Assessing Endocrine Resistance: Monitoring Circulating ESR1 mutations in Irosustat-Treated ER positive Breast Cancer

Assessing Endocrine Resistance: Monitoring Circulating ESR1 mutations in Irosustat-Treated ER positive Breast Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Endocrine Resistance: Monitoring Circulating ESR1 mutations in Irosustat-Treated ER positive Breast Cancer Karen Page, Luke J Martinson, Robert K Hastings, Emmanuel Acheampong, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7187693/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Dec, 2025 Read the published version in Breast Cancer Research and Treatment → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose: We aimed to investigate the prevalence and spectrum of ESR1 mutations alongside cell-free DNA (cfDNA) dynamics in patients with estrogen receptor-positive metastatic breast cancer recruited to the phase II IRIS study who had progressed on first-line aromatase inhibitor (AI) therapy and then continued their AI in combination with Irusostat (40mg), an irreversible steroid sulfatase inhibitor. Methods: cfDNA was isolated from 96 serial plasma samples from 24 patients, alongside primary tumour DNA (n = 16), and analysed by next-generation sequencing using a custom-designed mutation panel on the Illumina NovaSeq platform. Results: Thirteen of 16 tumour DNA samples harboured at least one somatic mutation across nine genes. Twenty one of 24 patients (88%) had at least one somatic mutation in cfDNA (248 total mutations across 10 genes). Circulating tumour DNA ESR1 mutations (ct ESR1 m) were the most prevalent, present in 16 patients (76%) with both stable (SD) and progressive disease (PD), showing no clear association with disease progression. Eleven patients had polyclonal ct ESR1 m within the ligand-binding domain, six at baseline, while five harboured a single ct ESR1 m variant. Five other patients acquired polyclonal mutations over treatment. Conclusion: Analysis of serial plasma samples revealed frequent detection of polyclonal ct ESR1 m in patients recruited to the IRIS study with both SD and PD. These findings underscore the challenge of targeting a single ESR1 mutation and emphasise the need for careful patient selection, specifically those with wild-type ESR1 , in trials investigating sequential estrogen-lowering therapies. Liquid biopsy circulating tumour DNA custom targeted next-generation sequencing Irusostat breast cancer Figures Figure 1 Introduction Breast cancer (BC) is the most common cancer in women worldwide, with more than 600,000 people dying annually and despite advances in treatment and detection, these deaths are largely due to metastatic recurrence occurring more than 5 years post diagnosis [ 1 ]. About 75% of BC are estrogen receptor alpha (ERα) positive (ER + ve), this plays a pivotal role in its development and progression as it relies upon estrogen-induced ERα transcriptional activation for growth. ER expression is related to patient age and correlates with lower tumour grade and proliferation, less aneuploidy, less frequent amplification of the c-erbB2 (HER2) oncogene and progesterone receptor (PR) expression [ 2 ]. These clinical factors, together with ER expression, guide treatment decisions, and particularly in those patients with metastatic disease, where endocrine therapy remains the most effective option. Endocrine therapy targets ER by depriving the tumour of estrogen (E2) or by inhibiting ER binding with an agonist. Aromatase inhibitors (AIs) such as anastrozole and letrozole, block aromatase and interfere with conversion of androgens into estrogens, and form the backbone of treatment for ER + ve BC (Supplementary Fig. 1). ESR1 gene mutations (ct ESR1 m) that typically occur in the ligand binding domain (LBD) of ERα lead to constitutional activation of the receptor and resistance to therapies [ 3 ]. With the advancement of endocrine therapies however, there is increased concern of the potential for resistance [ 4 ], and particularly that which is ‘acquired’, as approx. 20% of patients who present with early disease will develop resistance manifested as recurrences either during or after endocrine treatment [ 5 ]. This is defined by tumours which typically show a good overall early response, but over the course of therapy become unresponsive [ 6 ], compared to de novo resistance, which occurs before treatment with no response to first line endocrine therapies. Potential mechanisms of endocrine resistance include loss of estrogen dependence [ 7 ] or inefficiencies of therapies e.g., due to modulation of signalling cascades [ 8 , 9 ]. However, more recently, deep-sequencing studies have highlighted the importance of acquired mutations of ER in driving resistance [ 10 ], where acquisition of such mutations renders the cancer cells insensitive to AIs and is predicted to reduce sensitivity to anti-estrogens [ 3 , 11 ]. In addition to managing postmenopausal BC through decreasing circulating levels of oestradiol via inhibition of aromatase [ 12 ], the steroid sulphatase (STS) pathway, a second major pathway for estrogen biosynthesis, can also be targeted. Studies have shown increased protein levels of STS in BC are associated with large tumour size, increased risk of recurrence and poorer overall survival [ 13 ], therefore this alternative pathway is also of significance. Two phase I studies of a first-generation inhibitor of STS, Irusostat (STX64; a tricyclic coumarin sulfamate), showed it to be potent, well tolerated and caused a significant decrease in serum concentrations of steroids with estrogenic properties [ 14 , 15 ]. Following this, a phase II combination study (IRIS) was designed to investigate the efficacy and tolerability of Irosustat in postmenopausal women who had progressed on a first-line AI from which they had derived clinical benefit [ 16 ]. Patients were followed up each month for six months and three monthly thereafter, until disease progression or unacceptable toxicity occurred, with the hypothesis that the blockade of STS with Irosustat on the background of continued AI could result in clinical benefit. In this study, we analysed circulating cell-free DNA (cfDNA) from serial plasma samples of 24 patients enrolled in the IRIS phase II trial collected over a median of 3 months (range 1–18 months) on the study. Using a custom-designed targeted next-generation sequencing panel relevant to metastatic breast cancer, we profiled mutational hotspots, including ESR1 , to characterise the ctDNA genomic landscape in patients progressing on first line AI who were then continued on their AI therapy combined with the steroid sulfatase (STS) inhibitor Irosustat. Our objectives were to quantify circulating tumour DNA (ctDNA) levels, assess ctDNA dynamics, and explore how ctDNA ESR1 mutations (ct ESR1 m) may influence treatment response, as their impact on Irosustat efficacy remains unclear. Materials and Methods Patients and Samples The IRIS study (ClinicalTrials.gov NCT0178 5992) was a multicentre, open label phase II trial performed in nine academic medical centres in the United Kingdom conducted in accordance with Good Clinical Practice Guidelines and the Declaration of Helsinki. Ethical approval was given by the Riverside Research Ethics Committee (an Independent Ethics Committee; reference 12/LO/0477), and approved by the United Kingdom Medicines and Healthcare Products Regulatory Agency (EudraCT: 2011-005680-25). All participants gave written informed consent prior to participation and were over 18 years of age. Women were eligible if they were postmenopausal, with histologically confirmed ER + ve, HER2 -ve inoperable locally advanced or metastatic BC, where ER positivity was based on local laboratory assessment (Supplementary Table 1) and had developed progressive disease during first-line AI therapy for recurrent ER + BC. Eligible patients also had to have derived clinical benefit, defined as a documented objective response at any point or disease stabilisation (SD) for at least 6 months, from their first-line AI treatment. The disease had to be measurable by CT/MRI scan according to RECIST v1.1. Patients were monitored by serial blood sampling over a period of 1–18 months along with clinical evaluations. 