Weinshilboum, Richard M.

Abstract Background: Androgen receptor (AR) is expressed in 60%-90% of breast cancers. The role of AR in breast cancer largely depends on estrogen receptor (ER) status and remains controversial. In ER+ cancers, AR expression is associated with improved prognosis. Enzalutamide (ENZ), an AR antagonist, impairs AR signaling, inhibits ER+/AR+ breast cancer cell proliferation and has been shown to mitigate resistance to anti-estrogen therapies. A recent study identified that RAD140, an AR agonist, suppressed the growth of ER+/AR+ breast cancer via stimulating AR signaling, resulting in down regulation of ERα. Both AR agonists and antagonists are effective in treating ER+ breast cancers. Identifying the subgroup of patients who most likely will benefit from an individual drug is important in clinical practice. Here, we sought to characterize the relative AR to ER levels and their relationships to drug response in ER+ breast cancers.Methods: We evaluated AR and ER expression levels among 68 samples with ER+ breast cancers. On each tumor, IHC staining for AR and ER were performed and results were scored by multiplying the percentage of positive cells by the intensity. TCGA-RPPA (reverse phase protein array) dataset was used to verify AR protein distribution in ER+ cancers. We created MCF7 and T47D cells with doxycycline-inducible AR and ER expression system to manipulate the relative AR to ER ratios and determined the antitumor activity of ENZ and RAD140 by cell proliferation assays. The levels of AR and ER in cells were measured by western blot. Linear regression was used to test the association between dose-response area under curve (AUC) and AR, ER levels. Drug preference was modeled against AR/ER expression levels (AR/ER ratios) using logistic regression.Results: Among 68 ER+ breast cancers, 69.12% were AR-positive. More than 2/3 cases (48 of 68) had more ER than AR expressed. The AR to ER ratios varied from 0 to 6. In the TCGA cohort, 84.15% of 347 ER+ patients had AR/ER ratios less than 1.The range of AR to ER ratios in TCGA dataset were comparable with our data (0.004 to 4.210). In our cell line models, the AR/ER ratios were controlled between 0.19 to 4.05. We found that the AUC of RAD140 was negatively associated with AR protein levels (P=0.008) and AR/ER ratios (P=0.013), and not significantly associated with ER expression levels. On the other hand, the AUC of ENZ was significantly negatively associated with ER protein (P=0.0016) but postiviely associated with AR/ER ratio (p=0.037). Preferred treatment comparing efficacy of the two drug can be best determined at extremes of AR/ER ratios. Using clinically relevant dosages, our model predicted that ENZ (10µM) would be a preferred treatment choice and have a better treatment efficacy compared with RAD140 when the AR/ER ratio was ≤ 0.42, whereas RAD140 (1µM) would be the preferred choice with a better treatment efficacy compared with ENZ when AR/ER ratios were ≥ 3.1 The efficacy preference of the two drugs are equivocal for AR/ER ratios between 0.42 and 3.10. Conclusion: We developed preclinical models using AR and ER expression levels to predict AR-targeting drug response. The results support the use of RAD140 in AR high patients and those with an AR/ER ratio >3.10, and enzalutamide in AR low patients and those with an AR/ER ratio <0.42. Equipoise on choice of drug was found for AR/ER ratios of 0.42-3.10. RAD140 and enzalutamide are compelling candidates for monotherapy or combination with anti-estrogen therapies in ER+/AR+ breast cancer. Future clinical validation of the models and therapeutic effect is warranted. Citation Format: Lixuan Wei, Huanyao Gao, Jia Yu, Duan Liu, Huan Zhang, Thanh Nguyen, Marie R Passow, Jodi M Carter, Richard M Weinshilboum, James N Ingle, Liewei Wang. Computational modeling of androgen receptor (AR) and estrogen receptor as predictive biomarkers of response to AR agonists and antagonists [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-36.

