Triple Negative Breast Cancer (TNBC) is recognised as heterogeneous, with distinct subtypes specified by histopathologic and gene expression analysis. However, these do not align closely to treatment response and there is an on-going need for both clinically applicable biomarkers and new effective treatments. Comprehensive profiling of the TNBC tissue proteome has potential to bring new perspective to these challenges. We report global proteomic profiles of 312 TNBC cases derived from Data Independent Acquisition-Mass Spectrometry (DIA-MS) analysis, coupled with gene expression profiling in a subset of cases (n = 97). This showed differential expression of protein cassettes reflecting the key features of 1) cellular growth and proliferation, 2) immune activation, 3) mesenchymal elements and 4) luminal androgen receptor phenotype. In combination, these cassettes distinguished TNBC subtypes that align to potential treatments. We also found an association between immune activation and improved survival that was influenced by the presence of lymph node metastases. In our cohort and in a validation dataset, the combination of a five protein immune activation signature with lymph node status was highly predictive of survival, suggesting that a combination of tissue proteomics with clinical features could be an informative guide to TNBC management. This large proteomic study forms a resource to progress this goal.

For 2 decades, the American Society of Clinial Oncology-College of American Pathologists human epidermal growth factor receptor 2 (HER2) testing criteria have included 0 and 1+ scores, but this distinction was inconsequential. Now, based on the DESTINY Breast-04 Trial (DB-04) results, for patients with metastatic breast cancer it underpins eligibility for trastuzumab-deruxtecan treatment. Discerning 0 from 1+ immunohistochemistry (IHC) staining is challenging, as HER2 low is not a biologically distinct cancer subset, there are no reference standards or controls, and second-tier tests (eg, in situ hybridization) do not apply. Prior reports cast doubt on the reliability of pathologists' IHC scoring, with resulting treatment misalignments. With institutional review board approval, our group of 9 breast pathologists from 8 Australian laboratories had previously established HER2-low-focused scoring conventions, based on the American Society of Clinial Oncology- College of American Pathologists 2018 HER2 guidelines, and specifying common staining pitfalls. We reported the results of the first set of 60 breast cancers evaluated with these methods. After a 5month washout, for the present validation study, we have compiled a second set of 64 HER2negative invasive breast cancer core biopsies, all assessed with the Ventana 4B5 HER2 assay. We have each scored digitized images of HER2 IHC slides of the cases. Using the majority opinion as the target score, we have calculated our performance metrics. We have compared the results of our performance in set 1 and set 2 to assess the effectiveness of our approach and learning retention. The cases in this validation set included 40 (62.5%) HER2 low, 10 (17.2%) ultralow (UL), and 13 (18.8%) null cancers. Concordance was not achieved in 1 case. For distinguishing HER2 low from other cancers (UL and null combined) the mean values of our performance metrics were accuracy 89.58%, sensitivity 90.83%, specificity 87.50%, positive predictive value 95.63%, negative predictive value 83.59%, and Cohen kappa score 0.81. Comparing these results with our initial study, we have maintained our high level of performance across these parameters. Our mean kappa score is now in the excellent range for concordance. Maintaining high performance across a range of measures in 2 separate data sets validates the effectiveness of our HER2-low-focused scoring conventions. Having validated our approach, we will use these reference case sets with expert-level consensus scores for peer training and updating our national HER2 IHC external quality assurance program. In our ongoing studies, we are also assessing the performance of software algorithms to determine their suitability for the prescreening of HER2 IHC slides. (c) 2025 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The DESTINY Breast-04 trial revealed survival advantages of trastuzumab deruxtecan for women with metastatic HER2-low breast cancer (1+ or 2+ immunohistochemistry [IHC], without amplification). Although this trial applied the 2018 Americal Society of Clinial Oncology (ASCO)/College of American Pathologists (CAP) HER2 IHC scoring criteria, the subjectivity and imprecision in IHC scoring have raised concerns that patients' treatment may be misaligned. Our group of 9 experienced breast pathologists collated a deidentified set of 60 breast cancer core biopsies from 3 laboratories, evaluated with the Ventana 4B5 HER2 assay and mostly scored locally as HER2 0 or 1+. Based on ASCO/CAP 2018 criteria and our extensive experience of reporting HER2 IHC, we specified scoring conventions for cancers with low levels of HER2 protein expression, articulating specific scoring pitfalls. Each pathologist then reviewed digitized whole slide images of the IHC slides and scored the HER2 expression for each case. At a subsequent consensus workshop, we reviewed the cases jointly to establish consensus scores for each case and determine the percentage of HER2 expressing tumor cells. Consensus was reached on all cases, with 40 classified as 1+ and 3 as 2+ (not amplified), totaling 43 (71.7%) HER2-low cancers. The remaining cases were HER2 0. In 93.3% of cases (56/60), the consensus score matched with the majority opinion of pathologists' independent scores. Seven (41.2%) of the 17 cases reported locally as HER2 0 were classified as HER2 low. Conversely, among 32 cases with local scores of 1+, 7 (21.8%) were reclassified as ultralow or null. Individual pathologists' accuracy in matching the consensus scores ranged from 73.3% to 91.67% (mean, 80.74%). Among HER2-low cancers those in which <20% of the tumor cells expressed HER2 had the lowest concordance levels. Observers Cohen's κ coefficients for concordance were excellent for 4, good in 1, and moderate in the 4 observers. This reference set of cases with expert consensus HER2 scores will be invaluable for peer training and development of our national external quality assurance program for HER2-low cancers. For assessing breast cancers at the low end of HER2 protein expression, our targeted scoring criteria and explicit instruction on pitfalls improved pathologists' accuracy and concordance.

