). Conclusion: We did not observe significant associations between CYP2D6 metabolizer status or endoxifen with PFS. Small sample sizes and barriers to adequate samples in this trial prohibited determination of relationship between these markers and PFS.
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    Effects of exemestane and letrozole therapy on plasma concentrations of estrogens in a randomized trial of postmenopausal women with breast cancer
    (Springer, 2017-02) Robarge, Jason D.; Desta, Zereunesay; Nguyen, Anne T.; Li, Lang; Hertz, Daniel; Rae, James M.; Hayes, Daniel F.; Storniolo, Anna M.; Stearns, Vered; Flockhart, David A.; Skaar, Todd C.; Henry, N. Lynn; Medicine, School of Medicine
    PURPOSE: Inter-individual differences in estrogen concentrations during treatment with aromatase inhibitors (AIs) may contribute to therapeutic response and toxicity. The aim of this study was to determine plasma concentrations of estradiol (E2), estrone (E1), and estrone sulfate (E1S) in a large cohort of AI-treated breast cancer patients. METHODS: In a randomized, multicenter trial of postmenopausal women with early-stage breast cancer starting treatment with letrozole (n = 241) or exemestane (n = 228), plasma estrogen concentrations at baseline and after 3 months were quantitated using a sensitive mass spectrometry-based assay. Concentrations and suppression below the lower limit of quantification (LLOQ) were compared between estrogens and between drugs. RESULTS: The ranges of baseline estrogen concentrations were
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    Effects of SLCO1B1 polymorphisms on plasma estrogen concentrations in women with breast cancer receiving aromatase inhibitors exemestane and letrozole
    (Future Medicine, 2019-06-13) Dempsey, Jacqueline M.; Kidwell, Kelley M.; Gersch, Christina L; Pesch, Andrea M; Desta, Zeruesenay; Storniolo, Anna Maria; Stearns, Vered; Skaar, Todd C.; Hayes, Daniel F; Henry, N Lynn; Rae, James M; Hertz, Daniel L; Medicine, School of Medicine
    Aim: This study tested for associations between SLCO1B1 polymorphisms and circulating estrogen levels in women with breast cancer treated with letrozole or exemestane. Patients & methods: Postmenopausal women with hormone-receptor positive breast cancer were genotyped for SLCO1B1*5 (rs4149056) and rs10841753. Pretreatment and on-treatment plasma estrogens and aromatase inhibitor (AI) concentrations were measured. Regression analyses were performed to test for pharmacogenetic associations with estrogens and drug concentrations. Results: SLCO1B1*5 was associated with elevated pretreatment estrone sulfate and an increased risk of detectable estrone concentrations after 3 months of AI treatment. Conclusion: These findings suggest SLCO1B1 polymorphisms may have an effect on estrogenic response to AI treatment, and therefore may adversely impact the anticancer effectiveness of these agents.