Abstract Background: Cyclin dependent 4/6 kinase inhibitors (CDK4/6i) and endocrine therapy (ET) have improved progression-free survival (PFS) and overall survival in hormone-receptor (HR)-positive metastatic breast cancer (MBC), but progression of disease is inevitable. Serum thymidine kinase-1 (TK1) is a secreted marker of proliferation that is prognostic in patients (pts) with HR-positive, HER2-negative MBC and may be predictive of ET and CDK 4/6i response. PROMISE (NCT0281902) is a prospective study enrolling women with HR-positive MBC starting palbociclib (Pb) + letrozole (L) (1st line) or Pb + fulvestrant (2nd line). We undertook a comprehensive “omic” assessment of blood, tumor, urine and the fecal microbiome in order to identify novel genomic variants and pathways associated with an early decline in TK1 (measured after 2 months) and PFS. Additionally, patient derived xenografts/organoids were generated at baseline and progression to test new therapeutic approaches to overcome resistance to CDK4/6i and ET. We report the initial association between the baseline genomic landscape and baseline TK1 levels. Methods: FFPE tumor biopsies were obtained for DNA/RNA sequencing (TempusTM) and blood samples for TK1 (Divitum® assay, Biovica) were collected pretreatment (pre-Pb) and after 2 cycles of Pb + ET (post-Pb2). Both whole-exome (exome capture) sequencing (WES) and RNA-Seq used the Integrated DNA Technologies xGen Exome Research Panel v1.0 capture kit. TK1+ disease was defined as > 200 Du/L and TK1- disease as below limit of detection up to 200 Du/L. We tested the association between genomic and transcriptomic characteristics with baseline TK1 data in pretreatment samples where both WES and RNA-seq and TK1 was available. The data were analyzed using bioinformatics pipelines for somatic and germline mutations and copy number alterations. The current analysis focuses on baseline 1st-line pre-Pb omics data in conjunction with baseline TK1 levels. The database was locked for analysis on 5/29/2020. Results: Thirty-three pts (median age: 59 yrs.) were evaluable, with paired samples for TK1 in 32. Six pts had TK1+ disease pre-Pb and post-Pb2. Twenty-two pts had TK1- disease pre-Pb and post-Pb2. Four pts had a decrease in TK1 after 2 cycles of treatment that altered the classification from TK1+ to TK1-. Both baseline RNA seq and serum TK1 (n=16) were available for 4 TK1+ and 12 TK1- pts. In this group, 476 genes were differentially regulated (398 upregulated; 78 downregulated). Pathway analysis demonstrated enrichment in complement and coagulation cascade pathway, PPAR signaling pathway, and metabolism-related pathways related to up-regulation of CYP and UGT gene families. Further testing for the association of WES data with baseline TK1+ (n=8) and TK1- (n=16) disease demonstrated somatic copy number variations on chromosomes 6, 11, 12 and 15. CDK4 copy number gains were observed in 3/8 TK1+ pts and 0/16 TK1- pts. We also observed that somatic mutations (LOH, copy number and/or SNV/INDELs) were more prevalent in the TK1+ compared to the TK1- pre-Pb group in several cancer-associated genes (FAS [p=0.06] PTEN, PIK3CB, NAB2, SOX9 and FAT1 [p=0.08], TP53, and MAP2K4 [p=0.22]). Conversely, we also noted that 6/7 pts with GATA3 mutations had TK1- disease (p=0.23). Conclusions: Using a comprehensive “omics” approach, our data suggest that a secreted biomarker of proliferation (TK1) obtained prior to initiating CDK4/6i and ET for the first line treatment of HR+ MBC is associated with established and novel genes and pathways associated with prognosis of pts receiving ET and CDK 4/6i. Analysis of on-treatment (after 2 cycles) tumor RNA seq and its association with change in TK1 as well as data from the 2nd-line cohort will be presented at the meeting. Citation Format: Ciara C O Sullivan, Krishna R Kalari, Vera J Suman, Peter T Vedell, Ann Moyer, Abraham D Eyman Casey, Jason Sinnwell, Xiaojia Tang, Kevin Thompson, Alvaro Moreno-Aspitia, Donald W Northfelt, Minetta C Liu, Tufia C Haddad, Saranya Chumsri, Prema Peethambaram, Kathryn J Ruddy, Karthik V Giridhar, Roberto A Leon-Ferre, Adrian Nordmark, Mattias Bergqvist, Brendan P McMenomy, Richard M Weinshilboum, Liewei Wang, Matthew P Goetz. Novel genomic variants and pathways associated with baseline serum thymidine kinase 1 levels in HR-positive HER2-negative MBC patients commencing palbociclib and letrozole [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-24.

