PURPOSE:Gedatolisib potently targets all four class I PI3K isoforms and mTORC1 and mTORC2 to comprehensively block the PI3K/AKT/mTOR pathway and has shown compelling activity in early clinical trials with palbociclib and fulvestrant. METHODS:This phase III randomized trial (VIKTORIA-1; ClinicalTrials.gov identifier: NCT05501886) evaluated the efficacy of gedatolisib-based therapy, comparing gedatolisib, palbociclib, and fulvestrant (gedatolisib triplet) and gedatolisib plus fulvestrant (gedatolisib doublet) with fulvestrant monotherapy in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative (HER2-), PIK3CA wild-type (WT) advanced breast cancer. Eligible patients had disease progression during or after CDK4/6 inhibitor and aromatase inhibitor treatment. Comparison of progression-free survival as assessed by blinded independent central review for gedatolisib triplet versus fulvestrant and gedatolisib doublet versus fulvestrant was the primary objective. RESULTS:A total of 392 patients were randomly assigned 1:1:1. The median study follow-up was 10.1 months. The median progression-free survival was 9.3 months in the gedatolisib-triplet group, 2.0 months in the fulvestrant group (hazard ratio [HR] for progression or death, 0.24 [95% CI, 0.17 to 0.35]; P < .001), and 7.4 months in the gedatolisib-doublet group (HR, 0.33 [95% CI, 0.24 to 0.48]; P < .001 v fulvestrant). Grade ≥3 treatment-related adverse events (TRAEs) reported in the gedatolisib-triplet and gedatolisib-doublet groups, respectively, included neutropenia (62.3%, 0.8%), stomatitis (19.2%, 12.3%), rash (4.6%, 5.4%), hyperglycemia (2.3%, 2.3%), and diarrhea (1.5%, 0.8%). Study treatment discontinuation because of TRAEs was reported in 2.3% (triplet) and 3.1% (doublet) of patients. CONCLUSION:The addition of gedatolisib to fulvestrant, with or without palbociclib, significantly reduced the risk of disease progression or death in patients with hormone receptor-positive/HER2-, PIK3CA WT advanced breast cancer.

The computer analysis of Whole Slide Images (WSIs) has become increasingly prevalent in pathology-based diagnosis, although their analysis still presents considerable challenges due to the voluminous nature of the data. To address this issue, Multiple Instance Learning (MIL) has emerged as a viable approach in which WSIs are partitioned into tiles for processing. Nevertheless, previous MIL methodologies inadequately capture the essential spatial context between tiles, which is imperative for accurate diagnosis across various diseases. In parallel, approaches based on adapting Convolutional Neural Network (CNN) architectures to the high-resolution setting have also emerged. However, these methods are generally GPU memory-intensive, restricting the architecture’s size and scalability. In this paper, we present a novel framework, SparseXceptionMIL (SparseXMIL), aiming to enhance the GPU efficiency of spatial interaction modeling within WSI data through the introduction of a multidimensional sparse image representation and a novel pooling operator. By integrating sparse convolutions within the Xception architecture, this operator enables efficient spatial information modeling at both local and global scales. Empirical evaluations conducted on various classification tasks, encompassing subtyping for breast and lung carcinomas and predicting abnormalities in the DNA damage response in breast cancer WSIs, demonstrate that our approach outperforms state-of-the-art MIL methods in tasks where spatial context is important, and offers a better trade-off in terms of GPU memory requirements compared to CNN-based methods. These results underscore the potential of sparse convolutional architectures for efficient and scalable WSI analysis. Our experiments’ source code is available at https://github.com/loic-lb/SparseXMIL.

Primary resistance to lirafugratinib in FGFR inhibitor-naïve patients.

