Human genomic studies link reduced CUB domain-containing protein 1 (CDCP1) expression with myocardial recovery in heart failure. While CDCP1 regulates cardiac fibroblast proliferation in vitro, it's in vivo role in cardiac fibrosis remains unclear. Using a Cdcp1-knockout (KO) angiotensin II/phenylephrine mouse model, we show that Cdcp1 deletion reduces echocardiographic left ventricular mass, histologic cardiac fibrosis, and pro-fibrotic gene expression, along with decreased fibroblast activation and inflammatory markers. Spatial transcriptomics identified a pressure overload-expanded fibroblast subpopulation enriched for growth factor and TGF-β signaling (FB5), which was markedly attenuated in Cdcp1-KO hearts, alongside reduction of a pro-inflammatory cardiomyocyte subtype (CM4). Complementary studies in human ventricular fibroblasts demonstrate that CDCP1 knockdown reduced extracellular matrix gene expression and collagen I deposition. These findings establish CDCP1 as a regulator of cardiac fibrotic remodeling in vivo and open avenues for its further investigation as a potential therapeutic target.

Large-cohort GWAS for alcohol use disorder (AUD) drug treatment outcomes and AUD risk have repeatedly identified genetic loci that are splicing quantitative trait loci for the fibronectin III domain containing 4 (FNDC4) gene in the brain. However, FNDC4 function in the brain and how it might contribute to AUD pathophysiology remain unclear. In the present study, we characterized GWAS loci-associated FNDC4 splice isoforms and demonstrated that FNDC4 alternative splicing results in loss of function for FNDC4. We also investigated FNDC4 function using CRISPR/Cas9 editing and the creation of human induced pluripotent stem cell-derived (iPSC-derived) neural organoids joined with single-nucleus RNA sequencing, a series of studies that showed that FNDC4 KO resulted in a striking shift in the relative proportions of glutamatergic and GABAergic neurons in iPSC-derived forebrain organoids as well as changes in their electrical activity. We further explored a potential mechanism(s) of FNDC4-dependent neurogenesis, and the results suggested a role for FNDC4 in mediating neural cell surface interactions. In summary, this series of experiments indicates that FNDC4 plays a role in regulating cerebral cortical neurogenesis in the brain. This regulation may contribute to the response to AUD pharmacotherapy as well as the effects of alcohol on the brain.

Selective estrogen receptor modulators (SERMs) decrease the risk of breast cancer in high-risk women. We sought to determine the association between germline DNA methylation and single nucleotide polymorphism (SNP) biomarkers and benefit from SERM prevention. DNA from blood at time of entry on NSABP P-1 or P-2 was utilized from a matched case–control study of women receiving a SERM. Methylation was determined with Illumina Infinium Methylation EPIC BeadChipv2 that targets 937,055 sites. Differential methylation analysis was performed utilizing the Wilcoxon signed-rank test. Analysis was performed on 22 potentially relevant genes. Five modeling strategies for predicting case–control status were performed. Polygenic risk scores (PRS) were integrated with methylation data. Risk SNPs and methylation data were jointly analyzed. DNA methylation data were available for 1706 participants (587 cases, 1119 controls). Wilcoxon signed-rank analysis was performed on 887,318 CpG sites and 25,746 methylated regions. Six CpGs were significantly associated with breast cancer risk with smallest p-value of 3.70E−08 for the top CpG that was related to AFF3, which has been associated with resistance to tamoxifen. Dfferences in beta (methylation) values between cases and controls were small. No CpG regions were significantly associated. CYP1A1 and CYP3A7 were significantly associated with case–control status. Five prediction modeling strategies revealed median AUCs of 0.524–0.590. Integration of PRS with methylation did not improve predictive performance. Joint analysis of two previously published SNPs (related to ZNF423 and CTSO) and cg11423397 revealed an odds ratio of 16.5 for differences in breast cancer risk for those with all protective factors versus all risk factors. We identified differentially methylated CpG sites that achieved statistical significance but minimal differences in beta values. No CpG regions were significant. Differential methylation in two CYP genes was identified but of unclear importance. No improvement in performance from prediction models or integrating PRS and methylation was identified. Joint analysis of cg11423397 and SNPs from ZNF423 and CTSO suggest further discrimination of breast cancer risk. While current methylation approaches utilizing germline DNA show limited predictive utility for breast cancer risk in women receiving a SERM, our results point to specific methylation and genetic biomarkers that warrant further study.