Abstract Purpose: To determine genetic variants that could differentiate aromatase inhibitors (AIs) efficacy in early stage breast cancer. Experimental Design: We performed a stratified cox-proportional hazards analysis utilizing stratification factors and other covariates examining Breast Cancer Free Interval (BCFI) SNP-treatment interaction in Caucasian patients entered on the MA.27 trial. This analysis involved 4465 patients (2226 on anastrozole and 2239 on exemestane arm) including 245 (121 on anastrozole and 124 events on exemestane arm) with a breast event. Preclinical laboratory studies included luciferase activity, chromatin immunoprecipitation (ChIP) assay, and cell migration assays. Results: We identified 887 SNPs with a p-value <1E-4 that could differentiate anastrozole from exemestane efficacy. We next used GTEx databases to determine whether these SNPs might be cis-eQTLs with nearby genes, and found that 95 SNPs were eQTL with 14 genes. Functional validation of SNP effect in these 14 genes on response to anastrozole and exemestane revealed that 3 SNPs showed genotype-dependent differences between anastrozole and exemestane. Two of the three SNPs, rs1877193 and rs6735923 located upstream of LY75 gene, were associated with higher LY75 gene expression. Our drug-SNP interaction GWAS showed that both SNPs were associated with better BCFI for exemestane compared to anastrozole (HR= 0.447, 0.458). The SNP rs62293499 located downstream of the GPR160 gene was also associated with better BCFI for exemestane compared to anastrozole (HR=0.433). Interestingly, all 3 SNPs were associated with worse outcome (shorter BCFI) in anastrozole treated patients (HR=1.39~1.58), but with longer BCFI in the exemestane treated patients (HR=0.58~0.71) based on our GWAS results in MA.27 trial. However, all 3 SNPs showed no association with BCFI if the two treatment arms, anastrozole and exemestane, were combined (HR=0.92~1.08). Consistently, cells with Ly75 or GPR160 SNP variant genotypes were more sensitive to exemestane compared to anastrozole. Mechanistically, the 3 SNPs regulated estrogen receptor-dependant LY75 and GPR160 expression. LY75 suppression induced epithelial-to-mesenchymal transition (EMT) in breast cancer cell lines, accompanied by increased migratory capacity in vitro. LY75 knockdown also resulted in predominant downregulation of functional pathways such as cell proliferation, while pathways associated with mesenchymal stimulation were generally increased. GPR160 knockdown also resulted in downregulation of cell proliferation pathways. Conclusions: This SNP genotype and AI treatment interaction clinical study revealed unique genetic variants that differentiate anastrozole and exemestane efficacy. The signals were lost in the GWAS analysis when anastrozole and exemestane were combined. Preclinical laboratory studies revealed novel functions of LY75 and GPR160 in breast cancer. These findings represent potential steps towards individualized AI therapy. Citation Format: Junmei Cairns, James N. Ingle, Krishna R. Kalari, Lois E. Shepherd, Matthew J. Ellis, Paul E. Goss, Poulami Barman, Erin E. Carlson, Matthew P. Goetz, Richard M. Weinshilboum, Liewei Wang. The interaction between SNP genotype and aromatase inhibitor treatment response in early breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-103.

Aromatase inhibitors (AIs) reduce breast cancer recurrence and prolong survival, but up to 30% of patients exhibit recurrence. Using a genome-wide association study of patients entered on MA.27, a phase III randomized trial of anastrozole versus exemestane, we identified a single nucleotide polymorphism (SNP) in CUB And Sushi multiple domains 1 ( CSMD1) associated with breast cancer–free interval, with the variant allele associated with fewer distant recurrences. Mechanistically, CSMD1 regulates CYP19 expression in an SNP- and drug-dependent fashion, and this regulation is different among 3 AIs: anastrozole, exemestane, and letrozole. Overexpression of CSMD1 sensitized AI-resistant cells to anastrozole but not to the other 2 AIs. The SNP in CSMD1 that was associated with increased CSMD1 and CYP19 expression levels increased anastrozole sensitivity, but not letrozole or exemestane sensitivity. Anastrozole degrades estrogen receptor α (ERα), especially in the presence of estradiol (E2). ER + breast cancer organoids and AI- or fulvestrant-resistant breast cancer cells were more sensitive to anastrozole plus E2 than to AI alone. Our findings suggest that the CSMD1 SNP might help to predict AI response, and anastrozole plus E2 serves as a potential new therapeutic strategy for patients with AI- or fulvestrant-resistant breast cancers.

