Deciphering the Role of ASPM in Breast Cancer: A Comprehensive Multicohort Study.

Background: Assembly factor for spindle microtubules (ASPM) has gained significant attention in cancer research due to its association with tumor growth and progression. Through the analysis of large-scale genomic datasets, ASPM has been identified as the top upregulated gene in breast cancer (BC), characterized by high proliferation. This multicohort study aimed to investigate the clinicopathological and prognostic significance of ASPM mRNA and protein expression in BC.

Deciphering the Clinical Behaviour of Invasive Lobular Carcinoma of the Breast Defines an Aggressive Subtype.

Background: Invasive lobular carcinoma (ILC), the most common special type of breast cancer (BC), has unique clinical behaviour and is different from invasive ductal carcinoma of no special type (IDC-NST). However, ILC further comprises a diverse group of tumours with distinct features. This study aims to examine the clinicopathological and prognostic features of different variants of ILC, with a particular focus on characterising aggressive subtypes.

Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application.

In recent years, artificial intelligence (AI) has demonstrated exceptional performance in mitosis identification and quantification. However, the implementation of AI in clinical practice needs to be evaluated against the existing methods. This study is aimed at assessing the optimal method of using AI-based mitotic figure scoring in breast cancer (BC).

Novel 2 Gene Signatures Associated With Breast Cancer Proliferation: Insights From Predictive Differential Gene Expression Analysis.

The use of proliferation markers provides valuable information about the rate of tumor growth, which can guide treatment decisions. However, there is still a lack of consensus regarding the optimal molecular markers or tests to use in clinical practice. Integrating gene expression data with clinical and histopathologic parameters enhances our understanding of disease processes, facilitates the identification of precise prognostic predictors, and supports the development of effective therapeutic strategies.

Quantitative expression of oestrogen receptor in breast cancer: Clinical and molecular significance.

Background: Oestrogen receptor (ER) positive breast cancer (BC) patients are eligible for endocrine therapy (ET), regardless of ER immunohistochemical expression level. There is a wide spectrum of ER expression and the response to ET is not uniform. This study aimed to assess the clinical and molecular consequences of ER heterogeneity with respect to ET-response.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer.

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker.

AI-based intra-tumor heterogeneity score of Ki67 expression as a prognostic marker for early-stage ER+/HER2- breast cancer.

Early-stage estrogen receptor positive and human epidermal growth factor receptor negative (ER+/HER2-) luminal breast cancer (BC) is quite heterogeneous and accounts for about 70% of all BCs. Ki67 is a proliferation marker that has a significant prognostic value in luminal BC despite the challenges in its assessment. There is increasing evidence that spatial colocalization, which measures the evenness of different types of cells, is clinically important in several types of cancer.

Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence.

Background: Tumour infiltrating lymphocytes (TILs) are a prognostic parameter in triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). However, their role in luminal (oestrogen receptor positive and HER2 negative (ER + /HER2-)) BC remains unclear. In this study, we used artificial intelligence (AI) to assess the prognostic significance of TILs in a large well-characterised cohort of luminal BC.

Concordance of HER2-low scoring in breast carcinoma among expert pathologists in the United Kingdom and the republic of Ireland -on behalf of the UK national coordinating committee for breast pathology.

Background: Recent clinical evidence showed that breast cancer with low HER2 expression levels responded to trastuzumab deruxtecan therapy. The HER2-low cancers comprise immunohistochemistry (IHC) score 1+ and 2+ ISH non-amplified tumours, currently classified as HER2 negative. Little data exists on the reproducibility of pathologists reporting of HER2-low cancer.

Deciphering the Morphology of Tumor-Stromal Features in Invasive Breast Cancer Using Artificial Intelligence.

Tumor-associated stroma in breast cancer (BC) is complex and exhibits a high degree of heterogeneity. To date, no standardized assessment method has been established. Artificial intelligence (AI) could provide an objective morphologic assessment of tumors and stroma, with the potential to identify new features not discernible by visual microscopy.

Combined proliferation and apoptosis index provides better risk stratification in breast cancer.

Aims: Breast cancer (BC) risk stratification is critical for predicting behaviour and guiding management decision-making. Despite the well-established prognostic value of cellular proliferation in BC, the interplay between proliferation and apoptosis remains to be defined. In this study, we hypothesised that the combined proliferation and apoptosis indices can provide a more accurate in-vivo growth rate measure and a precise prognostic predictor.

Refining the definition of HER2-low class in invasive breast cancer.

Background: Emerging evidence indicates that breast cancer (BC) patients whose tumours express HER2 protein without HER2 gene amplification (HER2-low), can benefit from antibody-drug conjugates (ADC). However, the current definition of HER2-low BC remains incomplete with low rates of concordance. This study aims to refine HER2-low definition with emphasis on distinguishing HER2 score 0 from score 1+ to identify patients who are eligible for ADC.

Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice.

Using digitalized whole slide images (WSI) in routine histopathology practice is a revolutionary technology. This study aims to assess the clinical impacts of WSI quality and representation of the corresponding glass slides. 40,160 breast WSIs were examined and compared with their corresponding glass slides.