Concurrent presence of primary hemangioma and breast cancer metastasis within a lymph node: a case report inspired by the legacy of Professor Juan Rosai.

Secondary neoplastic lesions in lymph nodes are predominantly metastases from solid tumors, whereas primary lymph node hemangiomas are exceptionally uncommon, with only 24 well-documented cases in the literature. Histologically, they are characterized by endothelial cells that may appear flattened or enlarged, with variable vascular density, and the presence of stromal elements. Notably, the concurrent presence of a primary hemangioma and a metastasis from breast cancer - the latter being the most prevalent secondary lesion in axillary lymph nodes - represents an unprecedented observation. The unique case presented herein underscores the exceptional rarity of primary lymph node hemangiomas and demonstrates for the first time their possible coexistence with breast cancer metastasis within the same axillary lymph node. In sharing and discussing this case study, we pay homage to Professor Juan Rosai, whose work in redefining rare and complex diagnoses continues to enlighten our understanding of lymph node vascular lesions.

Standardized molecular pathology workflow for ctDNA-based ESR1 testing in HR+/HER2- metastatic breast cancer.

Mutations in the estrogen receptor alpha gene (ESR1) can lead to resistance to endocrine therapy (ET) in hormone receptor-positive (HR+)/ HER2- metastatic breast cancer (MBC). ESR1 mutations can be detected in up to 40 % of patients pretreated with ET in circulating tumor DNA (ctDNA). Data from prospective randomized trials highlight those patients with HR+/HER2- MBC with detectable ESR1 mutations experience better outcomes when receiving novel selective estrogen receptor degraders (SERDs). There is a high need for optimizing ESR1 testing strategies on liquid biopsy samples in HR+/HER2- MBC, including a hugh quality workflow implementation and molecular pathology reporting standardization. Our manuscript aims to elucidate the clinical and biological rationale for ESR1 testing in MBC, while critically examining the currently available guidelines and recommendations for this specific type of molecular testing on ctDNA. The objective will extend to the critical aspects of harmonization and standardization, specifically focusing on the pathology laboratory workflow. Finally, we propose a clear and comprehensive model for reporting ESR1 testing results on ctDNA in HR+/HER2- MBC.

The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy.

Multigene prognostic genomic assays have become indispensable in managing early breast cancer (EBC), offering crucial information for risk stratification and guiding adjuvant treatment strategies in conjunction with traditional clinicopathological parameters. The American Society of Clinical Oncology (ASCO) guidelines endorse these assays, though some clinical contexts still lack definitive recommendations. The dynamic landscape of EBC management demands further refinement and optimization of genomic assays to streamline their incorporation into clinical practice. The breast cancer community is poised at the brink of transformative advances in enhancing the clinical utility of genomic assays, aiming to significantly improve the precision and effectiveness of both diagnosis and treatment for women with EBC. This article methodically examines the testing methodologies, clinical validity and utility, costs, diagnostic frameworks, and methodologies of the established genomic tests, including the Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI). Among these tests, Prosigna and EndoPredict® have at present been validated only on a prognostic level, while Oncotype Dx, MammaPrint, and BCI hold both a prognostic and predictive role. Oncologists and pathologists engaged in the management of EBC will find in this review a thorough comparison of available genomic assays, as well as strategies to optimize the utilization of the information derived from them.

Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.

Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes.

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

PIK3CA testing in hormone receptor-positive/HER2-negative metastatic breast cancer: real-world data from Italian molecular pathology laboratories.

Introduction: PIK3CA gene mutations occur in approximately 40% of hormone receptor-positive/HER2-negative (HR+/HER2-) metastatic breast cancers (MBCs), electing them to targeted therapy. Testing PIK3CA status is complex due to selection of biological specimen and testing method. Materials & methods: This work investigates real-life experience on PIK3CA testing in HR+/HER2- MBC. Clinical, technical and molecular data on PIK3CA testing were collected from two referral laboratories. Additionally, the results of a nationwide PIK3CA survey involving 116 institutions were assessed. Results: Overall, n = 35 MBCs were PIK3CA-mutated, with mutations mostly occurring in exons 9 (n = 19; 51.4%) and 20 (n = 15; 40.5%). The nationwide survey revealed significant variability across laboratories in terms of sampling methodology, technical assessment and clinical report signing healthcare figures for PIK3CA molecular testing in diagnostic routine practice. Conclusion: This study provides insights into the real-world routine of PIK3CA testing in HR+/HER2- MBC and highlights the need for standardization and networking in predictive pathology.