Objectives Based on our previous findings that postmenopausal women with estrone (E1) and estradiol (E2) concentrations at or above 1.3 pg/ml and 0.5 pg/ml, respectively, after 6 months of adjuvant anastrozole therapy had a three-fold risk of recurrence, we aimed to identify a single-nucleotide polymorphism (SNP)-based model that would predict elevated E1 and E2 and then validate it in an independent dataset. Patients and methods The test set consisted of 322 women from the M3 study and the validation set consisted of 152 patients from MA.27. All patients were treated with adjuvant anastrozole, had on-anastrozole E1 and E2 concentrations and genome-wide genotyping. Results SNPs were identified from the M3 genome-wide association study. The best model to predict the E1-E2 phenotype with high balanced accuracy was a support vector machine model using clinical factors plus 46 SNPs. We did not have an independent cohort that is similar to the M3 study with clinical, E1-E2 phenotypes and genotype data to test our model. Hence, we chose a nested matched case-control cohort (MA.27 study) for testing. Our E1-E2 model was not validated but we found the MA.27 validation cohort was both clinically and genomically different. Conclusions We identified a SNP-based model that had excellent performance characteristics for predicting the phenotype of elevated E1 and E2 in women treated with anastrozole. This model was not validated in an independent dataset but that dataset was clinically and genomically substantially different. The model will need validation in a prospective study.

Several antiepileptic drugs (AEDs) have US Food and Drug Administration (FDA) approval for use as mood stabilizers in bipolar disorder (BD), but not all BD patients respond to these AED mood stabilizers (AED‐MSs). To identify genetic polymorphisms that contribute to the variability in AED‐MS response, we performed a discovery genome‐wide association study (GWAS) of 199 BD patients from the Mayo Clinic Bipolar Disorder Biobank. Most of these patients had been treated with the AED‐MS valproate/divalproex and/or lamotrigine. AED‐MS response was assessed using the Alda scale, which quantifies clinical improvement while accounting for potential confounding factors. We identified two genome‐wide significant single‐nucleotide polymorphism (SNP) signals that mapped to the THSD7A (rs78835388, P = 7.1E‐09) and SLC35F3 (rs114872993, P = 3.2E‐08) genes. We also identified two genes with statistically significant gene‐level associations: ABCC1 (P = 6.7E‐07; top SNP rs875740, P = 2.0E‐6), and DISP1 (P = 8.9E‐07; top SNP rs34701716, P = 8.9E‐07). THSD7A SNPs were previously found to be associated with risk for several psychiatric disorders, including BD. Both THSD7A and SLC35F3 are expressed in excitatory/glutamatergic and inhibitory/γ‐aminobutyric acidergic (GABAergic) neurons, which are targets of AED‐MSs. ABCC1 is involved in the transport of valproate and lamotrigine metabolites, and the SNPs in ABCC1 and DISP1 with the strongest evidence of association in our GWAS are strong splicing quantitative trait loci in the human gut, suggesting a possible influence on drug absorption. In conclusion, our pharmacogenomic study identified novel genetic loci that appear to contribute to AED‐MS treatment response, and may facilitate precision medicine in BD.

592 Background: Immune responses in the tumor microenvironment have prognostic and predictive value in BC. However, the potential of immune responses observed in peripheral blood as biomarkers in BC remains unclear. We have shown that a higher frequency of circulating monocytes and a lower frequency of antigen-experienced memory CD8+ T cells are associated with response to NAC in triple negative BC (Leon-Ferre et al SABCS 2019). Here, we used cytometry by time-of-flight (CyTOF) to evaluate associations between circulating immune cells, clinical features and response to T-based NAC in HER2+ BC. Methods: PBMC suspensions from 36 pts with stage I-III HER2+ BC were prospectively collected prior to initiation of T-based NAC, stained with 29 metal-tagged antibodies optimized to identify major human immune cell subsets, and acquired in the Helios CyTOF instrument. Differential abundance analysis of immune cells by clinical characteristics and by NAC response was evaluated using Wilcoxon rank sum test. % of immune cell subsets is presented as % of all PBMCs. Results: Most pts presented with ER- tumors (56%), measuring > 5cm (64%) and with nodal metastases (78%). After NAC, 16 pts (44%) achieved pathologic complete response (pCR). Analysis of preNAC PBMCs demonstrated a significantly higher number of B cells (8% vs 5%, p = 0.05) and effector memory CD8+ T cells (CD45RA-/CCR7-, 3 vs 1%, p = 0.02) in pts with pCR compared to those with residual disease. Of the B cell subsets, naïve B cells (CD24-/CD27-) were higher in pts who achieved pCR vs not (7% vs 4%, 0 = 0.04). Regarding clinical characteristics, cN+ pts at presentation exhibited a lower number of peripheral blood T cells compared to cN- pts (47% vs 63%, p = 0.03). Of the T cell subsets, overall CD4+ and naïve CD4+ T cells (CD45RA+/CCR7+) were lower in cN+ vs cN- pts (31% vs 45%, p = 0.05; and 11% vs 24%, p = 0.04). We also observed differences in CD56+/CD16- NK cells by ER status (ER- 1% vs ER+ 3%, p = 0.01), and a moderate negative correlation between age and % circulating CD8+ T cells (rho -0.4669, p = 0.004). Conclusions: Distinct peripheral blood immune cell profiles are observed in HER2+ BC at diagnosis, and are associated with response to T-based NAC and initial clinical characteristics. Notably, pts who later achieved pCR had a relative abundance of B cells and effector memory CD8+ T cells at diagnosis. These data suggest that immune cell phenotyping in peripheral blood may have potential as a biomarker to predict response to NAC in BC.