8ml blood was taken into K2 EDTA tubes (BD Biosciences) and processed to plasma within two hours of collection for extraction of cfDNA. Extraction and quantitation of DNA Total cfDNA was isolated from 115 serially collected blood plasma samples from 24 patients, using 4ml blood plasma with the MagMAX™ Cell-free DNA Isolation Kit (Thermo Fisher Scientific) as described previously [ 17 , 18 ]. Matching formalin-fixed paraffin-embedded (FFPE) tumour tissue was available for 16 of the 24 patients; 15 were derived from the primary tumour, and one from a metastatic relapse. Tumour DNA was isolated from FFPE tissue blocks using the GeneRead™ Kit (Qiagen), as described previously [ 18 ]. Quantitation and quality checks for cfDNA and tumour DNA were performed using the Agilent Tapestation cell-free DNA Screentape (Agilent) and Qubit™ dsDNA HS Assay kit (Thermo Fisher Scientific) respectively, according to manufacturer’s instructions. Targeted next generation sequencing A custom next-generation sequencing panel targeting 397 hotspot mutations across 19 genes (Supplementary Table 2) was developed by informaticians using a bespoke assay design pipeline (Nonacus Ltd). A total of 96 libraries were prepared from plasma DNA across 24 patients (median input: 50 ng). using this and the Cell3™ Target kit (Nonacus). Libraries were pooled equal amounts (n = 8) and hybridised with biotin-labelled DNA probes to enrich for the targeted regions. Additionally, 16 libraries were prepared from tumour FFPE DNA (median input: 55 ng), pooled together, and similarly enriched. All final captured library pools were sequenced on the Illumina NovaSeq platform. Bioinformatic analysis of raw sequencing data FASTQ files were processed using Nonacus' custom research tumour-only pipelines, which incorporate Sentieon tools (v202112.06) for alignment, variant calling, and quality control [ 19 ], FASTP (v0.23.4) for adapter and quality trimming (Chen et al, 2018), and the Ensembl Variant Effect Predictor (VEP) (v108.2) for variant annotation [ 20 ] Two workflows were used depending on sample type. For FFPE samples, raw FASTQ files were trimmed using FASTP (Chen et al, 2018) then aligned directly to the GRCh38 reference genome using sentieon bwa mem. Reads were sorted, indexed, and recalibrated using QualCal [ 19 ]. Somatic variants were called using TNhaplotyper2 in tumour only mode, followed by orientation bias and contamination correction using OrientationBias and ContaminationModel, as in the cfDNA workflow. UMI-specific steps were omitted. Variant refinement was carried out using TNfilter, with settings appropriate for FFPE data [ 19 ]. For cfDNA samples, raw FASTQ files containing UMIs were first processed using sentieon umi extract, and consensus reads were generated using Sentieon’s UMI consensus module. The resulting consensus FASTQ files were then trimmed using FASTP (Chen et al, 2018) to remove adapters and low-quality bases. Trimmed consensus reads were aligned to the GRCh38 reference genome using sentieon bwa mem, followed by sorting, indexing, and Base Quality Score Recalibration (BQSR) using QualCal [ 19 ]. Somatic variant calling was performed in tumour-only mode using TNhaplotyper2 [ 19 ] with orientation bias and tumour contamination correction via OrientationBias and ContaminationModel [ 19 ]. Variants were refined using TNfilter, with parameters optimized for cfDNA, and further filtered using BCFtools (v1.16) [ 21 ]. In both workflows, variants were annotated using the Ensembl Variant Effect Predictor (VEP, v108.2) [ 20 ] run in offline mode with cache version 108. Annotated VCFs were compressed and converted to MAF format using vcf2maf (v1.6.21) [ 22 ] for downstream analysis. Statistical analysis The Mann–Whitney non-parametric statistical test was used to compare cfDNA yields in patients with stable and progressive disease; Spearman’s rank correlation coefficient was used to investigate the correlation between disease status and ct ESR1 m variant allele fraction (VAF). These analyses were carried out using GraphPad Prism v10.2.3 software. All P values were two-sided and those < 0.05 were considered statistically significant. Results A total of 24 patients with ER+, HER2-ve, inoperable locally advanced or metastatic BC, who were progressing on first line AI were enrolled into the IRIS phase II trial. The mean patient age was 56 years (range: 31–76). All patients received the STS inhibitor Irosustat in combination with a first-line AI: exemestane (n = 3), letrozole (n = 16), or anastrozole (n = 5; Supplementary Table 1). At the time of Irosustat addition, 7 patients exhibited stable disease (SD), 15 showed progressive disease (PD) and two were unknown. Longitudinal plasma cfDNA samples were collected over a median of 3 months (range 1 to 18; average 4 samples per patients, total 96 across 24 patients). Matched FFPE primary tumour tissue was available for 16 of the patients. All 96 plasma cfDNA samples and 16 tumour DNA samples were successfully sequenced using a semi-automated, standardised workflow under good clinical laboratory practice (GCLP). The median cfDNA concentration in plasma was 24.6 ng/mL (range: 5.1–948.2 ng/mL), with no significant difference between patients with SD and PD (P = 0.0786, Mann–Whitney U test). Mutational Landscape in Primary Tumours Applying a cut off 5% VAF in the primary tumour FFPE DNA, targeted next-generation sequencing (NGS) identified 17 somatic missense mutations across 9 genes ( CDH1 , ERBB3 , ESR1 , GATA3 , KMT2C , NF1 , PIK3CA , MAP3K1 , and TP53 ) in tumours from 13/16 patients. Each of the 13 tumours harboured at least one somatic mutation (Fig. 1 A; Supplementary Table 4), with PIK3CA the most frequently mutated gene, (5 mutations in 5/13 tumours; 38%). ESR1 and TP53 mutations were each detected in 2 tumours (31%). Among 11 patients with PD, ct ESR1 m were detected in 2 patients (18%); one in metastatic tissue and one in primary tumour tissue. PIK3CA mutations were identified in 5 tumours. Circulating Tumour DNA profiles and ctESR1 m resistance dynamics In plasma, 21 of 24 patients (88%) had at least one high-confidence somatic mutation identified across 77/96 timepoints. A total of 248 mutations were detected spanning 10 genes ( AKT1 , CDH1 , ERBB3 , ESR1 , GATA3 , KMT2C , PIK3CA , MAP3K1 , RB1 , and TP53 ; Fig. 1 B; Supplementary Table 5). ESR1 was the most frequently mutated gene in cfDNA, detected in 16 of 21 patients (76%) and accounted for 131 of 248 mutations (53%). Common mutations present in both tumour and plasma samples were predominantly in TP53 and PIK3CA (Supplementary Table 6). However, an ESR1 mutation (p.D538G, 70.8% VAF) was also detected in the baseline plasma sample matched to one patient (P5, 0.75% VAF). At study entry, 14 out of 16 patients had detectable ct ESR1 m, with 6 of these cases exhibiting polyclonal mutations (Fig. 1 B), with seven patients showing ct ESR1 m evolving over time. In total, 11 patients (69%) had polyclonal mutations located in the ligand-binding domain (LBD), including p.D538G, p.Y537N/S/C, p.L536H/Q/P/R, and p.S463P (Supplementary Figs. 2 and 3). Of these, 6 patients had polyclonal ct ESR1 m at baseline, while 5 had single variants. The most prevalent mutation observed was p.D538G (32% of all ct ESR1 m events). Mutations in ESR1 , PIK3CA , and TP53 comprised 86% of all ctDNA alterations (214 of 248; Supplementary Figs. 2, 3). Correlation analysis revealed no significant association between treatment response and either ct ESR1 m VAF (P = 0.347, r = 0.087) or ct ESR1 m presence/absence (P = 0.432, r = − 0.168; Spearman’s rank correlation). Discussion Analysis of primary tumour DNA from patients progressing on AI and who were then continued on AI plus Irosustat, identified somatic mutations in key BC associated genes, most notably PIK3CA , TP53 and ESR1 . The high presence of PIK3CA mutations, which activate the PI3K/AKT/mTOR pathway can drive ER–independent tumour growth [ 24 ], while the presence of TP53 mutations is consistent with its known association with tumour progression and poor clinical outcomes [ 23 ]. In blood plasma, c tESR1 m were the most prevalent, with 53% of patients exhibiting one or more mutations, with 88% located in the LBD of ERα, aligning with previous studies that observed ct ESR1 m located in the LBD [ 3 , 11 , 23 ]. Mutations within the LBD are known to mimic estrogen binding, leading to the activation of ERα even in the presence of AIs, and this mechanism of ligand-independent activation is a well-characterised pathway for resistance to endocrine therapy in ER-positive BC [ 3 ]. The high frequency of polyclonal ct ESR1 m located in the LBD highlights the molecular heterogeneity of endocrine resistance in advanced ER-positive BC, making it difficult to target with a single endocrine therapy. The co-existence of multiple ct ESR1 m within individual patients likely reflects ongoing selective pressure from AI therapy and suggests convergent evolution towards ligand-independent ERα activation [ 3 ]. ESR1 m in primary tumours are extremely rare, they are detected in fewer than 1% of treatment-naïve cases, as demonstrated in the TCGA Breast Cancer study, which analysed over 800 primary breast tumours [ 24 ]. Here, a single ESR1 m (p.R394C) was identified in the primary tumour tissue but was absent from matched cfDNA. This discrepancy highlights both the technical limitations of NGS and the dynamic nature of tumour evolution under treatment pressure. Notably, p.R394C is located outside the LBD, where most activating, resistance-associated ESR1 m are found and its absence in cfDNA (and location outside the LBD) suggest it may not be a driver of aromatase inhibitor resistance and could represent a passenger mutation or a potential sequencing artefact. Although the earlier IPET study demonstrated a significant reduction in the proliferation marker Ki67 after just two weeks of Irosustat treatment [ 24 ], our findings suggest that patients harbouring ct ESR1 m at treatment initiation (14 of 24 patients; Fig. 1 B) are unlikely to derive substantial benefit from the addition of Irosustat. Given that Irosustat, an STS inhibitor, reduces the local conversion of inactive estrogen sulfates into active estrogens, we suggest the emergence of ligand-independent ct ESR1 m may undermine its efficacy, particularly when used in combination with AIs in patients who already exhibit endocrine