Radiopharmaceutical therapy (RPT), the administration of a radioactive element coupled with a targeting vector, is one of the most promising innovations in oncology, supported by clinical trials. A theranostic approach—the pairing of diagnostic and therapeutic RPTs sharing the same target—facilitates selective delivery of therapeutic radiation to cancer cells. Its advantages and limitations are determined by the molecular targeting mechanisms employed, as well as the types of ionising radiation emitted. Therefore, understanding the biology of cell-surface targets and molecular mechanisms governing target expression in cancers is critical to the development and clinical use of these agents. This review provides an overview of the latest advances in the application of targeted RPTs within oncology, as discussed at the Fourth Transatlantic Exchange in Oncology, a hybrid conference held in March 2025 that brought together experts from Dana-Farber Cancer Institute (Boston, MA, USA) and Gustave Roussy (Paris, France). Key topics included the targeting of prostate-specific membrane antigen (PSMA) for both imaging and therapy purposes in prostate cancer. In particular, PSMA-based imaging—encompassing both positron emission tomography (PET) and single-photon emission computed tomography (SPECT)—has become a fundamental tool for patient selection, evaluation of treatment response, and personalisation of therapeutic strategies. While theranostic approaches continue to pose challenges, they should increasingly enable improved treatment selection for patients with cancer, and more effective prediction of response and toxicity. Lessons learned from PSMA may apply to other emerging theranostic targets in prostate cancer and other tumour types, expanding the future potential of RPT applications. Beyond current achievements, new molecules and intensive translational research programs may optimise, potentiate and direct RPT. The impact of the expanding use of RPTs on healthcare systems was also addressed, defining strategies to overcome barriers and provide broader access to innovations in RPT in both clinical and research settings. Physicians now recognise that an improved understanding of the molecular differences and biology of treatment targets on cells can have therapeutic implications in patients with cancer. Radiopharmaceuticals are radioactive drugs that can be used for certain imaging tests and for treating specific types of cancer. The term ‘theranostics’ is a concept that includes the use of both diagnostic and therapeutic radio-pharmaceuticals with the same target. Imaging, such as positron emission tomography, is initially performed using a diagnostic radiopharmaceutical to determine if the target of interest is sufficiently present to proceed with the therapeutic radiopharmaceutical. This review paper provides an overview of the latest advances in the application of targeted radiopharmaceutical therapies within oncology in prostate and beyond prostate cancer, as discussed at the Fourth Transatlantic Exchange in Oncology, which brought together leading experts from Dana-Farber Cancer Institute, Boston, USA, and Gustave Roussy, Paris, France, in March 2025. Theranostic approaches continue to evolve rapidly. Imaging remains a cornerstone—enabling precise patient selection, real-time monitoring of treatment response, and personalisation of therapeutic strategies. Advances in target discovery, novel radiopharmaceutical design, and translational research programs are opening new avenues to optimise efficacy, mitigate toxicity, and expand indications to a growing number of tumour types. Physicians are increasingly convinced that these combined advances will transform the management of patients with cancer. To fully realise this potential, healthcare systems need to be more prepared to provide access to innovations in radiopharmaceutical therapy in both clinical and research settings.

Clinical and molecular evolution of patient ST3549.

BACKGROUND:Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS:In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS:Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION:Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING:None.

Clinical and molecular characteristics of FGFR inhibitor-naïve patients experiencing acquired resistance to lirafugratinib with on-target alterations, or unknown mechanisms (ST5822).

In vivo evaluation of lirafugratinib and futibatinib in ST4193 PDX.

