Artificial intelligence (AI) is rapidly transforming histopathology, with applications ranging from workflow optimisation and quality assurance to tumour diagnosis, grading, biomarker assessment and estimation of prognosis. While numerous AI algorithms have demonstrated promising analytical and clinical performance, pathology laboratories are increasingly adopting commercially available AI systems with regulatory-approval rather than developing their own algorithms. Existing guidance largely focuses on AI development, validation and regulatory approval, with comparatively little practical direction on the local verification, governance and ongoing assurance required for safe routine clinical implementation. This paper proposes a practical framework for the clinical implementation of AI specifically within pathology laboratories. Rather than addressing AI development, it focuses on the responsibilities of laboratories adopting established AI systems into clinical practice. The framework distinguishes AI applications according to their intended clinical function, recognising that diagnostic applications, biomarker evaluation, workflow optimisation and generative AI applications require different implementation, verification, governance and quality assurance strategies. It further distinguishes algorithm validation, local verification and continuous assurance as complementary stages of implementation and advocates a function-based, risk-proportionate approach integrated within existing laboratory quality management systems. Practical recommendations are provided for workflow integration, interoperability, human oversight, user competency, performance monitoring, incident management, software updates and proportionate re-verification throughout the AI operational lifecycle. By extending implementation beyond regulatory approval, this guidance complements existing AI development and regulatory frameworks rather than replacing them. It provides a practical governance framework for pathology laboratories, professional organisations, accreditation bodies, and healthcare providers to support the safe, standardised, and sustainable integration of AI into routine histopathology while maintaining diagnostic quality, patient safety, and clinical governance.

Fibroepithelial lesions (FELs) of the breast represent a diverse group of biphasic tumors with varying morphologies and clinical behavior. The classification of FELs is mainly based on a constellation of diagnostic criteria, and intralesional heterogeneity is not uncommon. Therefore, reporting FELs in a core needle biopsy (CNB) with limited tissue material can be challenging as not all the features may be represented for assessment. Differentiating a classic fibroadenoma from a well-sampled phyllodes tumor (PT) is generally straightforward. However, cellular fibroadenoma, morphologically heterogeneous benign PT, and myoid hamartoma can overlap histologically. Accurate grading of PT is also challenging on CNB and carries significant management implications. In this article, we provide an overview and propose a pragmatic approach to reporting FELs on CNB, particularly for lesions with overlapping features. Guidance using the UK/European "B" classification of FELs alongside descriptive reporting of the various lesions, is also presented to aid in management decisions.

Local recurrences (LR) can occur within residual breast tissue, chest wall, skin, or newly formed scar tissue. Artificial intelligence (AI) technologies can extract a wide range of tumor features from large datasets helping in oncological decision-making. Recently, machine learning (ML) models have been developed to predict breast cancer recurrence or distant metastasis (DM). However, there is still a lack of models that consider the localization of LR as a tumor feature. To address this gap, here, we analysed data from 154 patients including pathological, clinical, and follow-up data (with an average follow-up of 133.16 months) on both primary tumors (PT) and recurrences. By using ML methods we predicted the localization of LR and the occurrence of DM after LR. The performance (ROC AUC) of the best ML models was 0.75, and 0.69 for predicting LR in breast parenchyma, and surgical scar tissue, respectively, and 0.74 for predicting DM after LR. We identified recurrence localization, and the time elapsed between the detection of primary breast carcinoma and the recurrence, and adjuvant chemotherapy as the most important features associated with further DM. We conclude that combining traditional prognostic factors with ML may provide important tools in the risk assessment of patients with breast LR.

Phyllodes tumours (PTs) of the breast present diagnostic challenges due to their complex histological features and potential for malignant behaviour. The World Health Organisation (WHO) classification requires the presence of five adverse histological criteria to categorise PTs as malignant, aiming to avoid overdiagnosis and improve diagnostic consistency. However, emerging evidence suggests that these strict criteria may underdiagnose tumours with metastatic potential and histological features that would otherwise be considered malignant in soft tissue tumours, leading to significant implications for prognosis and treatment. Recent studies have highlighted cases where tumours classified as borderline PT by WHO criteria exhibited metastatic behaviour, emphasising the need to refine the diagnostic framework. Microscopic criteria used to classify PT also vary among reporting pathologists, resulting in suboptimal reproducibility. This review examines the histological parameters utilised in the classification of malignant PT, highlights existing evidence gaps and analyses international breast pathologist survey data to propose a pragmatic diagnostic approach. We recommend redefining malignant PTs to include cases meeting four of the five WHO criteria, supplemented by comprehensive sampling and clinical context. This approach balances the risk of underdiagnosis with the need for standardised, reproducible diagnostic practices. Future collaborative efforts should focus upon developing evidence-based, biologically relevant classification systems and leveraging technological advancements to enhance diagnostic precision. These efforts aim to refine classification, improve prognostic accuracy and optimise patient management strategies.