resistance. Therefore, retrospective analysis of this cohort underscores the importance of selecting patients with wild-type ESR1 for future studies involving sequential estrogen-lowering therapies. Finally, data from two recent clinical trials investigating the efficacy of oral selective estrogen receptor degraders (SERDs) in ct ESR1 m-positive patients with advanced breast cancer suggest a promising alternative to Irosustat. The EMERALD trial demonstrated that elacestrant, the first approved oral SERD, significantly improved progression-free survival (PFS) in patients with ESR1-mutant tumours who had received two prior lines of AI-based endocrine therapy [ 25 ]. More recently, the SERENA-6 trial evaluated camizestrant in patients who developed ct ESR1 m during first-line therapy [ 26 ]. In this trial, patients who were switched from an AI to camizestrant, while continuing a CDK4/6 inhibitor, experienced longer PFS than those who continued with the AI plus CDK4/6 inhibitor combination. Notably, the switch in therapy was guided by the emergence of ct ESR1 m detected via ctDNA testing, prior to clinical or radiologic progression. These findings underscore the clinical value of SERDs in overcoming ct ESR1 m-mediated endocrine resistance, and suggest that elacestrant or camizestrant may offer therapeutic advantages in settings where Irosustat demonstrates limited efficacy. Conclusion These findings emphasise the value of longitudinal liquid biopsy profiling to capture resistance mechanisms that may not be detectable in archival primary tumour tissue. The frequent detection of polyclonal ct ESR1 m in both stable and progressive disease further illustrates the challenge of targeting a single ESR1 variant in patients progressing on AI. However, our data support the use of ctDNA as a real-time biomarker for monitoring resistance and informing adaptive treatment strategies, particularly in sequential endocrine therapy where early identification of resistance-associated mutations may guide timely treatment modification. This is especially relevant in light of the recent ASCO recommendations supporting routine ct ESR1 m testing in patients with metastatic ER + ve, HER2-ve BC progressing on hormonal therapy, supported in the UK with ct ESR1 m being added to the cancer test directory. Declarations Acknowledgments of research support for the study This study was supported by program grant funding from Cancer Research UK to JAS and RCC (C14315/A23464) and a donation from Nonacus Ltd. Disclosures RKH and JL are employees of Nonacus Ltd. Funding This study was supported by program grant funding from Cancer Research UK to JAS and RCC (C14315/A23464) and a donation from Nonacus Ltd Author Contribution Author contributionsConceptualization: RCC, JS and CP; Methodology: KP, LJM, JAS, RCC and CP; Data Acquisition: KP and LJM, Formal Analysis: KP, MKW, RKH and JL.; Resources: CC and CP.; Data Curation, KP, LJM, MKW, RKH and JLL; Writing (Original Draft Preparation): KP, RKH, JS, CC and CP; Writing (Review & Editing): KP, JAS, RCC and CP; Supervision: JS, RCC and CP and Funding Acquisition: CC and CP. All authors reviewed the manuscript. Acknowledgement We thank the women who took part in this study; the doctors, nurses and support staff at the following local sites: Royal Liverpool University Hospital (3 patients); University College London Hospital (2 patients); Beatson West of Scotland Cancer Centre (4 patient); Imperial College NHS Foundation Trust, London (9 patients); Western General Hospital (1 patient); The Christie NHS Foundation Trust (5 patients). We also thank the independent members of the trial steering committee and the independent data monitoring committee. IRIS was an NIHR Clinical Research Network portfolio trial and we acknowledge the help of the local research networks that supported recruitment at UK sites. The research was carried out at the National Institute for Health and Care Research Leicester Biomedical Research Centre, and we also thank the support of the Leicester Cancer Research Centre. This research used the ALICE and SPECTRE high performance computing facilities at the University of Leicester, and NGS analysis used the Nonacus ctDNA research pipeline. Data Availability Data is provided within the manuscript or supplementary information files References Ferlay, J., et al., Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer, 2019. 144 (8): p. 1941-1953. Clark, G.M., C.K. Osborne, and W.L. McGuire, Correlations between estrogen receptor, progesterone receptor, and patient characteristics in human breast cancer. J Clin Oncol, 1984. 2 (10): p. 1102-9. Toy, W., et al., ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat Genet, 2013. 45 (12): p. 1439-45. Clarke, R., J.J. Tyson, and J.M. Dixon, Endocrine resistance in breast cancer--An overview and update. Mol Cell Endocrinol, 2015. 418 Pt 3 (0 3): p. 220-34. Jeselsohn, R., et al., ESR1 mutations-a mechanism for acquired endocrine resistance in breast cancer. Nat Rev Clin Oncol, 2015. 12 (10): p. 573-83. Rasha, F., M. Sharma, and K. Pruitt, Mechanisms of endocrine therapy resistance in breast cancer. Mol Cell Endocrinol, 2021. 532 : p. 111322. Zhang, Q.X., et al., An estrogen receptor mutant with strong hormone-independent activity from a metastatic breast cancer. Cancer Res, 1997. 57 (7): p. 1244-9. Li, J., et al., PTEN, a putative protein tyrosine phosphatase gene mutated in human brain, breast, and prostate cancer. Science, 1997. 275 (5308): p. 1943-7. Smith, C.L., Z. Nawaz, and B.W. O'Malley, Coactivator and corepressor regulation of the agonist/antagonist activity of the mixed antiestrogen, 4-hydroxytamoxifen. Mol Endocrinol, 1997. 11 (6): p. 657-66. Garcia-Becerra, R., et al., Mechanisms of resistance to endocrine therapy in breast cancer: focus on signaling pathways, miRNAs and genetically based resistance. Int J Mol Sci, 2012. 14 (1): p. 108-45. Robinson, D.R., et al., Activating ESR1 mutations in hormone-resistant metastatic breast cancer. Nat Genet, 2013. 45 (12): p. 1446-51. Palmieri, C., et al., Breast cancer: current and future endocrine therapies. Mol Cell Endocrinol, 2014. 382 (1): p. 695-723. Suzuki, T., et al., Estrogen sulfotransferase and steroid sulfatase in human breast carcinoma. Cancer Res, 2003. 63 (11): p. 2762-70. Stanway, S.J., et al., Phase I study of STX 64 (667 Coumate) in breast cancer patients: the first study of a steroid sulfatase inhibitor. Clin Cancer Res, 2006. 12 (5): p. 1585-92. Coombes, R.C., et al., A phase I dose escalation study to determine the optimal biological dose of irosustat, an oral steroid sulfatase inhibitor, in postmenopausal women with estrogen receptor-positive breast cancer. Breast Cancer Res Treat, 2013. 140 (1): p. 73-82. Palmieri, C., et al., IRIS study: a phase II study of the steroid sulfatase inhibitor Irosustat when added to an aromatase inhibitor in ER-positive breast cancer patients. Breast Cancer Res Treat, 2017. 165 (2): p. 343-353. Page, K., et al., Circulating Tumor DNA Profiling From Breast Cancer Screening Through to Metastatic Disease. JCO Precis Oncol, 2021. 5 . Page, K., et al., Prevalence of ctDNA in early screen-detected breast cancers using highly sensitive and specific dual molecular barcoded personalised mutation assays. Ann Oncol, 2021. 32 (8): p. 1057-1060. Niu, L., et al., Optimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline. bioRxiv, 2024. McLaren, W., et al., The Ensembl Variant Effect Predictor. Genome Biol, 2016. 17 (1): p. 122. Danecek, P., et al., Twelve years of SAMtools and BCFtools. Gigascience, 2021. 10 (2). Kandoth, C., mskcc/vcf2maf: vcf2maf v1.6. . 2020: Zenodo. Jeselsohn, R., et al., Emergence of constitutively active estrogen receptor-alpha mutations in pretreated advanced estrogen receptor-positive breast cancer. Clin Cancer Res, 2014. 20 (7): p. 1757-1767. Palmieri, C., et al., IPET study: an FLT-PET window study to assess the activity of the steroid sulfatase inhibitor irosustat in early breast cancer. Breast Cancer Res Treat, 2017. 166 (2): p. 527-539. Bidard, F.C., et al., Elacestrant (oral selective estrogen receptor degrader) Versus Standard Endocrine Therapy for Estrogen Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: Results From the Randomized Phase III EMERALD Trial. J Clin Oncol, 2022. 