Abstract Introduction: The Destiny Breast-04 Trial (DB-04) demonstrated the survival benefits of Trastuzumab Deruxtecan (T-DXd) for women with metastatic HER2 Low breast cancer, characterised by 1+ or 2+ IHC staining without amplification. While the DB-04 study applied the standard 2018 ASCO CAP IHC scoring criteria, in clinical practice, distinguishing HER2 0 from 1+ cancers is challenging as i) HER2 Low is not a biologically distinct subset of breast cancer, ii) there are no reference standards for HER2 Low cancers, iii) second-tier test, like ISH, are not applicable, and iv) there are no known controls for cases that have 0 or 1+ HER2 scores. For two decades this distinction was clinically immaterial, but now differentiating between HER2 0 and 1+ has now become crucial for determining patient eligibility for T-DXd therapy. Concerns regarding the subjectivity, imprecision and poor concordance between pathologists in scoring IHC in HER2 Low cancers raise the potential for misalignments in patient treatment. Ensuring pathologists have access to focused training for interpreting IHC scores at the low end of the HER2 expression spectrum, quality assurance procedures and reference sets are essential steps to help pathologists assess HER2 Low breast cancers more accurately and consistently. Design: In this study, a group of 9 experienced breast pathologists compiled a deidentified set of 60 breast cancer core biopsies from 3 laboratories. The Ventana 4B5 HER2 assay had been used for evaluation and the local laboratories had scored the samples as HER2 0 or 1+. We teased out the ASCO CAP 2018 criteria and used our collective expertise of reporting HER2 IHC for many years to specify HER2 Low-focused scoring conventions, including some potential pitfalls. Subsequently, using these conventions, each pathologist reviewed digitized whole slide images of the IHC slides and scored HER2 expression for each case. At a consensus workshop, the cases were jointly reviewed to establish consensus scores and determine the percentage of HER2-expressing tumor cells in each case. We then evaluated the concordance between individual pathologists' HER2 scores and the consensus opinion and ascertained reasons for discordance. Results: Among the cases discussed during the consensus conference, 43 out of 60 (71.7%) were classified as HER2 Low, with 40 cases designated as 1+ and three as 2+ (known to be not amplified). The consensus score matched the majority opinion of the pathologists' independent scores in 93.3% (56 out of 60) of the cases. Utilizing the HER2 Low-focused IHC scoring conventions, 7 out of 17 (41.2%) cases locally reported as HER2 0 were reclassified as HER2 Low. Conversely, among the 32 cases with local scores of 1+, 7 (21.8%) were reclassified as ultralow or null. When compared to the consensus score, individual pathologists' scores demonstrated concordance levels ranging from 71.7% to 91.7%, with a mean concordance rate of 81.3%. Cases with less than 20% of tumor cells expressing HER2 had lower inter observer concordance. This reference set of cases with expert consensus HER2 scores obtained through our study will be invaluable for peer training and the development of external quality assurance programs for HER2 Low cancers, including the quality assurance program of the Royal College of Pathologists of Australasia. Conclusion: This study revealed that when breast pathologists were provided explicit instructions on scoring pitfalls and HER2 Low-focused scoring conventions, their HER2 scores were concordant with expert consensus scores in 71.7% to 91.7% of cases. Discordant cases primarily involved cases with less than 20% of tumor cells expressing HER2. Utilising such an approach, peer training and quality assurance procedures will improve the accuracy and consistency of HER2 IHC assessment for better patient care. Reassessing older cases using HER2 Low focused scoring conventions may result in revisions of HER2 scores from HER2 Low to zero, and vice versa. Table. Individual pathologists' concordance with the consensus HER2 IHC score Applying our HER2 Low-focused IHC scoring conventions in a set of 60 core biopsies of invasive breast cancer with low or 0 HER2 protein expression. Citation Format: Gelareh Farshid, Beena Kumar, Nirmala Pathmanathan, Hema Mahajan, Ben Dessauvagie, Jane Armes, Cameron Snell, Amardeep Gilhotra. Improving HER2 Low Scoring Consistency and Accuracy: Insights from the Australian HER2 Low Concordance Study for Invasive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-25-12.