PD-L1 testing in metastatic triple-negative breast cancer: Interobserver and interplatform reproducibility of CE-IVD assays for CPS and IC scores.

PD-L1 test is recommended in different types of tumors to select patients eligible for immune checkpoint inhibitors (ICI) therapy. Several factors make this test challenging in metastatic triple-negative breast cancer (mTNBC). Different assays and platforms are available, each associated with distinct scoring systems and threshold values specific to the ICI compound used, i.e. CPS≥10 for pembrolizumab and IC ≥ 1 % for atezolizumab. Our objective was to assess the consistency of PD-L1 testing in mTNBC by examining interobserver and interassay reproducibility. We assessed n = 60 mTNBC samples for PD-L1 testing using 22C3 pharmDx assay on a Dako Autostainer Link 48 and VENTANA PD-L1 (SP263) on a Ventana BenchMark Ultra. Additionally, a subset of n = 19 samples was tested using the SP142 assay, also on the Ventana BenchMark Ultra. CPS with both 22C3 and SP263 was independently evaluated by five pathologists, all certified PD-L1 trainers. The IC with SP142 was assessed by three of these pathologists, who have particular expertise in breast pathology. Following the computation of the intraclass correlation coefficient (ICC) for each assay and their respective thresholds, we assessed the agreement between different raters and assays using Fleiss's κ, with a 95 % confidence interval (CI). Overall, we observed a significant (p < 0.001) ICC with both CPS assays [22C3 = 0.939 (CI:0.913-0.96); SP263 = 0.972 (CI:0.96-0.982); combined 22C3-SP263 = 0.909 (CI:0.874-0.938)]. Fleiss's κ confirmed an almost perfect agreement among pathologists and assays: 22C3 = 0.938 (CI:0.857-1.018); SP263 = 0.972 (CI:0.890-1.052); combined 22C3-SP263 = 0.907 (CI:0.869-0.945). Perfect inter-rater agreement was reached considering IC. This study establishes the reliability of assessing CPS in mTNBC using either the 22C3 pharmDx, as employed in the KEYNOTE studies, or the VENTANA SP263 assay. Each assay must be used on its designated platform, namely the Dako for 22C3 pharmDx and the Ventana for VENTANA SP263. It is important to remark that CPS and IC identify different patient cohorts and, therefore, are not interchangeable.

ESR1 mutations in HR+/HER2-metastatic breast cancer: Enhancing the accuracy of ctDNA testing.

Activating mutations of the estrogen receptor alpha gene (ESR1) are common mechanisms of endocrine therapy (ET) resistance in hormone receptor-positive (HR + )/Human Epidermal Growth Factor Receptor 2 (HER2)-negative metastatic breast cancer (MBC). Recent clinical findings emphasize that both old and new generations of selective ER degraders (SERDs) demonstrate enhanced clinical effectiveness in patients with MBC who have detectable ESR1 mutations via liquid biopsy. This stands in contrast to individuals with MBC carrying these mutations and undergoing conventional endocrine monotherapies like aromatase inhibitors (AIs). Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), has emerged as a promising, minimally invasive alternative to conventional tissue-based testing for identifying ESR1 mutations. Within the context of the PADA-1 and EMERALD trials, distinct molecular methodologies and assays, specifically digital droplet PCR (ddPCR) and next-generation sequencing (NGS), have been employed to evaluate the mutational status of ESR1 within ctDNA. This manuscript critically examines the advantages and indications of various ctDNA testing methods on liquid biopsy for HR+/HER2-negative MBC. Specifically, we delve into the capabilities of ddPCR and NGS in identifying ESR1 mutations. Each methodology boasts unique strengths and limitations: ddPCR excels in its analytical sensitivity for pinpointing hotspot mutations, while NGS offers comprehensive coverage of the spectrum of ESR1 mutations. The significance of meticulous sample handling and timely analysis is emphasized, acknowledging the transient nature of cfDNA. Furthermore, we underscore the importance of detecting sub-clonal ESR1 mutations, as these variants can exert a pivotal influence on predicting both endocrine therapy resistance and responsiveness to SERDs. In essence, this work discusses the role of ctDNA analysis for detecting ESR1 mutations and their implications in tailoring effective therapeutic strategies for HR+/HER2- MBC.