550 Background: Patients with node-positive HR+/HER2- early breast cancer are at high risk for relapse within 5 years of diagnosis, suggesting the potential need for treatment escalation. However, it is unclear which patients may experience worse recurrence-free outcomes and thus benefit from additional therapy. Ataraxis Breast (ATX) is an artificial intelligence (AI) test that integrates clinicopathologic variables with features extracted from whole-slide H&E images to estimate recurrence risk. Here, we perform a secondary analysis of the control arm of the UNIRAD trial, evaluating the ability of ATX to identify patients treated with standard-of-care therapy who may be candidates for treatment escalation. Methods: Clinical information and scanned H&E slides were sourced for 365 patients enrolled in the UNIRAD trial who were randomized to the control arm (standard-of-care therapy). ATX scores were generated using a locked model with pre-specified thresholds. No patients from UNIRAD were used in the training of ATX. Recurrence-free interval (RFI) was used as the primary endpoint. Kaplan-Meier estimators were used to predict the probability of meeting the RFI endpoint. To quantify relative differences in the hazard of experiencing an event contributing to the RFI endpoint associated with ATX scores, Cox proportional hazards models were fitted, from which hazard ratios (HRs) were estimated. The discriminative performance of ATX was evaluated using C-index. Results: Of the 365 patients randomized to the control arm of the UNIRAD trial with H&E slides available, 163 (45%) were classified as ATX low risk, and 202 (55%) as ATX high risk. Patients classified as ATX high risk had lower Kaplan-Meier-estimated probability of meeting the RFI endpoint (77%, 95% CI = 70-83%) than patients classified as ATX low risk (93%, 95% CI = 88-97%). Consistent with these findings, when modeled as a continuous variable, higher ATX scores were associated with a significantly higher hazard of an RFI-contributing event (HR = 1.57, 95% CI = 1.29-1.99, p-value < 0.001) and demonstrated strong discriminatory performance (C-index = 0.66, 95% CI = 0.59-0.72). This association remained significant after controlling for receipt of neoadjuvant therapy, tumor, and nodal stage (HR = 1.53, 95% CI = 1.05-2.23, p = 0.027). Conclusions: In the clinically homogenous UNIRAD trial cohort of patients with node-positive HR+/HER2- early breast cancer, ATX high risk patients treated with standard-of-care therapy had a significantly increased hazard of an RFI-contributing event. These findings suggest that AI-based risk stratification identifies biologically high risk patients who may derive benefit from adjuvant treatment escalation. Clinical trial information: NCT01805271 .

BACKGROUND:Adjuvant chemotherapy for hormone receptor-positive (HR+) breast cancer relies on taxanes, but existing tests do not identify which patients benefit from them. The SETER/PR index, a measure of endocrine-related transcriptional activity in HR + tumors, recently predicted benefit from paclitaxel when low (<0.75), but not for anthracycline-based therapy. We tested whether SETER/PR could predict benefit from docetaxel in node-positive, HR + patients enrolled in the PACS-01 trial (docetaxel after fluorouracil-epirubicin-cyclophosphamide (3FEC+3D) versus 6FEC). PATIENTS AND METHODS:SETER/PR index and Recurrence Score (RS) were obtained for 490 patients. SETER/PR was quantified using the QuantiGene Plex assay from RNA remaining after RS testing. Pre-specified analyses assessed SETER/PR as a continuous variable and using the predefined <0.75 cut point, as well as continuous RS and the >25 cut point. The primary endpoint was distant recurrence-free interval (DRFI). Predictive value was assessed using Cox models including biomarker, treatment arm, and interaction term. RESULTS:Continuous SETER/PR demonstrated significant interaction with treatment on DRFI (Pinteraction = 0.028), whereas predefined <0.75 cut point was not predictive (Pinteraction = 0.668). Exploratory analyses identified a cut point at 1.50 (Pinteraction = 0.013): patients with SETER/PR ≥ 1.50 had worse outcomes with 3FEC+3D versus 6FEC (HR 3.16, 95%CI 1.28-7.85), while outcomes were similar between arms when SETER/PR < 1.50 (HR 0.83, 95%CI 0.51-1.35). RS did not predict differential benefit, either continuously (Pinteraction = 0.670) or at the >25 threshold (Pinteraction = 0.534). CONCLUSION:Including sequential docetaxel (3FEC+3D) was less effective than continued anthracycline chemotherapy (6FEC) when breast cancer had high endocrine-related transcriptional activity (i.e., SETER/PR index ≥1.50). TRIAL REGISTRATION:PACS-01.

