Dynamic Monitoring and Identification of Reliable Biomarkers to Predict Efficacy of Bireociclib and Fulvestrant: An Exploratory ctDNA Analysis of the BRIGHT-2 Study

Dynamic Monitoring and Identification of Reliable Biomarkers to Predict Efficacy of Bireociclib and Fulvestrant: An Exploratory ctDNA Analysis of the BRIGHT-2 Study | 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 Article Dynamic Monitoring and Identification of Reliable Biomarkers to Predict Efficacy of Bireociclib and Fulvestrant: An Exploratory ctDNA Analysis of the BRIGHT-2 Study Binghe Xu, Yan Wang, Hangcheng Xu, Yiran Zhou, Liang Cui, Qiang Sa, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8242447/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Bireociclib, a novel cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor, has demonstrated efficacy in hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer. This exploratory analysis aimed to identify biomarkers of response and resistance to bireociclib through dynamic circulating tumor DNA (ctDNA) profiling. Methods In this exploratory analysis of the phase Ⅲ BRIGHT-2 trial, plasma samples were collected at baseline, on-treatment, and end-of-treatment from patients randomized 2:1 to receive bireociclib plus fulvestrant or placebo plus fulvestrant. ctDNA was extracted and profiled using a 1,021-gene targeted sequencing panel. Somatic single-nucleotide variants, insertions/deletions, and copy number alterations were identified, and the molecular tumor burden index (mTBI) was calculated. Associations between baseline and longitudinal ctDNA features and clinical outcomes were assessed using Kaplan–Meier estimates, Cox regression, stratified log-rank tests, and treatment–biomarker interaction analyses with false discovery rate adjustment. Results A total of 596 plasma samples were successfully sequenced across three time points. The most frequently altered genes were PIK3CA (48%), TP53 (37%), and ESR1 (23%), defining the mutational landscape of East Asian HR+/HER2 − advanced breast cancer. Baseline ctDNA negativity or low mTBI, together with on-treatment ctDNA clearance or mTBI reduction, identified patients most likely to benefit from bireociclib. Within the bireociclib-treated cohort, PIK3CA–ESR1 co-mutation was associated with significantly prolonged PFS (p = 0.003) and OS (p = 0.024), and longitudinal clearance of these mutations conferred outcomes exceeding those of persistently negative patients. Mechanisms of acquired resistance to bireociclib were heterogeneous, involving activation of the PI3K/AKT pathway, amplifications of FGFR1 , MDM2 , and MYC , as well as upregulation of MAPK signaling. Conclusions Both baseline ctDNA features and on-treatment ctDNA dynamics demonstrated clinically relevant predictive value for treatment response and survival outcomes of bireociclib. These findings provide a molecular framework for patient stratification and highlight dynamic ctDNA monitoring as a tool to guide precision use of CDK4/6 inhibitors. Health sciences/Oncology/Cancer/Breast cancer Health sciences/Oncology/Cancer/Tumour biomarkers CDK4/6 inhibitor advanced breast cancer ctDNA bireociclib prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Hormone receptor–positive, human epidermal growth factor receptor 2–negative (HR+/HER2−) breast cancer represents the most prevalent molecular subtype of advanced breast cancer (ABC). The introduction of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors in combination with endocrine therapy has fundamentally reshaped the treatment landscape, leading to substantial improvements in progression-free survival (PFS) and overall survival (OS). Mechanistically, endocrine therapy suppresses estrogen-driven cyclin D expression, whereas CDK4/6 inhibition prevents retinoblastoma (RB) protein phosphorylation, cooperatively enforcing G1 cell-cycle arrest and delaying the emergence of endocrine resistance [ 1 ]. Despite these advances, considerable interpatient heterogeneity in clinical benefit persists, and both primary and acquired resistance to CDK4/6 inhibitors remain inevitable in a substantial proportion of patients. Several resistance mechanisms have been described, including RB1 loss, activation of receptor tyrosine kinase (RTK)/RAS signaling, cyclin E overexpression, CDK2 hyperactivation, and AURKA amplification; however, most evidence is derived from preclinical models or tumor tissue obtained after progression. To date, these alterations have not been translated into robust, clinically actionable biomarkers for patient stratification or early intervention [ 2 – 4 ]. Bireociclib is a novel, orally bioavailable CDK4/6 inhibitor independently developed in China. The phase Ⅱ BRIGHT-1 study and the randomized phase Ⅲ BRIGHT-2 trial demonstrated that bireociclib, both as monotherapy and in combination with fulvestrant, confers significant clinical benefit with a favorable safety profile in patients with HR+/HER2 − ABC, including clinically challenging subgroups such as those with endocrine-resistant disease or visceral metastases [ 5 – 7 ]. However, the molecular determinants underlying sensitivity and resistance to bireociclib, particularly in comparison with endocrine therapy alone, remain poorly defined [ 2 , 8 ]. Prior exploratory analyses of BRIGHT-2 identified baseline peripheral blood inflammatory markers as prognostic but not predictive of treatment benefit [ 9 ], underscoring the unmet need for tumor-informed biomarkers that can capture both disease biology and treatment-specific effects. Circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive approach capable of capturing tumor genomic heterogeneity and enabling real-time monitoring of tumor evolution under therapeutic pressure. Longitudinal ctDNA profiling offers the unique opportunity to integrate baseline genomic context with dynamic molecular responses, thereby informing both early efficacy assessment and mechanisms of acquired resistance. Leveraging serial plasma samples collected at baseline, during treatment, and at the end of treatment from the BRIGHT-2 trial [ 6 , 7 ], we conducted a large-scale longitudinal ctDNA analysis using a 1,021-gene targeted panel to characterize the mutational landscape of East Asian patients with HR+/HER2 − advanced breast cancer, identify baseline genomic features associated with sensitivity or resistance to CDK4/6 inhibition, and determine whether on-treatment ctDNA dynamics can serve as early indicators of therapeutic benefit while revealing mechanisms of resistance. Method Trial design and patients BRIGHT-2 is a randomized, double-blind, phase Ⅲ trial of bireociclib or placebo with fulvestrant in women with HR+/HER2 − ABC. Eligible patients were randomly assigned to receive bireociclib or placebo plus fulvestrant at a 2:1 ratio. The primary endpoint was investigator-assessed PFS defined by RECIST version 1.1. The overall trial design, eligibility criteria, and statistical methods of survival outcomes and adverse events have been described previously [ 6 , 7 ]. Dynamic monitoring of ctDNA and its exploratory evaluation as biomarkers were prospectively included in the study protocol. As of February 22, 2024, a pre-specified number of PFS events for the final analysis was reached. This analysis utilized efficacy and survival data up to this cutoff date. The BRIGHT-2 study was approved by the ethical and local institutional review boards for the sites participating in the clinical trial, and was conducted according to the Declaration of Helsinki. All patients provided written informed consent prior to enrollment. Plasma collection and 1,021 ctDNA panel assessment According to the study protocol, 10 milliliters peripheral blood samples were collected from all the patients for ctDNA analysis at three timepoints: baseline (day 1 of cycle 1, C1D1), on-treatment (day 1 of cycle 5, C5D1) and EOT. Cell-free DNA (cfDNA) was extracted from plasma samples with the Enhanced Magnetic Circulating DNA Kit (Thermo Fisher Scientific, USA), while germline genomic DNA (gDNA) was isolated from peripheral blood lymphocytes of the first centrifugation using the CWE9600 Blood DNA Kit (CWBIO, Beijing, China). DNA concentration was quantified on a Qubit fluorometer with the AccuGreen HS dsDNA Quantitation Kit (Biotium, USA). After shearing 1.0 µg of gDNA to 200–250 bp fragments (Covaris S2), sequencing libraries were constructed from both 10–80 ng cfDNA and sheared gDNA using the Hieff NGS Ultima DNA Library Prep Kit for MGI (Yeasen, Shanghai, China), respectively. A custom-designed panel covering ~ 1.6 Mbp genome and targeting 1,021 cancer-related genes was used for hybridization enrichment with DNA libraries, and then sequenced using DNBSEQ-T7RS sequencing instrument (MGI Tech, Shenzhen, China) with 2 × 100bp paired-end reads. Selected regions and genes of the targeted panel were listed in Supplementary Table 1 . Every specific gene was classified as "altered" if more than one alteration was detected (defined as the presence of a copy number variation, short insertion/deletion, or mutation); otherwise, it was classified as “wild-type (WT)”. Identification of gene alterations and mTBI analysis After removing adapters and low-quality reads, the clean reads were mapped to the human reference genome (hg19) using BWA18 (version 0.7.12-r1039). The Picard software MarkDuplicates (v4.0.4.0; Broad Institute, Cambridge, MA, USA) was used for realignment and recalibration. Somatic single nucleotide variants (SNVs) and small insertions and deletions were determined by MuTect2 and realDcaller (Geneplus-Beijing, inhouse). CNVKit was employed to detect copy number alterations (CNVs). Somatic alterations were filtered with matched patient’s whole blood controls to remove germline mutations [ 10 ]. For each ctDNA sample, the molecular tumor burden index (mTBI) was determined using the mean variant allele frequency (VAF) of the clonal mutations [ 11 ]. The change in mTBI (ΔmTBI) was calculated as the difference in mTBI between the on-treatment and the paired baseline ctDNA sample. Statistical analysis All the analyses were performed using R software (version 4.3.3) with two-sided 95% confidence intervals (CIs). Continuous data were summarized descriptively, with categorical data as frequencies. PFS was estimated by Kaplan-Meier and compared using stratified log-rank tests. The objective response rate (ORR), disease control rate (DCR), and clinical benefit rate (CBR) were assessed with the Cochran-Mantel-Haenszel test. Fisher’s exact test was performed to compare differences in categorical variables between groups. Continuous variables were compared between two groups using the Wilcoxon rank-sum test. P values were estimated using the log-rank test. Hazard ratios (HRs) and 95% CIs were derived from unstratified Cox proportional hazards models. The interaction analyses between treatment and gene mutation were conducted using “TableSubgroupMultiCox” function from “jstable” package, with the resulting interaction p values adjusted for multiple testing via False Discovery Rate (FDR) method. The “surv_cutpoint” function from “survminer” package was used to determine the optimal cut-off values of mTBI based on PFS data. Functional enrichment analysis for reactome pathways was conducted with the “clusterProfiler” R package. Results Baseline ctDNA Landscape and Sample Collection in HR+/HER2− Advanced Breast Cancer Between December 8, 2021 and October 24, 2022, 305 patients with HR+/HER2− ABC were enrolled across 64 hospitals in China and randomly assigned to receive bireociclib plus fulvestrant (n = 204) or placebo plus fulvestrant (n = 101). During the treatment process, plasma samples were collected for ctDNA examination at baseline, on-treatment and EOT. In the bireociclib arm, plasma at C1D1, C5D1 and EOT was collected from 197, 139, and 86 patients, respectively; whereas in the placebo arm, plasma was available from 79, 46, and 49 patients at these corresponding time points. The ctDNA sample collection process is illustrated in Supplementary Figure 1 . In the intention-to-treat (ITT) population, median PFS was 14.7 months in the bireociclib plus fulvestrant arm versus 7.3 months in the placebo arm (HR = 0.55, 95% CI 0.41–0.75, P < 0.001). Among patients with evaluable ctDNA, median PFS was 14.7 months and 6.0 months in the bireociclib and placebo groups, respectively (HR = 0.48, 95% CI 0.35–0.66, P < 0.001). Baseline clinicopathologic characteristics were well balanced across treatment arms in both the ITT and ctDNA-evaluable populations ( Supplementary Table 2 ). Figure 1 displays genes with an alteration frequency > 5% at baseline across all patients with evaluable ctDNA (n = 219), along with their associations with ORR and clinicopathological characteristics. PIK3CA , TP53 , and ESR1 were the three most frequently altered genes, with frequencies of 48%, 37%, and 23%, respectively. Several alterations appeared to be associated with specific clinical features ( Supplementary Figure 2 ). Notably, BRCA1 alterations are more common in postmenopausal patients. ESR1 alterations are frequently detected in postmenopausal patients and in those with liver metastases, secondary endocrine resistance, and more than three metastatic sites. TP53 alterations were enriched in patients with Ki67 ≥15% or liver metastases, while PTEN mutations were more frequent in those with Ki67 <15%. Collectively, poorer ECOG performance status, postmenopausal status, higher tumor burden, and a greater number of prior endocrine therapies were correlated with a higher prevalence of detectable genomic alterations. Baseline ctDNA, mTBI, and Pathway-Level Genomic Alterations Stratify Therapeutic Outcomes For baseline ctDNA status, 152 and 67 patients were positive in bireociclib and placebo arms, respectively. In both treatment arms, ctDNA-positive patients had shorter PFS and OS than ctDNA-negative patients ( Figure 2A and 2B ). In the bireociclib arm, median PFS was 11.2 months in ctDNA-positive patients, whereas median PFS was not reached (NR) in ctDNA-negative patients (HR = 2.28, 95% CI 1.31–3.94, p = 0.003). A similar pattern was observed in the placebo arm, where median PFS was 5.6 months for ctDNA-positive patients and 17.5 months for ctDNA-negative patients (HR = 2.64, 95% CI 1.13–6.16, p = 0.02). Although OS data remain immature, consistent differences favoring ctDNA-negative patients were also observed in both the bireociclib and placebo arms (p < 0.001 and p = 0.021, respectively). The association between specific gene alterations and survival in the bireociclib and placebo arms are displayed in Supplementary Figure 3 . Across both treatment arms, alterations in TP53 , MYC , and PTPRD were associated with shorter PFS, whereas alterations in FGF19 , FGF4 , CCND1 , FGF3 , and TP53 were linked