Triple-negative breast cancer (TNBC) is known to have a relatively poor outcome with variable prognoses, raising the need for more informative risk stratification. We investigated a set of digital, artificial intelligence (AI)-based spatial tumour microenvironment (sTME) features and explored their prognostic value in TNBC. After performing tissue classification on digitised haematoxylin and eosin (H&E) slides of TNBC cases, we employed a deep learning-based algorithm to segment tissue regions into tumour, stroma, and lymphocytes in order to compute quantitative features concerning the spatial relationship of tumour with lymphocytes and stroma. The prognostic value of the digital features was explored using survival analysis with Cox proportional hazard models in a cross-validation setting on two independent international multi-centric TNBC cohorts: The Australian Breast Cancer Tissue Bank (AUBC) cohort (n = 318) and The Cancer Genome Atlas Breast Cancer (TCGA) cohort (n = 111). The proposed digital stromal tumour-infiltrating lymphocytes (Digi-sTILs) score and the digital tumour-associated stroma (Digi-TAS) score were found to carry strong prognostic value for disease-specific survival, with the Digi-sTILs and Digi-TAS scores giving C-index values of 0.65 (p = 0.0189) and 0.60 (p = 0.0437), respectively, on the TCGA cohort as a validation set. Combining the Digi-sTILs feature with the patient's positivity status for axillary lymph nodes yielded a C-index of 0.76 on unseen validation cohorts. We surmise that the proposed digital features could potentially be used for better risk stratification and management of TNBC patients. (c) 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

SP142 programmed cell death ligand 1 (PD-L1) status predicts response to atezolizumab in triple-negative breast carcinoma (TNBC). Prevalence of VENTANA PD-L1 (SP142) Assay positivity, concordance with the VENTANA PD-L1 (SP263) Assay and Dako PD-L1 IHC 22C3 pharmDx assay, and association with clinicopathologic features were assessed in 447 TNBCs. SP142 PD-L1 intraobserver and interobserver agreement was investigated in a subset of 60 TNBCs, with scores enriched around the 1% cutoff. The effect of a 1-hour training video on pretraining and posttraining scores was ascertained. At a 1% cutoff, 34.2% of tumors were SP142 PD-L1 positive. SP142 PD-L1 positivity was significantly associated with tumor-infiltrating lymphocytes (P <0.01), and node negativity (P=0.02), but not with tumor grade (P=0.35), tumor size (P=0.58), or BRCA mutation (P=0.53). Overall percentage agreement (OPA) for intraobserver and interobserver agreement was 95.0% and 93.7%, respectively, among 5 pathologists trained in TNBC SP142 PD-L1 scoring. In 5 TNBC SP142 PD-L1-naive pathologists, significantly higher OPA to the reference score was achieved after video training (posttraining OPA 85.7%, pretraining OPA 81.5%, P<0.05). PD-L1 status at a 1% cutoff was assessed by SP142 and SP263 in 420 cases, and by SP142 and 22C3 in 423 cases, with OPA of 88.1% and 85.8%, respectively. The VENTANA PD-L1 (SP142) Assay is reproducible for classifying TNBC PD-L1 status by trained observers; however, it is not analytically equivalent to the VENTANA PD-L1 (SP263) Assay and Dako PD-L1 IHC 22C3 pharmDx assay.