PURPOSE:The use of reversible fibroblast growth factor receptor 2 (FGFR) inhibitors leads to the emergence of "undruggable" FGFR2 kinase domain mutations, hampering sequential treatment strategies. Lirafugratinib and futibatinib are irreversible FGFR inhibitors with the most promising clinical activity against FGFR2-driven tumors. EXPERIMENTAL DESIGN:We characterized resistance to lirafugratinib with circulating tumor DNA, tissue whole-exome sequencing, and bulk RNA sequencing in 30 patients with FGFR2-driven cancers, treated in the phase I/II ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy. RESULTS:Among the 30 patients included, 18 (60%) had intrahepatic cholangiocarcinoma and 12 (40%) had other tumor types. Twenty-two patients (73%) were FGFR inhibitor-naïve. Among those experiencing primary resistance to lirafugratinib, we identified potential resistance mechanisms in five of six pretreatment samples. Patients with acquired lirafugratinib resistance manifested an unprecedented emergence of FGFR2 mutations in the M538 and/or L618 residues of the kinase domain, documented in 11 of 16 cases (69%). Compared with futibatinib resistance, FGFR2 molecular brake (N550) and gatekeeper (V565) mutations were rare. Leveraging the spectrum of FGFR2 kinase domain mutations at resistance to lirafugratinib and futibatinib, respectively, we identified the complementarity of the two irreversible inhibitors. On the basis of viability assays in FGFR2::BICC1-dependent Ba/F3 models and in vivo studies on patient-derived xenografts, we propose treatment sequences with the two agents. After lirafugratinib progression, three patients received futibatinib and experienced prolonged disease response. CONCLUSIONS:The complementary activity of lirafugratinib and futibatinib against FGFR2 kinase domain mutations supports their sequential use when precise resistance mutations are detected in patients.

Differential impact on intracellular signaling exerted by lirafugratinib and futibatinib in FGFR2::BICC1 Ba/F3 with a kinase domain with no mutations (wild-type, WT), and with M538I or L618F mutations.

1012 Background: T-DXd is approved for adult pts with HER2+ mBC who received a prior anti-HER2–based regimen, or as 1L therapy when given in combination with pertuzumab (P). DESTINY-Breast07 (NCT04538742) is a Phase 1b/2, open-label, platform study exploring the safety, tolerability, and antitumor activity of T-DXd ± other anticancer agents in HER2+ mBC. 1L T-DXd ± P recently showed encouraging clinical activity and safety profiles consistent with previous reports. D, an anti-PD-L1 antibody, has shown efficacy in combination with T-DXd in HER2-low, hormone receptor (HR)–negative mBC. As part of the DESTINY-Breast07 final analysis, here we report the dose-expansion phase for T-DXd + D as a 1L treatment in HER2+ mBC. Methods: Pts had locally assessed HER2+ (IHC 3+ or IHC 2+/ISH+) mBC. A disease-free interval of ≥12 months (mo) from (neo)adjuvant therapy was required; no prior therapy for mBC was allowed. Pts were stratified by HR (positive vs negative), disease (recurrent vs de novo), and PD-L1 status (positive vs negative; positive defined as ≥1% IHC). Pts received T-DXd 5.4 mg/kg IV, in combination with D 1120 mg IV, every 3 weeks. Primary endpoints were safety and tolerability; secondary endpoints included confirmed ORR (cORR), duration of response (DOR) and progression-free survival (PFS) per RECIST 1.1 by investigator, time to progression on subsequent therapy or death (PFS2) by investigator, and overall survival (OS). Results: At data cutoff (DCO) (January 31, 2025), 64 pts were randomized to the T-DXd + D module, and 63 received treatment. Median follow up was 30.1 mo; median total treatment duration was 26.7 mo for T-DXd and 24.6 mo for D. Efficacy results are given in the Table. The most common adverse events (AEs) were nausea (79.4%), vomiting (46.0%), neutropenia (46.0% by grouped term [GT]), anemia (44.4% by GT), and fatigue (38.1%). Grade ≥3 AEs occurred in 58.7% (n=37/63) and serious AEs in 30.2% (n=19/63) of pts. There were two deaths due to AEs (3.2%): one pt with neutropenia and septic shock and one pt with sepsis. Adjudicated drug-related interstitial lung disease (ILD)/pneumonitis events occurred in 11 (17.5%; Grade 1, n=1; Grade 2, n=8; Grade 3, n=2) pts. Additional data by subgroups (stratification factors and biomarkers) will be presented. Conclusions: Encouraging clinical activity was seen for T-DXd + D as a 1L treatment for HER2+ mBC. Safety profiles were consistent with the known profiles for each therapy, with no fatal ILD events. These promising results provide a rationale for further investigation of this treatment combination. Clinical trial information: NCT04538742 . T-DXd + D (n=64) cORR (80% CI), % 82.8 (75.2, 88.8) mDOR* (Q1–Q3), mo 36.1 (23.3, NE) mPFS* (80% CI), mo 37.7 (35.1, NE) PFS rate at 24 mo (80% CI), % 75.5 (67.2, 82.0) mOS (80% CI), mo NE (NE, NE) mPFS2 (80% CI), mo NE (NE, NE) *Most pts were censored at DCO; m, median; NE, not evaluable; Q, quartile.