Antidepressants are widely prescribed for major depressive disorder, yet only one-third of patients achieve remission after initial treatment. Previous genome-wide association studies (GWAS) of clinically assessed antidepressant response combined multiple antidepressant classes, potentially obscuring class-specific effects. This study focused on selective serotonin reuptake inhibitors (SSRIs), often first-line due to better tolerability. Data from 15 cohorts across four ancestries were integrated: European (N = 3887; 11 studies), East Asian (N = 1068; 4), African (N = 277; 1), and Admixed American (N = 250; 1). GWAS of non-remission and percentage improvement were conducted within cohorts, followed by ancestry-specific meta-analyses and trans-ancestry meta-regression. Single nucleotide polymorphism (SNP)-based heritability was estimated in European samples. Polygenic scores were used for leave-one-out prediction and to assess shared genetic architecture with psychiatric traits. Gene-level and gene-set enrichment analyses were also performed. No genome-wide significant variants were identified for either outcome in any ancestry-specific or trans-ancestry analyses. However, trans-ancestry meta-regression yielded eight independent loci with suggestive associations (p < 1 × 10 -5 ) for non-remission and 17 for percentage improvement. Gene-set analyses revealed nominal enrichment of the serotonergic synapse pathway for non-remission. SNP-based heritability estimates were not significantly different from zero for either outcome. Better SSRI response was nominally associated with lower genetic predisposition to major depressive disorder, post-traumatic stress disorder, and schizophrenia. This study represents the largest trans-ancestry GWAS of SSRI response, highlighting emerging biological signals. Limited power emphasises the need for larger and ancestrally diverse cohorts to better characterise the genetic architecture of antidepressant response.

Abstract Background: The increasing volume and diversity of clinical genomic reports pose a significant challenge across healthcare institutions for the interpretation and proper implementation of precision oncology research. Reports from multiple different vendors (e.g., Invitae, Ambry Genetics, Foundation Medicine) are typically PDFs and exhibit substantial heterogeneity in panel design, gene coverage, and reporting standards, which hinders efficient retrospective data mining and patient cohort identification within the electronic medical records. We sought to develop a framework to interrogate all of these reports. Methods: We extracted genomic reports from patients with breast cancer treated with neoadjuvant chemotherapy and developed MolHarmonizer, a novel, scalable framework leveraging Python and Gemini LLMs, designed to process and harmonize genomic data from disparate multi-vendor reports. Gemini LLMs are employed explicitly for robust information extraction, normalization, and structuring of key genomic features, transforming unstructured data into a unified, queryable dataset. Results: Our MolHarmonizer framework successfully processed 1,147 genomic reports from 1703 breast cancer patients (2006-2023) from 23 different companies, demonstrating robust capability to extract and standardize critical actionable biomarkers. Data sources included Invitae (n=554), Ambry Genetics (n=189), Natera (n=95), Mayo Clinic (n=88), Tempus (n=63), Guardant Health (n=47), and Foundation Medicine (n=37), with others contributing less than 20 reports. Of the samples, 827/1147 (72.1%) were germline (blood/saliva). A majority of the patients were tested using the panels due to a personal/family history (n=925). Overall, 413/1147 (36.0%) reports identified at least one mutation. For breast cancer, 75 reports showed BRCA1/2 mutations (37 BRCA1, 37 BRCA2, and one patient with both BRCA1 and 2). Other mutations identified included: PIK3CA (n=40), TP53 (n=96), PTEN (n=21), ESR1 (n=13) and AKT1/2 (n=8). Conclusion: MolHarmonizer, a powerful framework leveraging Gemini LLMs, effectively addresses genomic data heterogeneity by automating biomarker extraction and harmonization. This enables rapid cohort identification and deep retrospective analyses for clinical insights, biomarker discovery, understanding disease history, facilitating novel pattern discovery, e.g., predicting BRCA1 mutations from WSI, and accelerating research within our neoadjuvant BC cohort. Future plans include expanding to include over 20,000 breast cancer patients, developing a user-friendly chatbot, and ensuring inter-institutional adaptability for a variety of complex diseases. Citation Format: Krishna Rani Kalari, Xiaojia Tang, Thanmayee Boyapati, Tanya L. Hoskin, Sumathilatha Myla, Sumedha G. Penheiter, Richard M. Weinshilboum, Liewei Wang, Hamid R. Tizhoosh, Karthik Vikram Giridhar, Matthew P. Goetz, Judy C. Boughey. Development of an LLM framework for analysis of heterogeneous breast cancer patients genomic reports [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2756.

