Tamoxifen (TAM) remains the adjuvant therapy of choice for pre-menopausal women with ERα-positive breast cancer. Resistance and recurrence remain, however, a major challenge with many women relapsing and subsequently dying. The insulin-like growth factor (IGF) axis is involved in breast cancer pathogenesis and progression to endocrine resistant disease, but there is very little data on the expression and potential role of IGF-binding proteins (IGFBP) during acquisition of the resistant phenotype. The aim of this study was to determine the expression and functional role of IGFBP-2 and -5 in the development of TAM resistance (TamR) in vitro and to test retrospectively whether they were predictive of resistance in a tissue microarray of 77 women with primary breast cancers who relapsed on/after endocrine therapy and 193 who did not with long term follow up. Reciprocal expression of IGFBP-2 and IGFBP-5 was observed at both mRNA and protein level in TamR cells. IGFBP-2 expression was increased by 10-fold while IGFBP-5 was decreased by 100-fold, compared to TAM-sensitive control cells. shRNA-mediated silencing of IGFBP-2 in TamR cells restored TAM sensitivity suggesting a causal role for this gene in TamR. While silencing of IGFBP-5 in control cells had no effect on TAM sensitivity, it significantly increased the migratory capacity of these cells. Quantitative image analysis of immunohistochemical data failed, however, to demonstrate an effect of IGFBP2 expression in endocrine-relapsed patients. Likewise, IGFBP-2 and IGFBP-5 expression failed to show any significant associations with survival either in patients relapsing or those not relapsing on/after endocrine therapy. By contrast, in silico mining of a separate published dataset showed that in patients who received endocrine treatment, loss of expression of IGBP-5 was significantly associated with worse survival. Overall these data suggest that co-ordinated and reciprocal alteration in IGFBP-2 and −5 expression may play a role in the acquisition of endocrine resistance.

CIP2A is emerging as an oncoprotein overexpressed commonly across many tumours and generally correlated with higher tumour grade and therapeutic resistance. CIP2A drives an oncogenic potential through inhibiting protein phosphatase 2A, stabilizing MYC, and promoting epithelial-to-mesenchymal transition, although further biological mechanisms for CIP2A are yet to be defined. CIP2A protein expression was studied by immunohistochemistry in oestrogen receptor-positive primary breast cancers (n = 250) obtained from the Leeds Tissue Bank. In total, 51 cases presented with a relapse or metastasis during adjuvant treatment with tamoxifen and were regarded as tamoxifen resistant. CIP2A expression was scored separately for cytoplasmic, nuclear, or membranous staining, and scores were tested for statistically significant relationships with clinicopathological features. Membranous CIP2A was preferentially expressed in cases who experienced a recurrence during tamoxifen treatment thus predicting a worse overall survival (log rank = 8.357, p = 0.004) and disease-free survival (log rank = 21.766, p < 0.001). Cox multivariate analysis indicates that it is an independent prognostic indicator for overall survival (hazard ratio = 4.310, p = 0.013) and disease-free survival (hazard ratio = 5.449, p = 0.002). In this study, we propose the assessment of membranous CIP2A expression as a potential novel prognostic and predictive indicator for tamoxifen resistance and recurrence within oestrogen receptor-positive breast cancer.

e12517 Background: HER2 amplification or overexpression is negative prognostic factor that occurs in circa 15% of primary invasive breast cancers, with positive results opening up eligibility for HER2 targeted (e.g. trastuzumab) combination therapy. However, HER2 intratumoral heterogeneity has been proposed as an explanation for the development of resistance to anti-HER2 targeted therapy. The aim of this retrospective study was to test the prognostic value of a HER2 heterogeneity index on ER+ breast cancer H&E whole slide images (WSIs). Methods: ER+ breast cancers slides ( n=60 cases) of known HER2 status (immunohistochemically assessed over the 0 to 3+ range, with HER2 2+ borderline cases validated by fluorescence in situ hybridization) were digitized on an Aperio AT3 scanner. A subset of these patients ( n=29) was accounted for by HER2 amplified/borderline cases. A HER2 heterogeneity index was tested and compared to standard clinical HER2 status in these cases and related to progression free survival (PFS). Survival analyses were performed using Kaplan-Meier (KM; with median cut-off) and Cox Proportional Hazards (as a continuous variable) models. Results: The HER2 heterogeneity index performed better in terms of prognostication than clinical HER2 status alone in relation to PFS (KM P=0.019; HR 8.06, P=0.01 vs. KM P=0.02; HR 6.75, P=0.048). These differences were more pronounced in the HER2 amplified/borderline tumor subset, where the HER2 heterogeneity index outperformed clinical HER2 status (KM P=0.04; HR 6.38, P=0.001 vs. KM P=0.10; HR 0.64, P=0.20). Conclusions: These findings highlight the merit of identifying HER2 heterogeneity from H&E slides alone and establish this index as a robust prognostic factor in determining PFS in ER+ breast tumors. Future work will extend this investigation into ER- tumors and evaluate patient-specific tumor responses to anti-HER2 targeted therapy.