Assisted vaginal birth can be lifesaving but also has implications for both mother and baby.This presentation will look at the current evidence available to maximising outcomes for maternal and neonatal considerations but also those skills required for the next generation of obstetricians

Mitotic count is a semiquantitative part of the routine histological grading of breast cancers and introduces significant interobserver reliability issues. One potential systematic solution is artificial intelligence (AI) and computer vision algorithms. Previous literature has shown proprietary AI models to be effective at counting breast cancer mitoses.1 Aim: To evaluate the efficacy of training a deep learning computer vision model using only opensource software, to improve the democratisation of AI in this application. Method: 778 images of breast carcinoma slides from Sunshine Coast University Hospital were split into training, validation and test sets and labelled by a trained non-pathologist. A ScaledYOLOv4 computer vision architecture was trained on 659 images, and the model was evaluated on the validation set (68 images), unseen by the model during training. Results: The model demonstrated a sensitivity of 0.92 and a positive predictive value (PPV) of 0.64. Discussion: The model's main weakness is its frequent misidentification of pyknotic cells. The model is most effective in tumours with high mitotic counts, as the ratio of mitotic figures to pyknotic cells is high. Next steps include creating opensource databases for improved image quantity, and standardisation of data to encourage further, higher quality opensource projects. 1.Pantanowitz L, Hartman D, Qi Y, et al. Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses. Diagn Pathol 2020; 15: 80.

The authors regret that Donal Brennan was missing from the author list. The details shown above are now correct with Dr Brennan included. Dr. Brennan contributed to conceptualisation and data curation and final review of manuscript. Dr. Brennan does not have any conflicts to disclose. The authors would like to apologise for any inconvenience caused. Complete pathological response following levonorgestrel intrauterine device in clinically stage 1 endometrial adenocarcinoma: Results of a randomized clinical trialGynecologic OncologyVol. 161Issue 1PreviewIntrauterine levonorgestrel (LNG-IUD) is used to treat patients with endometrial adenocarcinoma (EAC) and endometrial hyperplasia with atypia (EHA) but limited evidence is available on its effectiveness. The study determined the extent to which LNG-IUD with or without metformin (M) or weight loss (WL) achieves a pathological complete response (pCR) in patients with EAC or EHA. Full-Text PDF Open Access

Breast cancer is the dominant cancer among women as it accounts for about one-quarter of all cancer cases in females. The digitized images of Hematoxylin and Eosin (H&E) stained slides of breast cancer specimens carry valuable diagnostic information. However, inspecting these slides manually is a non-trivial task prone to subjective interpretation. Digital pathology (DP) and artificial intelligence (AI) open an opportunity for objective interpretation of the image data. It is challenging to automate the segmentation process in the whole slide images due to the visual complexity of tissue appearance without the need for tedious and time-consuming fine annotations. Many algorithms classify the tissue regions into different types instead of segmenting them, as the classification algorithms require coarse annotations that are easier to acquire. In this paper, we propose a new segmentation framework that combines the simple non-iterative clustering algorithm with a standard convolutional neural network (CNN) classifier to segment whole slide images into different tissue types. In addition, a graph-based post-processing step is applied to improve the framework segmentation performance further. The results show promising improvement to the CNN classifier based coarse segmentation, which would give better feasibility to quantify and study tissues' mutual relationships.

Purpose. Intrauterine levonorgestrel (LNG-IUD) is used to treat patients with endometrial adenocarcinoma (EAC) and endometrial hyperplasia with atypia (EHA) but limited evidence is available on its effectiveness. The study de term fined the extent to which LNG-IUD with or without metformin (M) or weight loss (WL) achieves a pathological complete response (pCR) in patients with EAC or EHA. Patients and methods. This phase II randomized controlled clinical trial enrolled patients with histologically confirmed, clinically stage 1 GIGO grade 1 EAC or EHA a body mass index > 30 kg/m2; a depth of myometrial invasion of less than 50% on MRI; a serum CA125 <= 30 U/mL. All patients received LNG-IUD and were randomized to observation (OBS), M (500 mg orally twice daily), or WL (pooled analysis). The primary outcome measure was the proportion of patients developing a pCR (defined as absence of any evidence of EAC or EHA) after 6 months. Results. From December 2012 to October 2019, 165 patients were enrolled and 154 completed the 6-months follow up. Women had a mean age of 53 years, and a mean BMI of 48 kg/m 2 . Ninety-six patients were diagnosed with EAC (58%) and 69 patients with EHA (42%). Thirty-five participants were randomized to OBS, 36 to WL and 47 to M (10 patients were withdrawn). After 6 months the rate of pCR was 61% (95% Cl 42% to 77%) for OBS, 67% (95% CI 48% to 82%) for WL and 57% (95% CI 41% to 72%) for M. Across the three treatment groups, the pCR was 82% and 43% for EHA and EAC, respectively. Conclusion. Complete response rates at 6 months were encouraging for patients with EAC and EHA across the three groups. (C) 2021 The Authors. Published by Elsevier Inc.