PURPOSE:Establish the safety, tolerability, and preliminary activity of trastuzumab deruxtecan (T-DXd) in combination with other anticancer therapies in human epidermal growth factor receptor 2 (HER2)-low metastatic breast cancer (mBC). PATIENTS AND METHODS:DESTINY-Breast08 was a two-part, open-label, multicenter, phase Ib study. Patients with locally confirmed HER2-low mBC received T-DXd plus capecitabine, durvalumab + paclitaxel, capivasertib, anastrozole, or fulvestrant. Eligibility criteria for hormone receptor status varied across modules and between study parts. Primary objectives were safety/tolerability and determining recommended phase II doses (RP2D); secondary endpoints included objective response rate (ORR; per investigator). RESULTS:In the dose-finding phase, 37 patients were assigned to a module. RP2Ds were determined for T-DXd plus capecitabine, capivasertib, anastrozole, or fulvestrant. For strategic reasons, T-DXd + durvalumab + paclitaxel was not pursued beyond the dose-finding phase (n = 3). In the dose-expansion phase, 101 patients were assigned to a module. For T-DXd + capecitabine, grade ≥3 adverse events (AE) occurred in 55% (11/20) of patients, and the ORR was 60%. For T-DXd + capivasertib, grade ≥3 AEs occurred in 67.5% (27/40) of patients, and the ORR was 60%. For T-DXd + anastrozole, grade ≥3 AEs occurred in 47.6% (10/21) of patients, and the ORR was 71.4%. For T-DXd + fulvestrant, grade ≥3 AEs occurred in 55% (11/20) of patients, and the ORR was 40%. Adjudicated drug-related interstitial lung disease/pneumonitis events were reported for T-DXd + capecitabine (3/20; grade 2, n = 2; grade 5, n = 1), T-DXd + capivasertib (8/40; all grade ≤2), and T-DXd + fulvestrant (5/20; all grade 2). CONCLUSIONS:Safety results were generally consistent with known individual profiles for T-DXd and combination drugs. T-DXd plus capecitabine, capivasertib, anastrozole, or fulvestrant demonstrated preliminary clinical activity in patients with HER2-low mBC.

Pregnancy-Associated Breast Cancer (PABC) accounts for pregnancy-related breast cancer (PrBC), occurring during pregnancy and the first postpartum year, and postpartum breast cancer (PPBC), arising up to 5-10 years after childbirth. It represents an increasingly oncological challenge as delayed childbearing trends extend maternal reproductive age. Occurring in approximately 1:3000 pregnancies, PABC accounts for 0.2-3.8 % of all breast cancer cases. PABC is often associated with aggressive clinic-biological characteristics, including higher prevalence of triple-negative subtypes, increased lymph node involvement, and more frequent advanced-stage presentation compared to age-matched non-pregnant controls. The complex mammary microenvironment during pregnancy, lactation, and postpartum involution undergoes extensive hormonal-driven remodeling that creates a biphasic landscape, initially providing a permissive environment for carcinogenesis while conferring long-term protective effects. The molecular mechanisms underlying this transformation remain incompletely understood and represent an active area of investigation. Molecular profiling of PABC reveals enhanced proliferative signaling pathways, metabolic reprogramming, tumor-promoting inflammatory responses, and compromised DNA damage repair mechanisms. While PABC shares similar genomic architecture with non-pregnancy-associated breast cancers, distinct gene expression signatures have been identified that may contribute to its aggressive phenotype. This comprehensive review examines the physiological breast changes occurring throughout the reproductive cycle and their relationship to PABC carcinogenesis. We analyze the molecular profile and clinicopathological features that distinguish PABC from conventional breast cancer, while addressing the therapeutic challenges posed by fetal safety considerations. Additionally, we evaluate the safety profiles of novel therapeutic agents during pregnancy and lactation, highlighting the critical need for new pregnancy-compatible treatment strategies.

