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.

Evaluation of margins during radical prostatectomy: confocal microscopy vs frozen section analysis.

OBJECTIVES: To test the performance of ex vivo fluorescence confocal microscopy (FCM; Vivascope 2500M-G4), as compared to intra-operative frozen section (IFS) analysis, to evaluate surgical margins during robot-assisted radical prostatectomy (RARP), with final pathology as the reference standard. METHODS: Overall, 54 margins in 45 patients treated with RARP were analysed with: (1) ex vivo FCM; (2) IFS analysis; and (3) final pathology. FCM margins were evaluated by two different pathologists (experienced [M.I.: 10 years] vs highly experienced [G.R.: >30 years]) as strongly negative, probably negative, doubtful, probably positive, or strongly positive. First, inter-observer agreement (Cohen's κ) between pathologists was tested. Second, we reported the sensitivity, specificity, positive predictive (PPV) and negative predictive value (NPV) of ex vivo FCM. Finally, agreement between ex vivo FCM and IFS analysis (Cohen's κ) was reported. For all analyses, four combinations of FCM results were evaluated. RESULTS: At ex vivo FCM, the inter-observer agreement between pathologists ranged from moderate (κ = 0.74) to almost perfect (κ = 0.90), according to the four categories of results. Indeed, at ex vivo FCM, the highly experienced pathologist reached the best balance between sensitivity (70.5%) specificity (91.8%), PPV (80.0%) and NPV (87.1%). Conversely, on IFS analysis, the sensitivity, specificity, PPV and NPV were, respectively, 88.2% vs 100% vs 100% vs 94.8%. The agreement between the ex vivo FCM and IFS analyses ranged from moderate (κ = 0.62) to strong (κ = 0.86), according to the four categories of results. CONCLUSION: Evaluation of prostate margins at ex vivo FCM appears to be feasible and reliable. The agreement between readers encourages its widespread use in daily practice. Nevertheless, as of today, the performance of FCM seems to be sub-par when compared to the established standard of care (IFS analysis).

A Phase 3 Prospective Randomized Trial to Evaluate the Impact of Augmented Reality During Robot-assisted Radical Prostatectomy on the Rates of Postoperative Surgical Margins: A Clinical Trial Protocol.

We designed a phase 3, prospective, randomized trial to evaluate the impact of augmented reality and augmented reality frozen section analysis in reducing the rates of positive surgical margins after robot-assisted radical prostatectomy.

Proteomic insights into mental health status: plasma markers in young adults.

Global emphasis on enhancing prevention and treatment strategies necessitates an increased understanding of the biological mechanisms of psychopathology. Plasma proteomics is a powerful tool that has been applied in the context of specific mental disorders for biomarker identification. The p-factor, also known as the "general psychopathology factor", is a concept in psychopathology suggesting that there is a common underlying factor that contributes to the development of various forms of mental disorders. It has been proposed that the p-factor can be used to understand the overall mental health status of an individual. Here, we aimed to discover plasma proteins associated with the p-factor in 775 young adults in the FinnTwin12 cohort. Using liquid chromatography-tandem mass spectrometry, 13 proteins with a significant connection with the p-factor were identified, 8 of which were linked to epidermal growth factor receptor (EGFR) signaling. This exploratory study provides new insight into biological alterations associated with mental health status in young adults.

Upregulation of Integrin beta-3 in astrocytes upon Alzheimer's disease progression in the 5xFAD mouse model.