High stage and recurrent ovarian clear cell carcinoma (OCC) are associated with poor prognosis and resistance to chemotherapy. A distinguishing histological feature of OCC is abundant cytoplasmic stores of glucose, in the form of glycogen, that can be mobilized for cellular metabolism. Here, we report the effect on preclinical models of OCC of disrupting glycogen utilization using the glucose analogue 2-deoxy-D-glucose (2DG). At concentrations significantly lower than previously reported for other cancers, 2DG markedly improves the efficacy in vitro of carboplatin chemotherapy against chemo-sensitive TOV21G and chemo-resistant OVTOKO OCC cell lines, and this is accompanied by the depletion of glycogen. Of note, 2DG doses-of more than 10-fold lower than previously reported for other cancers-significantly improve the efficacy of carboplatin against cell line and patient-derived xenograft models in mice that mimic the chemo-responsiveness of OCC. These findings are encouraging, in that 2DG doses, which are substantially lower than previously reported to cause adverse events in cancer patients, can safely and significantly improve the efficacy of carboplatin against OCC. Our results thus justify clinical trials to evaluate whether low dose 2DG improves the efficacy of carboplatin in OCC patients.

Incorporation of genome and exome sequencing into fetal and neonatal autopsy investigations has been shown to improve diagnostic yield. This requires deoxyribonucleic acid (DNA) to be extracted from either the placenta or autopsy tissue for molecular testing. However, the sources and quality of DNA obtained are highly variable and there are no adequate published data on what tissue is most ideal to sample for DNA extraction in this setting. Here we compare the quality of DNA extracted from sampling the placenta and various solid organs at fetal and neonatal autopsy, thereby determining the optimal tissue from which to source DNA for ancillary testing as part of the modern perinatal autopsy. A total of 898 tissue samples were obtained at autopsy from 176 fetuses (gestational ages 17-40 weeks) and 44 neonates (age range 0-28 days) at our tertiary institution. Fetal tissue was processed using the QIAsymphony DSP DNA Mini kit and placental tissue was extracted using the New iGENatal Kit. DNA concentration was quantified using the Qubit dsDNA BR Assay Kit. DNA integrity, as stratified by gel electrophoresis was classified as high (>= 5 kb) or low quality (<5 kb). Genome sequencing was performed on the extracted DNA, together with respective parental DNA from blood samples, and confirmed absence of maternal contamination in all cases. Analyses used logistic mixed models to test for associations between tissue types, intrauterine retention times, delivery to autopsy and death to autopsy intervals with DNA quality. In the fetal cohort, the placenta had the highest proportion of high quality DNA samples (93.1%), and liver had the lowest proportion (35.3%). Among the neonates, all tissue samples with the exception of liver had over 88% high DNA quality with the placenta also yielding the highest quality (100%). There was statistically significant deterioration in DNA quality with prolonged time interval between demise and autopsy (>= 5 days). In the 726 fetal samples, the odds of obtaining higher quality DNA from the placenta, thymus, and spleen were 70.4 [95% confidence interval (CI) 29.2-169.6], 3.6 (95% CI 2.0-6.6) and 3.3 (95% CI 1.8-6.1) times, respectively, more likely than samples from the liver (p values <0.001). DNA yield from other fetal solid organs investigated was not significantly superior to that from the liver. This study shows that, when available, refrigerated unfixed placenta is the most suitable source of high quality DNA during perinatal investigations. Of the solid fetal organs sampled at autopsy, lymphocyte-rich, lytic enzymes-poor organs such as thymus and spleen were significantly more likely to yield good quality DNA than the liver.