to poorer OS. Interaction analyses assessing the modifying effect of treatment on PFS indicated that only CCND1 and FGF19 alterations retained evidence of treatment interaction after correction for multiple testing (FDR-adjusted p = 0.03 and 0.002, respectively; Figure 2C ), suggesting that patients harboring these alterations derived greater PFS benefit from bireociclib compared with placebo. Associations between baseline genetic mutations and treatment responses are shown in Figure 2D and 2E . In both the bireociclib and placebo arms, mTOR mutations were detected exclusively in responders, while PIK3CA and TP53 mutations were more frequent in non-responders than responders. Additionally, mutations in AKT1 , CDH1 , and LRP1B were statistically associated with worse response in the bireociclib arm, whereas no such association was observed in the placebo arm due to its low response. The mTBI is a core quantitative metric used to assessing ctDNA fraction. Patients with high mTBI level had worse PFS (p < 0.001, Figure 3A ) and OS (p = 0.014, Figure 3B ) than their counterparts in each treatment arm. Regarding treatment response, responders had conspicuously lower mTBI levels than non-responders in the bireociclib arm (p = 0.0369, Supplementary Figure 4 ), whereas no significant correlation between mTBI and response was observed in the placebo arm. Subsequently, univariate Cox regression analyses of baseline characteristics and mTBI were performed separately in each arm ( Supplementary Table 3 and 4 ). The features with univariate p＜0.1 in either arm were included in multivariate analyses alongside mTBI. Multivariate analysis demonstrated that mTBI was an independent prognostic factor for PFS in both arms (p = 0.002 and < 0.001, respectively; Figure 3C and Supplementary Figure 5 ). Exploratory pathway-level analyses revealed that alterations in the PI3K signaling pathway were associated with shorter PFS (HR = 1.73, 95% CI 1.08–2.75, p = 0.02) and OS (HR = 2.43, 95% CI 1.21–4.89, p = 0.01), exclusively in the bireociclib arm ( Supplementary Figure 6 ). Alterations in the MYC pathway correlated with poorer PFS and OS in both treatment arms ( Supplementary Figure 7 ). Within the bireociclib cohort, patients harboring homologous recombination repair (HRR) pathway alterations, including germline BRCA mutations ( gBRCAm ), experienced shorter PFS (HR = 2.21, 95% CI 1.49–3.29, p < 0.001) and OS (HR = 2.40, 95% CI 1.35–4.25, p = 0.002) compared with those without HRR alterations, whereas no significant associations were observed in the placebo arm ( Supplementary Figure 8 ). Separate analyses of patients with gBRCAm or non- BRCA HRR mutations indicated that only patients with gBRCAm in the bireociclib arm exhibited distinctly poorer outcomes compared with gBRCAm –wild-type patients. No clear differences were observed in the remaining comparisons ( Supplementary Figure 9 ). PIK3CA – ESR1 and TP53 – ESR1 Co-mutations Define Distinct Predictive and Prognostic Subgroups Co-mutation analyses between the three most frequently altered genes were performed, including PIK3CA and ESR1 , as well as TP53 and ESR1 . For PIK3CA – ESR1 co-mutation analysis, patients were stratified into four molecular subgroups as PIK3CA⁺/ESR1⁺ , PIK3CA⁻ /ESR1⁻ , PIK3CA⁻/ESR1⁺ , and PIK3CA⁺/ESR1⁻ . In the bireociclib arm, median PFS across these subgroups were NR, 14.5 months, 8.3 months, and 8.8 months, respectively; while median OS were NR, NR, 20.8 months, and 19.2 months. Patients harboring concurrent PIK3CA and ESR1 mutations experienced significantly longer PFS than those with other genotypic profiles (p = 0.003, Figure 4A ). Although OS data are not yet mature, a consistent trend toward improved OS was observed in the PIK3CA – ESR1 co-mutant subgroup (p = 0.024, Figure 4B ). Notably, this survival advantage was not observed in the placebo arm ( Figure 4C and 4D ). A formal interaction test between treatment assignment and the four PIK3CA – ESR1 genotypic subgroups, adjusted for relevant clinicopathologic covariates, demonstrated that patients with PIK3CA⁺/ESR1⁺ tumors derived the greatest benefit from bireociclib (HR = 0.02, 95% CI 0.00–0.34; P = 0.007; Supplementary Figure 10 ), followed by those with PIK3CA⁺/ESR1⁻ disease (HR = 0.56, 95% CI 0.32–0.99; P = 0.047). In contrast, no meaningful differences between bireociclib and placebo were observed in either of the PIK3CA⁻ subgroups, yielding an overall interaction that did not reach statistical significance across the four genotypic categories (p for interaction = 0.201). Within the two PIK3CA⁺ subgroups, a significant interaction was observed between ESR1 mutation status and treatment effect (p for interaction = 0.03, Supplementary Figure 11 ), suggesting that ESR1 mutation status may serve as a positive predictive biomarker for bireociclib efficacy in this molecular context. An analogous four-group stratification was applied for the TP53–ESR1 co-mutation analysis ( TP53⁺/ESR1⁺ , TP53⁻/ESR1⁻ , TP53⁻/ESR1⁺ , and TP53⁺/ESR1⁻ ). In the bireociclib arm, patients with TP53⁻/ESR1⁺ tumors exhibited the most favorable PFS, which was NR, followed by those with TP53⁻/ESR1⁻ and TP53⁺/ESR1⁺ disease (median PFS 17.4 and 13.3 months, respectively), whereas the TP53⁺/ESR1⁻ subgroup demonstrated the poorest PFS of 7.3 months, with significant differences observed across the four groups (p < 0.001, Figure 4E ). OS comparisons showed differences across the four subgroups that were directionally consistent with the PFS findings (p = 0.006, Figure 4F ). Given the immaturity of OS data, median OS was reached only in the TP53⁺/ESR1⁺ and TP53⁺/ESR1⁻ subgroups (23.6 and 19.1 months, respectively). In the placebo arm, both PFS and OS also differed significantly among the four TP53 – ESR1 subgroups (p < 0.001 and p = 0.036, respectively; Figure 4G and 4H ), with more favorable outcomes consistently observed in TP53 -wildtype tumors. These findings suggest that TP53 status functions primarily as a prognostic factor for patients with HR+/HER2− ABC. On-treatment ctDNA dynamics predict efficacy with bireociclib plus fulvestrant We analyzed the dynamic changes of ctDNA from C1D1 to C5D1 and categorized patients into three subgroups, including C1D1 - /C5D1 - , C1D1⁺/C5D1 - , and C1D1 ± /C5D1 + . In the bireociclib arm, patients with persistent or converted to positive (C1D1 ± /C5D1 + ) ctDNA status were demonstrated with significantly inferior PFS and OS compared to those with C1D1⁻/C5D1⁻ or C1D1⁺/C5D1⁻ (overall p = 0.003 and ＜0.001, respectively; Figure 5A and 5B ). In the placebo arm, only a trend towards prolonged PFS was observed for C1D1⁻/C5D1⁻ subgroup compared to the other two groups (overall p = 0.048, Supplementary Figure 12A ), and OS did not differ significantly (overall p = 0.581, Supplementary Figure 12B ). The C1D1 + /C5D1 - subgroup showed the greatest PFS benefit from bireociclib treatment compared to placebo (HR = 0.268, p=0.008, Supplementary Figure 13 ). Efficacy comparisons revealed that the responders had a notably higher proportion of patients with ctDNA clearance status (C1D1⁺/C5D1⁻) than non-responders in the bireociclib arm (p = 0.011, Figure 5C ), whereas the distribution of ctDNA dynamic status did not differ between responders and non-responders in the placebo arm (p = 0.464, Figure 5D ). Dynamic changes in mTBI were further evaluated by stratifying patients into increase (Δ≥0) or decrease (Δ<0) over time. In the bireociclib arm, patients with increasing mTBI had a markedly shorter median PFS than those with declining mTBI (5.6 months vs. 14.6 months; HR = 2.93, 95% CI 1.50–5.73, p = 0.001; Figure 5E ). A similar pattern was observed for OS, with a median OS of 19.6 months in the mTBI Δ≥0 subgroup and NR in the Δ<0 subgroup (HR = 2.49, 95% CI 0.99–6.24, p = 0.044; Figure 5H ). In the placebo arm, increasing mTBI was also associated with shorter PFS (p = 0.025); however, no difference in OS was observed between mTBI subgroups (p = 0.552; Supplementary Figure 14 ). Dynamic profiling of frequently mutated genes demonstrated that in the bireociclib arm, patients with baseline PIK3CA or ESR1 mutations who achieved ctDNA clearance at C5D1 had markedly prolonged PFS and OS. Among patients stratified by dynamic PIK3CA status, median PFS was NR in the C1D1 ⁺ /C5D1 ⁻ subgroup, compared with 11.1 months in the C1D1 ⁻ /C5D1 ⁻ subgroup and 9.1 months in the C1D1 ⁺ /C5D1 ⁺ subgroup (overall p = 0.025, Figure 5F ). Similarly, when stratified by dynamic ESR1 status, median PFS was NR for C1D1 ⁺ /C5D1 ⁻ patients, 11.1 months for C1D1 ⁻ /C5D1 ⁻ patients, and 8.2 months for C1D1 ⁺ /C5D1 ⁺ patients (overall p = 0.003, Figure 5I ). Although OS data remain immature, median OS was NR in both the PIK3CA or ESR1 C1D1 ⁺ /C5D1 ⁻ and C1D1 ⁻ /C5D1 ⁻ subgroups; comparisons across the three dynamic subgroups demonstrated a significant difference, with the most pronounced survival benefit observed in patients achieving ctDNA clearance ( Figure 5G and 5J ). In contrast, neither PFS nor OS differed across dynamic PIK3CA or ESR1 mutation subgroups in the placebo arm. ( Supplementary Figure 15 ). End of treatment mutation landscape and the resistant mechanisms In comparative analyses of across three time points, no genes exhibited statistically significant dynamic changes in the bireociclib arm. In contrast, 15 genes in the placebo arm demonstrated fluctuations in mutation frequency from C1D1 to C5D1 and EOT, enriched in NOTCH signaling pathway and cell adhesion/junction pathways, among others. ( Supplementary Figure 16 ). We systematically analyzed the mutational landscape across longitudinal timepoints (C1D1, C5D1, and EOT) in each patient. As shown in Supplementary Figure 17 , 81.8% of patients exhibited mutations shared across all three timepoints in bireociclib group, among which PIK3CA|p.E545K , AKT1|p.E17K ，and PIK3CA|p.H1047R were the most frequent, indicating their potential role as early clonal driver events. In addition, ESR1|p.E380Q and MDM4|Amp were the most common private mutations detected exclusively at C1D1 and were subsequently cleared during treatment, suggesting that the subclones harboring these alterations were sensitive to therapy. Conversely, FGFR1|Amp , MDM2|Amp , MYC|Amp , PIK3CA|Amp , and PIK3CA|p.E545K emerged as the most frequent EOT-specific private mutations, suggesting that they are potential mechanisms driving resistance to bireociclib. In the placebo group, the most frequent EOT-specific private mutations were ESR1|p.D538G , ESR1|p.Y537S , MDM2|Amp , CCND1|Amp , ESR1|p.L536P , FGF3/4/19|Amp , FGFR1|Amp , and IFNG|Amp ( Supplementary Figure 18 ). To identify the acquired mutations during treatment and the underlying disease progression mechanism, we selected genes mutated exclusively at EOT but not at baseline and performed reactome pathway enrichment analysis. A total of 511 and 357 genes with EOT-specific mutations were revealed in the bireociclib and placebo arm, respectively ( Figure 6 ). Notably, the bireociclib group unique enrich pathways were highly enriched in the MAPK family signaling pathways, indicating the resistance to bireociclib is likely driven by activation of the MAPK/RAF/RAS signaling axis. Discussion Currently, CDK4/6 inhibitors are widely established in combination with endocrine therapy for HR+/HER2− ABC. However, identifying patients who are most likely to benefit and monitoring dynamic biomarkers of response remain key clinical challenges [12]. In this study, we observed that patients with baseline ctDNA negativity or low mTBI levels experienced significantly improved outcomes. Mechanistic investigations revealed heterogeneous resistance patterns in the bireociclib group, including amplifications in FGFR1 , MDM2 , and MYC , as well as activation of the MAPK/RAF/RAS signaling axis. In contrast, resistance in the placebo arm was largely driven by ESR1 mutations, consistent with canonical endocrine resistance. Beyond single-gene and canonical pathway alterations, our data highlight the clinical relevance of co-mutational contexts. Notably, patients harboring concurrent PIK3CA and ESR1 mutations at baseline derived the greatest PFS benefit from bireociclib, and longitudinal clearance of either mutation was associated with particularly favorable outcomes, even exceeding those observed in patients with persistently negative ctDNA. In contrast, co-mutation analyses involving TP53 and ESR1 revealed a distinct pattern: TP53 status primarily stratified prognosis irrespective of treatment assignment, with consistently inferior outcomes observed in TP53 -mutant tumors. These findings suggest that, unlike PIK3CA – ESR1 co-mutation, which defines a treatment-sensitive molecular context, TP53 – ESR1 co-mutation reflects underlying disease aggressiveness rather than differential sensitivity to CDK4/6 inhibition. PIK3CA and ESR1 co-mutation detected in 13.2% of patients in the bireociclib arm and 10.4% in the placebo arm, consistent with prior reports ranging from 10% to 15% [13, 14]. The impact of PIK3CA and ESR1 co-mutations on survival outcomes in HR+/HER2− ABC has remained controversial. While multiple studies have demonstrated that the adverse prognostic effect associated with ESR1 mutations can be mitigated by SERD-based therapy [15-17], PIK3CA mutations have more consistently been linked to inferior clinical outcomes [18, 19], and direct comparisons of co-mutant tumors versus other genotypic subsets have been limited. A similar pattern was reported in the EMBER-3 trial of the oral SERD imlunestrant, in which exploratory analyses showed that patients with concurrent PI3K pathway and ESR1 alterations derived the greatest PFS benefit from imlunestrant plus abemaciclib compared with imlunestrant monotherapy, exceeding that observed in tumors harboring either alteration alone [20]. Absolute median PFS was likewise longest in the co-mutant subgroup (12.9 months versus 7.5–11.1months), supporting the concept that dual pathway alterations define a molecular context of enhanced sensitivity to CDK4/6 inhibitor–based therapy. In line with these findings, the ReDiscover study, which enrolled patients with PIK3CA -mutant HR⁺/HER2⁻ metastatic breast cancer, reported a higher ORR in patients with concurrent PIK3CA and ESR1 mutations compared with those harboring PIK3CA mutations alone (60% vs. 28.57%) [21]. In contrast, translational analyses from two additional studies did not observe differences in PFS between PIK3CA/ESR1 co-mutant and PIK3CA -mutant/ ESR1 –wild-type tumors treated with PI3K inhibitors and endocrine therapy, highlighting the context-dependent nature of these associations [13, 22]. Mechanistically, ESR1 mutations result in constitutive activation of the ER signaling pathway [23], while PIK3CA mutations enhance PI3K pathway signaling, promoting cell survival and