The concept of "HER2-negative" breast cancer is evolving, with the recognition of HER2-low and HER2-ultralow subsets. These subsets are clinically relevant regarding treatment with the antibody-drug conjugate trastuzumab deruxtecan (T-DXd), which has shown survival benefit in patients with metastatic carcinoma with minimal HER2 protein expression that lack HER2 gene amplification by in situ hybridization. In clinical trials using T-DXd, HER2-low was defined as an immunohistochemistry (IHC) score 1+ or an IHC score 2+ without HER2 gene amplification. HER2-ultralow was defined as faint or barely perceptible, incomplete membrane staining in >0% to ≤10% of tumor cells (IHC score 0+/with membrane staining) and HER2-null as the complete absence of staining (IHC score 0/absent membrane staining). These results now necessitate more detailed evaluation and reporting of traditional "HER2-negative" results to identify patients with metastatic breast cancer who may benefit from T-DXd therapy. Both the US Food and Drug Administration and the European Medicines Agency have extended the regulatory approval of T-DXd to patients with metastatic breast cancer showing HER2-low or HER2-ultralow expressions. Updated clinical management guidelines now, therefore, incorporate the spectrum of HER2 results into treatment selection algorithms in the metastatic setting. To align histopathologic practice with these developments, the College of American Pathologists has issued a new biomarker-reporting template that recommends explicit distinction between IHC 0/absent membrane staining and IHC 0+/with membrane staining. Key concerns among pathologists include assay variability, scoring reproducibility, and quality assurance standards for accurately detecting such low levels of HER2 expression. This manuscript provides expert consensus, evidence-based practical recommendations for identifying and reporting tumors with HER2-low and HER2-ultralow expression. We emphasize standardized testing protocols, validated assays, robust internal and external controls, and focused training for pathologists. A universal structured pathology report is proposed to highlight the accurate distinction between IHC 0 (null), IHC 0+ (ultralow), and HER2-low expressions.

Previous literature extensively explored biomarkers to personalize treatment for breast cancer patients. The clinical need is especially high in patients with triple-negative breast cancer (TNBC) due to its aggressive nature and limited treatment modalities. This review aims to evaluate the value of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) as prognostic biomarkers in TNBC patients and assess their clinical potential. A literature search was conducted in PubMed, Embase, Emcare, Web of Science, and Cochrane Library. Papers comparing survival outcomes of TNBC patients with low/high or negative/positive TSR and immune cells were included. The most frequently mentioned subgroups of TILs were selected and reported in this review. Data from 43 articles on TILs and eight articles on TSR were included. Among TNBC patients, high CD8 expression was generally associated with better survival. Notable, the poor survival outcomes were related to high intra-tumoral PD-L1 expression, whereas high stromal PD-L1 expression more often was correlated with favorable outcomes. For the TSR, a high amount of stroma in the primary tumor of TNBC patients was consistently associated with worse survival. This review highlights that a high number of CD8-positive T-cells is a promising prognostic factor for TNBC patients. PD-L1 expression analyzed for intra-tumoral and stromal expression separately reports strong but contrasting information. Finally, the TSR shows potential to be an important prognostic marker, especially for TNBC patients. Utilizing both biomarkers, either on itself or combined, could enhance clinical decision-making and personalization of treatment.

BACKGROUND/AIM:The prognostic significance of proliferating cell nuclear antigen (PCNA) has not yet been defined in either colorectal adenoma or carcinoma. This study aimed to compare the differences in PCNA expression between pathologically altered tissue (polyp, adenoma, carcinoma) and the surrounding tissue (termed PCNA expression difference, PCNA-ED) as a potential prognostic marker in colorectal tumor progression. PATIENTS AND METHODS:Tissue specimens used for this study were obtained from 63 non-neoplastic epithelial polyps, 211 colorectal adenomas, and 156 colorectal adenocarcinomas, as well as adjacent normal mucosa. RESULTS:PCNA-ED was absent in non-neoplastic polyps, present in 13.7% of adenomas, and significantly more frequent in adenocarcinomas (33.3%). Higher PCNA-ED correlated with increasing adenoma size, grade of dysplasia, depth of invasion, and Dukes staging. High PCNA-ED was significantly associated with early recurrence, lymphovascular invasion, liver metastases, and reduced survival. Among patients with Astler-Coller B2 tumors, high PCNA-ED suggested a need for adjuvant chemotherapy. CONCLUSION:PCNA-ED is strongly associated with malignant transformation, recurrence, and adverse prognosis in colorectal neoplasms. Its measurement may offer valuable prognostic insight and inform postoperative management strategies.