40 (28): p. 3246-3256. Bidard, F.C., et al., First-Line Camizestrant for Emerging ESR1-Mutated Advanced Breast Cancer. N Engl J Med, 2025. Additional Declarations No competing interests reported. Supplementary Files PageetalSupplementaryTables.xlsx Supplementary Table 1. Clinical details for all 24 patients in the patient cohort, part of the IRIS study. This includes receptor status, tumour information, AI therapy and disease response. Supplementary Table 2. List of SNVs present on the custom mutation panel. Supplementary Table 3. Levels of cfDNA (ng/ml) in all patient samples in the study cohort (n=96), timepoints and the date the blood sample was taken. Supplementary Table 4. Summary of SNVs detected in FFPE tumour tissue DNA. Table includes gene ID, amino acid change, chromosome, location, total read count, total reads count for the reference allele, total read count for the variant allele, variant allele frequency, VAF (%) and tumour type. Supplementary Table 5. Summary of SNVs detected in plasma samples from IRIS cohort. Table includes gene ID, amino acid change, chromosome, location, total read count, total reads count for the reference allele, total read count for the variant allele and variant allele frequency, VAF (%). Supplementary Table 6. SNVs present in matched FFPE tumour DNA and cfDNA. Table includes gene ID, amino acid change, VAF (%) from FFPE tumour and all cfDNA timepoints. NS indicates no sample taken (timepoint not analysed). SupplementaryFigure1.tif Supplementary Figure 1. Estrogen biosynthesis pathways and targets of endocrine therapies. SupplementaryFigure2.tif Supplementary Figure 2. CtDNA dynamics and cfDNA levels over time in patients with stable disease with at least two ctDNA positive timepoints. Dotted line indicates mutation also detected in tumour DNA. A) Patient 1; B) Patient 7; C) Patient 8; D) Patient 17; E) Patient 18 and F) Patient 19. SupplementaryFigure3.tif Supplementary Figure 3. CtDNA dynamics and cfDNA levels over time in patients with progressive disease with at least two ctDNA positive timepoints. Dotted line indicates mutation also detected in tumour DNA. A) Patient 4; B) Patient 5; C) Patient 6; D) Patient 9; E) Patient 10; F) Patient 12; G) Patient 13; H) Patient 14; I) Patient 16; J) Patient 21; K) Patient 22; L) Patient 23 and M) Patient 24. Cite Share Download PDF Status: Published Journal Publication published 09 Dec, 2025 Read the published version in Breast Cancer Research and Treatment → Version 1 posted Editorial decision: Revision requested 17 Aug, 2025 Reviews received at journal 16 Aug, 2025 Reviews received at journal 09 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviewers agreed at journal 03 Aug, 2025 Reviewers invited by journal 03 Aug, 2025 Editor assigned by journal 23 Jul, 2025 Submission checks completed at journal 23 Jul, 2025 First submitted to journal 22 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7187693","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496417711,"identity":"3f3b2ecf-8943-4dd3-8a2e-3edea2f0c916","order_by":0,"name":"Karen Page","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie3RsQrCMBCA4SuC00HXSMW+woUuDlVfxVLQpYPg4mgJmKXgWt9CcHUIOHTpQ7QIdtXNQdDqJAhpR4f8Uwh8SY4AmEx/GIMgLq4LwO/NTgMJBU/pQ6x1SzLfOEifdUvSk4HwfPL7tpRVcTuCa6/RIx1xsIzPEc2Q5TmP0wvwVKE31ZEBq2+J6ITEIkugAmsP6KkGsnGG9ERyq1I8FEwaifMmQKq+BbgABcGbaB/WS0rBEwrrWSK+SxQL01N3qR2fZfOyuK/GE1tmxfWu/NFWigPTkZ8jmn7FZDKZTG16Ac/zRG+zB/m4AAAAAElFTkSuQmCC","orcid":"","institution":"University of Leicester","correspondingAuthor":true,"prefix":"","firstName":"Karen","middleName":"","lastName":"Page","suffix":""},{"id":496417712,"identity":"82a59087-cadb-43c2-b2b9-aa51944d3158","order_by":1,"name":"Luke J Martinson","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Luke","middleName":"J","lastName":"Martinson","suffix":""},{"id":496417713,"identity":"8868b7b9-c0cf-41ee-9b7b-3fed0ed7a1fb","order_by":2,"name":"Robert K Hastings","email":"","orcid":"","institution":"Nonacus Ltd","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"K","lastName":"Hastings","suffix":""},{"id":496417714,"identity":"866126db-735e-4aa8-8a95-614879a0233c","order_by":3,"name":"Emmanuel Acheampong","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"","lastName":"Acheampong","suffix":""},{"id":496417715,"identity":"607d7221-9b7d-486f-acda-3955e7b8d992","order_by":4,"name":"Marc K Wadsley","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Marc","middleName":"K","lastName":"Wadsley","suffix":""},{"id":496417716,"identity":"57b3d25f-574a-4a4e-9e15-950d143d56c9","order_by":5,"name":"Rebecca C Allsopp","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Rebecca","middleName":"C","lastName":"Allsopp","suffix":""},{"id":496417717,"identity":"5d992950-cdc4-46cc-9bae-9456da5181ff","order_by":6,"name":"Jin-Li Luo","email":"","orcid":"","institution":"Nonacus Ltd","correspondingAuthor":false,"prefix":"","firstName":"Jin-Li","middleName":"","lastName":"Luo","suffix":""},{"id":496417718,"identity":"087304ff-2737-4457-a121-3701642fa1a3","order_by":7,"name":"R. Charles Coombes","email":"","orcid":"","institution":"Imperial College","correspondingAuthor":false,"prefix":"","firstName":"R.","middleName":"Charles","lastName":"Coombes","suffix":""},{"id":496417719,"identity":"b4b07e56-b08f-4221-973b-0801d0e3327a","order_by":8,"name":"Jacqueline A Shaw","email":"","orcid":"","institution":"University of Leicester","correspondingAuthor":false,"prefix":"","firstName":"Jacqueline","middleName":"A","lastName":"Shaw","suffix":""},{"id":496417720,"identity":"31fa16be-b421-497e-9bee-c4c5ba973f26","order_by":9,"name":"Carlo Palmieri","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Carlo","middleName":"","lastName":"Palmieri","suffix":""}],"badges":[],"createdAt":"2025-07-22 13:38:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7187693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7187693/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10549-025-07857-6","type":"published","date":"2025-12-09T15:58:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88517686,"identity":"89bc3118-56c8-4231-97ee-a3c332ad6b9d","added_by":"auto","created_at":"2025-08-07 09:11:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":502754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOncoprint illustrating the mutational landscape in patients treated with AI and Irosustat, enrolled in IRIS study (n=24). \u003c/strong\u003e(A) Missense (purple) or truncated (green) mutations detected in FFPE tumour DNA from BC patients (n=16); with either stable (n=5; deep pink) or progressive disease (n=9; turquoise) and unknown disease stage (n=1; orange). P indicates patient number; cancer type is indicated (infiltrating ductal carcinoma, pink and unknown, blue); (B) Missense mutations detected in cfDNA from patients (n=24) treated with different AI therapies (exemestane (pink), letrozole (green) and anastrozole (blue); with either stable (n=7; deep pink) or progressive disease (n=15; turquoise) and unknown disease stage (n=1; orange). P indicates patient number followed by either BL (baseline), numbers indicating timepoints in months or EOS (end of study).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/9e3e3f8864fc320925c717a7.png"},{"id":98243914,"identity":"a48a0753-f57e-4c97-83fd-e8dd815c6fab","added_by":"auto","created_at":"2025-12-15 16:11:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1124382,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/257d813f-f3d1-4d5d-8964-b7f6bae57082.pdf"},{"id":88517688,"identity":"20433e77-045f-45d1-b761-b5488a547a93","added_by":"auto","created_at":"2025-08-07 09:11:07","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":53942,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e. Clinical details for all 24 patients in the patient cohort, part of the IRIS study. This includes receptor status, tumour information, AI therapy and disease response.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e. List of SNVs present on the custom mutation panel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 3\u003c/strong\u003e. Levels of cfDNA (ng/ml) in all patient samples in the study cohort (n=96), timepoints and the date the blood sample was taken.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 4. \u003c/strong\u003eSummary of SNVs detected in\u003cstrong\u003e \u003c/strong\u003eFFPE tumour tissue DNA. Table includes gene ID, amino acid change, chromosome, location, total read count, total reads count for the reference allele, total read count for the variant allele, variant allele frequency, VAF (%) and tumour type.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 5. \u003c/strong\u003eSummary of SNVs detected in\u003cstrong\u003e \u003c/strong\u003eplasma samples from IRIS cohort. Table includes gene ID, amino acid change, chromosome, location, total read count, total reads count for the reference allele, total read count for the variant allele and variant allele frequency, VAF (%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table 6. \u003c/strong\u003eSNVs present in matched FFPE tumour DNA and cfDNA. Table includes gene ID, amino acid change, VAF (%) from FFPE tumour and all cfDNA timepoints. NS indicates no sample taken (timepoint not analysed).\u003c/p\u003e","description":"","filename":"PageetalSupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/2c2f9494435999836db83de6.xlsx"},{"id":88517689,"identity":"f507e5a3-bb16-410b-b25d-3ff6f7f62244","added_by":"auto","created_at":"2025-08-07 09:11:07","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":95646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1. \u003c/strong\u003eEstrogen biosynthesis pathways and targets of endocrine therapies\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/99eca6f4b07c9de1393e7703.tif"},{"id":88517692,"identity":"f455da15-ceef-4752-80fb-3ea34bc0391b","added_by":"auto","created_at":"2025-08-07 09:11:07","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":142328,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2. \u003c/strong\u003eCtDNA dynamics and cfDNA levels over time in patients with stable disease with at least two ctDNA positive timepoints. Dotted line indicates mutation also detected in tumour DNA. A) Patient 1; B) Patient 7; C) Patient 8; D) Patient 17; E) Patient 18 and F) Patient 19.