proliferation. Although isolated PI3K mutations can drive ER-independent signaling, the presence of co-mutations maintains ER as a dominant oncogenic driver. Within this framework, the combination of fulvestrant, an ER degrader targeting upstream signaling, and a CDK4/6 inhibitor, which blocks the downstream Cyclin D–CDK4/6–Rb axis, achieves a comprehensive blockade of this critical proliferative “highway,” providing a mechanistic rationale for the pronounced clinical benefit observed in co-mutant patients. Clinical evidence from the INAVO‑120 study has demonstrated that first-line treatment with a CDK4/6 inhibitor combined with fulvestrant and a PI3K inhibitor can significantly improve outcomes in patients with PIK3CA -mutant HR+/HER2− ABC [24]. In this context, the pronounced efficacy of bireociclib plus fulvestrant in the PIK3CA and ESR1 co-mutant subgroup, which accounts for approximately 27% of patients with PIK3CA mutations, suggests its potential as an alternative therapeutic option for patients who are unable to tolerate toxicities associated with PI3K inhibitors. The previous studies have demonstrated the status of ctDNA, along with mTBI or ctDNA-related indicators, provide critical insights for clinical practice [18, 25-28]. In our study, patients exhibiting pretreatment positive ctDNA or high level of mTBI represent a high-risk of poorer clinical outcomes despite the addition of a CDK4/6 inhibitor. These patients may be candidates for future clinical trials exploring intensified novel agents. Conversely, in patients with undetectable baseline ctDNA, fulvestrant monotherapy showed non-inferior PFS compared to bireociclib plus fulvestrant, suggesting the potential for treatment de-escalation to endocrine monotherapy. Based on the results from the BRIGHT-1 study, bireociclib monotherapy is an effective therapeutic option subsequent progression [5]. The translational analysis of phase Ⅲ SONIA trial, which compared first-line versus second-line CDK4/6 inhibitor in addition to endocrine therapy, revealed that in the high ctDNA subgroup, first-line CDK4/6 inhibitor use remarkably prolonged both first and second PFS (PFS1 and PFS2) [29]. However, in the low ctDNA subgroup, no significant differences in PFS1 or PFS2 were observed [30]. Based on these data, it is necessary to reconsider the necessity of applying CDK4/6 inhibitors as early as possible for every patient. In summary, pretreatment ctDNA levels may help to identify patients who were most likely to benefit from either escalate or de-escalate strategies. Furthermore, dynamic monitoring of ctDNA and related biomarkers also provides guidance for adapting treatment strategies. In terms of study design, the on-treatment sampling time point (C5D1) was set later than other studies [31, 32], which was considered from the perspective of relatively long PFS and OS in HR-positive breast cancer, as well as the wide window of response time. In bireociclib group, the median time to response was 3.7 months, which aligns closely with the C5D1 time point. Selecting C5D1 allowed for the assessment of complete ctDNA clearance rather than merely a reduction. Dynamic analysis further revealed that clearance of overall ctDNA or individual genes could significantly predict survival outcomes. This liquid biopsy-based approach is technically simpler than traditional tissue biopsy and may offer earlier predictive method for survival compared to conventional imaging-based assessment of tumor response. However, this study had several limitations. Firstly, the limited sample size and low mutation frequency precluded reliable evaluation of the predictive or prognostic value of rare mutations, resulting in wide 95% confidence intervals. This limitation was particularly relevant for analyses of the relationship between co-mutation status and survival outcomes. In the placebo arm, the numbers of patients with PIK3CA⁺/ESR1⁺ or TP53⁺/ESR1⁺ tumors were small, necessitating cautious interpretation of these results. Furthermore, our work represents a translational sequencing analysis of clinical samples and did not include in vitro studies to explore the underlying molecular mechanisms. Finally, DNA sequencing was performed only on peripheral blood samples without paired tumor tissue for dual validation. Despite these limitations, this study constitutes the first translational ctDNA analysis of the novel CDK4/6 inhibitor bireociclib and remains among the most comprehensive translational sequencing efforts to date, leveraging the largest gene panel and multi‑timepoint sampling strategy in the field. Compared with the methods used in PALOMA-3 [33] (Guardant360 panel of approximately 70 genes), MONARCH-2 [34] (ddPCR assessing approximately two genes), and MONALEESA-3 [8] (SureSelect XT custom probes covering approximately 558 genes), the 1,021-gene panel offers substantially broader genomic coverage. Future studies are planned to both validate the impact of PIK3CA and ESR1 co-mutations in vitro and in animal models, and to elucidate the molecular mechanisms driving these effects. Notably, baseline characteristics were homogeneous [6], enabling the characterization of ctDNA profiles in East Asian patients with HR-positive ABC. Declarations Authors' contributions Yan Wang, Hangcheng Xu, and Yiran Zhou: Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, and Writing - original draft. Liang Cui: Data curation, Software, Formal analysis, Investigation, Visualization, and Methodology. Qiang Sa, Hong Cheng, and Renchi Gao: Data Curation, Formal Analysis, and Writing - Original Draft. Qingyuan Zhang, Huiping Li, Zhongsheng Tong and Quchang Ouyang: Conceptualization, Resources, Data Curation, Investigation, Methodology and Project administration. Xinxin Tan and Jing Bai: Data curation, Software, Formal analysis, Investigation, and Methodology. Li Wang, Xianghui Duan and Fan Yang: Conceptualization, Data Curation, Software, Funding acquisition, Validation, Methodology, and Project administration. Jiayu Wang and Binghe Xu: Conceptualization, Resources, Funding acquisition, Validation, Methodology, Project administration, and Writing-review and editing. Conflict of interest statement The authors declare no conflict of interest. Acknowledgements We are grateful to all the patients, principal investigators and every healthcare personnel who participated in the BRIGHT-2 study for their contributions to medical development. Availability of data and materials The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2025) at the National Genomics Data Center (Nucleic Acids Res 2025), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA-Human: HRA014553) that are controlled access at https://ngdc.cncb.ac.cn/gsa-human. Funding This work was supported by the National High Level Hospital Clinical Research Funding (2025-LYZX-D-A02); Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS, 2021-I2M-1-014; 2023-12M-2-004); the National Major Scientific and Technological Special Project for “Significant New Drugs Development” (No. 2018ZX09711002-011-027) and Noncommunicable Chronic Diseases-National Science and Technology Major Project (2025ZD0552500); Xuanzhu Biopharmaceutical Co., Ltd. References Goel S, Bergholz JS, Zhao JJ (2022) Targeting CDK4 and CDK6 in cancer. Nat Rev Cancer 22(6):356–372 Asghar US, Kanani R, Roylance R, Mittnacht S (2022) Systematic Review of Molecular Biomarkers Predictive of Resistance to CDK4/6 Inhibition in Metastatic Breast Cancer. JCO precision Oncol 6:e2100002 Main SC, Cescon DW, Bratman SV (2022) Liquid biopsies to predict CDK4/6 inhibitor efficacy and resistance in breast cancer. Cancer drug Resist (Alhambra Calif) 5(3):727–748 Asciolla JJ, Wu X, Adamopoulos C, Gavathiotis E, Poulikakos PI (2025) Resistance mechanisms and therapeutic strategies of CDK4 and CDK6 kinase targeting in cancer. Nat cancer 6(1):24–40 Wang J, Zhang Q, Sun T, Li H, Cheng Y, Tong Z, Li H, Li W, Wang J, Teng Y et al (2025) An open-label, single-arm, multicenter, phase II trial of bireociclib as monotherapy for heavily pretreated HR-positive, HER2-negative advanced breast cancer patients: BRIGHT-1 trial. Cancer Commun (London England) 45(6):640–653 Wang J, Zhang Q, Li H, Tong Z, Ouyang Q, Li H, Teng Y, Wang B, Sun T, Wang J et al (2025) Bireociclib plus fulvestrant for HR+/HER2- advanced female breast cancer progressed on or after endocrine therapy: phase 3 BRIGHT-2 study interim analysis. Nat Commun 16(1):3350 Wang J, Zhang Q, Li H, Tong Z, Ouyang Q, Li H, Teng Y, Wang B, Sun T, Wang J et al (2025) Abstract CT099: BRIGHT-2 final analysis: A phase III trial of bireociclib plus fulvestrant as second-line endocrine therapy for patients with advanced HR+/HER2-breast cancer. Cancer Res 85(8Supplement2):CT099–CT099 André F, Su F, Solovieff N, Hortobagyi G, Chia S, Neven P, Bardia A, Tripathy D, Lu YS, Lteif A et al (2023) Pooled ctDNA analysis of MONALEESA phase III advanced breast cancer trials. Annals oncology: official J Eur Soc Med Oncol 34(11):1003–1014 Xu H, Wang Y, Sa Q, Zhou Y, Ma F, Zhang P, Fan Y, Cai R, Li Q, Lan B et al (2025) Associations Between Dynamic Hematological Indicators and Outcomes in HR-positive, HER2-negative Metastatic Breast Cancer Treated with Bireociclib or Placebo Plus Fulvestrant: Findings from the BRIGHT-2 Trial. Breast :104598 Ai X, Cui J, Zhang J, Chen R, Lin W, Xie C, Liu A, Zhang J, Yang W, Hu X et al (2021) Clonal Architecture of EGFR Mutation Predicts the Efficacy of EGFR-Tyrosine Kinase Inhibitors in Advanced NSCLC: A Prospective Multicenter Study (NCT03059641). Clin cancer research: official J Am Association Cancer Res 27(3):704–712 Wang Y, Zhao C, Chang L, Jia R, Liu R, Zhang Y, Gao X, Li J, Chen R, Xia X et al (2019) Circulating tumor DNA analyses predict progressive disease and indicate trastuzumab-resistant mechanism in advanced gastric cancer. EBioMedicine 43:261–269 da Silva JL, Oliveira LJC, de Resende CAA, Reinert T, de Albuquerque LZ, Leite da Silva LF, Mano MS (2025) Understanding and overcoming CDK4/6 inhibitor resistance in HR+/HER2- metastatic breast cancer: clinical and molecular perspectives. Therapeutic Adv Med Oncol 17:17588359251353623 Dempsey N, Chamorro Y, Tolman D, Sandoval-Leon AC, Drusbosky L, Lewis C, Ahluwalia MS, Mahtani RL (2023) Incidence and outcomes among patients with HR+/HER2- metastatic breast cancer (mBC) with co-occurring ESR1 and PIK3CA mutations detected by ctDNA and treated with alpelisib: A retrospective review. 41(16suppl):e13068–e13068 Szostakowska-Rodzos M, Grzybowska EA, Mysliwy I, Zub R, Jagiello-Gruszfeld A, Rubach M, Konieczna A, Fabisiewicz A (2025) The Combined Assessment of CTC and ESR1 Status in Liquid Biopsy Samples Enhances the Clinical Value of Prediction in Metastatic Breast Cancer. Int J Mol Sci 26(5) Bardia A, Cortés J, Bidard FC, Neven P, Garcia-Sáenz J, Aftimos P, O'Shaughnessy J, Lu J, Tonini G, Scartoni S et al (2024) Elacestrant in ER+, HER2- Metastatic Breast Cancer with ESR1-Mutated Tumors: Subgroup Analyses from the Phase III EMERALD Trial by Prior Duration of Endocrine Therapy plus CDK4/6 Inhibitor and in Clinical Subgroups. Clin cancer research: official J Am Association Cancer Res 30(19):4299–4309 Wong NZH, Yap DWT, Ong RJM, Zhao JJ, Chan YH, Tey JCS, Sundar R, Lim JSJ, Dawood SS (2023) Efficacy of Oral SERDs in the treatment of ER+, HER2 - metastatic breast cancer, a stratified analysis of the ESR1 wild type and mutant subgroups. Annals oncology: official J Eur Soc Med Oncol Turner NC, Swift C, Kilburn L, Fribbens C, Beaney M, Garcia-Murillas I, Budzar AU, Robertson JFR, Gradishar W, Piccart M et al (2020) ESR1 Mutations and Overall Survival on Fulvestrant versus Exemestane in Advanced Hormone Receptor-Positive Breast Cancer: A Combined Analysis of the Phase III SoFEA and EFECT Trials. Clin cancer research: official J Am Association Cancer Res 26(19):5172–5177 Chiu J, Su F, Joshi M, Masuda N, Ishikawa T, Aruga T, Zarate JP, Babbar N, Balbin OA, Yap YS (2023) Potential value of ctDNA monitoring in metastatic HR + /HER2 - breast cancer: longitudinal ctDNA analysis in the phase Ib MONALEESASIA trial. BMC Med 21(1):306 Dieci MV, Vernaci G, Colangelo C, Bria E, Massa D, Di Liso E, Giorgi CA, Giarratano T, Napetti D, Bonomi G et al PIK3CA mutations and first-line outcomes in endocrine-resistant HR+/HER2- metastatic breast cancer: A multicentric real-world study. European journal of cancer (Oxford, England : (1990)) 2025, 234:116194) 2025, 234:116194 Manich CS, Carey LA, Curigliano G, Harbeck; N, O'Shaughnessy; J, Bidard FC, Casalnuovo ML, Kim S-B, Tokunaga; E, Masuda; N et al (2025) 297O - Imlunestrant (Imlu) with or without abemaciclib (Abema) in advanced breast cancer (ABC): A subgroup analysis in CDK4/6 inhibitor (CDK4/6i)-pretreated patients (pts) from EMBER-3. ESMO Breast Cancer Annual Congress 2970 Sammons SL, Manich CS, Italiano A, Schram AM, Ortega PT, Schott AF, Guerrero A, Aix SP, Nanda R, Wisinski KBet al: Updated efficacy of mutant-selective PI3Kα inhibitor RLY-2608 in combination with fulvestrant in patients with PIK3CA-mutant HR+HER2- advanced breast cancer:ReDiscover trial. 