A genome-wide association study (GWAS) identified neuron navigator 3 (NAV3) as a potential genetic determinant of myocardial recovery in dilated cardiomyopathy (DCM). This study aimed to understand its functional role in cardiac pathophysiology by leveraging omics approaches. Single-cell RNA-seq transcriptomic data from previously published adult human hearts indicate that NAV3 expression is highest in cardiac fibroblasts, suggesting its functional role in these cells. In vitro, stimulation of primary human ventricular cardiac fibroblasts with transforming growth factor β1 (TGF-β1) induced NAV3 expression in a dose and time-dependent manner. Small-interfering-RNA-mediated knockdown of NAV3 significantly attenuated TGF-β1-induced fibroblast activation, reducing the expression of α-smooth muscle actin (α-SMA), collagens, and fibronectin. RNA sequencing of NAV3-silenced fibroblasts, confirmed by Western blot, revealed upregulation of cell cycle regulators and downregulation of profibrotic markers, suggesting that NAV3 facilitates TGF-β1-induced cell cycle arrest and fibroblast-to-myofibroblast transition. Notably, NAV3 silencing did not alter canonical SMAD2/3 phosphorylation, implying a role for NAV3 in modulating fibrotic signaling through other pathways. Our findings provide functional and mechanistic insights into NAV3's novel role in cardiac fibrosis, showing that reduced NAV3 expression attenuates TGF-β1-mediated fibroblast activation by regulating cell cycle signaling. These results support further investigation of NAV3 as a potential modulator of cardiac fibrosis and myocardial recovery in DCM.NEW & NOTEWORTHY This study uncovers a previously unrecognized role for NAV3 in TGF-β1-driven cardiac fibroblast activation. We show that NAV3 facilitates profibrotic remodeling through noncanonical signaling and cell cycle arrest, independently of SMAD2/3. These findings position NAV3 as a novel regulator of fibroblast phenotype and a potential modulator of cardiac fibrosis.

Background Pharmacogenomic studies on antidepressant treatment outcomes could be conducted using previously collected data from electronic health record (EHR)-linked biobanks. However, absence of EHR based outcome measures is an unmet need in designing such studies We aimed to define EHR-derived antidepressant outcome measures and explore their utility in showing associations between treatment outcomes and Cytochrome P450 (CYP) metabolizer phenotypes in a proof-of-concept study. Methods Using data from the EHR-linked cohort, Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT 10K) Study, we collected prescription data and patient health questionnaire 9 (PHQ-9) scores to compute 3 proxy measures for antidepressant response, efficacy, and acceptability: change in PHQ-9 scores, longest treatment interval with a single antidepressant, and antidepressant non-refill. Subsequently, we tested the association of both prescription-based outcomes with DNA-predicted CYP metabolizer phenotypes in European-ancestry participants. Results We identified 3920 RIGHT 10K participants with at least 1 antidepressant prescription and European-ancestry. Participants had a mean age of 61 years and 72% were women. Implementation of the PHQ-9 outcome was not feasible because of missingness. Of both prescription-based outcomes, antidepressant non-refill reproduced several known antidepressant-CYP interactions. However, the pilot was limited by small subgroups of participants with non-normal metabolizer phenotypes. Conclusions Derived from structured data, antidepressant non-refill is a promising outcome measure for EHR-linked biobanks that partially reproduced antidepressant-CYP interactions. However, testing on larger datasets is necessary to understand whether it would be a useful for pharmacogenomic research.