\u003c/p\u003e","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/00b628c700ab4af36bf2128c.tif"},{"id":88517695,"identity":"13b71358-add2-4dd2-9777-494545bf52f7","added_by":"auto","created_at":"2025-08-07 09:11:07","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":217258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3. \u003c/strong\u003eCtDNA dynamics and cfDNA levels over time in patients with progressive disease with at least two ctDNA positive timepoints.\u003cstrong\u003e \u003c/strong\u003eDotted line indicates mutation also detected in tumour DNA. A) Patient 4; B) Patient 5; C) Patient 6; D) Patient 9; E) Patient 10; F) Patient 12; G) Patient 13; H) Patient 14; I) Patient 16; J) Patient 21; K) Patient 22; L) Patient 23 and M) Patient 24.\u003c/p\u003e","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-7187693/v1/51daaa44c8b76aecd45b7585.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssessing Endocrine Resistance: Monitoring Circulating ESR1 mutations in Irosustat-Treated ER positive Breast Cancer\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most common cancer in women worldwide, with more than 600,000 people dying annually and despite advances in treatment and detection, these deaths are largely due to metastatic recurrence occurring more than 5 years post diagnosis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. About 75% of BC are estrogen receptor alpha (ERα) positive (ER\u0026thinsp;+\u0026thinsp;ve), this plays a pivotal role in its development and progression as it relies upon estrogen-induced ERα transcriptional activation for growth. ER expression is related to patient age and correlates with lower tumour grade and proliferation, less aneuploidy, less frequent amplification of the c-erbB2 (HER2) oncogene and progesterone receptor (PR) expression [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These clinical factors, together with ER expression, guide treatment decisions, and particularly in those patients with metastatic disease, where endocrine therapy remains the most effective option.\u003c/p\u003e\u003cp\u003eEndocrine therapy targets ER by depriving the tumour of estrogen (E2) or by inhibiting ER binding with an agonist. Aromatase inhibitors (AIs) such as anastrozole and letrozole, block aromatase and interfere with conversion of androgens into estrogens, and form the backbone of treatment for ER\u0026thinsp;+\u0026thinsp;ve BC (Supplementary Fig.\u0026nbsp;1). \u003cem\u003eESR1\u003c/em\u003e gene mutations (ct\u003cem\u003eESR1\u003c/em\u003em) that typically occur in the ligand binding domain (LBD) of ERα lead to constitutional activation of the receptor and resistance to therapies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With the advancement of endocrine therapies however, there is increased concern of the potential for resistance [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and particularly that which is \u0026lsquo;acquired\u0026rsquo;, as approx. 20% of patients who present with early disease will develop resistance manifested as recurrences either during or after endocrine treatment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This is defined by tumours which typically show a good overall early response, but over the course of therapy become unresponsive [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], compared to \u003cem\u003ede novo\u003c/em\u003e resistance, which occurs before treatment with no response to first line endocrine therapies. Potential mechanisms of endocrine resistance include loss of estrogen dependence [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] or inefficiencies of therapies e.g., due to modulation of signalling cascades [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, more recently, deep-sequencing studies have highlighted the importance of acquired mutations of ER in driving resistance [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], where acquisition of such mutations renders the cancer cells insensitive to AIs and is predicted to reduce sensitivity to anti-estrogens [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to managing postmenopausal BC through decreasing circulating levels of oestradiol via inhibition of aromatase [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], the steroid sulphatase (STS) pathway, a second major pathway for estrogen biosynthesis, can also be targeted. Studies have shown increased protein levels of STS in BC are associated with large tumour size, increased risk of recurrence and poorer overall survival [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], therefore this alternative pathway is also of significance. Two phase I studies of a first-generation inhibitor of STS, Irusostat (STX64; a tricyclic coumarin sulfamate), showed it to be potent, well tolerated and caused a significant decrease in serum concentrations of steroids with estrogenic properties [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Following this, a phase II combination study (IRIS) was designed to investigate the efficacy and tolerability of Irosustat in postmenopausal women who had progressed on a first-line AI from which they had derived clinical benefit [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Patients were followed up each month for six months and three monthly thereafter, until disease progression or unacceptable toxicity occurred, with the hypothesis that the blockade of STS with Irosustat on the background of continued AI could result in clinical benefit.\u003c/p\u003e\u003cp\u003eIn this study, we analysed circulating cell-free DNA (cfDNA) from serial plasma samples of 24 patients enrolled in the IRIS phase II trial collected over a median of 3 months (range 1\u0026ndash;18 months) on the study. Using a custom-designed targeted next-generation sequencing panel relevant to metastatic breast cancer, we profiled mutational hotspots, including \u003cem\u003eESR1\u003c/em\u003e, to characterise the ctDNA genomic landscape in patients progressing on first line AI who were then continued on their AI therapy combined with the steroid sulfatase (STS) inhibitor Irosustat. Our objectives were to quantify circulating tumour DNA (ctDNA) levels, assess ctDNA dynamics, and explore how ctDNA \u003cem\u003eESR1\u003c/em\u003e mutations (ct\u003cem\u003eESR1\u003c/em\u003em) may influence treatment response, as their impact on Irosustat efficacy remains unclear.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003ePatients and Samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003e The IRIS study (ClinicalTrials.gov NCT0178 5992) was a multicentre, open label phase II trial performed in nine academic medical centres in the United Kingdom conducted in accordance with Good Clinical Practice Guidelines and the Declaration of Helsinki. Ethical approval was given by the Riverside Research Ethics Committee (an Independent Ethics Committee; reference 12/LO/0477), and approved by the United Kingdom Medicines and Healthcare Products Regulatory Agency (EudraCT: 2011-005680-25). All participants gave written informed consent prior to participation and were over 18 years of age.\u003c/p\u003e\u003cp\u003eWomen were eligible if they were postmenopausal, with histologically confirmed ER\u0026thinsp;+\u0026thinsp;ve, HER2 -ve inoperable locally advanced or metastatic BC, where ER positivity was based on local laboratory assessment (Supplementary Table\u0026nbsp;1) and had developed progressive disease during first-line AI therapy for recurrent ER\u0026thinsp;+\u0026thinsp;BC. Eligible patients also had to have derived clinical benefit, defined as a documented objective response at any point or disease stabilisation (SD) for at least 6 months, from their first-line AI treatment. The disease had to be measurable by CT/MRI scan according to RECIST v1.1. Patients were monitored by serial blood sampling over a period of 1\u0026ndash;18 months along with clinical evaluations. 8ml blood was taken into K2 EDTA tubes (BD Biosciences) and processed to plasma within two hours of collection for extraction of cfDNA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExtraction and quantitation of DNA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal cfDNA was isolated from 115 serially collected blood plasma samples from 24 patients, using 4ml blood plasma with the MagMAX\u0026trade; Cell-free DNA Isolation Kit (Thermo Fisher Scientific) as described previously [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Matching formalin-fixed paraffin-embedded (FFPE) tumour tissue was available for 16 of the 24 patients; 15 were derived from the primary tumour, and one from a metastatic relapse. Tumour DNA was isolated from FFPE tissue blocks using the GeneRead\u0026trade; Kit (Qiagen), as described previously [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Quantitation and quality checks for cfDNA and tumour DNA were performed using the Agilent Tapestation cell-free DNA Screentape (Agilent) and Qubit\u0026trade; dsDNA HS Assay kit (Thermo Fisher Scientific) respectively, according to manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTargeted next generation sequencing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA custom next-generation sequencing panel targeting 397 hotspot mutations across 19 genes (Supplementary Table\u0026nbsp;2) was developed by informaticians using a bespoke assay design pipeline (Nonacus Ltd). A total of 96 libraries were prepared from plasma DNA across 24 patients (median input: 50 ng). using this and the Cell3\u0026trade; Target kit (Nonacus). Libraries were pooled equal amounts (n\u0026thinsp;=\u0026thinsp;8) and hybridised with biotin-labelled DNA probes to enrich for the targeted regions. Additionally, 16 libraries were prepared from tumour FFPE DNA (median input: 55 ng), pooled together, and similarly enriched. All final captured library pools were sequenced on the Illumina NovaSeq platform.