Integrins are receptors that have been linked to various brain disorders, including Alzheimer's disease (AD), the most prevalent neurodegenerative disorder. While Integrin beta-3 (ITGB3) is known to participate in multiple cellular processes such as adhesion, migration, and signaling, its specific role in AD remains poorly understood, particularly in astrocytes, the main glial cell type in the brain. In this study, we investigated alterations in ITGB3 gene and protein expression during aging in different brain regions of the 5xFAD mouse model of AD and assessed the interplay between ITGB3 and astrocytes. Primary cultures from adult mouse brains were used to gain further insight into the connection between ITGB3 and amyloid beta (Aß) in astrocytes. In vivo studies showed a correlation between ITGB3 and the astrocytic marker GFAP in the 5xFAD brains, indicating its association with reactive astrocytes. In vitro studies revealed increased gene expression of ITGB3 upon Aß treatment. Our findings underscore the potential significance of ITGB3 in astrocyte reactivity in the context of Alzheimer's disease.

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.

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Since the release of the DESTINY-Breast04 (DB-04) trial findings in June 2022, the field of pathology has seen a renaissance of HER2 as a predictive biomarker in breast cancer. The trial focused on patients with metastatic breast cancer who were classified as "HER2-low," i.e., those with immunohistochemistry (IHC) HER2 1 + or 2 + and negative in situ hybridization (ISH) results. The study revealed that treating these patients with trastuzumab deruxtecan (T-DXd) instead of the oncologist's chosen chemotherapy led to outstanding improvements in survival. This has challenged the existing binary HER2 pathological classification system, which categorized tumors as either positive (overexpression/amplification) or negative, as per the ASCO/CAP 2018 guideline reaffirmed by ASCO/CAP 2023 guideline update. Given that DB-04 excluded patients with HER2 IHC score 0 status, the results of the ongoing DB-06 trial may shed further light on the potential benefits of T-DXd therapy for these patients. Roughly half of all breast cancers are estimated to belong to the HER2-low category, which does not represent a distinct or specific subtype of cancer. Instead, it encompasses a diverse group of tumors that exhibit clinical, morphological, immunohistochemical, and molecular variations. However, HER2-low offers a distinctive biomarker status that identifies a specific therapeutic regimen (i.e., T-DXd) linked to a favorable prognosis in breast cancer. This unique association emphasizes the importance of accurately identifying these tumors. Differentiating between a HER2 IHC score 0 and score 1 + has not been clinically significant until now. To ensure accurate classification and avoid misdiagnosis, it is necessary to adopt standardized procedures, guidelines, and specialized training for pathologists in interpreting HER2 expression in the lower spectrum. Additionally, the utilization of artificial intelligence holds promise in supporting this endeavor. Here, we address the current state of the art and unresolved issues in assessing HER2-low status, with a particular emphasis on the score 0. We explore the dilemma surrounding the exclusion of HER2-zero patients from potentially beneficial therapy based on traditional HER2 testing. Additionally, we examine the clinical context, considering that DB-04 primarily involved heavily pretreated late-stage metastatic breast cancers. We also delve into emerging evidence suggesting that extrapolating HER2-low status from the original diagnosis may lead to misleading results. Finally, we provide recommendations for conducting high-quality testing and propose a standardized pathology report in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Clinicopathological features and survival outcomes of luminal-like breast tumors with estrogen receptor loss at metastatic recurrence: A case-control study.

INTRODUCTION: Estrogen receptor (ER) loss at metastatic relapse occurs in up to 20% of luminal-like primary breast tumors. Data about clinicopathological features associated with ER loss and its prognostic significance are limited. METHODS: In a nested-case-control study, we compared clinicopathological characteristics and clinical outcomes between a cohort of 51 patients with primary ER+ /HER2- and paired triple-negative metastasis (LUM-TN) and two control cohorts of paired early-metastatic ER+ /HER2- (LUM-LUM, n = 50) and triple-negative (TN-TN, n = 49) breast cancers. Stromal tumor-infiltrating lymphocytes (TILs) were assessed according to the TILs Working Group recommendations as continuous and discrete variables with cutoffs (20%, 40%). RESULTS: LUM-TN tumors had lower ER expression than LUM-LUM tumors, but lower grade and Ki67 than TN-TN cases. Median distant-metastasis free survival was similar for LUM-TN and LUM-LUM cohorts, but significantly longer than in TN-TN cases (log-rank P < 0.001). LUM-TN and TN-TN cohorts had a comparable survival from the time of metastatic recurrence, which was significantly shorter than in patients with LUM-LUM tumors (log-rank P < 0.001). High TILs were associated with worse outcomes in patients with ER loss (P < 0.001). CONCLUSIONS: Breast tumors with ER loss at metastatic relapse have intermediate features and outcomes compared with metastatic luminal-like and ab initio triple-negative tumors. Further investigation on the biological mechanisms underpinning the loss of ER expression is ongoing.