Searchable abstracts of presentations at key conferences in oncology ISSN 2631-4657 (online)

Recent pre-clinical studies indicate that activated progesterone receptor (PR) (particularly the PR-B isoform) binds to oestrogen receptor-α (ER) and reprogrammes transcription toward better breast cancer outcomes. We investigated whether ER and PR-B interactions were present in breast tumours and associated with clinical parameters including response to aromatase inhibitors. We developed a proximity ligation assay to detect ER and PR-B (ER:PR-B) interactions in formalin-fixed paraffin-embedded tissues. The assay was validated in a cell line and patient-derived breast cancer explants and applied to a cohort of 229 patients with ER-positive and HER2-negative breast cancer with axillary nodal disease. Higher frequency of ER:PR-B interaction correlated with increasing patient age, lower tumour grade and mitotic index. A low frequency of ER:PR-B interaction was associated with higher risk of relapse. In multivariate analysis, ER:PR-B interaction frequency was an independent predictive factor for relapse, whereas PR expression was not. In subset analysis, low frequency of ER:PR-B interaction was predictive of relapse on adjuvant aromatase inhibitor (HR 4.831, p = 0.001), but not on tamoxifen (HR 1.043, p = 0.939). This study demonstrates that ER:PR-B interactions have utility in predicting patient response to adjuvant AI therapy.

LINE-1 (L1) retrotransposons are a source of insertional mutagenesis in tumor cells. However, the clinical significance of L1 mobilization during tumorigenesis remains unclear. Here, we applied retrotransposon capture sequencing (RC-seq) to multiple single-cell clones isolated from five ovarian cancer cell lines and HeLa cells and detected endogenous L1 retrotransposition in vitro. We then applied RC-seq to ovarian tumor and matched blood samples from 19 patients and identified 88 tumor-specific L1 insertions. In one tumor, an intronic de novo L1 insertion supplied a novel cis-enhancer to the putative chemoresistance gene STC1. Notably, the tumor subclone carrying the STC1 L1 mutation increased in prevalence after chemotherapy, further increasing STC1 expression. We also identified hypomethylated donor L1s responsible for new L1 insertions in tumors and cultivated cancer cells. These congruent in vitro and in vivo results highlight L1 insertional mutagenesis as a common component of ovarian tumorigenesis and cancer genome heterogeneity.

Death in the fetal, perinatal, and early infant age-group has a multitude of causes, a proportion of which is presumed to be genetic. Defining a specific genetic aberration leading to the death is problematic at this young age, due to limited phenotype–genotype correlation inherent in the underdeveloped phenotype, the inability to assess certain phenotypic traits after death, and the problems of dealing with rare disorders. In this study, our aim was to increase the yield of identification of a defined genetic cause of an early death. Therefore, we employed whole genome sequencing and bioinformatic filtering techniques as a comprehensive, unbiased genetic investigation into 16 fetal, perinatal, and early infant deaths, which had undergone a full autopsy. A likely genetic cause was identified in two cases (in genes; COL2A1 and RYR1) and a speculative genetic cause in a further six cases (in genes: ARHGAP35, BBS7, CASZ1, CRIM1, DHCR7, HADHB, HAPLN3, HSPG2, MYO18B, and SRGAP2). This investigation indicates that whole genome sequencing is a significantly enabling technology when determining genetic causes of early death.

AimsProgesterone receptor (PR) expression is prognostic in early stage breast cancer. There are several reports of discordant expression between primary tumour and axillary lymph node (ALN) metastasis expression of oestrogen receptor (ER) and PR. We sought to determine whether expression of these biomarkers in the synchronous ALN metastases of ER positive (+), HER2 negative (−) breast cancer could provide more accurate prognostic information.MethodsThe retrospective cohort included 229 patients from a single institution with ER+, HER2− breast cancer who had synchronous ALN metastatic disease (2005–2014). PR expression was correlated with relapse-free survival, and subset analysis was performed for patients who received adjuvant tamoxifen or an aromatase inhibitor.ResultsOne patient had an ER+ primary tumour, which was ER− in the ALN metastasis. 27 (11.3%) were PR− in the primary tumour and 56 (23.6%) in the ALN metastasis. The predominant change was from PR+ in the primary tumour to PR− in the lymph node. Absence of PR expression in the ALN was significantly associated with relapse; however, this was not the case in the primary tumour. In a subset analysis of patients taking adjuvant endocrine therapy, poorer prognosis was limited to those with PR− metastases on tamoxifen (HR=5.203, 95% CI 1.649 to 16.416, p=0.005). No significant prognostic effect of PR− metastases in patients taking aromatase inhibitors was seen (HR=1.519, 95% CI 0.675 to 3.418, p=0.312).ConclusionsEvaluation of PR expression in ALN metastasis may enable prediction of patients who are less likely to benefit from adjuvant tamoxifen. This study should be replicated in other cohorts.