2025, 43(16_suppl):1086–1086 Chen JW, Jacot W, Cortés J, Krop IE, Dent S, Harbeck N, De Laurentiis M, Diéras V, Im YH, Stout TJ et al (2023) ER+, HER2- advanced breast cancer treated with taselisib and fulvestrant: genomic landscape and associated clinical outcomes. Mol Oncol 17(10):2000–2016 Will M, Liang J, Metcalfe C, Chandarlapaty S (2023) Therapeutic resistance to anti-oestrogen therapy in breast cancer. Nat Rev Cancer 23(10):673–685 Wedam S, Narayan P, Gittleman H, Cheng J, Bhatnagar V, Sabit H, Price LSL, Rahman NA, Chiu HJ, Biel N et al (2025) US Food and Drug Administration Approval Summary: Inavolisib With Palbociclib and Fulvestrant for Endocrine-Resistant, PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative, Locally Advanced or Metastatic Breast Cancer. J Clin oncology: official J Am Soc Clin Oncol 43(28):3123–3131 Zhou Y, Zhang Z, Chen H, Huang F, Shen L, Tao S, Qian W, Hong H, Pan C, Wang Z et al (2025) Efficacy, Safety, and Biomarkers of Neoadjuvant Dalpiciclib (CDK4/6 inhibitor) plus Aromatase Inhibitors in Operable HER2-Negative Luminal B Breast Cancer: A Prospective, Single-Center, Single-Arm, Phase II Trial (DANCER). MedComm 6(10):e70402 Fuentes-Antrás J, Elliott MJ, Main SC, Echelard P, Dou A, Bedard PL, Amir E, Nadler MB, Meti N, Gregorio N et al (2025) Personalized ctDNA monitoring in metastatic HR+/HER2- breast cancer patients during endocrine and CDK4/6 inhibitor therapy. NPJ breast cancer 11(1):74 Mamann A, Pradat Y, Bidard FC, Delaloge S, Cabel L, Faull I, Marques S, Bachelot T, Dalenc F, de la Motte Rouge T et al (2025) Prognostic significance of early on-treatment evolution of circulating tumor DNA in advanced ER-positive/HER2-negative breast cancer. Annals oncology: official J Eur Soc Med Oncol 36(11):1342–1355 Darrigues L, Pierga JY, Bernard-Tessier A, Bièche I, Silveira AB, Michel M, Loirat D, Cottu P, Cabel L, Dubot C et al (2021) Circulating tumor DNA as a dynamic biomarker of response to palbociclib and fulvestrant in metastatic breast cancer patients. Breast cancer research: BCR 23(1):31 Sonke GS, van Ommen-Nijhof A, Wortelboer N, van der Noort V, Swinkels ACP, Blommestein HM, Guerrero Paez C, Mol L, Beeker A, Beelen K et al (2024) Early versus deferred use of CDK4/6 inhibitors in advanced breast cancer. Nature 636(8042):474–480 Jongbloed EM, Wortelboer N, de Weerd V, Beaufort CM, Ruigrok-Ritstier K, Van MN, Kraan J, van Zweeden AA, van der Padt-Pruijsten A, Hamming LC et al (2025) Early versus deferred use of CDK4/6 inhibitors in advanced breast cancer: circulating tumor DNA analysis of a randomized phase 3 trial. Nat Med Jeselsohn R, Fu J, Ren Y, Mahtani R, Ma C, DeMichele A, Cristofanilli M, Meisel J, Miller KD, Abdou Y et al (2025) Circulating tumor DNA mutational landscape and dynamics after progression on a CDK4/6 inhibitor in the PACE phase II trial for metastatic HR-positive/HER2-negative breast cancer. ESMO open 10(8):105506 O'Leary B, Hrebien S, Morden JP, Beaney M, Fribbens C, Huang X, Liu Y, Bartlett CH, Koehler M, Cristofanilli M et al (2018) Early circulating tumor DNA dynamics and clonal selection with palbociclib and fulvestrant for breast cancer. Nat Commun 9(1):896 O'Leary B, Cutts RJ, Huang X, Hrebien S, Liu Y, André F, Loibl S, Loi S, Garcia-Murillas I, Cristofanilli M et al (2021) Circulating Tumor DNA Markers for Early Progression on Fulvestrant With or Without Palbociclib in ER+ Advanced Breast Cancer. J Natl Cancer Inst 113(3):309–317 Tolaney SM, Toi M, Neven P, Sohn J, Grischke EM, Llombart-Cussac A, Soliman H, Wang H, Wijayawardana S, Jansen VM et al (2022) Clinical Significance of PIK3CA and ESR1 Mutations in Circulating Tumor DNA: Analysis from the MONARCH 2 Study of Abemaciclib plus Fulvestrant. Clin cancer research: official J Am Association Cancer Res 28(8):1500–1506 Additional Declarations There is NO Competing Interest. Supplementary Files SupplementMaterials.docx Supplement Materials Cite Share Download PDF Status: Posted Version 1 posted 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-8242447","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588232459,"identity":"3c833dec-2ec7-43ac-b13b-d963a87068e4","order_by":0,"name":"Binghe Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYFACHoYDDEBkL5F84MCHH6RoMZzzLPHgzB4itTCAtBjcf2N8mIONCA0GN3IPHi74dUfOcHbOh8NA/fL8Ygfwa5GckZdweGbfM2N76dwNhwssGAxnzk7Ar4VfIsfgMG/P4cSNs4FaZvAwJBjcJqCFDaqlfsONnAeHediI0AK2hefH4QSDGzkMxGmR7HmXcJi34bDhxhlpBsBAliDsF4PjuYc/8/w5LA+MyscfPvywkeeXJqAFDBjb4EwJIpSDwR9iFY6CUTAKRsGIBAA+flC+EYLz9QAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4195-337X","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":true,"prefix":"","firstName":"Binghe","middleName":"","lastName":"Xu","suffix":""},{"id":588232460,"identity":"dfbf0810-3812-4fbc-8b3a-df229f9f3e1e","order_by":1,"name":"Yan Wang","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""},{"id":588232461,"identity":"2fa396b2-d5ec-4266-be8b-05e8d674bdbc","order_by":2,"name":"Hangcheng Xu","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Hangcheng","middleName":"","lastName":"Xu","suffix":""},{"id":588232462,"identity":"ae2cac68-0c25-44a3-b324-fe35f482724c","order_by":3,"name":"Yiran Zhou","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Yiran","middleName":"","lastName":"Zhou","suffix":""},{"id":588232463,"identity":"121b6918-c67d-4e95-b088-2e57414463ed","order_by":4,"name":"Liang Cui","email":"","orcid":"https://orcid.org/0000-0002-4785-9678","institution":"Geneplus-Beijing Institute","correspondingAuthor":false,"prefix":"","firstName":"Liang","middleName":"","lastName":"Cui","suffix":""},{"id":588232464,"identity":"79608e1b-fd30-49af-97af-1ece3e2d7303","order_by":5,"name":"Qiang Sa","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Sa","suffix":""},{"id":588232465,"identity":"8027db1c-66bc-479b-8c7d-b10509baa07d","order_by":6,"name":"Hong Cheng","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Cheng","suffix":""},{"id":588232466,"identity":"1daf29bf-1214-429b-9381-528b4368ae8a","order_by":7,"name":"Renchi Gao","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Renchi","middleName":"","lastName":"Gao","suffix":""},{"id":588232467,"identity":"576faaaf-9080-4e12-9ce6-ba748f354275","order_by":8,"name":"Qingyuan Zhang","email":"","orcid":"https://orcid.org/0000-0001-8116-5293","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qingyuan","middleName":"","lastName":"Zhang","suffix":""},{"id":588232468,"identity":"5e99e864-d116-459f-bb59-37a4fcf4c9da","order_by":9,"name":"Hui-Ping Li","email":"","orcid":"","institution":"Department of Breast Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital \u0026 Institute","correspondingAuthor":false,"prefix":"","firstName":"Hui-Ping","middleName":"","lastName":"Li","suffix":""},{"id":588232469,"identity":"a4ee7bce-c292-449b-b146-245069f170d8","order_by":10,"name":"Sheng Tong","email":"","orcid":"","institution":"Department of Breast Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin","correspondingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Tong","suffix":""},{"id":588232470,"identity":"d9fac968-bfc8-4713-aab9-5de40e7b7e4a","order_by":11,"name":"Quchang Ouyang","email":"","orcid":"","institution":"Hunan Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Quchang","middleName":"","lastName":"Ouyang","suffix":""},{"id":588232471,"identity":"875dfe79-aeb5-4f9f-a5bd-4fa8566a100b","order_by":12,"name":"Xinxin Tan","email":"","orcid":"","institution":"Geneplus-Shenzhen Clinical Laboratory.","correspondingAuthor":false,"prefix":"","firstName":"Xinxin","middleName":"","lastName":"Tan","suffix":""},{"id":588232472,"identity":"b9fe5f09-f660-4694-a6b4-6c18add66508","order_by":13,"name":"Jing Bai","email":"","orcid":"","institution":"Geneplus-Beijing Institute","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Bai","suffix":""},{"id":588232473,"identity":"32868d93-ba2b-49f4-81a0-e029abc9f2a2","order_by":14,"name":"Li Wang","email":"","orcid":"","institution":"Xuanzhu Biopharmaceutical Co.Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Wang","suffix":""},{"id":588232474,"identity":"144d9e04-53df-4789-8581-8b44e8fec976","order_by":15,"name":"Xianghui Duan","email":"","orcid":"","institution":"Xuanzhu Biopharmaceutical Co.Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Xianghui","middleName":"","lastName":"Duan","suffix":""},{"id":588232475,"identity":"3633539a-8974-4afa-976b-f3a34440b275","order_by":16,"name":"Fan Yang","email":"","orcid":"","institution":"Xuanzhu Biopharmaceutical Co.Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Yang","suffix":""},{"id":588232476,"identity":"bfb86795-0a56-4543-af04-c752027044c7","order_by":17,"name":"Jiayu Wang","email":"","orcid":"","institution":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.","correspondingAuthor":false,"prefix":"","firstName":"Jiayu","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-11-30 13:55:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8242447/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8242447/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104399330,"identity":"163e0d55-8296-49c8-9798-e2408e5aca94","added_by":"auto","created_at":"2026-03-11 12:05:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4595133,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBaseline genetic alteration heatmap and the corresponding clinical features.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eORR, objective response rate; HER2, human epidermal growth factor receptor 2; ER, estrogen receptor; PR, progesterone receptor; NE, not evaluable; ECOG, Eastern Cooperative Oncology Group.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/ffe858952be1bc89e2e430e7.png"},{"id":104398852,"identity":"a4af35e8-8dfc-457c-a9ab-c9d99d81743b","added_by":"auto","created_at":"2026-03-11 12:03:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3095202,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation of baseline ctDNA status and specific genetic mutations with treatment response and survival.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Kaplan-Meier curve for PFS by treatment groups and ctDNA status. (B) Kaplan-Meier curve for OS by treatment groups and ctDNA status. (C) The interaction analyses between genetic status and interventions. (D) Association of gene mutations with efficacy in bireociclib group. (E) Association of gene mutations with efficacy in placebo group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e mut, mutation; PFS, progression-free survival; HR, hazard ratio; CI, confidential interval; FDR, false discovery rate; Adj, adjusted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks: \u003c/strong\u003eThe optimal cutoff value of mTBI was 3.05, which was determined using PFS data from all baseline ctDNA-positive patients across bireociclib and placebo arms.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/d1420411d54c9fa9d7345846.png"},{"id":103600971,"identity":"eda71f0a-881c-481b-bbae-fb15ad586b9a","added_by":"auto","created_at":"2026-02-27 14:07:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3815918,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrognostic value of baseline mTBI for survival.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Kaplan-Meier curve for PFS by treatment groups and mTBI level. (B) Kaplan-Meier curve for OS by treatment groups and mTBI level. (C) The multivariate COX analysis of baseline characteristics and mTBI status in bireociclib group for PFS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eN/No., number; HR, hazard ratio; CI, confidential interval; ECOG, Eastern Cooperative Oncology Group; mTBI, molecular tumor burden index; AI, aromatase inhibitor; SERM, selective estrogen receptor modulator.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/f2751b51874220fc1be7c466.png"},{"id":104398884,"identity":"e51db494-d0f1-4a1d-b919-70511ae39cf6","added_by":"auto","created_at":"2026-03-11 12:04:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3676132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePIK3CA–ESR1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTP53–ESR1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eco-mutations on PFS and OS in HR+/HER2− advanced breast cancer.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Kaplan-Meier curve for PFS by \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutation status in bireociclib group. (B) Kaplan-Meier curve for OS by \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutation status in bireociclib group. (C) Kaplan-Meier curve for PFS by \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutation status in placebo group. (D) Kaplan-Meier curve for OS by \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003emutation status in placebo group. (E) Kaplan-Meier curve for PFS by \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutation status in bireociclib group. (F) Kaplan-Meier curve for OS by \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003emutation status in bireociclib group. (G) Kaplan-Meier curve for PFS by \u003cem\u003eTP53\u003c/em\u003eand \u003cem\u003eESR1\u003c/em\u003e mutation status in placebo group. (H) Kaplan-Meier curve for OS by \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutation status in placebo group.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/e5f355a7a6a1b8ff71923e91.png"},{"id":103600973,"identity":"bb898761-406d-4344-8427-387ed2dbee01","added_by":"auto","created_at":"2026-02-27 14:07:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4387765,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between dynamic ctDNA change and survival outcomes and efficacy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Kaplan-Meier curve for PFS of different C1D1-C5D1 ctDNA status subgroups in bireociclib group. (B) Kaplan-Meier curve for OS of different C1D1-C5D1 ctDNA status subgroups in bireociclib group. (C) Patient distribution by C1D1-C5D1 ctDNA statusin responder and non-responder subgroups of bireociclib group. (D) Patient distribution by C1D1-C5D1 ctDNA statusin responder and non-responder subgroups of placebo group. (E) Kaplan-Meier curves for PFS of dynamic mTBI in bireociclib group. (F) Kaplan-Meier Curves for PFS of dynamic \u003cem\u003ePIK3CA\u003c/em\u003e status subgroups in bireociclib group. (G) Kaplan-Meier Curves for PFS of dynamic \u003cem\u003eESR1\u003c/em\u003e status subgroups in bireociclib group. (H) Kaplan-Meier curves for OS of dynamic mTBI in bireociclib group. (I) Kaplan-Meier Curves for OS of dynamic \u003cem\u003ePIK3CA\u003c/em\u003estatus subgroups in bireociclib group. (J) Kaplan-Meier Curves for OS of dynamic \u003cem\u003eESR1\u003c/em\u003e status subgroups in bireociclib group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003eC1D1, day 1 of cycle 1; C5D1, day 1 of cycle 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRemarks: \u003c/strong\u003eBased on the ctDNA positivity or negativity dynamics between C1D1 and C5D1, patients were categorized into four groups: C1D1⁺/C5D1⁺, C1D1⁺/C5D1⁻, C1D1⁻/C5D1⁺, and C1D1⁻/C5D1⁻. Due to the small number of patients in the C1D1⁻/C5D1⁺ group, they were combined with the C1D1⁺/C5D1⁺ group for subsequent analyses.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/1c79afb69b081156121d7e79.png"},{"id":103600972,"identity":"9450cf2b-d6c6-4d13-b286-cbf7d9733e94","added_by":"auto","created_at":"2026-02-27 14:07:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2853404,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReactome pathway enrichment analysis of EOT-specific mutations.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Inter-group shared enrichment pathways. (B) Intra-group unique enrichment pathways.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/b7707e2631cba26e1e314ac2.png"},{"id":104407562,"identity":"33560b2c-b38c-4a7d-b398-e9580e1db9d2","added_by":"auto","created_at":"2026-03-11 12:38:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":21867207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/cb2af30f-f6dc-403d-8025-7109760c9e3b.pdf"},{"id":103600967,"identity":"f650c6b0-748a-42ff-b679-f8108127de71","added_by":"auto","created_at":"2026-02-27 14:07:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4554460,"visible":true,"origin":"","legend":"Supplement Materials","description":"","filename":"SupplementMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8242447/v1/94ea167784951318622ae110.