Following a wide interdisciplinary consultation, the present recommendations have been finalized after their public discussion at the 5th Hungarian Consensus Conference on Breast Cancer. The recommendations cover non-operative, intraoperative and postoperative diagnostics, the determination of prognostic and predictive markers and the content of the cytology and histology reports. Furthermore, it touches some special issues such as the current status of multigene molecular markers, the role of pathologists in clinical trials and prerequisites for their involvement. The most important changes include the integration of the ASCO/CAP HER2 assessment guidelines from 2023, the reformulation of the role of cytology in breast cancer diagnostics, diagnostic categories of non-operative lymph node assessment, and the revision of PD-L1 assessment related information. The recommendations include the core and non-core elements of the ICCR (International Collaboration on Cancer Reporting) breast cancer related datasets.

Background: Triple negative breast cancers (TNBC), a heterogenous group of tumors represent about 15% of all breast cancers with limited biomarkers and treatment options. Tumor-stroma ratio (TSR) is a proven prognostic and predictive factor in various tumor types, including breast carcinomas, representing the stromal percentage in the most stroma abundant area of the tumor. The overall stromal ratio (OSR), which defines the stroma ratio of the entire tumor area on whole slide images (WSI) has scarcely been examined in the literature. Several studies suggest that changes in the extracellular matrix (ECM) composition and organization could promote tumor growth, but the results have not been consistent. The aim of our study was to investigate the prognostic value of stromal ratio and specific ECM proteins, including major structural components as type-I and type-III collagens as well as fibrillin-1. Understanding whether the expression of these proteins is associated with clinicopathological parameters and outcomes in the TNBC subtype offers valuable insight into the molecular mechanisms driving tumor development and metastasis. We sought to determine if automated digital image analysis (DIA) methods could provide an objective approach for analyzing stromal ratio and ECM components on H&E and immunohistochemically (IHC) stained slides. Methods: Our cohort included 101 female TNBC patients, primarily treated with surgery between 2005 and 2016. Representative H&E-stained WSIs were used to evaluate the TSR and OSR by two observers visually and through DIA. IHC was performed on tissue microarrays (TMAs) and scoring was determined both visually and through DIA for type-I collagen expression, type-III collagen expression and intensity, and fibrillin-1 expression and intensity. We employed the QuantCenter module of the SlideViewer program (v2.6; 3DHISTECH Ltd., Hungary), a DIA tool, to calculate the percentage of clusters representing the tumor, stroma, and background or cell-free area, as well as the intensity of the IHC staining. Statistical analyses were conducted using IBM SPSS statistics (v29 for Windows). Results: The intra- and interobserver variability of the determination of TSR and OSR scores were good or excellent and significant (r=.866-.979, p<.01). The correlation between the visual and DIA assessed scores were good or excellent for both on the H&E and on the IHC-stained TMAs (r=.927-969), although only poor to moderate determining intensity of the IHC-staining (r=.398-.566). We found that high OSR correlates with worse overall survival, advanced pN categories, lower sTIL, lower mitotic index, and patient age (p<.05). TSR showed significant connections to the pN categories and mitotic index (p<.01). High type-I collagen (>45%), type-III collagen (>30%), and fibrillin-1 (>20%) expression levels were linked to significantly worse OS (p=.004, p=.013, and p=.005, respectively) and PFS (p=.028, p=.025, and p=.002, respectively) suggesting their roles in promoting tumor progression and metastasis. Multivariate analysis confirmed the independent prognostic value of high DIA OSR (HR=1.037, p=.028), type-I collagen (HR=3.075, p=.01), type-III collagen (HR=3.467, p=.007), and fibrillin-1 (HR=3.439, p=.017) for OS and type-I collagen (HR=2.725, p=0.017), type-III collagen (HR=3.825, p=.011), and fibrillin-1 (HR=3.815, p=.018) for PFS. Conclusion: We identified promising extracellular matrix protein biomarkers that had not been previously examined in detail in TNBCs. Additionally, DIA proved to be a valuable tool in reliably separating the tumor tissue from its adjacent microenvironment in H&E-stained WSI for the objective measurement of TSR and OSR and to measure the expression of ECM proteins in IHC-stained samples. Citation Format: Zsófia Karancsi, Barbara Gregus, Tibor Krenács, Gábor Cserni, Ágnes Nagy, Klementina-Fruzsina Szőcs-Trinfa, Janina Kulka, Anna Mária Tőkés. Prognostic Value of Stromal Markers in Triple-Negative Breast Cancer: A Digital Image Analysis Approach [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P1-04-24.