Natural killer (NK) cells are effectors of innate antitumor immunity, yet their therapeutic potential in solid tumors remains largely unrealized. Breast cancer exemplifies this paradox: NK cells are present in circulation and detectable within tumors, but their cytotoxic activity is limited. Recent advances in single-cell and spatial profiling reveal that NK-cell failure in breast cancer does not result from simple immune absence but from multilayered constraints imposed by the tumor ecosystem. Soluble mediators, metabolic pressures, stromal architecture, and suppressive immune networks reprogram NK-cell identity and uncouple activation from cytotoxicity. Understanding how these constraints shape NK-cell states reframes breast cancer as a model of innate immune dysfunction and highlights new opportunities to reestablish NK-cell function through immunotherapies.

INTRODUCTION:Breast cancer in young adults (YA) aged 20-40 years has distinct clinical and biological traits compared with older patients. This study evaluated the genomic landscape of metastatic breast cancers (MBC) among YA. METHODS:Patients with MBC enrolled in the STING molecular profile platform (NCT04932525) between 2021 and May 2023 were included. Clinical and genomic features were analyzed by age (≤40 vs > 40 years). Tumor profiling used the FoundationOne Liquid CDx assay (324 genes) at baseline or later in the disease course. Variant frequencies were compared across age groups. RESULTS:Of 432 eligible patients, 68 (16 %) were YA. Among 37 YA with hormone receptor positive (HR+) BC, frequent alterations included TP53 (39 %), ESR1 (27 %), PIK3CA (25 %), FGFR3 (18 %), FGFR4 (18 %), FGFR19 (18 %), CCND1 (18 %). Compared with older patients, YA with HR + tumors had fewer RB1 (7 % vs 8 %; p = 0.03) and PIK3CA (25 % vs 31 %; p = 0.03) alterations. Among 28 YA with triple negative BC, the most common alterations were TP53 (100 %), PTEN (26 %), BRCA1 (22 %), RB1 (17 %). PTEN mutations were more frequent among YA with TNBC than older patients (26 % vs 8 %; p = 0.009). Tiers I-III genomic alterations according to the ESMO scale of clinical actionability (ESCAT) were identified in 54 YA (79 %), including 48 tiers I-II alterations comprising ESR1 (n = 12), gBRCA1/2 (n = 11), PIK3CA (n = 13). CONCLUSIONS:ESCAT tiers I-III alterations were reported in 79 % YA with MBC which supports the role of molecular profiling in YA. The differences detected in the genomic profiles of YA with BC and older patients may allude to potential different underlying disease biology.

554 Background: The 21-gene recurrence score (RS) is a foundational tool for risk-stratifying HR+/HER2- early breast cancer (EBC). However, clinical outcomes vary within RS categories. RlapsRisk BC (RR), an AI pathology-based test, integrates features from H&E-stained whole-slide images with clinical data (age, tumor size, nodal status) and was developed using 7 retrospective cohorts totaling 6,039 patients. We evaluated the clinical validity of RR and its histology-only component (RR-H) beyond RS and standard clinicopathologic factors. Methods: The clinical validity of RR was established through a validation program of 4 cohorts and over 8,521 patients across diverse geographic regions and laboratory settings. This included 3 international cohorts (n=933) and a prospective-retrospective analysis of the TAILORx trial, where RR-H was evaluable in 7,585 (97.5% of analyzable patients). The primary endpoint was distant recurrence-free interval (DRFI). In TAILORX, we assessed the additive value of the RR-H score to a base model (composed of age, tumor size, histological grade and RS) using Cox proportional hazards models and C-index comparison. Results: Across international validation cohorts (median follow-up 7.5 years, 9,8% DRFI events), RR successfully stratified patients (HR=4.91; 95% CI: 3.13-7.71; p < 0.00001), and identified a low-risk population with a 97.5% (95% CI: 95.8%-98.5%) 5-year DRFI rate. In the TAILORx population (n=7,584), the RR-H score was a highly significant independent predictor of DRFI. Incorporating RR-H as a continuous variable to the base model (including RS) significantly increased the C-index from 0.6730 to 0.7007 (p < 0.0001). The estimated HR for a 1-point difference in RR-H was 1.108 (95% CI: 1.078-1.138; p < 0.0001). When analyzed by quartiles, patients in the highest risk group (Q4) exhibited a significantly higher risk of distant recurrence compared to the lowest risk group (Q1) HR= 2.656 (95% CI: 2.003-3.522). Concordance analysis revealed that RR-H is independent of stromal TILs (R 2 =0.01). While RR-H correlated with increasing histological grade, substantial distribution overlap confirms intra-grade prognostic granularity. Furthermore, RR-H distributions were consistent across ILC and non-NLC. Conclusions: RR demonstrated robust and reproducible prognostic value across 8520 patients from diverse populations and settings establishing its clinical validity. Additional findings on TAILORx demonstrate that RR-H provides significant, independent prognostic value that complements existing prognostic tools (including genomic assays and clinicopathological factors), suggesting that integrating AI-pathology can refine precision risk assessment, and thus optimize adjuvant treatment in HR+ HER2- EBC.