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Dynamic Monitoring and Identification of Reliable Biomarkers to Predict Efficacy of Bireociclib and Fulvestrant: An Exploratory ctDNA Analysis of the BRIGHT-2 Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHormone receptor\u0026ndash;positive, human epidermal growth factor receptor 2\u0026ndash;negative (HR+/HER2\u0026minus;) breast cancer represents the most prevalent molecular subtype of advanced breast cancer (ABC). The introduction of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors in combination with endocrine therapy has fundamentally reshaped the treatment landscape, leading to substantial improvements in progression-free survival (PFS) and overall survival (OS). Mechanistically, endocrine therapy suppresses estrogen-driven cyclin D expression, whereas CDK4/6 inhibition prevents retinoblastoma (RB) protein phosphorylation, cooperatively enforcing G1 cell-cycle arrest and delaying the emergence of endocrine resistance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these advances, considerable interpatient heterogeneity in clinical benefit persists, and both primary and acquired resistance to CDK4/6 inhibitors remain inevitable in a substantial proportion of patients. Several resistance mechanisms have been described, including RB1 loss, activation of receptor tyrosine kinase (RTK)/RAS signaling, cyclin E overexpression, CDK2 hyperactivation, and AURKA amplification; however, most evidence is derived from preclinical models or tumor tissue obtained after progression. To date, these alterations have not been translated into robust, clinically actionable biomarkers for patient stratification or early intervention [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Bireociclib is a novel, orally bioavailable CDK4/6 inhibitor independently developed in China. The phase Ⅱ BRIGHT-1 study and the randomized phase Ⅲ BRIGHT-2 trial demonstrated that bireociclib, both as monotherapy and in combination with fulvestrant, confers significant clinical benefit with a favorable safety profile in patients with HR+/HER2\u0026thinsp;\u0026minus;\u0026thinsp;ABC, including clinically challenging subgroups such as those with endocrine-resistant disease or visceral metastases [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the molecular determinants underlying sensitivity and resistance to bireociclib, particularly in comparison with endocrine therapy alone, remain poorly defined [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Prior exploratory analyses of BRIGHT-2 identified baseline peripheral blood inflammatory markers as prognostic but not predictive of treatment benefit [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], underscoring the unmet need for tumor-informed biomarkers that can capture both disease biology and treatment-specific effects.\u003c/p\u003e \u003cp\u003eCirculating tumor DNA (ctDNA) analysis has emerged as a minimally invasive approach capable of capturing tumor genomic heterogeneity and enabling real-time monitoring of tumor evolution under therapeutic pressure. Longitudinal ctDNA profiling offers the unique opportunity to integrate baseline genomic context with dynamic molecular responses, thereby informing both early efficacy assessment and mechanisms of acquired resistance. Leveraging serial plasma samples collected at baseline, during treatment, and at the end of treatment from the BRIGHT-2 trial [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], we conducted a large-scale longitudinal ctDNA analysis using a 1,021-gene targeted panel to characterize the mutational landscape of East Asian patients with HR+/HER2\u0026thinsp;\u0026minus;\u0026thinsp;advanced breast cancer, identify baseline genomic features associated with sensitivity or resistance to CDK4/6 inhibition, and determine whether on-treatment ctDNA dynamics can serve as early indicators of therapeutic benefit while revealing mechanisms of resistance.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTrial design and patients\u003c/h2\u003e \u003cp\u003eBRIGHT-2 is a randomized, double-blind, phase Ⅲ trial of bireociclib or placebo with fulvestrant in women with HR+/HER2\u0026thinsp;\u0026minus;\u0026thinsp;ABC. Eligible patients were randomly assigned to receive bireociclib or placebo plus fulvestrant at a 2:1 ratio. The primary endpoint was investigator-assessed PFS defined by RECIST version 1.1. The overall trial design, eligibility criteria, and statistical methods of survival outcomes and adverse events have been described previously [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Dynamic monitoring of ctDNA and its exploratory evaluation as biomarkers were prospectively included in the study protocol. As of February 22, 2024, a pre-specified number of PFS events for the final analysis was reached. This analysis utilized efficacy and survival data up to this cutoff date. The BRIGHT-2 study was approved by the ethical and local institutional review boards for the sites participating in the clinical trial, and was conducted according to the Declaration of Helsinki. All patients provided written informed consent prior to enrollment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePlasma collection and 1,021 ctDNA panel assessment\u003c/h3\u003e\n\u003cp\u003eAccording to the study protocol, 10 milliliters peripheral blood samples were collected from all the patients for ctDNA analysis at three timepoints: baseline (day 1 of cycle 1, C1D1), on-treatment (day 1 of cycle 5, C5D1) and EOT. Cell-free DNA (cfDNA) was extracted from plasma samples with the Enhanced Magnetic Circulating DNA Kit (Thermo Fisher Scientific, USA), while germline genomic DNA (gDNA) was isolated from peripheral blood lymphocytes of the first centrifugation using the CWE9600 Blood DNA Kit (CWBIO, Beijing, China). DNA concentration was quantified on a Qubit fluorometer with the AccuGreen HS dsDNA Quantitation Kit (Biotium, USA).\u003c/p\u003e \u003cp\u003eAfter shearing 1.0 \u0026micro;g of gDNA to 200\u0026ndash;250 bp fragments (Covaris S2), sequencing libraries were constructed from both 10\u0026ndash;80 ng cfDNA and sheared gDNA using the Hieff NGS Ultima DNA Library Prep Kit for MGI (Yeasen, Shanghai, China), respectively. A custom-designed panel covering\u0026thinsp;~\u0026thinsp;1.6 Mbp genome and targeting 1,021 cancer-related genes was used for hybridization enrichment with DNA libraries, and then sequenced using DNBSEQ-T7RS sequencing instrument (MGI Tech, Shenzhen, China) with 2 \u0026times; 100bp paired-end reads. Selected regions and genes of the targeted panel were listed in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e. Every specific gene was classified as \"altered\" if more than one alteration was detected (defined as the presence of a copy number variation, short insertion/deletion, or mutation); otherwise, it was classified as \u0026ldquo;wild-type (WT)\u0026rdquo;.\u003c/p\u003e\n\u003ch3\u003eIdentification of gene alterations and mTBI analysis\u003c/h3\u003e\n\u003cp\u003eAfter removing adapters and low-quality reads, the clean reads were mapped to the human reference genome (hg19) using BWA18 (version 0.7.12-r1039). The Picard software MarkDuplicates (v4.0.4.0; Broad Institute, Cambridge, MA, USA) was used for realignment and recalibration. Somatic single nucleotide variants (SNVs) and small insertions and deletions were determined by MuTect2 and realDcaller (Geneplus-Beijing, inhouse). CNVKit was employed to detect copy number alterations (CNVs). Somatic alterations were filtered with matched patient\u0026rsquo;s whole blood controls to remove germline mutations [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. For each ctDNA sample, the molecular tumor burden index (mTBI) was determined using the mean variant allele frequency (VAF) of the clonal mutations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The change in mTBI (ΔmTBI) was calculated as the difference in mTBI between the on-treatment and the paired baseline ctDNA sample.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll the analyses were performed using R software (version 4.3.3) with two-sided 95% confidence intervals (CIs). Continuous data were summarized descriptively, with categorical data as frequencies. PFS was estimated by Kaplan-Meier and compared using stratified log-rank tests. The objective response rate (ORR), disease control rate (DCR), and clinical benefit rate (CBR) were assessed with the Cochran-Mantel-Haenszel test. Fisher\u0026rsquo;s exact test was performed to compare differences in categorical variables between groups. Continuous variables were compared between two groups using the Wilcoxon rank-sum test. P values were estimated using the log-rank test. Hazard ratios (HRs) and 95% CIs were derived from unstratified Cox proportional hazards models. The interaction analyses between treatment and gene mutation were conducted using \u0026ldquo;TableSubgroupMultiCox\u0026rdquo; function from \u0026ldquo;jstable\u0026rdquo; package, with the resulting interaction p values adjusted for multiple testing via False Discovery Rate (FDR) method. The \u0026ldquo;surv_cutpoint\u0026rdquo; function from \u0026ldquo;survminer\u0026rdquo; package was used to determine the optimal cut-off values of mTBI based on PFS data. Functional enrichment analysis for reactome pathways was conducted with the \u0026ldquo;clusterProfiler\u0026rdquo; R package.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline ctDNA Landscape and Sample Collection in HR+/HER2\u0026minus; Advanced Breast Cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween December 8, 2021 and October 24, 2022, 305 patients with HR+/HER2\u0026minus; ABC were enrolled across 64 hospitals in China and randomly assigned to receive bireociclib plus fulvestrant (n = 204) or placebo plus fulvestrant (n = 101). During the treatment process, plasma samples were collected for ctDNA examination at baseline, on-treatment and EOT. In the bireociclib arm, plasma at C1D1, C5D1 and EOT was collected from 197, 139, and 86 patients, respectively; whereas in the placebo arm, plasma was available from 79, 46, and 49 patients at these corresponding time points. The ctDNA sample collection process is illustrated in \u003cstrong\u003e\u003cem\u003eSupplementary Figure 1\u003c/em\u003e\u003c/strong\u003e. In the intention-to-treat (ITT) population, median PFS was 14.7 months in the bireociclib plus fulvestrant arm versus 7.3 months in the placebo arm (HR = 0.55, 95% CI 0.41\u0026ndash;0.75, P \u0026lt; 0.001). Among patients with evaluable ctDNA, median PFS was 14.7 months and 6.0 months in the bireociclib and placebo groups, respectively (HR = 0.48, 95% CI 0.35\u0026ndash;0.66, P \u0026lt; 0.001). Baseline clinicopathologic characteristics were well balanced across treatment arms in both the ITT and ctDNA-evaluable populations (\u003cstrong\u003e\u003cem\u003eSupplementary Table 2\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFigure 1\u003c/em\u003e\u003c/strong\u003e displays genes with an alteration frequency \u0026gt; 5% at baseline across all patients with evaluable ctDNA (n = 219), along with their associations with ORR and clinicopathological characteristics. \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eTP53\u003c/em\u003e, and \u003cem\u003eESR1\u003c/em\u003e were the three most frequently altered genes, with frequencies of 48%, 37%, and 23%, respectively. Several alterations appeared to be associated with specific clinical features (\u003cstrong\u003e\u003cem\u003eSupplementary\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eFigure 2\u003c/em\u003e\u003c/strong\u003e). Notably, \u003cem\u003eBRCA1\u003c/em\u003e alterations are more common in postmenopausal patients. \u003cem\u003eESR1\u003c/em\u003e alterations are frequently detected in postmenopausal patients and in those with liver metastases, secondary endocrine resistance, and more than three metastatic sites. \u003cem\u003eTP53\u003c/em\u003e alterations were enriched in patients with Ki67 \u0026ge;15% or liver metastases, while \u003cem\u003ePTEN\u003c/em\u003e mutations were more frequent in those with Ki67 \u0026lt;15%. Collectively, poorer ECOG performance status, postmenopausal status, higher tumor burden, and a greater number of prior endocrine therapies were correlated with a higher prevalence of detectable genomic alterations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline ctDNA, mTBI, and Pathway-Level Genomic Alterations Stratify Therapeutic Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor baseline ctDNA status, 152 and 67 patients were positive in bireociclib and placebo arms, respectively. In both treatment arms, ctDNA-positive patients had shorter PFS and OS than ctDNA-negative patients (\u003cstrong\u003e\u003cem\u003eFigure 2A and 2B\u003c/em\u003e\u003c/strong\u003e). In the bireociclib arm, median PFS was 11.2 months in ctDNA-positive patients, whereas median PFS was not reached (NR) in ctDNA-negative patients (HR = 2.28, 95% CI 1.31\u0026ndash;3.94, p = 0.003). A similar pattern was observed in the placebo arm, where median PFS was 5.6 months for ctDNA-positive patients and 17.5 months for ctDNA-negative patients (HR = 2.64, 95% CI 1.13\u0026ndash;6.16, p = 0.02). Although OS data remain immature, consistent differences favoring ctDNA-negative patients were also observed in both the bireociclib and placebo arms (p \u0026lt; 0.001 and p = 0.021, respectively).\u003c/p\u003e\n\u003cp\u003eThe association between specific gene alterations and survival in the bireociclib and placebo arms are displayed in \u003cstrong\u003e\u003cem\u003eSupplementary Figure 3\u003c/em\u003e\u003c/strong\u003e. Across both treatment arms, alterations in \u003cem\u003eTP53\u003c/em\u003e, \u003cem\u003eMYC\u003c/em\u003e, and \u003cem\u003ePTPRD\u003c/em\u003e were associated with shorter PFS, whereas alterations in \u003cem\u003eFGF19\u003c/em\u003e, \u003cem\u003eFGF4\u003c/em\u003e, \u003cem\u003eCCND1\u003c/em\u003e, \u003cem\u003eFGF3\u003c/em\u003e, and \u003cem\u003eTP53\u003c/em\u003e were linked to poorer OS. Interaction analyses assessing the modifying effect of treatment on PFS indicated that only \u003cem\u003eCCND1\u003c/em\u003e and \u003cem\u003eFGF19\u003c/em\u003e alterations retained evidence of treatment interaction after correction for multiple testing (FDR-adjusted p = 0.03 and 0.002, respectively; \u003cstrong\u003e\u003cem\u003eFigure 2C\u003c/em\u003e\u003c/strong\u003e), suggesting that patients harboring these alterations derived greater PFS benefit from bireociclib compared with placebo.