Supplementary Notes (S1-S5)Supplementary Tables (S1 - S5; S10 - S11)Supplementary Figures (S1 - S12)

Supplementary File 3: Excel file with Supplementary tables S6 - S9

Tamoxifen undergoes metabolic activation by cytochrome P450 (CYP) enzymes to metabolites with more potent anti-estrogenic effects. Numerous studies demonstrate decreased tamoxifen efficacy associated with reduced CYP2D6 activity or lower Z-endoxifen concentrations. Women taking tamoxifen frequently experience vasomotor symptoms (VMS) that may require medical treatment. Many medications used for VMS or depression are CYP substrates that may reduce Z-endoxifen concentrations. While the drug-drug interactions (DDI) from potent CYP2D6 inhibitors (CYPi) on tamoxifen metabolism has been studied, the impact of less potent CYPi including drugs used to treat VMS remains largely unknown. We performed a prospective trial to evaluate the impact of gabapentin or non-potent CYPi (venlafaxine citalopram) on plasma concentrations of tamoxifen and its metabolites (Z-endoxifen, N-desmethyl-tamoxifen (NDMT) and 4-hydroxy-tamoxifen (4HT). Patients enrolled were intermediate to extensive metabolizers by CYP2D6 genotyping. While tamoxifen and NDMT plasma concentrations were not significantly altered, the percent decrease in plasma Z-endoxifen concentration was statistically significant with the addition of venlafaxine (n = 22) or citalopram (n = 18) (median − 14.7 and − 14.4

Opioid use disorder (OUD) affects over 40 million people worldwide, creating significant social and economic burdens. Medication for opioid use disorder (MOUD) is often considered the primary treatment approach for OUD. MOUD, including methadone, buprenorphine, and naltrexone, is effective for some, but its benefits may be limited by poor adherence to treatment recommendations. Immunopharmacotherapy offers an innovative approach by using vaccines to generate antibodies that neutralize opioids, blocking them from crossing the blood-brain barrier and reducing their psychoactive effects. To date, only 3 clinical trials for opioid vaccines have been published. While these studies demonstrated the potential of opioid vaccines for relapse prevention, there is currently no standardized protocol for evaluating their effectiveness. We have reviewed recent preclinical studies that demonstrated the efficacy of vaccines targeting opioids, including heroin, morphine, oxycodone, hydrocodone, and fentanyl. These studies showed that vaccines against opioids reduced drug reinforcement, decreased opioid-induced antinociception, and increased survival rates against lethal opioid doses. These studies also demonstrated the importance of vaccine formulation and the use of adjuvants in enhancing antibody production and specificity. Finally, we highlighted the strengths and concerns associated with the opioid vaccine treatment, including ethical considerations.

Excel file with regulon edges and ChIPseq enrichment scores for TraRe, GRNboost2 and ARACNE-AP

Background: Cardiac fibrosis is a critical and independent driver of heart failure (HF), characterized by excessive extracellular matrix (ECM) deposition. Decreased CDCP1 (CUB domain-containing protein 1) expression has been associated with myocardial recovery in human genome wide association studies by attenuating PDGF-BB driven cardiac fibroblast proliferation with no effect on canonical TGF-beta mediated transdifferentiation in-vitro. In-vivo, Cdcp1 deletion significantly reduced cardiac fibrosis and dysfunction in an angiotensin II/phenylephrine-induced pressure overload mouse model. However, its upstream regulators and its downstream effects on molecular signaling pathways that modulate ECM remodeling are unknown. Hypothesis: CDCP1 promotes human cardiac fibroblast mediated ECM remodeling in the HF microenvironment. Methods: Human ventricular fibroblasts (HVF) were treated with PDGF-BB (20 ng/ml), TGF-β (10 ng/ml), or Angiotensin II (100 ng/ml) for 48 hours. CDCP1 knockdown (KD) was achieved through siRNA transfection. Gene expression analysis was performed using qRT-PCR and protein quantification by Western blot. Both intact HVF and decellularized ECM were immunostained for collagen 1 to evaluate for ECM compositional changes. Results: Individual and combination treatments with fibrotic stimuli significantly increased CDCP1 expression (Figure 1A-1B). CDCP1 KD resulted in reduction of key ECM markers COL1A1, CTGF, and LOX (Figure 1C) across all fibrotic stimuli . Immunostaining of HVF after treatment with fibrotic stimuli showed reduced collagen 1 production with CDCP1 KD (Figure 1D). Western blot analysis showed increased phosphorylation of Src (tyr416) with 6h of treatment with fibrotic stimuli which was nullified by silencing of CDCP1 (Figure 1E). Conclusion: Our findings demonstrate that CDCP1 is necessary for ECM synthesis and Src signaling across multiple profibrotic pathways. Selective targeting of CDCP1 to modulate Src signaling pathways could provide novel therapeutic avenues for HF and fibrosis treatment.