Revolutionizing Cancer Research: The Impact of Artificial Intelligence in Digital Biobanking.

BACKGROUND: Biobanks are vital research infrastructures aiming to collect, process, store, and distribute biological specimens along with associated data in an organized and governed manner. Exploiting diverse datasets produced by the biobanks and the downstream research from various sources and integrating bioinformatics and "omics" data has proven instrumental in advancing research such as cancer research. Biobanks offer different types of biological samples matched with rich datasets comprising clinicopathologic information. As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research. METHODS: In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. We look at the different data that ranges from specimen-related data, including digital images, patient health records and downstream genetic/genomic data and resulting "Big Data" and the analytic approaches used for analysis. RESULTS: These cutting-edge technologies can address the challenges faced by translational and clinical research, enhancing their capabilities in data management, analysis, and interpretation. By leveraging AI, biobanks can unlock valuable insights from their vast repositories, enabling the identification of novel biomarkers, prediction of treatment responses, and ultimately facilitating the development of personalized cancer therapies. CONCLUSIONS: The integration of biobanking with AI has the potential not only to expand the current understanding of cancer biology but also to pave the way for more precise, patient-centric healthcare strategies.

Circulating tumour DNA testing in metastatic breast cancer: Integration with tissue testing.

Breast cancer biomarker profiling predominantly relies on tissue testing (surgical and/or biopsy samples). However, the field of liquid biopsy, particularly the analysis of circulating tumour DNA (ctDNA), has witnessed remarkable progress and continues to evolve rapidly. The incorporation of ctDNA-based testing into clinical practice is creating new opportunities for patients with metastatic breast cancer (MBC). ctDNA offers advantages over conventional tissue analyses, as it reflects tumour heterogeneity and enables multiple serial biopsies in a minimally invasive manner. Thus, it serves as a valuable complement to standard tumour tissues and, in certain instances, may even present a potential alternative approach. In the context of MBC, ctDNA testing proves highly informative in the detection of disease progression, monitoring treatment response, assessing actionable biomarkers, and identifying mechanisms of resistance. Nevertheless, ctDNA does exhibit inherent limitations, including its generally low abundance, necessitating timely blood samplings and rigorous management of the pre-analytical phase. The development of highly sensitive assays and robust bioinformatic tools has paved the way for reliable ctDNA analyses. The time has now come to establish how ctDNA and tissue analyses can be effectively integrated into the diagnostic workflow of MBC to provide patients with the most comprehensive and accurate profiling. In this manuscript, we comprehensively analyse the current methodologies employed in ctDNA analysis and explore the potential benefits arising from the integration of tissue and ctDNA testing for patients diagnosed with MBC.

Advancing the PD-L1 CPS test in metastatic TNBC: Insights from pathologists and findings from a nationwide survey.

Pembrolizumab has received approval as a first-line treatment for unresectable/metastatic triple-negative breast cancer (mTNBC) with a PD-L1 combined positive score (CPS) of ≥ 10. However, assessing CPS in mTNBC poses challenges. Firstly, it represents a novel analysis for breast pathologists. Secondly, the heterogeneity of PD-L1 expression in mTNBC further complicates the assessment. Lastly, the lack of standardized assays and staining platforms adds to the complexity. In KEYNOTE trials, PD-L1 expression was evaluated using the IHC 22C3 pharmDx kit as a companion diagnostic test. However, both the 22C3 pharmDx and VENTANA PD-L1 (SP263) assays are validated for CPS assessment. Consequently, assay-platform choice, staining conditions, and scoring methods can significantly impact the testing outcomes. This consensus paper aims to discuss the intricacies of PD-L1 CPS testing in mTNBC and provide practical recommendations for pathologists. Additionally, we present findings from a nationwide Italian survey elucidating the state-of-the-art in PD-L1 CPS testing in mTNBC.