Abstract The aim of this study was to assess return to work (RTW) after breast cancer (BC) by baseline employment status. Using data from the CANTO cohort (NCT01993498), we examined RTW among women below age 57 at BC diagnosis 2 and 4 years after BC diagnosis. We also assessed continuous work between years 2 and 4 post-diagnosis. Poisson regression models investigated associations between baseline employment (self-employed vs. employees) and RTW outcomes, adjusting for clinical, sociodemographic, and work-related factors and quality of life. We used education (above high school; high school or lower) as a proxy to further distinguish between white collar self-employees vs. blue collar self-employees (vs. employees). About 8% of women were self-employed at diagnosis. RTW was slightly higher among the self-employed compared to employees 2 years (N = 3178; PR = 1.04, 95%CI 0.98–1.10) and 4 years after diagnosis (N = 2329; PR = 1.05, 0.99–1.12). This effect was limited to white collar self-employed women. Among those who returned to work 2 years after diagnosis (N = 1683), self-employed women showed a 1.15 (1.01–1.31) higher prevalence of continuous work until year 4 post-diagnosis than employees. Self-employed women do not strongly differ from employees when assessing RTW at specific time points, however once returned to work, they experience fewer work interruptions than employees. This was observed in adjusted models, showing the intrinsic importance of job status in the RTW process. These findings highlight the importance of viewing RTW as an ongoing process, in order to provide appropriate and sustained support.

The retinoblastoma protein (Rb) is a tumour suppressor best known for repressing E2F transcription factors and halting cell cycle progression1. In hormone receptor-positive (HR+) breast cancer, CDK4/6 inhibitors activate Rb by preventing its phosphorylation, forming a key component of current endocrine therapy regimens2. How pharmacologically activated Rb remodels chromatin and influences transcription beyond cell cycle arrest remains poorly understood. Here we show that CDK4/6 inhibition induces redistribution of hypophosphorylated Rb to promoters and enhancers. Although Rb predictably binds to cell cycle gene promoters to repress transcription, at other sites, it unexpectedly promotes expression of oestrogen-responsive genes by integrating into oestrogen receptor (ER)-rich transcriptional hubs. CDK4/6 inhibition enhances ER target gene expression in breast cancer cells, patient-derived xenografts and clinical HR+ breast cancer samples in an Rb-dependent manner. This reprogramming is mediated in part by KDM5A, whose interaction with Rb contributes to gene regulation at these loci. Critically, components of this Rb-driven ER transcriptional program are pro-proliferative. In endocrine-sensitive tumours, this effect can be neutralized with anti-oestrogen therapy, explaining therapeutic synergy. In endocrine-resistant settings such as ESR1-mutant breast cancer, the program persists, limiting the therapeutic efficacy of CDK4/6 inhibition. These findings reframe Rb as a dual-function transcriptional regulator that, although enforcing cell cycle arrest, can also activate programs that counteract its tumour suppressor function.