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBioinformatic analysis of raw sequencing data\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFASTQ files were processed using Nonacus' custom research tumour-only pipelines, which incorporate Sentieon tools (v202112.06) for alignment, variant calling, and quality control [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], FASTP (v0.23.4) for adapter and quality trimming (Chen et al, 2018), and the Ensembl Variant Effect Predictor (VEP) (v108.2) for variant annotation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Two workflows were used depending on sample type.\u003c/p\u003e\u003cp\u003eFor FFPE samples, raw FASTQ files were trimmed using FASTP (Chen et al, 2018) then aligned directly to the GRCh38 reference genome using sentieon bwa mem. Reads were sorted, indexed, and recalibrated using QualCal [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Somatic variants were called using TNhaplotyper2 in tumour only mode, followed by orientation bias and contamination correction using OrientationBias and ContaminationModel, as in the cfDNA workflow. UMI-specific steps were omitted. Variant refinement was carried out using TNfilter, with settings appropriate for FFPE data [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor cfDNA samples, raw FASTQ files containing UMIs were first processed using sentieon umi extract, and consensus reads were generated using Sentieon\u0026rsquo;s UMI consensus module. The resulting consensus FASTQ files were then trimmed using FASTP (Chen et al, 2018) to remove adapters and low-quality bases. Trimmed consensus reads were aligned to the GRCh38 reference genome using sentieon bwa mem, followed by sorting, indexing, and Base Quality Score Recalibration (BQSR) using QualCal [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSomatic variant calling was performed in tumour-only mode using TNhaplotyper2 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] with orientation bias and tumour contamination correction via OrientationBias and ContaminationModel [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Variants were refined using TNfilter, with parameters optimized for cfDNA, and further filtered using BCFtools (v1.16) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn both workflows, variants were annotated using the Ensembl Variant Effect Predictor (VEP, v108.2) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] run in offline mode with cache version 108. Annotated VCFs were compressed and converted to MAF format using vcf2maf (v1.6.21) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] for downstream analysis.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe Mann\u0026ndash;Whitney non-parametric statistical test was used to compare cfDNA yields in patients with stable and progressive disease; Spearman\u0026rsquo;s rank correlation coefficient was used to investigate the correlation between disease status and ct\u003cem\u003eESR1\u003c/em\u003em variant allele fraction (VAF). These analyses were carried out using GraphPad Prism v10.2.3 software. All P values were two-sided and those\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 24 patients with ER+, HER2-ve, inoperable locally advanced or metastatic BC, who were progressing on first line AI were enrolled into the IRIS phase II trial. The mean patient age was 56 years (range: 31\u0026ndash;76). All patients received the STS inhibitor Irosustat in combination with a first-line AI: exemestane (n\u0026thinsp;=\u0026thinsp;3), letrozole (n\u0026thinsp;=\u0026thinsp;16), or anastrozole (n\u0026thinsp;=\u0026thinsp;5; Supplementary Table\u0026nbsp;1). At the time of Irosustat addition, 7 patients exhibited stable disease (SD), 15 showed progressive disease (PD) and two were unknown. Longitudinal plasma cfDNA samples were collected over a median of 3 months (range 1 to 18; average 4 samples per patients, total 96 across 24 patients). Matched FFPE primary tumour tissue was available for 16 of the patients. All 96 plasma cfDNA samples and 16 tumour DNA samples were successfully sequenced using a semi-automated, standardised workflow under good clinical laboratory practice (GCLP). The median cfDNA concentration in plasma was 24.6 ng/mL (range: 5.1\u0026ndash;948.2 ng/mL), with no significant difference between patients with SD and PD (P\u0026thinsp;=\u0026thinsp;0.0786, Mann\u0026ndash;Whitney U test).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMutational Landscape in Primary Tumours\u003c/b\u003e\u003c/p\u003e\u003cp\u003eApplying a cut off 5% VAF in the primary tumour FFPE DNA, targeted next-generation sequencing (NGS) identified 17 somatic missense mutations across 9 genes (\u003cem\u003eCDH1\u003c/em\u003e, \u003cem\u003eERBB3\u003c/em\u003e, \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eGATA3\u003c/em\u003e, \u003cem\u003eKMT2C\u003c/em\u003e, \u003cem\u003eNF1\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eMAP3K1\u003c/em\u003e, and \u003cem\u003eTP53\u003c/em\u003e) in tumours from 13/16 patients. Each of the 13 tumours harboured at least one somatic mutation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; Supplementary Table\u0026nbsp;4), with \u003cem\u003ePIK3CA\u003c/em\u003e the most frequently mutated gene, (5 mutations in 5/13 tumours; 38%). \u003cem\u003eESR1\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e mutations were each detected in 2 tumours (31%). Among 11 patients with PD, ct\u003cem\u003eESR1\u003c/em\u003em were detected in 2 patients (18%); one in metastatic tissue and one in primary tumour tissue. \u003cem\u003ePIK3CA\u003c/em\u003e mutations were identified in 5 tumours.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCirculating Tumour DNA profiles and ctESR1\u003c/b\u003e\u003cb\u003em\u003c/b\u003e \u003cb\u003eresistance dynamics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn plasma, 21 of 24 patients (88%) had at least one high-confidence somatic mutation identified across 77/96 timepoints. A total of 248 mutations were detected spanning 10 genes (\u003cem\u003eAKT1\u003c/em\u003e, \u003cem\u003eCDH1\u003c/em\u003e, \u003cem\u003eERBB3\u003c/em\u003e, \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eGATA3\u003c/em\u003e, \u003cem\u003eKMT2C\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eMAP3K1\u003c/em\u003e, \u003cem\u003eRB1\u003c/em\u003e, and \u003cem\u003eTP53\u003c/em\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; Supplementary Table\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003cem\u003eESR1\u003c/em\u003e was the most frequently mutated gene in cfDNA, detected in 16 of 21 patients (76%) and accounted for 131 of 248 mutations (53%). Common mutations present in both tumour and plasma samples were predominantly in \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003ePIK3CA\u003c/em\u003e (Supplementary Table\u0026nbsp;6). However, an \u003cem\u003eESR1\u003c/em\u003e mutation (p.D538G, 70.8% VAF) was also detected in the baseline plasma sample matched to one patient (P5, 0.75% VAF).\u003c/p\u003e\u003cp\u003eAt study entry, 14 out of 16 patients had detectable ct\u003cem\u003eESR1\u003c/em\u003em, with 6 of these cases exhibiting polyclonal mutations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), with seven patients showing ct\u003cem\u003eESR1\u003c/em\u003em evolving over time. In total, 11 patients (69%) had polyclonal mutations located in the ligand-binding domain (LBD), including p.D538G, p.Y537N/S/C, p.L536H/Q/P/R, and p.S463P (Supplementary Figs.\u0026nbsp;2 and 3). Of these, 6 patients had polyclonal ct\u003cem\u003eESR1\u003c/em\u003em at baseline, while 5 had single variants. The most prevalent mutation observed was p.D538G (32% of all ct\u003cem\u003eESR1\u003c/em\u003em events).\u003c/p\u003e\u003cp\u003eMutations in \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, and \u003cem\u003eTP53\u003c/em\u003e comprised 86% of all ctDNA alterations (214 of 248; Supplementary Figs.\u0026nbsp;2, 3). Correlation analysis revealed no significant association between treatment response and either ct\u003cem\u003eESR1\u003c/em\u003em VAF (P\u0026thinsp;=\u0026thinsp;0.347, r\u0026thinsp;=\u0026thinsp;0.087) or ct\u003cem\u003eESR1\u003c/em\u003em presence/absence (P\u0026thinsp;=\u0026thinsp;0.432, r = \u0026minus;\u0026thinsp;0.168; Spearman\u0026rsquo;s rank correlation).