Abstract Purpose: To determine if the degree of estrogen suppression with aromatase inhibitors (AI: anastrozole, exemestane, letrozole) is associated with efficacy in early-stage breast cancer, and to examine for differences in the mechanism of action between the three AIs. Experimental Design: Matched case–control studies [247 matched sets from MA.27 (anastrozole vs. exemestane) and PreFace (letrozole) trials] were undertaken to assess whether estrone (E1) or estradiol (E2) concentrations after 6 months of adjuvant therapy were associated with risk of an early breast cancer event (EBCE). Preclinical laboratory studies included luciferase activity, cell proliferation, radio-labeled ligand estrogen receptor binding, surface plasmon resonance ligand receptor binding, and nuclear magnetic resonance assays. Results: Women with E1 ≥1.3 pg/mL and E2 ≥0.5 pg/mL after 6 months of AI treatment had a 2.2-fold increase in risk (P = 0.0005) of an EBCE, and in the anastrozole subgroup, the increase in risk of an EBCE was 3.0-fold (P = 0.001). Preclinical laboratory studies examined mechanisms of action in addition to aromatase inhibition and showed that only anastrozole could directly bind to estrogen receptor α (ERα), activate estrogen response element-dependent transcription, and stimulate growth of an aromatase-deficient CYP19A1−/− T47D breast cancer cell line. Conclusions: This matched case–control clinical study revealed that levels of estrone and estradiol above identified thresholds after 6 months of adjuvant anastrozole treatment were associated with increased risk of an EBCE. Preclinical laboratory studies revealed that anastrozole, but not exemestane or letrozole, is a ligand for ERα. These findings represent potential steps towards individualized anastrozole therapy.

Single nucleotide variants in the open reading frames (ORFs) of pharmacogenes are important causes of interindividual variability in drug response. The functional characterization of variants of unknown significance within ORFs remains a major challenge for pharmacogenomics. Deep mutational scanning (DMS) is a high‐throughput technique that makes it possible to analyze the functional effect of hundreds of variants in a parallel and scalable fashion. We adapted a “landing pad” DMS system to study the function of missense variants in the ORFs of cytochrome P450 family 2 subfamily C member 9 ( CYP2C9 ) and cytochrome P450 family 2 subfamily C member 19 ( CYP2C19 ). We studied 230 observed missense variants in the CYP2C9 and CYP2C19 ORFs and found that 19 of 109 CYP2C9 and 36 of 121 CYP2C19 variants displayed less than ~ 25% of the wild‐type protein expression, a level that may have clinical relevance. Our results support DMS as an efficient method for the identification of damaging ORF variants that might have potential clinical pharmacogenomic application.

We previously reported that testis‐specific Y‐encoded‐like protein (TSPYLs) are transcription regulators for CYP3A4, CYP2C9, and CYP2C19. Here, we observed dual roles for TSPYLs in mediating serotonin transport and the metabolism of selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder (MDD). The widely prescribed SSRIs, citalopram, and escitalopram are metabolized mainly by CYP2C19. The TSPYL1 rs3828743 single nucleotide polymorphism (SNP), which decreases its suppression of CYP2C19 expression, was associated with rapid escitalopram metabolism and worse treatment response in the Mayo PGRN‐AMPS clinical trial. We also found that TSPYLs can regulate expression of the serotonin transporter protein, SLC6A4, and, in turn, serotonin transport into cells. The SNPs in tight linkage disequilibrium with the TSPYL1 rs10223646 SNP were significantly correlated with baseline severity of depression in patients with MDD in the Sequenced Treatment Alternatives to Relieve Depression and International SSRI Pharmacogenomics Consortium clinical trials. Our findings suggest that genetic variation in TSPYL genes may be novel indicators for baseline severity of depression and SSRI poor response.