PPAR-gamma agonist pioglitazone recovers mitochondrial quality control in fibroblasts from PITRM1-deficient patients.

Introduction: Biallelic variants in PITRM1 are associated with a slowly progressive syndrome characterized by intellectual disability, spinocerebellar ataxia, cognitive decline and psychosis. The pitrilysin metallopeptidase 1 (PITRM1) is a mitochondrial matrix enzyme, which digests diverse oligopeptides, including the mitochondrial targeting sequences (MTS) that are cleaved from proteins imported across the inner mitochondrial membrane by the mitochondrial processing peptidase (MPP). Mitochondrial peptidases also play a role in the maturation of Frataxin, the protein affected in Friedreich's ataxia. Recent studies in yeast indicated that the mitochondrial matrix protease Ste23, which is a homologue of the human insulin-degrading enzyme (IDE), cooperates with Cym1 (homologue of PITRM1) to ensure the proper functioning of the preprotein processing machinery. In humans, IDE could be upregulated by Peroxisome Proliferator-Activated Receptor Gamma (PPARG) agonists. Methods: We investigated preprotein processing, mitochondrial membrane potential and MTS degradation in control and patients' fibroblasts, and we evaluated the pharmacological effect of the PPARG agonist Pioglitazone on mitochondrial proteostasis. Results: We discovered that PITRM1 dysfunction results in the accumulation of MTS, leading to the disruption and dissipation of the mitochondrial membrane potential. This triggers a feedback inhibition of MPP activity, consequently impairing the processing and maturation of Frataxin. Furthermore, we found that the pharmacological stimulation of PPARG by Pioglitazone upregulates IDE and also PITRM1 protein levels restoring the presequence processing machinery and improving Frataxin maturation and mitochondrial function. Discussion: Our findings provide mechanistic insights and suggest a potential pharmacological strategy for this rare neurodegenerative mitochondrial disease.

Immune Biomarkers in Triple-Negative Breast Cancer: Improving the Predictivity of Current Testing Methods.

Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis and disease recurrence. The limited treatment options and the development of resistance to chemotherapy make it particularly difficult to manage these patients. However, recent research has been shifting its focus towards biomarker-based approaches for TNBC, with a particular emphasis on the tumor immune landscape. Immune biomarkers in TNBC are now a subject of great interest due to the presence of tumor-infiltrating lymphocytes (TILs) in these tumors. This characteristic often coincides with the presence of PD-L1 expression on both neoplastic cells and immune cells within the tumor microenvironment. Furthermore, a subset of TNBC harbor mismatch repair deficient (dMMR) TNBC, which is frequently accompanied by microsatellite instability (MSI). All of these immune biomarkers hold actionable potential for guiding patient selection in immunotherapy. To fully capitalize on these opportunities, the identification of additional or complementary biomarkers and the implementation of highly customized testing strategies are of paramount importance in TNBC. In this regard, this article aims to provide an overview of the current state of the art in immune-related biomarkers for TNBC. Specifically, it focuses on the various testing methodologies available and sheds light on the immediate future perspectives for patient selection. By delving into the advancements made in understanding the immune landscape of TNBC, this study aims to contribute to the growing body of knowledge in the field. The ultimate goal is to pave the way for the development of more personalized testing strategies, ultimately improving outcomes for TNBC patients.

Nanopore long-read next-generation sequencing for detection of mitochondrial DNA large-scale deletions.

Primary mitochondrial diseases are progressive genetic disorders affecting multiple organs and characterized by mitochondrial dysfunction. These disorders can be caused by mutations in nuclear genes coding proteins with mitochondrial localization or by genetic defects in the mitochondrial genome (mtDNA). The latter include point pathogenic variants and large-scale deletions/rearrangements. MtDNA molecules with the wild type or a variant sequence can exist together in a single cell, a condition known as mtDNA heteroplasmy. MtDNA single point mutations are typically detected by means of Next-Generation Sequencing (NGS) based on short reads which, however, are limited for the identification of structural mtDNA alterations. Recently, new NGS technologies based on long reads have been released, allowing to obtain sequences of several kilobases in length; this approach is suitable for detection of structural alterations affecting the mitochondrial genome. In the present work we illustrate the optimization of two sequencing protocols based on long-read Oxford Nanopore Technology to detect mtDNA structural alterations. This approach presents strong advantages in the analysis of mtDNA compared to both short-read NGS and traditional techniques, potentially becoming the method of choice for genetic studies on mtDNA.