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAnalysis of primary tumour DNA from patients progressing on AI and who were then continued on AI plus Irosustat, identified somatic mutations in key BC associated genes, most notably \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e. The high presence of \u003cem\u003ePIK3CA\u003c/em\u003e mutations, which activate the PI3K/AKT/mTOR pathway can drive ER\u0026ndash;independent tumour growth [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], while the presence of TP53 mutations is consistent with its known association with tumour progression and poor clinical outcomes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn blood plasma, c\u003cem\u003etESR1\u003c/em\u003em were the most prevalent, with 53% of patients exhibiting one or more mutations, with 88% located in the LBD of ERα, aligning with previous studies that observed ct\u003cem\u003eESR1\u003c/em\u003em located in the LBD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Mutations within the LBD are known to mimic estrogen binding, leading to the activation of ERα even in the presence of AIs, and this mechanism of ligand-independent activation is a well-characterised pathway for resistance to endocrine therapy in ER-positive BC [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe high frequency of polyclonal ct\u003cem\u003eESR1\u003c/em\u003em located in the LBD highlights the molecular heterogeneity of endocrine resistance in advanced ER-positive BC, making it difficult to target with a single endocrine therapy. The co-existence of multiple ct\u003cem\u003eESR1\u003c/em\u003em within individual patients likely reflects ongoing selective pressure from AI therapy and suggests convergent evolution towards ligand-independent ERα activation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eESR1\u003c/em\u003em in primary tumours are extremely rare, they are detected in fewer than 1% of treatment-na\u0026iuml;ve cases, as demonstrated in the TCGA Breast Cancer study, which analysed over 800 primary breast tumours [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Here, a single \u003cem\u003eESR1\u003c/em\u003em (p.R394C) was identified in the primary tumour tissue but was absent from matched cfDNA. This discrepancy highlights both the technical limitations of NGS and the dynamic nature of tumour evolution under treatment pressure. Notably, p.R394C is located outside the LBD, where most activating, resistance-associated \u003cem\u003eESR1\u003c/em\u003em are found and its absence in cfDNA (and location outside the LBD) suggest it may not be a driver of aromatase inhibitor resistance and could represent a passenger mutation or a potential sequencing artefact.\u003c/p\u003e\u003cp\u003eAlthough the earlier IPET study demonstrated a significant reduction in the proliferation marker Ki67 after just two weeks of Irosustat treatment [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], our findings suggest that patients harbouring ct\u003cem\u003eESR1\u003c/em\u003em at treatment initiation (14 of 24 patients; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) are unlikely to derive substantial benefit from the addition of Irosustat. Given that Irosustat, an STS inhibitor, reduces the local conversion of inactive estrogen sulfates into active estrogens, we suggest the emergence of ligand-independent ct\u003cem\u003eESR1\u003c/em\u003em may undermine its efficacy, particularly when used in combination with AIs in patients who already exhibit endocrine resistance. Therefore, retrospective analysis of this cohort underscores the importance of selecting patients with wild-type \u003cem\u003eESR1\u003c/em\u003e for future studies involving sequential estrogen-lowering therapies.\u003c/p\u003e\u003cp\u003eFinally, data from two recent clinical trials investigating the efficacy of oral selective estrogen receptor degraders (SERDs) in ct\u003cem\u003eESR1\u003c/em\u003em-positive patients with advanced breast cancer suggest a promising alternative to Irosustat. The EMERALD trial demonstrated that elacestrant, the first approved oral SERD, significantly improved progression-free survival (PFS) in patients with ESR1-mutant tumours who had received two prior lines of AI-based endocrine therapy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. More recently, the SERENA-6 trial evaluated camizestrant in patients who developed ct\u003cem\u003eESR1\u003c/em\u003em during first-line therapy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this trial, patients who were switched from an AI to camizestrant, while continuing a CDK4/6 inhibitor, experienced longer PFS than those who continued with the AI plus CDK4/6 inhibitor combination. Notably, the switch in therapy was guided by the emergence of ct\u003cem\u003eESR1\u003c/em\u003em detected via ctDNA testing, prior to clinical or radiologic progression.\u003c/p\u003e\u003cp\u003eThese findings underscore the clinical value of SERDs in overcoming ct\u003cem\u003eESR1\u003c/em\u003em-mediated endocrine resistance, and suggest that elacestrant or camizestrant may offer therapeutic advantages in settings where Irosustat demonstrates limited efficacy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese findings emphasise the value of longitudinal liquid biopsy profiling to capture resistance mechanisms that may not be detectable in archival primary tumour tissue. The frequent detection of polyclonal ct\u003cem\u003eESR1\u003c/em\u003em in both stable and progressive disease further illustrates the challenge of targeting a single \u003cem\u003eESR1\u003c/em\u003e variant in patients progressing on AI. However, our data support the use of ctDNA as a real-time biomarker for monitoring resistance and informing adaptive treatment strategies, particularly in sequential endocrine therapy where early identification of resistance-associated mutations may guide timely treatment modification. This is especially relevant in light of the recent ASCO recommendations supporting routine ct\u003cem\u003eESR1\u003c/em\u003em testing in patients with metastatic ER\u0026thinsp;+\u0026thinsp;ve, HER2-ve BC progressing on hormonal therapy, supported in the UK with ct\u003cem\u003eESR1\u003c/em\u003em being added to the cancer test directory.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments of research support for the study\u003c/h2\u003e\n\u003cp\u003eThis study was supported by program grant funding from Cancer Research UK to JAS and RCC (C14315/A23464) and a donation from Nonacus Ltd.\u003c/p\u003e\n\u003ch2\u003eDisclosures\u003c/h2\u003e\n\u003cp\u003eRKH and JL are employees of Nonacus Ltd.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by program grant funding from Cancer Research UK to JAS and RCC (C14315/A23464) and a donation from Nonacus Ltd\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAuthor contributionsConceptualization: RCC, JS and CP; Methodology: KP, LJM, JAS, RCC and CP; Data Acquisition: KP and LJM, Formal Analysis: KP, MKW, RKH and JL.; Resources: CC and CP.; Data Curation, KP, LJM, MKW, RKH and JLL; Writing (Original Draft Preparation): KP, RKH, JS, CC and CP; Writing (Review \u0026amp; Editing): KP, JAS, RCC and CP; Supervision: JS, RCC and CP and Funding Acquisition: CC and CP. All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe thank the women who took part in this study; the doctors, nurses and support staff at the following local sites: Royal Liverpool University Hospital (3 patients); University College London Hospital (2 patients); Beatson West of Scotland Cancer Centre (4 patient); Imperial College NHS Foundation Trust, London (9 patients); Western General Hospital (1 patient); The Christie NHS Foundation Trust (5 patients). We also thank the independent members of the trial steering committee and the independent data monitoring committee. IRIS was an NIHR Clinical Research Network portfolio trial and we acknowledge the help of the local research networks that supported recruitment at UK sites. The research was carried out at the National Institute for Health and Care Research Leicester Biomedical Research Centre, and we also thank the support of the Leicester Cancer Research Centre. This research used the ALICE and SPECTRE high performance computing facilities at the University of Leicester, and NGS analysis used the Nonacus ctDNA research pipeline.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFerlay, J., et al., \u003cem\u003eEstimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods.\u003c/em\u003e Int J Cancer, 2019. \u003cstrong\u003e144\u003c/strong\u003e(8): p. 1941-1953.\u003c/li\u003e\n\u003cli\u003eClark, G.M., C.K. Osborne, and W.L. McGuire, \u003cem\u003eCorrelations between estrogen receptor, progesterone receptor, and patient characteristics in human breast cancer.\u003c/em\u003e J Clin Oncol, 1984. \u003cstrong\u003e2\u003c/strong\u003e(10): p. 1102-9.\u003c/li\u003e\n\u003cli\u003eToy, W., et al., \u003cem\u003eESR1 ligand-binding domain mutations in hormone-resistant breast cancer.\u003c/em\u003e Nat Genet, 2013. \u003cstrong\u003e45\u003c/strong\u003e(12): p. 1439-45.\u003c/li\u003e\n\u003cli\u003eClarke, R., J.J. Tyson, and J.M. Dixon, \u003cem\u003eEndocrine resistance in breast cancer--An overview and update.\u003c/em\u003e Mol Cell Endocrinol, 2015. \u003cstrong\u003e418 Pt 3\u003c/strong\u003e(0 3): p. 220-34.\u003c/li\u003e\n\u003cli\u003eJeselsohn, R., et al., \u003cem\u003eESR1 mutations-a mechanism for acquired endocrine resistance in breast cancer.\u003c/em\u003e Nat Rev Clin Oncol, 2015. \u003cstrong\u003e12\u003c/strong\u003e(10): p. 573-83.\u003c/li\u003e\n\u003cli\u003eRasha, F., M. Sharma, and K. Pruitt, \u003cem\u003eMechanisms of endocrine therapy resistance in breast cancer.