\u003c/p\u003e\n\u003cp\u003eAssociations between baseline genetic mutations and treatment responses are shown in \u003cstrong\u003e\u003cem\u003eFigure 2D and 2E\u003c/em\u003e\u003c/strong\u003e. In both the bireociclib and placebo arms, \u003cem\u003emTOR\u003c/em\u003e mutations were detected exclusively in responders, while \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e mutations were more frequent in non-responders than responders. Additionally, mutations in \u003cem\u003eAKT1\u003c/em\u003e, \u003cem\u003eCDH1\u003c/em\u003e, and \u003cem\u003eLRP1B\u003c/em\u003e were statistically associated with worse response in the bireociclib arm, whereas no such association was observed in the placebo arm due to its low response.\u003c/p\u003e\n\u003cp\u003eThe mTBI is a core quantitative metric used to assessing ctDNA fraction. Patients with high mTBI level had worse PFS (p \u0026lt; 0.001, \u003cstrong\u003e\u003cem\u003eFigure 3A\u003c/em\u003e\u003c/strong\u003e) and OS (p = 0.014, \u003cstrong\u003e\u003cem\u003eFigure 3B\u003c/em\u003e\u003c/strong\u003e) than their counterparts in each treatment arm. Regarding treatment response, responders had conspicuously lower mTBI levels than non-responders in the bireociclib arm (p = 0.0369, \u003cstrong\u003e\u003cem\u003eSupplementary Figure 4\u003c/em\u003e\u003c/strong\u003e), whereas no significant correlation between mTBI and response was observed in the placebo arm. Subsequently, univariate Cox regression analyses of baseline characteristics and mTBI were performed separately in each arm (\u003cstrong\u003e\u003cem\u003eSupplementary Table 3 and 4\u003c/em\u003e\u003c/strong\u003e). The features with univariate p＜0.1 in either arm were included in multivariate analyses alongside mTBI. Multivariate analysis demonstrated that mTBI was an independent prognostic factor for PFS in both arms (p = 0.002 and \u0026lt; 0.001, respectively; \u003cstrong\u003e\u003cem\u003eFigure 3C and Supplementary Figure 5\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExploratory pathway-level analyses revealed that alterations in the PI3K signaling pathway were associated with shorter PFS (HR = 1.73, 95% CI 1.08\u0026ndash;2.75, p = 0.02) and OS (HR = 2.43, 95% CI 1.21\u0026ndash;4.89, p = 0.01), exclusively in the bireociclib arm (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 6\u003c/em\u003e\u003c/strong\u003e). Alterations in the MYC pathway correlated with poorer PFS and OS in both treatment arms (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 7\u003c/em\u003e\u003c/strong\u003e). Within the bireociclib cohort, patients harboring homologous recombination repair (HRR) pathway alterations, including germline \u003cem\u003eBRCA\u003c/em\u003e mutations (\u003cem\u003egBRCAm\u003c/em\u003e), experienced shorter PFS (HR = 2.21, 95% CI 1.49\u0026ndash;3.29, p \u0026lt; 0.001) and OS (HR = 2.40, 95% CI 1.35\u0026ndash;4.25, p = 0.002) compared with those without HRR alterations, whereas no significant associations were observed in the placebo arm (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 8\u003c/em\u003e\u003c/strong\u003e). Separate analyses of patients with \u003cem\u003egBRCAm\u003c/em\u003e or non-\u003cem\u003eBRCA\u003c/em\u003e HRR mutations indicated that only patients with \u003cem\u003egBRCAm\u003c/em\u003e in the bireociclib arm exhibited distinctly poorer outcomes compared with \u003cem\u003egBRCAm\u003c/em\u003e\u0026ndash;wild-type patients. No clear differences were observed in the remaining comparisons (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 9\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePIK3CA\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eESR1\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eand \u003cem\u003eTP53\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eESR1\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Co-mutations Define Distinct Predictive and Prognostic Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCo-mutation analyses between the three most frequently altered genes were performed, including \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e, as well as \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e. For \u003cem\u003ePIK3CA\u003c/em\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003cem\u003eESR1\u003c/em\u003e co-mutation analysis, patients were stratified into four molecular subgroups as \u003cem\u003ePIK3CA⁺/ESR1⁺\u003c/em\u003e, \u003cem\u003ePIK3CA⁻\u003c/em\u003e\u003cem\u003e/ESR1⁻\u003c/em\u003e, \u003cem\u003ePIK3CA⁻/ESR1⁺\u003c/em\u003e, and \u003cem\u003ePIK3CA⁺/ESR1⁻\u003c/em\u003e. In the bireociclib arm, median PFS across these subgroups were NR, 14.5 months, 8.3 months, and 8.8 months, respectively; while median OS were NR, NR, 20.8 months, and 19.2 months. Patients harboring concurrent \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutations experienced significantly longer PFS than those with other genotypic profiles (p = 0.003, \u003cstrong\u003e\u003cem\u003eFigure 4A\u003c/em\u003e\u003c/strong\u003e). Although OS data are not yet mature, a consistent trend toward improved OS was observed in the \u003cem\u003ePIK3CA\u003c/em\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003cem\u003eESR1\u003c/em\u003e co-mutant subgroup (p = 0.024, \u003cstrong\u003e\u003cem\u003eFigure 4B\u003c/em\u003e\u003c/strong\u003e). Notably, this survival advantage was not observed in the placebo arm (\u003cstrong\u003e\u003cem\u003eFigure 4C and 4D\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eA formal interaction test between treatment assignment and the four \u003cem\u003ePIK3CA\u003c/em\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003cem\u003eESR1\u0026nbsp;\u003c/em\u003egenotypic subgroups, adjusted for relevant clinicopathologic covariates, demonstrated that patients with \u003cem\u003ePIK3CA⁺/ESR1⁺\u003c/em\u003e tumors derived the greatest benefit from bireociclib (HR = 0.02, 95% CI 0.00\u0026ndash;0.34; P = 0.007; \u003cstrong\u003e\u003cem\u003eSupplementary Figure 10\u003c/em\u003e\u003c/strong\u003e), followed by those with \u003cem\u003ePIK3CA⁺/ESR1⁻\u003c/em\u003e disease (HR = 0.56, 95% CI 0.32\u0026ndash;0.99; P = 0.047). In contrast, no meaningful differences between bireociclib and placebo were observed in either of the \u003cem\u003ePIK3CA⁻\u003c/em\u003e subgroups, yielding an overall interaction that did not reach statistical significance across the four genotypic categories (p for interaction = 0.201). Within the two \u003cem\u003ePIK3CA⁺\u003c/em\u003e subgroups, a significant interaction was observed between \u003cem\u003eESR1\u003c/em\u003e mutation status and treatment effect (p for interaction = 0.03, \u003cstrong\u003e\u003cem\u003eSupplementary Figure 11\u003c/em\u003e\u003c/strong\u003e), suggesting that \u003cem\u003eESR1\u003c/em\u003e mutation status may serve as a positive predictive biomarker for bireociclib efficacy in this molecular context.\u003c/p\u003e\n\u003cp\u003eAn analogous four-group stratification was applied for the \u003cem\u003eTP53\u0026ndash;ESR1\u003c/em\u003e co-mutation analysis (\u003cem\u003eTP53⁺/ESR1⁺\u003c/em\u003e, \u003cem\u003eTP53⁻/ESR1⁻\u003c/em\u003e, \u003cem\u003eTP53⁻/ESR1⁺\u003c/em\u003e, and \u003cem\u003eTP53⁺/ESR1⁻\u003c/em\u003e). In the bireociclib arm, patients with \u003cem\u003eTP53⁻/ESR1⁺\u003c/em\u003e tumors exhibited the most favorable PFS, which was NR, followed by those with \u003cem\u003eTP53⁻/ESR1⁻\u003c/em\u003e and \u003cem\u003eTP53⁺/ESR1⁺\u003c/em\u003e disease (median PFS 17.4 and 13.3 months, respectively), whereas the \u003cem\u003eTP53⁺/ESR1⁻\u003c/em\u003e subgroup demonstrated the poorest PFS of 7.3 months, with significant differences observed across the four groups (p \u0026lt; 0.001, \u003cstrong\u003e\u003cem\u003eFigure 4E\u003c/em\u003e\u003c/strong\u003e). OS comparisons showed differences across the four subgroups that were directionally consistent with the PFS findings (p = 0.006, \u003cstrong\u003e\u003cem\u003eFigure 4F\u003c/em\u003e\u003c/strong\u003e). Given the immaturity of OS data, median OS was reached only in the TP53⁺/ESR1⁺ and TP53⁺/ESR1⁻ subgroups (23.6 and 19.1 months, respectively).\u003c/p\u003e\n\u003cp\u003eIn the placebo arm, both PFS and OS also differed significantly among the four \u003cem\u003eTP53\u003c/em\u003e\u003cem\u003e\u0026ndash;\u003c/em\u003e\u003cem\u003eESR1\u0026nbsp;\u003c/em\u003esubgroups (p \u0026lt; 0.001 and p = 0.036, respectively; \u003cstrong\u003e\u003cem\u003eFigure 4G and 4H\u003c/em\u003e\u003c/strong\u003e), with more favorable outcomes consistently observed in \u003cem\u003eTP53\u003c/em\u003e-wildtype tumors. These findings suggest that \u003cem\u003eTP53\u003c/em\u003e status functions primarily as a prognostic factor for patients with HR+/HER2\u0026minus; ABC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOn-treatment ctDNA dynamics predict efficacy with bireociclib plus fulvestrant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed the dynamic changes of ctDNA from C1D1 to C5D1\u0026nbsp;and categorized patients into three subgroups, including C1D1\u003csup\u003e-\u003c/sup\u003e/C5D1\u003csup\u003e-\u003c/sup\u003e, C1D1⁺/C5D1\u003csup\u003e-\u003c/sup\u003e, and C1D1\u003csup\u003e\u0026plusmn;\u003c/sup\u003e/C5D1\u003csup\u003e+\u003c/sup\u003e. In the bireociclib arm, patients with persistent or converted to positive (C1D1\u003csup\u003e\u0026plusmn;\u003c/sup\u003e/C5D1\u003csup\u003e+\u003c/sup\u003e) ctDNA status were demonstrated with significantly inferior PFS and OS compared to those with C1D1⁻/C5D1⁻ or C1D1⁺/C5D1⁻ (overall p = 0.003 and ＜0.001, respectively; \u003cstrong\u003e\u003cem\u003eFigure 5A and 5B\u003c/em\u003e\u003c/strong\u003e). In the placebo arm, only a trend towards prolonged PFS was observed for C1D1⁻/C5D1⁻ subgroup compared to the other two groups (overall p = 0.048, \u003cstrong\u003e\u003cem\u003eSupplementary Figure 12A\u003c/em\u003e\u003c/strong\u003e), and OS did not differ significantly (overall p = 0.581, \u003cstrong\u003e\u003cem\u003eSupplementary Figure\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e12B\u003c/em\u003e\u003c/strong\u003e). The C1D1\u003csup\u003e+\u003c/sup\u003e/C5D1\u003csup\u003e-\u003c/sup\u003e subgroup showed the greatest PFS benefit from bireociclib treatment compared to placebo (HR = 0.268, p=0.008, \u003cstrong\u003e\u003cem\u003eSupplementary Figure 13\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEfficacy comparisons revealed that the responders had a notably higher proportion of patients with ctDNA clearance status (C1D1⁺/C5D1⁻) than non-responders in the bireociclib arm (p = 0.011, \u003cstrong\u003e\u003cem\u003eFigure 5C\u003c/em\u003e\u003c/strong\u003e), whereas the distribution of ctDNA dynamic status did not differ between responders and non-responders in the placebo arm (p = 0.464, \u003cstrong\u003e\u003cem\u003eFigure 5D\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDynamic changes in mTBI were further evaluated by stratifying patients into increase (\u0026Delta;\u0026ge;0) or decrease (\u0026Delta;\u0026lt;0) over time. In the bireociclib arm, patients with increasing mTBI had a markedly shorter median PFS than those with declining mTBI (5.6 months vs. 14.6 months; HR = 2.93, 95% CI 1.50\u0026ndash;5.73, p = 0.001; \u003cstrong\u003e\u003cem\u003eFigure 5E\u003c/em\u003e\u003c/strong\u003e). A similar pattern was observed for OS, with a median OS of 19.6 months in the mTBI \u0026Delta;\u0026ge;0 subgroup and NR in the \u0026Delta;\u0026lt;0 subgroup (HR = 2.49, 95% CI 0.99\u0026ndash;6.24, p = 0.044; \u003cstrong\u003e\u003cem\u003eFigure 5H\u003c/em\u003e\u003c/strong\u003e). In the placebo arm, increasing mTBI was also associated with shorter PFS (p = 0.025); however, no difference in OS was observed between mTBI subgroups (p = 0.552; \u003cstrong\u003e\u003cem\u003eSupplementary Figure 14\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eDynamic profiling of frequently mutated genes demonstrated that in the bireociclib arm, patients with baseline \u003cem\u003ePIK3CA\u003c/em\u003e or \u003cem\u003eESR1\u003c/em\u003e mutations who achieved ctDNA clearance at C5D1 had markedly prolonged PFS and OS. Among patients stratified by dynamic \u003cem\u003ePIK3CA\u003c/em\u003e status, median PFS was NR in the C1D1\u003csup\u003e⁺\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e subgroup, compared with 11.1 months in the C1D1\u003csup\u003e⁻\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e subgroup and 9.1 months in the C1D1\u003csup\u003e⁺\u003c/sup\u003e/C5D1\u003csup\u003e⁺\u003c/sup\u003e subgroup (overall p = 0.025, \u003cstrong\u003e\u003cem\u003eFigure 5F\u003c/em\u003e\u003c/strong\u003e). Similarly, when stratified by dynamic \u003cem\u003eESR1\u003c/em\u003e status, median PFS was NR for C1D1\u003csup\u003e⁺\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e patients, 11.1 months for C1D1\u003csup\u003e⁻\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e patients, and 8.2 months for C1D1\u003csup\u003e⁺\u003c/sup\u003e/C5D1\u003csup\u003e⁺\u003c/sup\u003e patients (overall p = 0.003, \u003cstrong\u003e\u003cem\u003eFigure 5I\u003c/em\u003e\u003c/strong\u003e). Although OS data remain immature, median OS was NR in both the \u003cem\u003ePIK3CA\u003c/em\u003e or \u003cem\u003eESR1\u003c/em\u003e C1D1\u003csup\u003e⁺\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e and C1D1\u003csup\u003e⁻\u003c/sup\u003e/C5D1\u003csup\u003e⁻\u003c/sup\u003e subgroups; comparisons across the three dynamic subgroups demonstrated a significant difference, with the most pronounced survival benefit observed in patients achieving ctDNA clearance (\u003cstrong\u003e\u003cem\u003eFigure 5G and 5J\u003c/em\u003e\u003c/strong\u003e). In contrast, neither PFS nor OS differed across dynamic \u003cem\u003ePIK3CA\u003c/em\u003e or \u003cem\u003eESR1\u003c/em\u003e mutation subgroups in the placebo arm. (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 15\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnd of treatment mutation landscape and the resistant mechanisms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn comparative analyses of across three time points, no genes exhibited statistically significant dynamic changes in the bireociclib arm. In contrast, 15 genes in the placebo arm demonstrated fluctuations in mutation frequency from C1D1 to C5D1 and EOT, enriched in NOTCH signaling pathway and cell adhesion/junction pathways, among others. (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 16\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eWe systematically analyzed the mutational landscape across longitudinal timepoints (C1D1, C5D1, and EOT) in each patient. As shown in \u003cstrong\u003e\u003cem\u003eSupplementary Figure 17\u003c/em\u003e\u003c/strong\u003e, 81.8% of patients exhibited mutations shared across all three timepoints in bireociclib group, among which \u003cem\u003ePIK3CA|p.E545K\u003c/em\u003e, \u003cem\u003eAKT1|p.E17K\u003c/em\u003e，and \u003cem\u003ePIK3CA|p.H1047R\u003c/em\u003e were the most frequent, indicating their potential role as early clonal driver events. In addition, \u003cem\u003eESR1|p.E380Q\u003c/em\u003e and \u003cem\u003eMDM4|Amp\u003c/em\u003e were the most common private mutations detected exclusively at C1D1 and were subsequently cleared during treatment, suggesting that the subclones harboring these alterations were sensitive to therapy. Conversely, \u003cem\u003eFGFR1|Amp\u003c/em\u003e, \u003cem\u003eMDM2|Amp\u003c/em\u003e, \u003cem\u003eMYC|Amp\u003c/em\u003e, \u003cem\u003ePIK3CA|Amp\u003c/em\u003e, and \u003cem\u003ePIK3CA|p.E545K\u003c/em\u003e emerged as the most frequent EOT-specific private mutations, suggesting that they are potential mechanisms driving resistance to bireociclib. In the placebo group, the most frequent EOT-specific private mutations were \u003cem\u003eESR1|p.D538G\u003c/em\u003e, \u003cem\u003eESR1|p.Y537S\u003c/em\u003e, \u003cem\u003eMDM2|Amp\u003c/em\u003e, \u003cem\u003eCCND1|Amp\u003c/em\u003e, \u003cem\u003eESR1|p.L536P\u003c/em\u003e, \u003cem\u003eFGF3/4/19|Amp\u003c/em\u003e, \u003cem\u003eFGFR1|Amp\u003c/em\u003e, and \u003cem\u003eIFNG|Amp\u003c/em\u003e (\u003cstrong\u003e\u003cem\u003eSupplementary Figure 18\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTo identify the acquired mutations during treatment and the underlying disease progression mechanism, we selected genes mutated exclusively at EOT but not at baseline and performed reactome pathway enrichment analysis. A total of 511 and 357 genes with EOT-specific mutations were revealed in the bireociclib and placebo arm, respectively (\u003cstrong\u003e\u003cem\u003eFigure 6\u003c/em\u003e\u003c/strong\u003e). Notably, the bireociclib group unique enrich pathways were highly enriched in the MAPK family signaling pathways, indicating the resistance to bireociclib is likely driven by activation of the MAPK/RAF/RAS signaling axis.