Breast Cancer with Brain Metastasis: Molecular Insights and Clinical Management.

Breast cancer is the most frequently diagnosed malignancy worldwide and the leading cause of cancer-related death among women. Brain metastases are a primary contributor to mortality, as they often go undetected until late stages due to their dormant nature. Moreover, the clinical management of brain metastases is complicated by the relevant issue of blood-brain barrier penetration. The molecular pathways involved in the formation, progression, and colonization of primary breast tumors and subsequent brain metastases are diverse, posing significant hurdles due to the heterogeneous nature of breast cancer subtypes. Despite advancements in primary breast cancer treatments, the prognosis for patients with brain metastases remains poor. In this review, we aim to highlight the biological mechanisms of breast cancer brain metastases by evaluating multi-step genetic pathways and to discuss currently available and emerging treatment strategies to propose a prospective overview of the management of this complex disease.

Computational pathology to improve biomarker testing in breast cancer: how close are we?

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided.

Variants in ATP5F1B are associated with dominantly inherited dystonia.

ATP5F1B is a subunit of the mitochondrial ATP synthase or complex V of the mitochondrial respiratory chain. Pathogenic variants in nuclear genes encoding assembly factors or structural subunits are associated with complex V deficiency, typically characterized by autosomal recessive inheritance and multisystem phenotypes. Movement disorders have been described in a subset of cases carrying autosomal dominant variants in structural subunits genes ATP5F1A and ATP5MC3. Here, we report the identification of two different ATP5F1B missense variants (c.1000A>C; p.Thr334Pro and c.1445T>C; p.Val482Ala) segregating with early-onset isolated dystonia in two families, both with autosomal dominant mode of inheritance and incomplete penetrance. Functional studies in mutant fibroblasts revealed no decrease of ATP5F1B protein amount but severe reduction of complex V activity and impaired mitochondrial membrane potential, suggesting a dominant-negative effect. In conclusion, our study describes a new candidate gene associated with isolated dystonia and confirms that heterozygous variants in genes encoding subunits of the mitochondrial ATP synthase may cause autosomal dominant isolated dystonia with incomplete penetrance, likely through a dominant-negative mechanism.

Biallelic Variants in ENDOG Associated with Mitochondrial Myopathy and Multiple mtDNA Deletions.

Endonuclease G (ENDOG) is a nuclear-encoded mitochondrial-localized nuclease. Although its precise biological function remains unclear, its proximity to mitochondrial DNA (mtDNA) makes it an excellent candidate to participate in mtDNA replication, metabolism and maintenance. Indeed, several roles for ENDOG have been hypothesized, including maturation of RNA primers during mtDNA replication, splicing of polycistronic transcripts and mtDNA repair. To date, ENDOG has been deemed as a determinant of cardiac hypertrophy, but no pathogenic variants or genetically defined patients linked to this gene have been described. Here, we report biallelic ENDOG variants identified by NGS in a patient with progressive external ophthalmoplegia, mitochondrial myopathy and multiple mtDNA deletions in muscle. The absence of the ENDOG protein in the patient's muscle and fibroblasts indicates that the identified variants are pathogenic. The presence of multiple mtDNA deletions supports the role of ENDOG in mtDNA maintenance; moreover, the patient's clinical presentation is very similar to mitochondrial diseases caused by mutations in other genes involved in mtDNA homeostasis. Although the patient's fibroblasts did not present multiple mtDNA deletions or delay in the replication process, interestingly, we detected an accumulation of low-level heteroplasmy mtDNA point mutations compared with age-matched controls. This may indicate a possible role of ENDOG in mtDNA replication or repair. Our report provides evidence of the association of ENDOG variants with mitochondrial myopathy.