Mismatch repair deficiency (dMMR) with microsatellite instability (MSI) is frequent in cancer, particularly in gastrointestinal and endometrial malignancies. The increased tumor mutational burden renders dMMR/MSI tumors suitable targets for immune checkpoint inhibitors—provided the regulatory genetic defect can be detected. dMMR and MSI are considered equally effective predictors of the efficacy of ICIs; however, while dMMR testing is based on detection of missing MMR proteins in immunohistochemistry (IHC), MSI polymerase chain reaction (PCR) testing focuses on the consequences of dMMR at the genomic level. A retrospective analysis was carried out in a large cancer cohort (n = 1306). dMMR was tested by four IHC reactions (MLH1, PMS2, MSH2, MSH6), and MSI was assessed by pentaplex PCR (BAT-25, BAT-26, MONO-27, NR-21, NR-24) in 703 cases. In 64 cases (5

Background and ObjectivesCurrent national or regional guidelines for the pathology reporting on invasive breast cancer differ in certain aspects, resulting in divergent reporting practice and a lack of comparability of data. Here we report on a new international dataset for the pathology reporting of resection specimens with invasive cancer of the breast. The dataset was produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter‐)national pathology and cancer organizations.Methods and ResultsThe established ICCR process for dataset development was followed. An international expert panel consisting of breast pathologists, a surgeon, and an oncologist prepared a draft set of core and noncore data items based on a critical review and discussion of current evidence. Commentary was provided for each data item to explain the rationale for selecting it as a core or noncore element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the document was finalized and ratified, and the dataset, which includes a synoptic reporting guide, was published on the ICCR website.ConclusionsThis first international dataset for invasive cancer of the breast is intended to promote high‐quality, standardized pathology reporting. Its widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will help to improve the management of invasive breast cancer patients.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis and limited treatment options. This study evaluates the prognostic value of stromal markers in TNBC, focusing on the tumor–stroma ratio (TSR) and overall stroma ratio (OSR) in whole slide images (WSI), as well as the expression of type-I collagen, type-III collagen, and fibrillin-1 on tissue microarrays (TMAs), using both visual assessment and digital image analysis (DIA). A total of 101 female TNBC patients, primarily treated with surgery between 2005 and 2016, were included. We found that high visual OSR correlates with worse overall survival (OS), advanced pN categories, lower stromal tumor-infiltrating lymphocyte count (sTIL), lower mitotic index, and patient age (p < 0.05). TSR showed significant connections to the pN category and mitotic index (p < 0.01). High expression levels of type-I collagen (>45%), type-III collagen (>30%), and fibrillin-1 (>20%) were linked to significantly worse OS (p = 0.004, p = 0.013, and p = 0.005, respectively) and progression-free survival (PFS) (p = 0.028, p = 0.025, and p = 0.002, respectively), validated at the mRNA level. Our results highlight the importance of stromal characteristics in promoting tumor progression and metastasis and that targeting extracellular matrix (ECM) components may offer novel therapeutic strategies. Furthermore, DIA can be more accurate and objective in evaluating TSR, OSR, and immunodetected stromal markers than traditional visual examination.