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrently, CDK4/6 inhibitors are widely established in combination with endocrine therapy for HR+/HER2− ABC. However, identifying patients who are most likely to benefit and monitoring dynamic biomarkers of response remain key clinical challenges [12]. In this study, we observed that patients with baseline ctDNA negativity or low mTBI levels experienced significantly improved outcomes. Mechanistic investigations revealed heterogeneous resistance patterns in the bireociclib group, including amplifications in \u003cem\u003eFGFR1\u003c/em\u003e, \u003cem\u003eMDM2\u003c/em\u003e, and \u003cem\u003eMYC\u003c/em\u003e, as well as activation of the MAPK/RAF/RAS signaling axis. In contrast, resistance in the placebo arm was largely driven by ESR1 mutations, consistent with canonical endocrine resistance.\u003c/p\u003e\n\u003cp\u003eBeyond single-gene and canonical pathway alterations, our data highlight the clinical relevance of co-mutational contexts. Notably, patients harboring concurrent \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutations at baseline derived the greatest PFS benefit from bireociclib, and longitudinal clearance of either mutation was associated with particularly favorable outcomes, even exceeding those observed in patients with persistently negative ctDNA. In contrast, co-mutation analyses involving \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e revealed a distinct pattern: \u003cem\u003eTP53\u003c/em\u003e status primarily stratified prognosis irrespective of treatment assignment, with consistently inferior outcomes observed in \u003cem\u003eTP53\u003c/em\u003e-mutant tumors. These findings suggest that, unlike \u003cem\u003ePIK3CA\u003c/em\u003e\u003cem\u003e–\u003c/em\u003e\u003cem\u003eESR1\u003c/em\u003e co-mutation, which defines a treatment-sensitive molecular context, \u003cem\u003eTP53\u003c/em\u003e\u003cem\u003e–\u003c/em\u003e\u003cem\u003eESR1\u003c/em\u003e co-mutation reflects underlying disease aggressiveness rather than differential sensitivity to CDK4/6 inhibition.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e co-mutation detected in 13.2% of patients in the bireociclib arm and 10.4% in the placebo arm, consistent with prior reports ranging from 10% to 15% [13, 14]. The impact of \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e co-mutations on survival outcomes in HR+/HER2− ABC has remained controversial. While multiple studies have demonstrated that the adverse prognostic effect associated with \u003cem\u003eESR1\u003c/em\u003e mutations can be mitigated by SERD-based therapy [15-17], \u003cem\u003ePIK3CA\u003c/em\u003e mutations have more consistently been linked to inferior clinical outcomes [18, 19], and direct comparisons of co-mutant tumors versus other genotypic subsets have been limited. A similar pattern was reported in the EMBER-3 trial of the oral SERD imlunestrant, in which exploratory analyses showed that patients with concurrent PI3K pathway and \u003cem\u003eESR1\u003c/em\u003e alterations derived the greatest PFS benefit from imlunestrant plus abemaciclib compared with imlunestrant monotherapy, exceeding that observed in tumors harboring either alteration alone [20]. Absolute median PFS was likewise longest in the co-mutant subgroup (12.9 months versus 7.5–11.1months), supporting the concept that dual pathway alterations define a molecular context of enhanced sensitivity to CDK4/6 inhibitor–based therapy. In line with these findings, the ReDiscover study, which enrolled patients with \u003cem\u003ePIK3CA\u003c/em\u003e-mutant HR⁺/HER2⁻ metastatic breast cancer, reported a higher ORR in patients with concurrent \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e mutations compared with those harboring \u003cem\u003ePIK3CA\u003c/em\u003e mutations alone (60% vs. 28.57%) [21]. In contrast, translational analyses from two additional studies did not observe differences in PFS between \u003cem\u003ePIK3CA/ESR1\u003c/em\u003e co-mutant and \u003cem\u003ePIK3CA\u003c/em\u003e-mutant/\u003cem\u003eESR1\u003c/em\u003e–wild-type tumors treated with PI3K inhibitors and endocrine therapy, highlighting the context-dependent nature of these associations [13, 22].\u003c/p\u003e\n\u003cp\u003eMechanistically, \u003cem\u003eESR1\u003c/em\u003e mutations result in constitutive activation of the ER signaling pathway [23], while \u003cem\u003ePIK3CA\u003c/em\u003e mutations enhance PI3K pathway signaling, promoting cell survival and proliferation. Although isolated PI3K mutations can drive ER-independent signaling, the presence of co-mutations maintains ER as a dominant oncogenic driver. Within this framework, the combination of fulvestrant, an ER degrader targeting upstream signaling, and a CDK4/6 inhibitor, which blocks the downstream Cyclin D–CDK4/6–Rb axis, achieves a comprehensive blockade of this critical proliferative “highway,” providing a mechanistic rationale for the pronounced clinical benefit observed in co-mutant patients. Clinical evidence from the INAVO‑120 study has demonstrated that first-line treatment with a CDK4/6 inhibitor combined with fulvestrant and a PI3K inhibitor can significantly improve outcomes in patients with \u003cem\u003ePIK3CA\u003c/em\u003e-mutant HR+/HER2− ABC [24]. In this context, the pronounced efficacy of bireociclib plus fulvestrant in the \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e co-mutant subgroup, which accounts for approximately 27% of patients with \u003cem\u003ePIK3CA\u003c/em\u003e mutations, suggests its potential as an alternative therapeutic option for patients who are unable to tolerate toxicities associated with PI3K inhibitors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe previous studies have demonstrated the status of ctDNA, along with mTBI or ctDNA-related indicators, provide critical insights for clinical practice [18, 25-28]. In our study, patients exhibiting pretreatment positive ctDNA or high level of mTBI represent a high-risk of poorer clinical outcomes despite the addition of a CDK4/6 inhibitor. These patients may be candidates for future clinical trials exploring intensified novel agents. Conversely, in patients with undetectable baseline ctDNA, fulvestrant monotherapy showed non-inferior PFS compared to bireociclib plus fulvestrant, suggesting the potential for treatment de-escalation to endocrine monotherapy. Based on the results from the BRIGHT-1 study, bireociclib monotherapy is an effective therapeutic option subsequent progression [5]. The translational analysis of phase Ⅲ SONIA trial, which compared first-line versus second-line CDK4/6 inhibitor in addition to endocrine therapy, revealed that in the high ctDNA subgroup, first-line CDK4/6 inhibitor use remarkably prolonged both first and second PFS (PFS1 and PFS2) [29]. However, in the low ctDNA subgroup, no significant differences in PFS1 or PFS2 were observed [30]. Based on these data, it is necessary to reconsider the necessity of applying CDK4/6 inhibitors as early as possible for every patient. In summary, pretreatment ctDNA levels may help to identify patients who were most likely to benefit from either escalate or de-escalate strategies.\u003c/p\u003e\n\u003cp\u003eFurthermore, dynamic monitoring of ctDNA and related biomarkers also provides guidance for adapting treatment strategies. In terms of study design, the on-treatment sampling time point (C5D1) was set later than other studies [31, 32], which was considered from the perspective of relatively long PFS and OS in HR-positive breast cancer, as well as the wide window of response time. In bireociclib group, the median time to response was 3.7 months, which aligns closely with the C5D1 time point. Selecting C5D1 allowed for the assessment of complete ctDNA clearance rather than merely a reduction. Dynamic analysis further revealed that clearance of overall ctDNA or individual genes could significantly predict survival outcomes. This liquid biopsy-based approach is technically simpler than traditional tissue biopsy and may offer earlier predictive method for survival compared to conventional imaging-based assessment of tumor response.\u003c/p\u003e\n\u003cp\u003eHowever, this study had several limitations. Firstly, the limited sample size and low mutation frequency precluded reliable evaluation of the predictive or prognostic value of rare mutations, resulting in wide 95% confidence intervals. This limitation was particularly relevant for analyses of the relationship between co-mutation status and survival outcomes. In the placebo arm, the numbers of patients with \u003cem\u003ePIK3CA⁺/ESR1⁺\u003c/em\u003e or \u003cem\u003eTP53⁺/ESR1⁺\u003c/em\u003e tumors were small, necessitating cautious interpretation of these results. Furthermore, our work represents a translational sequencing analysis of clinical samples and did not include in vitro studies to explore the underlying molecular mechanisms. Finally, DNA sequencing was performed only on peripheral blood samples without paired tumor tissue for dual validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite these limitations, this study constitutes the first translational ctDNA analysis of the novel CDK4/6 inhibitor bireociclib and remains among the most comprehensive translational sequencing efforts to date, leveraging the largest gene panel and multi‑timepoint sampling strategy in the field. Compared with the methods used in PALOMA-3 [33] (Guardant360 panel of approximately 70 genes), MONARCH-2 [34] (ddPCR assessing approximately two genes), and MONALEESA-3 [8] (SureSelect XT custom probes covering approximately 558 genes), the 1,021-gene panel offers substantially broader genomic coverage. Future studies are planned to both validate the impact of \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eESR1\u003c/em\u003e co-mutations in vitro and in animal models, and to elucidate the molecular mechanisms driving these effects. Notably, baseline characteristics were homogeneous [6], enabling the characterization of ctDNA profiles in East Asian patients with HR-positive ABC.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYan Wang, Hangcheng Xu, and Yiran Zhou: Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, and Writing - original draft. Liang Cui: Data curation, Software, Formal analysis, Investigation, Visualization, and Methodology. Qiang Sa, Hong Cheng, and Renchi Gao: Data Curation, Formal Analysis, and Writing - Original Draft. Qingyuan Zhang, Huiping Li, Zhongsheng Tong and Quchang Ouyang: Conceptualization, Resources, Data Curation, Investigation, Methodology and Project administration. Xinxin Tan and Jing Bai: Data curation, Software, Formal analysis, Investigation, and Methodology. Li Wang, Xianghui Duan and Fan Yang: Conceptualization, Data Curation, Software, Funding acquisition, Validation, Methodology, and Project administration. Jiayu Wang and Binghe Xu: Conceptualization, Resources, Funding acquisition, Validation, Methodology, Project administration, and Writing-review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to all the patients, principal investigators and every healthcare personnel who participated in the BRIGHT-2 study for their contributions to medical development.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics \u0026amp; Bioinformatics 2025) at the National Genomics Data Center (Nucleic Acids Res 2025), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA-Human: HRA014553) that are controlled access at https://ngdc.cncb.ac.cn/gsa-human.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National High Level Hospital Clinical Research Funding (2025-LYZX-D-A02); Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS, 2021-I2M-1-014; 2023-12M-2-004); the National Major Scientific and Technological Special Project for “Significant New Drugs Development” (No. 2018ZX09711002-011-027) and Noncommunicable Chronic Diseases-National Science and Technology Major Project (2025ZD0552500); Xuanzhu Biopharmaceutical Co., Ltd.