Supplementary File 2: Excel file with CommunityAMARETTO Enrichment results

Triple-negative breast cancer (TNBC) represents the most malignant subtype of breast cancer. The clinical application of PARP inhibitors (PARPi) is limited by the low frequency of BRCA1/2 mutations in TNBC. Here, we identified that MTAP deletion sensitized genotoxic agents in our clinical cohort of metastatic TNBC. Further study demonstrated that MTAP deficiency or inhibition rendered TNBC susceptibility to chemotherapeutic agents, particularly PARPi. Mechanistically, targeting MTAP that synergized with PARPi by disrupting the METTL16-MAT2A axis involved in methionine metabolism and depleting in vivo s-adenosylmethionine (SAM) levels. Exhausted SAM in turn impaired PARPi-induced DNA damage repair through attenuation of MRE11 recruitment and end resection by diminishing MRE11 methylation. Notably, brain metastatic TNBC markedly benefited from a lower dose of PARPi and MTAP deficiency/inhibition synergy due to the inherently limited methionine environment in the brain. Collectively, our findings revealed a feed-forward loop between methionine metabolism and DNA repair through SAM, highlighting a therapeutic strategy of PARPi combined with MTAP deficiency/inhibition for TNBC.

Acamprosate is an FDA-approved medication for the treatment of alcohol use disorder (AUD), however, only about 50% of patients will respond to acamprosate. Previously, we conducted an acamprosate trial (n=442), which is one of the largest acamprosate clinical studies ever conducted and currently the only study with multi-omics data. To date, no biological measures are utilized to predict response to acamprosate treatment. We set out to apply our established pharmaco-omics informed genomics strategy to identify potential biomarkers associated with acamprosate treatment response. Our open-label acamprosate clinical trial recruited 442 patients with AUD, all of whom were treated with acamprosate for three months. The primary outcomes were 1) relapse to alcohol use and 2) relapse to heavy drinking. Alcohol consumption was measured using the self-reported timeline follow back method. Plasma protein levels were measured using Olink proximity extension immunoassays. Our established “Pharmaco-Omics-informed genome-wide association study (GWAS)” research strategy identified 12 proteins, including interleukin-17 receptor B (IL17RB), that were associated with acamprosate treatment response. A GWAS for IL17RB concentrations identified several genome-wide significant signals. Specifically, the top hit single nucleotide polymorphism (SNP) rs6801605 with a minor allele frequency of 38% in the European American population mapped 4 kilobase (Kb) upstream of IL17RB, and intron 1 of the choline dehydrogenase (CHDH) gene on chromosome 3 (p: 4.8E-20). The variant genotype (AA) for the SNP rs6801605 was associated with lower IL17RB protein expression. In addition, we identified a series of genetic variants in IL17RB that were associated with acamprosate treatment outcomes. Furthermore, the variant genotypes for all of those IL17RB SNPs were protective against alcohol relapse. Finally, we demonstrated that the basal level of mRNA expression of IL17RB was inversely correlated with those of nuclear factor-κB (NF-κB) subunits, and a significantly higher expression of NF-κB subunits was observed in AUD patients who relapsed to alcohol use. This study illustrates that IL17RB genetic variants might contribute to acamprosate treatment outcomes. This series of studies represents an important step toward generating functional hypotheses that could be tested to gain insight into mechanisms underlying variation in acamprosate treatment response phenotypes.