e12518 Background: Despite its purported prognostic significance in breast cancer, Ki67 index assessment remains poorly standardized and features high discordance rates amongst pathologists. Moreover, its clinical utility is presently confined to low stage, ER+/HER2- tumors in determining the advisability of adjuvant chemotherapy. Unfortunately, established cut-offs limit its utility to tumors with either high or low Ki67 index extremes. While Ki67 is a marker of actively dividing cells, it fails to capture the detail of cell cycle phase and dynamics which could be informative in terms of prognosis and tumor sensitivity to specific therapies (e.g. CDK4/6 inhibitors). This study therefore developed two novel indices as surrogates of (i) Ki67 index and (ii) quiescent cell population load (QPL). Methods: Breast cancer (comprising evenly distributed hormone receptor/HER2 status cases) H&E slides ( n = 79 cases/108 slides) were digitized on an Aperio DT3 scanner, and used to extract surrogate Ki67 and QPL indices. Sections were also stained for Ki67 by immunohistochemistry (IHC) using a clinically validated assay and digitized. Whole slide image (WSI) tumor Ki67 counts were performed on QuPath and used to validate the surrogate Ki67 index (Cohen’s kappa score). Indices (i) and (ii) were related to progression free survival (PFS). Survival analyses were performed using Kaplan-Meier (KM; with median cut-off) and Cox Proportional Hazards (as a continuous variable) models. Results: The surrogate Ki67 index showed good concordance with IHC scores (kappa = 0.76; 95%CI 0.61-0.91; P< 0.00001). However, this surrogate index performed better as a prognostic indicator of PFS compared to conventional Ki67 IHC (KM P = 0.048; HR = 1.35, P = 0.015 vs. KM P = 0.70; HR = 1.23, P = 0.08). Prognostically, the QPL index outperformed both Ki67 indices (KM P = 0.03; HR = 3.22, P = 0.001). Conclusions: We have developed two novel surrogate indices of Ki67 and QPL that can be readily automated to analyze H&E breast cancer WSIs. Our results show that both outperformed conventional Ki67 IHC evaluation in terms of prognostication, applied across molecular subtypes, improved informativeness of mid-range Ki67 index calls, and could potentially have predictive merit in selecting patients for cell cycle targeted therapies such as CDK4/6 inhibitors.

593 Background: Digital pathology has fostered the development of automated diagnostic solutions. However, current technologies in breast cancer remain unable to determine HER2 amplification status, which is established by immunohistochemistry (IHC) and/or fluorescent in situ hybridization (FISH). These ancillary tests carry a significant cost, prolong diagnostic time and fail to capture HER2 tumor heterogeneity and tumor infiltrating lymphocyte (TIL) burden, both of which determine the effectiveness anti-HER2 targeted therapy. Methods: This study describes the real-life clinical context development and validation of a patented novel, universal, automated, white-box, scanning platform agnostic solution that determines HER2 amplification status, prognostically significant TIL levels and tumor heterogeneity index (HI) from hematoxylin and eosin (H&E) stained malignant breast biopsy whole slide images (WSIs) alone. Unlike conventional artificial intelligence-based approaches, the underlying proprietary algorithm’s prediction criteria are explainable and are based on deterministic, hard-coded observational relationships of scale constructed from image morphological features mapped to observables representing underlying tumor-related perturbations in biological pathways/mitotic checkpoints.This includes G1/S deregulation signatures reflecting oncogenic HER2-neu. Results: Blinded validation of HER2 status prediction (n = 197 WSIs; 118 independent cases/patients) showed excellent diagnostic performance (κ = 0.85) relative to existing standard-of-care methodologies. This was independent of WSI file format, background histology, tumor subtype/grade or hormone receptor status. The device also displayed good accuracy (92%) in determining TIL profiles, and its combined HER2-TIL and HER2-HI prediction scales both exhibited a significant association with progression-free survival (CoxPH hazard ratio: 1.856; 95% CI: 1.002-3.438; p = 0.049 and CoxPH hazard ratio: 3.45; 95% CI: 0.95-12.55; p = 0.060). Conclusions: This technology opens up the future possibility of bypassing existing ancillary HER2 profiling investigations, thus potentially reducing laboratory workloads/healthcare costs while accelerating diagnostic turnaround times for patient benefit. In the interim, if used as an adjunct tool, this device could provide an objective HER2 testing reference scale while the robustness of its prediction of patient response to anti-HER2 targeted therapy is fully explored.