Invasive micropapillary carcinoma of the breast is characterized by clusters of cells presenting with inverted polarity. Although the apico-basal polarity is a fundamental property of the epithelium, the biological alterations leading to the inside-out pattern observed in invasive micropapillary carcinoma (IMPC) remain mostly unknown. The regulation of tight junctions in polarity formation and maintenance is acknowledged. By using immunohistochemistry, we have analysed claudin-1, -3, -4, and -7 tight junction proteins expression and their prognostic value on IMPCs and compared them to invasive breast carcinomas of no special type (IBC-NST) tumors. Our cohort consisted of 37 IMPCs, 36 IBC-NST and 9 mixed IMPC/IBC-NST tumors. Two scoring systems were used to quantify protein expression: a 4-tier scoring system and the H-score method. Distant metastasis free survival (DMFS) intervals and overal survival (OS) data were used for prognosis evaluation. The analysed samples were characterized mainly by low or no claudin-1 expression whereas claudins-3, -4 and -7 showed variable positivity. We have found no significant differences in claudin-3 and -4 protein expression between IMPC and IBC-NST groups with either scoring methods, however high claudin-7 expression was found in significantly more IMPCs than IBC-NST tumors according to the H-score system (p = 0.02). The 4-tier scoring method revealed association of claudin-7 expression with molecular tumor subtypes (p = 0.001). IMPC and IBC-NST tumors did not show difference in DMFS (p = 0.70). In the analysis of pure IMPC and IBC-NST tumors, positive/high claudin-4 protein expression was significantly associated with shorter DMFS (p = 0.02/p = 0.008, respectively according to the two scoring methods). Claudin-3 and claudin-7 expression showed no association with DMFS or OS. Changes in epithelial polarity seem not to be related to claudin-1, -3, and -4 expression. Increased claudin-4 expression may have a role in breast cancer progression.

AIMS:The International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations, is an initiative aimed at providing a unified international approach to reporting cancer. ICCR recently published new data sets for the reporting of invasive breast carcinoma, surgically removed lymph nodes for breast tumours and ductal carcinoma in situ, variants of lobular carcinoma in situ and low-grade lesions. The data set in this paper addresses the neoadjuvant setting. The aim is to promote high-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment that can be used for subsequent management decisions for each patient.METHODS:The ICCR convened expert panels of breast pathologists with a representative surgeon and oncologist to critically review and discuss current evidence. Feedback from the international public consultation was critical in the development of this data set.RESULTS:The expert panel concluded that a dedicated data set was required for reporting of breast specimens post-neoadjuvant therapy with inclusion of data elements specific to the neoadjuvant setting as core or non-core elements. This data set proposes a practical approach for handling and reporting breast resection specimens following neoadjuvant therapy. The comments for each data element clarify terminology, discuss available evidence and highlight areas with limited evidence that need further study. This data set overlaps with, and should be used in conjunction with, the data sets for the reporting of invasive breast carcinoma and surgically removed lymph nodes from patients with breast tumours, as appropriate. Key issues specific to the neoadjuvant setting are included in this paper. The entire data set is freely available on the ICCR website.CONCLUSIONS:High-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment are critical for subsequent management decisions for each patient.

Angiosarcoma (AS) of the breast, a rare mesenchymal neoplasm, exhibits distinct forms based on etiological and genetic features. While cases with typical clinical presentation and morphology allow for a straightforward diagnosis, challenges arise when clinical data are scarce, diagnostic material is limited, or morphological characteristics overlap with other tumors, including undifferentiated carcinomas. The trichorhinophalangeal syndrome protein 1 (TRPS1), once regarded as highly specific for breast carcinomas, now faces doubts regarding its reliability. This study explores TRPS1 expression in breast AS. Our investigation revealed that 60% of AS cases displayed TRPS1 labeling, contrasting with the 40% lacking expression. Scoring by four independent readers established a consensus, designating 12/35 ASs as unequivocally TRPS1-positive. However, uncertainty surrounded nine further cases due to a lack of reader agreement (being substantial as reflected by a kappa value of 0.76). These findings challenge the perceived specificity of TRPS1, shedding light on its presence in a noteworthy proportion of breast ASs. Consequently, the study underscores the importance of a comprehensive approach in evaluating breast ASs and expands the range of entities within the differential diagnosis associated with TRPS1 labeling.

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. (c) 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Current clinical guidelines recommend mismatch repair (MMR) protein immunohistochemistry (IHC) or molecular microsatellite instability (MSI) tests as predictive markers of immunotherapies. Most of the pathological guidelines consider MMR protein IHC as the gold standard test to identify cancers with MMR deficiency and recommend molecular MSI tests only in special circumstances or to screen for Lynch syndrome. However, there are data in the literature which suggest that the two test types may not be equal. For example, molecular epidemiology studies reported different rates of deficient MMR (dMMR) and MSI in various cancer types. Additionally, direct comparisons of the two tests revealed relatively frequent discrepancies between MMR IHC and MSI tests, especially in non-colorectal and non-endometrial cancers and in cases with unusual dMMR phenotypes. There are also scattered clinical data showing that the efficacy of immune checkpoint inhibitors is different if the patient selection was based on dMMR versus MSI status of the cancers. All these observations question the current dogma that dMMR phenotype and genetic MSI status are equal predictive markers of the immunotherapies.