Second generation androgen receptor signaling inhibitors (ARSIs), such as abiraterone, have demonstrated improved survival in metastatic castration-resistant prostate cancer (mCRPC) patients, however, acquired resistance to these agents often arises. Novel and alternative therapies are needed to combat the ARSI resistant tumor. In the last two decades patient-derived xenograft (PDX) and PDX organoids have become pivotal models in anticancer drug development and biomarker discovery due to their ability to faithfully recapitulate the complex and heterogeneous tumor biology. We analyzed RNAseq data from mCRPC patients and corresponding PDX models (PROMOTE study, NCT #01953640) and employed L1000 Chem Perturbation down/up signatures database to find candidate drugs to overcome abiraterone resistance by reverse signature search. We then performed proliferation assay using 49 compounds in three PROMOTE-PDX organoid models (2 abiraterone-resistant and 1 abiraterone-sensitive) using our semi high-throughput drug screening platform. Overall, we identified a total of 32 compounds with IC50<10µM in at least one of the models, among which, 5 agents are active in all three models and 5 in at least two of the models. (Table 1). Within active compounds we find selective kinase inhibitors (BRAF, JAK2, AKT, FLT3) and histone deacetylase inhibitors (belinostat and pracinostat). Particularly interesting are two drugs that are only active in the abiraterone resistant setting but not the sensitive PDX. In summary, we leveraged RNAseq data from mCRPC patients and PDX models and performed a high-throughput drug screen in PDX-derived organoid models to identify potential drugs that could overcome abiraterone-resistance in lethal advanced prostate cancer. These data highlight potential drug combinations or subsequent therapeutic strategies for these patients. Irene Marín-Goñi, Huanyao Gao, Joachim L. Petit, Shreya Indulkar, Adam M. Kase, Cassandra N. Moore, Krishna R. Kalari, Michael T. Barrett, Richard Weinshilboum, Winston Tan, John A. Copland, Liewei Wang. Overcoming resistance in mCRPC: drug discovery using PDX models and high-throughput drug screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5658.

Large-cohort genome-wide association studies (GWAS) for alcohol use disorder (AUD) and AUD-related phenotypes have identified more than one hundred genetic loci. Functional study of those GWAS-identified loci might represent an important step toward understanding AUD pathophysiology. We found that genetic loci which are splicing quantitative trait loci (sQTLs) for the fibronectin III domain containing 4 (FNDC4) gene in the brain were identified by GWAS for both AUD drug treatment outcomes and AUD risk. However, FNDC4 function in the brain and how it might contribute to AUD pathophysiology remain unknown. In the present study, we characterized GWAS locus-associated FNDC4 splice isoforms, studies which suggested that FNDC4 alternative splicing results in loss-of-function for FNDC4. We also investigated FNDC4 function using CRISPR/cas9 gene editing, and the creation of human induced pluripotent stem cell (iPSC)-derived neural organoids joined with single-nucleus RNA sequencing. We observed that knock-out (KO) of FNDC4 resulted in a striking shift in the relative proportions of glutamatergic and GABAergic neurons in iPSC-derived neural organoids, suggesting a possible important role for FNDC4 in neurogenesis. We also explored potential mechanism(s) of FNDC4-dependent neurogenesis with results that suggested a role for FNDC4 in mediating neural cell-cell interaction. In summary, this series of experiments indicates that FNDC4 plays a role in regulating cerebral cortical neurogenesis in the brain. This regulation may contribute to the response to AUD pharmacotherapy as well as the effects of alcohol on the brain.

The role of germline genetics in adjuvant aromatase inhibitor (AI) treatment efficacy in ER-positive breast cancer is poorly understood. We employed a two-stage candidate gene approach to examine associations between survival endpoints and common germline variants in 753 endocrine resistance-related genes. For a discovery cohort, we screened the Breast Cancer Association Consortium database (n ≥ 90,000 cases) and retrieved 2789 AI-treated patients. Cox model-based analysis revealed 125 variants associated with overall, distant relapse-free, and relapse-free survival (p-value ≤ 1E-04). In validation analysis using five independent cohorts (n = 8857), none of the six selected candidates representing major linkage blocks at CELA2B/CASP9, NR1I2/GSK3B, LRP1B, and MIR143HG (CARMN) were validated. We discuss potential reasons for the failed validation and replication of published findings, including study/treatment heterogeneity and other limitations inherent to genomic treatment outcome studies. For the future, we envision prospective longitudinal studies with sufficiently long follow-up and endpoints that reflect the dynamic nature of endocrine resistance.