\u003c/em\u003e Mol Cell Endocrinol, 2021. \u003cstrong\u003e532\u003c/strong\u003e: p. 111322.\u003c/li\u003e\n\u003cli\u003eZhang, Q.X., et al., \u003cem\u003eAn estrogen receptor mutant with strong hormone-independent activity from a metastatic breast cancer.\u003c/em\u003e Cancer Res, 1997. \u003cstrong\u003e57\u003c/strong\u003e(7): p. 1244-9.\u003c/li\u003e\n\u003cli\u003eLi, J., et al., \u003cem\u003ePTEN, a putative protein tyrosine phosphatase gene mutated in human brain, breast, and prostate cancer.\u003c/em\u003e Science, 1997. \u003cstrong\u003e275\u003c/strong\u003e(5308): p. 1943-7.\u003c/li\u003e\n\u003cli\u003eSmith, C.L., Z. Nawaz, and B.W. O\u0026apos;Malley, \u003cem\u003eCoactivator and corepressor regulation of the agonist/antagonist activity of the mixed antiestrogen, 4-hydroxytamoxifen.\u003c/em\u003e Mol Endocrinol, 1997. \u003cstrong\u003e11\u003c/strong\u003e(6): p. 657-66.\u003c/li\u003e\n\u003cli\u003eGarcia-Becerra, R., et al., \u003cem\u003eMechanisms of resistance to endocrine therapy in breast cancer: focus on signaling pathways, miRNAs and genetically based resistance.\u003c/em\u003e Int J Mol Sci, 2012. \u003cstrong\u003e14\u003c/strong\u003e(1): p. 108-45.\u003c/li\u003e\n\u003cli\u003eRobinson, D.R., et al., \u003cem\u003eActivating ESR1 mutations in hormone-resistant metastatic breast cancer.\u003c/em\u003e Nat Genet, 2013. \u003cstrong\u003e45\u003c/strong\u003e(12): p. 1446-51.\u003c/li\u003e\n\u003cli\u003ePalmieri, C., et al., \u003cem\u003eBreast cancer: current and future endocrine therapies.\u003c/em\u003e Mol Cell Endocrinol, 2014. \u003cstrong\u003e382\u003c/strong\u003e(1): p. 695-723.\u003c/li\u003e\n\u003cli\u003eSuzuki, T., et al., \u003cem\u003eEstrogen sulfotransferase and steroid sulfatase in human breast carcinoma.\u003c/em\u003e Cancer Res, 2003. \u003cstrong\u003e63\u003c/strong\u003e(11): p. 2762-70.\u003c/li\u003e\n\u003cli\u003eStanway, S.J., et al., \u003cem\u003ePhase I study of STX 64 (667 Coumate) in breast cancer patients: the first study of a steroid sulfatase inhibitor.\u003c/em\u003e Clin Cancer Res, 2006. \u003cstrong\u003e12\u003c/strong\u003e(5): p. 1585-92.\u003c/li\u003e\n\u003cli\u003eCoombes, R.C., et al., \u003cem\u003eA phase I dose escalation study to determine the optimal biological dose of irosustat, an oral steroid sulfatase inhibitor, in postmenopausal women with estrogen receptor-positive breast cancer.\u003c/em\u003e Breast Cancer Res Treat, 2013. \u003cstrong\u003e140\u003c/strong\u003e(1): p. 73-82.\u003c/li\u003e\n\u003cli\u003ePalmieri, C., et al., \u003cem\u003eIRIS study: a phase II study of the steroid sulfatase inhibitor Irosustat when added to an aromatase inhibitor in ER-positive breast cancer patients.\u003c/em\u003e Breast Cancer Res Treat, 2017. \u003cstrong\u003e165\u003c/strong\u003e(2): p. 343-353.\u003c/li\u003e\n\u003cli\u003ePage, K., et al., \u003cem\u003eCirculating Tumor DNA Profiling From Breast Cancer Screening Through to Metastatic Disease.\u003c/em\u003e JCO Precis Oncol, 2021. \u003cstrong\u003e5\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003ePage, K., et al., \u003cem\u003ePrevalence of ctDNA in early screen-detected breast cancers using highly sensitive and specific dual molecular barcoded personalised mutation assays.\u003c/em\u003e Ann Oncol, 2021. \u003cstrong\u003e32\u003c/strong\u003e(8): p. 1057-1060.\u003c/li\u003e\n\u003cli\u003eNiu, L., et al., \u003cem\u003eOptimizing Accuracy and Efficiency in Analyzing Non-UMI Liquid Biopsy Datasets Using the Sentieon ctDNA Pipeline.\u003c/em\u003e bioRxiv, 2024.\u003c/li\u003e\n\u003cli\u003eMcLaren, W., et al., \u003cem\u003eThe Ensembl Variant Effect Predictor.\u003c/em\u003e Genome Biol, 2016. \u003cstrong\u003e17\u003c/strong\u003e(1): p. 122.\u003c/li\u003e\n\u003cli\u003eDanecek, P., et al., \u003cem\u003eTwelve years of SAMtools and BCFtools.\u003c/em\u003e Gigascience, 2021. \u003cstrong\u003e10\u003c/strong\u003e(2).\u003c/li\u003e\n\u003cli\u003eKandoth, C., \u003cem\u003emskcc/vcf2maf: vcf2maf v1.6. \u003c/em\u003e. 2020: Zenodo.\u003c/li\u003e\n\u003cli\u003eJeselsohn, R., et al., \u003cem\u003eEmergence of constitutively active estrogen receptor-alpha mutations in pretreated advanced estrogen receptor-positive breast cancer.\u003c/em\u003e Clin Cancer Res, 2014. \u003cstrong\u003e20\u003c/strong\u003e(7): p. 1757-1767.\u003c/li\u003e\n\u003cli\u003ePalmieri, C., et al., \u003cem\u003eIPET study: an FLT-PET window study to assess the activity of the steroid sulfatase inhibitor irosustat in early breast cancer.\u003c/em\u003e Breast Cancer Res Treat, 2017. \u003cstrong\u003e166\u003c/strong\u003e(2): p. 527-539.\u003c/li\u003e\n\u003cli\u003eBidard, F.C., et al., \u003cem\u003eElacestrant (oral selective estrogen receptor degrader) Versus Standard Endocrine Therapy for Estrogen Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: Results From the Randomized Phase III EMERALD Trial.\u003c/em\u003e J Clin Oncol, 2022. \u003cstrong\u003e40\u003c/strong\u003e(28): p. 3246-3256.\u003c/li\u003e\n\u003cli\u003eBidard, F.C., et al., \u003cem\u003eFirst-Line Camizestrant for Emerging ESR1-Mutated Advanced Breast Cancer.\u003c/em\u003e N Engl J Med, 2025.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Liquid biopsy, circulating tumour DNA, custom targeted next-generation sequencing, Irusostat, breast cancer","lastPublishedDoi":"10.21203/rs.3.rs-7187693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7187693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e We aimed to investigate the prevalence and spectrum of \u003cem\u003eESR1\u003c/em\u003e mutations alongside cell-free DNA (cfDNA) dynamics in patients with estrogen receptor-positive metastatic breast cancer recruited to the phase II IRIS study who had progressed on first-line aromatase inhibitor (AI) therapy and then continued their AI in combination with Irusostat (40mg), an irreversible steroid sulfatase inhibitor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e cfDNA was isolated from 96 serial plasma samples from 24 patients, alongside primary tumour DNA (n = 16), and analysed by next-generation sequencing using a custom-designed mutation panel on the Illumina NovaSeq platform.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Thirteen of 16 tumour DNA samples harboured at least one somatic mutation across nine genes. Twenty one of 24 patients (88%) had at least one somatic mutation in cfDNA (248 total mutations across 10 genes). Circulating tumour DNA \u003cem\u003eESR1\u003c/em\u003e mutations (ct\u003cem\u003eESR1\u003c/em\u003em) were the most prevalent, present in 16 patients (76%) with both stable (SD) and progressive disease (PD), showing no clear association with disease progression. \u0026nbsp;Eleven patients had polyclonal ct\u003cem\u003eESR1\u003c/em\u003em within the ligand-binding domain, six at baseline, while five harboured a single ct\u003cem\u003eESR1\u003c/em\u003em variant. Five other patients acquired polyclonal mutations over treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Analysis of serial plasma samples revealed frequent detection of polyclonal ct\u003cem\u003eESR1\u003c/em\u003em in patients recruited to the IRIS study with both SD and PD. These findings underscore the challenge of targeting a single \u003cem\u003eESR1\u003c/em\u003e mutation and emphasise the need for careful patient selection, specifically those with wild-type \u003cem\u003eESR1\u003c/em\u003e, in trials investigating sequential estrogen-lowering therapies.\u003c/p\u003e","manuscriptTitle":"Assessing Endocrine Resistance: Monitoring Circulating ESR1 mutations in Irosustat-Treated ER positive Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 09:11:02","doi":"10.21203/rs.3.rs-7187693/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-17T12:47:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-16T17:03:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-09T19:29:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172374658461166344753893296456621507427","date":"2025-08-04T19:33:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108005183786629711520472326613134669645","date":"2025-08-03T16:41:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-03T15:38:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-23T08:17:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-23T08:16:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research and Treatment","date":"2025-07-22T13:35:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"41bacac8-7af6-45c9-a704-a5c27c642d40","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:03:49+00:00","versionOfRecord":{"articleIdentity":"rs-7187693","link":"https://doi.org/10.1007/s10549-025-07857-6","journal":{"identity":"breast-cancer-research-and-treatment","isVorOnly":false,"title":"Breast Cancer Research and Treatment"},"publishedOn":"2025-12-09 15:58:35","publishedOnDateReadable":"December 9th, 2025"},"versionCreatedAt":"2025-08-07 09:11:02","video":"","vorDoi":"10.1007/s10549-025-07857-6","vorDoiUrl":"https://doi.org/10.1007/s10549-025-07857-6","workflowStages":[]},"version":"v1","identity":"rs-7187693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7187693","identity":"rs-7187693","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}