ECP 2023 Abstracts

S167 Virchows Archiv (2023) 483 (Suppl 1):S1–S391 13 of the ER, PgR, HER2, and Ki67 antibodies has been done. In each molecular type of breast cancer, the proportion of the pCR was cal- culated using the prognostic relevance of the residual cancer burden system. Results: Present study revealed pathomorphology, IHC of primary and residual tumours, as well as the frequency of pCR after neoad- juvant chemotherapy. The surrogate molecular subtype of primary tumours was arranged as follows: luminal A (17.5%), luminal B, HER- 2-negative (48.8%,), luminal B, HER-2-positive (12.5%), HER-2-pos- itive (6.2%), triple negative subtype (15.0%). Complete morphologic response was reported in 9 cases, of which luminal B HER-2-negative phenotype and luminal B HER-2-positive were 33.3% each, triple nega- tive - 22.2% and HER-2 positive phenotype - 11.2%. Conclusion: Determination of residual tumour burden after neoad- juvant therapy provides an opportunity to predict the probability of favourable outcome of patients’ treatment. Further studies to improve the methods of the evaluation the degree of the RCB after neoadjuvant chemotherapy suggested. E-PS-02-058 Malignant adenomyoepithelioma with patterns of adenoid cystic carcinoma of the breast: a case report G. Richter*, P. Richter, C. Uleer, T. Noesselt *Institute of Pathology, Germany Background & objectives: An adenomyoepithelioma (AME) is a composite tumour with a predominant and generally solid prolifera- tion of phenotypically variable myoepthelial cells. An adenoid cystic carcinoma (ACC) is an epimyoepithelial carcinoma of low malignant potential that histologically similar to the salvary gland counterpart. Methods: We present a case of a 68 years old Caucasian female with solid tumour of the breast. The specimens were routinely stained with hematoxylin and eosin. Moreover, Periodic acid–Schiff (PAS) were processed. Immunohistochemically stained with primary anti- bodies Pan-cytokeratin (Roche), cytokeratin 5/6 (Roche), cytokeratin 7 (Roche), e-cadherin (Roche), SOX 10, CD117, S100 and KI-67 (Roche). Results: Histological examination shows a compact aggregate of tubulus with prominent myoepithelial cells and compressed lumens. In association we find a small focus of trabecular tubular pattern with spaces of variable shape, containing myxoid mucosubstances. Using Immunohistochemistry we detected a positive reaction for Pan-cytoker- atin, cytokeratin 5/6, cytokeratin 7 and a negative reaction for oestrogen and progesteron receptor in the tumour cells. In accordance with the dako score we detected a Her-2 score 0 (negative). Moreover a posi- tive reaction of the tumour cells for SOX 10 and CD117 was detected. Conclusion: Adenomoyeptheliomas are composed of two cell com- ponents with epithelial and myoepithelial cells and have mostly a benign behaviour. But in low number one of the components or both become malignant. Most malignant alterations appear as focal lesions arising within a classic benign AME and in addition, distinctive pat- terns of adenoid cystic carcinoma have been observed – like the case we present. E-PS-02-059 Immunohistochemical expression of primary breast tumours deter- mines the metastatic organ M.G. Rodríguez Guevara*, E. Honrado-Franco, O. Sanz-Guadar- rama, J. Alzoghby-Abi-Chaker, S. Marín-Asencio, O. García-Gal- vis, M. López-Flores, A. López-González, L. López-González, R. Canseco Fernández, C. Martínez-Martínez, S. Sáez-Ávarez *Complejo Asistencial Universitario de León, Spain Background & objectives: Breast cancer often metastasizes to bones, lungs, brain, and liver in advanced stages. Gene expression of primary breast tumours in patients with metastatic disease has been correlated with tumour behaviour. Therefore, understanding these metastatic mechanisms has clinical and prognostic implications. Methods: We present the study of 100 cases of metastatic breast cancer in one or several organs (liver, bone, brain and lung). We analysed the expres- sion of the oestrogen receptor, progesterone receptor, Ki-67 and HER-2 in primary breast tumours, to obtain an immunohistochemical profile of metastasis to each organ and the influence of the size and lymph node involvement and survival. Results: Triple negative tumours, metastasize more frequently to the brain 9/22 (41%) and lung 15/39 (38%) than to bone 14/58 (24%) and liver 7/24 (3%). HER-2 positive tumours (3+) are more likely to metastasize to the brain 8/22 (36%) and to the lungs 8/39 (20%) than to the bone 4/58 (7%) and the liver 4/24 (2%). Ki67 expression is greater than 10% in 80% of pri- mary breast tumours regardless of the site of metastasis. The lowest median survival rate after metastasis is in brain (19 months) while the highest was in lung metastasis (50 months). The median survival rate after metastasis to bone and liver is 27 and 35 months, respectively. Conclusion: We present a large study revealing the association between the immunohistochemical expression profiling patterns and organ-specific metastasis in breast carcinomas. Triple negative and HER-2 breast tumours, are more likely to metastasize to the lung and brain than to bone and liver. Metastasis to a specific organ was not influenced by tumour size or lymph node involvement. Survival varies depending on the metastasized organ. E-PS-02-060 End-to-end deep neural network for ER, PR and Ki-67 stained WSI automatic proliferation index (PI) quantification for breast cancer tissue Y. Salhi*, J. Rynkiewicz, C. Bossard, S. Salhi, J. Chetritt *DiaDeep, France Background & objectives: We develop an end-to-end pipeline based on a deep neural network for the quantification and assesfsment of nuclear biomarkers ER, PR and Ki-67 in breast adenocarcinoma stained WSI. The proliferation index as well as hotspot detection for Ki67 are proposed. Methods: A modified U-Net network with an adequate backbone is pro- posed, trained and validated on 1656 images. Testing was carried on a left- out set of 701 images originating from 23 patients. The proposed algorithm allows the quantification of tumour cells, detection of hotspots and the quan- tification of the corresponding proliferation index and tumour expression. Performances were investigated using external datasets. Results: In this study, the model’s performance in estimating ER, PR, and Ki-67 index scores was evaluated on a left-out dataset and two external datasets (n=23, 50, 130). The model outperformed existing frameworks on the same test data for the Ki-67 (n=23) with an accuracy of 95.96%. On the external datasets, i.e. AIDPATH (n=50) and IHP Group (n=130), the model achieved an averaged accuracy score of 98.3% and 96.7%, respec- tively for the three biomarkers. Also, the hotspots for Ki-67 prediction were accurately inferred based on the prediction outcomes and those were com- pared to expert pathologists annotations. Additionally, the proposed end- to-end approach enables faster inference times compared to other available algorithms. Conclusion: AI models for whole-slide image processing are usually task- specific and require complex processing pipelines. Unlike most algorithms that use a two-step approach to identify invasive areas and hot-spots before quantifying PI, the proposed end-to-end approach achieves this in a sin- gle step with promising results. This approach is easily adaptable to other biomarkers for prognosis and theranostics, as it doesn’t require specialized intermediate models. E-PS-02-061 HER2 spatial distribution affects neoadjuvant treatment response in breast cancer: the pisa prediction groups proposal C. Scatena*, R. Scarpitta, L. Lacitignola, B. Fuochi, P. Cinacchi, A. Fontana, G.N. Fanelli, A.G. Naccarato