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGoel S, Bergholz JS, Zhao JJ (2022) Targeting CDK4 and CDK6 in cancer. Nat Rev Cancer 22(6):356\u0026ndash;372\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsghar US, Kanani R, Roylance R, Mittnacht S (2022) Systematic Review of Molecular Biomarkers Predictive of Resistance to CDK4/6 Inhibition in Metastatic Breast Cancer. JCO precision Oncol 6:e2100002\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMain SC, Cescon DW, Bratman SV (2022) Liquid biopsies to predict CDK4/6 inhibitor efficacy and resistance in breast cancer. Cancer drug Resist (Alhambra Calif) 5(3):727\u0026ndash;748\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsciolla JJ, Wu X, Adamopoulos C, Gavathiotis E, Poulikakos PI (2025) Resistance mechanisms and therapeutic strategies of CDK4 and CDK6 kinase targeting in cancer. Nat cancer 6(1):24\u0026ndash;40\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zhang Q, Sun T, Li H, Cheng Y, Tong Z, Li H, Li W, Wang J, Teng Y et al (2025) An open-label, single-arm, multicenter, phase II trial of bireociclib as monotherapy for heavily pretreated HR-positive, HER2-negative advanced breast cancer patients: BRIGHT-1 trial. Cancer Commun (London England) 45(6):640\u0026ndash;653\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zhang Q, Li H, Tong Z, Ouyang Q, Li H, Teng Y, Wang B, Sun T, Wang J et al (2025) Bireociclib plus fulvestrant for HR+/HER2- advanced female breast cancer progressed on or after endocrine therapy: phase 3 BRIGHT-2 study interim analysis. Nat Commun 16(1):3350\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zhang Q, Li H, Tong Z, Ouyang Q, Li H, Teng Y, Wang B, Sun T, Wang J et al (2025) Abstract CT099: BRIGHT-2 final analysis: A phase III trial of bireociclib plus fulvestrant as second-line endocrine therapy for patients with advanced HR+/HER2-breast cancer. Cancer Res 85(8Supplement2):CT099\u0026ndash;CT099\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndr\u0026eacute; F, Su F, Solovieff N, Hortobagyi G, Chia S, Neven P, Bardia A, Tripathy D, Lu YS, Lteif A et al (2023) Pooled ctDNA analysis of MONALEESA phase III advanced breast cancer trials. Annals oncology: official J Eur Soc Med Oncol 34(11):1003\u0026ndash;1014\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu H, Wang Y, Sa Q, Zhou Y, Ma F, Zhang P, Fan Y, Cai R, Li Q, Lan B et al (2025) Associations Between Dynamic Hematological Indicators and Outcomes in HR-positive, HER2-negative Metastatic Breast Cancer Treated with Bireociclib or Placebo Plus Fulvestrant: Findings from the BRIGHT-2 Trial. Breast :104598\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAi X, Cui J, Zhang J, Chen R, Lin W, Xie C, Liu A, Zhang J, Yang W, Hu X et al (2021) Clonal Architecture of EGFR Mutation Predicts the Efficacy of EGFR-Tyrosine Kinase Inhibitors in Advanced NSCLC: A Prospective Multicenter Study (NCT03059641). Clin cancer research: official J Am Association Cancer Res 27(3):704\u0026ndash;712\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Zhao C, Chang L, Jia R, Liu R, Zhang Y, Gao X, Li J, Chen R, Xia X et al (2019) Circulating tumor DNA analyses predict progressive disease and indicate trastuzumab-resistant mechanism in advanced gastric cancer. EBioMedicine 43:261\u0026ndash;269\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eda Silva JL, Oliveira LJC, de Resende CAA, Reinert T, de Albuquerque LZ, Leite da Silva LF, Mano MS (2025) Understanding and overcoming CDK4/6 inhibitor resistance in HR+/HER2- metastatic breast cancer: clinical and molecular perspectives. Therapeutic Adv Med Oncol 17:17588359251353623\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDempsey N, Chamorro Y, Tolman D, Sandoval-Leon AC, Drusbosky L, Lewis C, Ahluwalia MS, Mahtani RL (2023) Incidence and outcomes among patients with HR+/HER2- metastatic breast cancer (mBC) with co-occurring\u0026thinsp;\u0026lt;\u0026thinsp;i\u0026gt;ESR1\u0026thinsp;and \u003cem\u003ePIK3CA\u003c/em\u003e mutations detected by ctDNA and treated with alpelisib: A retrospective review. 41(16suppl):e13068\u0026ndash;e13068\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzostakowska-Rodzos M, Grzybowska EA, Mysliwy I, Zub R, Jagiello-Gruszfeld A, Rubach M, Konieczna A, Fabisiewicz A (2025) The Combined Assessment of CTC and ESR1 Status in Liquid Biopsy Samples Enhances the Clinical Value of Prediction in Metastatic Breast Cancer. Int J Mol Sci 26(5)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBardia A, Cort\u0026eacute;s J, Bidard FC, Neven P, Garcia-S\u0026aacute;enz J, Aftimos P, O'Shaughnessy J, Lu J, Tonini G, Scartoni S et al (2024) Elacestrant in ER+, HER2- Metastatic Breast Cancer with ESR1-Mutated Tumors: Subgroup Analyses from the Phase III EMERALD Trial by Prior Duration of Endocrine Therapy plus CDK4/6 Inhibitor and in Clinical Subgroups. Clin cancer research: official J Am Association Cancer Res 30(19):4299\u0026ndash;4309\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong NZH, Yap DWT, Ong RJM, Zhao JJ, Chan YH, Tey JCS, Sundar R, Lim JSJ, Dawood SS (2023) Efficacy of Oral SERDs in the treatment of ER+, HER2 - metastatic breast cancer, a stratified analysis of the ESR1 wild type and mutant subgroups. Annals oncology: official J Eur Soc Med Oncol\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurner NC, Swift C, Kilburn L, Fribbens C, Beaney M, Garcia-Murillas I, Budzar AU, Robertson JFR, Gradishar W, Piccart M et al (2020) ESR1 Mutations and Overall Survival on Fulvestrant versus Exemestane in Advanced Hormone Receptor-Positive Breast Cancer: A Combined Analysis of the Phase III SoFEA and EFECT Trials. Clin cancer research: official J Am Association Cancer Res 26(19):5172\u0026ndash;5177\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiu J, Su F, Joshi M, Masuda N, Ishikawa T, Aruga T, Zarate JP, Babbar N, Balbin OA, Yap YS (2023) Potential value of ctDNA monitoring in metastatic HR + /HER2 - breast cancer: longitudinal ctDNA analysis in the phase Ib MONALEESASIA trial. BMC Med 21(1):306\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDieci MV, Vernaci G, Colangelo C, Bria E, Massa D, Di Liso E, Giorgi CA, Giarratano T, Napetti D, Bonomi G et al PIK3CA mutations and first-line outcomes in endocrine-resistant HR+/HER2- metastatic breast cancer: A multicentric real-world study. \u003cem\u003eEuropean journal of cancer (Oxford, England\u003c/em\u003e: (1990)) 2025, 234:116194) 2025, 234:116194\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManich CS, Carey LA, Curigliano G, Harbeck; N, O'Shaughnessy; J, Bidard FC, Casalnuovo ML, Kim S-B, Tokunaga; E, Masuda; N et al (2025) 297O - Imlunestrant (Imlu) with or without abemaciclib (Abema) in advanced breast cancer (ABC): A subgroup analysis in CDK4/6 inhibitor (CDK4/6i)-pretreated patients (pts) from EMBER-3. ESMO Breast Cancer Annual Congress 2970\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSammons SL, Manich CS, Italiano A, Schram AM, Ortega PT, Schott AF, Guerrero A, Aix SP, Nanda R, Wisinski KBet al: Updated efficacy of mutant-selective PI3Kα inhibitor RLY-2608 in combination with fulvestrant in patients with \u0026lt;\u0026thinsp;i\u0026gt;PIK3CA-mutant HR+HER2- advanced breast cancer:ReDiscover trial. 2025, 43(16_suppl):1086\u0026ndash;1086\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen JW, Jacot W, Cort\u0026eacute;s J, Krop IE, Dent S, Harbeck N, De Laurentiis M, Di\u0026eacute;ras V, Im YH, Stout TJ et al (2023) ER+, HER2- advanced breast cancer treated with taselisib and fulvestrant: genomic landscape and associated clinical outcomes. Mol Oncol 17(10):2000\u0026ndash;2016\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWill M, Liang J, Metcalfe C, Chandarlapaty S (2023) Therapeutic resistance to anti-oestrogen therapy in breast cancer. Nat Rev Cancer 23(10):673\u0026ndash;685\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWedam S, Narayan P, Gittleman H, Cheng J, Bhatnagar V, Sabit H, Price LSL, Rahman NA, Chiu HJ, Biel N et al (2025) US Food and Drug Administration Approval Summary: Inavolisib With Palbociclib and Fulvestrant for Endocrine-Resistant, PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative, Locally Advanced or Metastatic Breast Cancer. J Clin oncology: official J Am Soc Clin Oncol 43(28):3123\u0026ndash;3131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, Zhang Z, Chen H, Huang F, Shen L, Tao S, Qian W, Hong H, Pan C, Wang Z et al (2025) Efficacy, Safety, and Biomarkers of Neoadjuvant Dalpiciclib (CDK4/6 inhibitor) plus Aromatase Inhibitors in Operable HER2-Negative Luminal B Breast Cancer: A Prospective, Single-Center, Single-Arm, Phase II Trial (DANCER). \u003cem\u003eMedComm\u003c/em\u003e 6(10):e70402\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuentes-Antr\u0026aacute;s J, Elliott MJ, Main SC, Echelard P, Dou A, Bedard PL, Amir E, Nadler MB, Meti N, Gregorio N et al (2025) Personalized ctDNA monitoring in metastatic HR+/HER2- breast cancer patients during endocrine and CDK4/6 inhibitor therapy. NPJ breast cancer 11(1):74\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMamann A, Pradat Y, Bidard FC, Delaloge S, Cabel L, Faull I, Marques S, Bachelot T, Dalenc F, de la Motte Rouge T et al (2025) Prognostic significance of early on-treatment evolution of circulating tumor DNA in advanced ER-positive/HER2-negative breast cancer. Annals oncology: official J Eur Soc Med Oncol 36(11):1342\u0026ndash;1355\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarrigues L, Pierga JY, Bernard-Tessier A, Bi\u0026egrave;che I, Silveira AB, Michel M, Loirat D, Cottu P, Cabel L, Dubot C et al (2021) Circulating tumor DNA as a dynamic biomarker of response to palbociclib and fulvestrant in metastatic breast cancer patients. Breast cancer research: BCR 23(1):31\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSonke GS, van Ommen-Nijhof A, Wortelboer N, van der Noort V, Swinkels ACP, Blommestein HM, Guerrero Paez C, Mol L, Beeker A, Beelen K et al (2024) Early versus deferred use of CDK4/6 inhibitors in advanced breast cancer. Nature 636(8042):474\u0026ndash;480\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJongbloed EM, Wortelboer N, de Weerd V, Beaufort CM, Ruigrok-Ritstier K, Van MN, Kraan J, van Zweeden AA, van der Padt-Pruijsten A, Hamming LC et al (2025) Early versus deferred use of CDK4/6 inhibitors in advanced breast cancer: circulating tumor DNA analysis of a randomized phase 3 trial. Nat Med\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeselsohn R, Fu J, Ren Y, Mahtani R, Ma C, DeMichele A, Cristofanilli M, Meisel J, Miller KD, Abdou Y et al (2025) Circulating tumor DNA mutational landscape and dynamics after progression on a CDK4/6 inhibitor in the PACE phase II trial for metastatic HR-positive/HER2-negative breast cancer. ESMO open 10(8):105506\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Leary B, Hrebien S, Morden JP, Beaney M, Fribbens C, Huang X, Liu Y, Bartlett CH, Koehler M, Cristofanilli M et al (2018) Early circulating tumor DNA dynamics and clonal selection with palbociclib and fulvestrant for breast cancer. Nat Commun 9(1):896\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Leary B, Cutts RJ, Huang X, Hrebien S, Liu Y, Andr\u0026eacute; F, Loibl S, Loi S, Garcia-Murillas I, Cristofanilli M et al (2021) Circulating Tumor DNA Markers for Early Progression on Fulvestrant With or Without Palbociclib in ER+ Advanced Breast Cancer. J Natl Cancer Inst 113(3):309\u0026ndash;317\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolaney SM, Toi M, Neven P, Sohn J, Grischke EM, Llombart-Cussac A, Soliman H, Wang H, Wijayawardana S, Jansen VM et al (2022) Clinical Significance of PIK3CA and ESR1 Mutations in Circulating Tumor DNA: Analysis from the MONARCH 2 Study of Abemaciclib plus Fulvestrant. Clin cancer research: official J Am Association Cancer Res 28(8):1500\u0026ndash;1506\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CDK4/6 inhibitor, advanced breast cancer, ctDNA, bireociclib, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-8242447/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8242447/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBireociclib, a novel cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor, has demonstrated efficacy in hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer. This exploratory analysis aimed to identify biomarkers of response and resistance to bireociclib through dynamic circulating tumor DNA (ctDNA) profiling.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn this exploratory analysis of the phase Ⅲ BRIGHT-2 trial, plasma samples were collected at baseline, on-treatment, and end-of-treatment from patients randomized 2:1 to receive bireociclib plus fulvestrant or placebo plus fulvestrant. ctDNA was extracted and profiled using a 1,021-gene targeted sequencing panel. Somatic single-nucleotide variants, insertions/deletions, and copy number alterations were identified, and the molecular tumor burden index (mTBI) was calculated. Associations between baseline and longitudinal ctDNA features and clinical outcomes were assessed using Kaplan\u0026ndash;Meier estimates, Cox regression, stratified log-rank tests, and treatment\u0026ndash;biomarker interaction analyses with false discovery rate adjustment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 596 plasma samples were successfully sequenced across three time points. The most frequently altered genes were \u003cem\u003ePIK3CA\u003c/em\u003e (48%), \u003cem\u003eTP53\u003c/em\u003e (37%), and \u003cem\u003eESR1\u003c/em\u003e (23%), defining the mutational landscape of East Asian HR+/HER2\u0026thinsp;\u0026minus;\u0026thinsp;advanced breast cancer. Baseline ctDNA negativity or low mTBI, together with on-treatment ctDNA clearance or mTBI reduction, identified patients most likely to benefit from bireociclib. Within the bireociclib-treated cohort, \u003cem\u003ePIK3CA\u0026ndash;ESR1\u003c/em\u003e co-mutation was associated with significantly prolonged PFS (p\u0026thinsp;=\u0026thinsp;0.003) and OS (p\u0026thinsp;=\u0026thinsp;0.024), and longitudinal clearance of these mutations conferred outcomes exceeding those of persistently negative patients. Mechanisms of acquired resistance to bireociclib were heterogeneous, involving activation of the PI3K/AKT pathway, amplifications of \u003cem\u003eFGFR1\u003c/em\u003e, \u003cem\u003eMDM2\u003c/em\u003e, and \u003cem\u003eMYC\u003c/em\u003e, as well as upregulation of MAPK signaling.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBoth baseline ctDNA features and on-treatment ctDNA dynamics demonstrated clinically relevant predictive value for treatment response and survival outcomes of bireociclib. These findings provide a molecular framework for patient stratification and highlight dynamic ctDNA monitoring as a tool to guide precision use of CDK4/6 inhibitors.\u003c/p\u003e","manuscriptTitle":"Dynamic Monitoring and Identification of Reliable Biomarkers to Predict Efficacy of Bireociclib and Fulvestrant: An Exploratory ctDNA Analysis of the BRIGHT-2 Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 14:07:39","doi":"10.21203/rs.3.rs-8242447/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"292b2303-b874-414f-8708-43bb5221967a","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62577038,"name":"Health sciences/Oncology/Cancer/Breast cancer"},{"id":62577039,"name":"Health sciences/Oncology/Cancer/Tumour biomarkers"}],"tags":[],"updatedAt":"2026-02-27T14:07:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 14:07:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8242447","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8242447","identity":"rs-8242447","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}