Emissions from modern engines induce distinct effects in human olfactory mucosa cells, depending on fuel and aftertreatment.

Ultrafine particles (UFP) with a diameter of ≤0.1 µm, are contributors to ambient air pollution and derived mainly from traffic emissions, yet their health effects remain poorly characterized. The olfactory mucosa (OM) is located at the rooftop of the nasal cavity and directly exposed to both the environment and the brain. Mounting evidence suggests that pollutant particles affect the brain through the olfactory tract, however, the exact cellular mechanisms of how the OM responds to air pollutants remain poorly known. Here we show that the responses of primary human OM cells are altered upon exposure to UFPs and that different fuels and engines elicit different adverse effects. We used UFPs collected from exhausts of a heavy-duty-engine run with renewable diesel (A0) and fossil diesel (A20), and from a modern diesel vehicle run with renewable diesel (Euro6) and compared their health effects on the OM cells by assessing cellular processes on the functional and transcriptomic levels. Quantification revealed all samples as UFPs with the majority of particles being ≤0.1 µm by an aerodynamic diameter. Exposure to A0 and A20 induced substantial alterations in processes associated with inflammatory response, xenobiotic metabolism, olfactory signaling, and epithelial integrity. Euro6 caused only negligible changes, demonstrating the efficacy of aftertreatment devices. Furthermore, when compared to A20, A0 elicited less pronounced effects on OM cells, suggesting renewable diesel induces less adverse effects in OM cells. Prior studies and these results suggest that PAHs may disturb the inflammatory process and xenobiotic metabolism in the OM and that UFPs might mediate harmful effects on the brain through the olfactory route. This study provides important information on the adverse effects of UFPs in a human-based in vitro model, therefore providing new insight to form the basis for mitigation and preventive actions against the possible toxicological impairments caused by UFP exposure.

Immune microenvironment dynamics in breast cancer during pregnancy: impact of gestational age on tumor-infiltrating lymphocytes and prognosis.

Background: Breast cancer during pregnancy (PrBC) is a rare condition known for its aggressive clinical behavior. The presence of tumor-infiltrating lymphocytes (TILs) has been shown to have a significant impact on the prognosis of these patients. Despite some biological characteristics of the tumor that may differ depending on the gestational age, little is known about the dynamics of the immune landscape within the tumor microenvironment (TME) in PrBC. Therefore, in this study, our objective was to gain comprehensive insights into the relationship between gestational age at breast cancer diagnosis and the composition of the TME. Methods: n = 108 PrBC were selected from our institutional registry and categorized based on the gestational age by trimester. For all cases, TILs were profiled according to the International TILs Working Group recommendations, and subtyped by CD4, CD8, and forkhead box P3 (FOXP3) immunohistochemistry. PD-L1 was tested according to the combined positive score (CPS) using the IHC 22C3 pharmDx assay, with a cutoff value of ≥10 for positivity. The statistical approach encompassed Fisher's and Chi-squared tests, with appropriate adjustments for multiple comparisons, logistic regression models, and survival analyses based on the Kaplan-Meier method. Results: The proportion of patients with poorly differentiated (G3) neoplasms increased as the gestational age advanced (first trimester, n = 25, 56.8%; second trimester, n = 27, 69.2%; third trimester, n = 21, 87.5%; p = 0.03). The histologic subtypes as well as the hormone receptor (HR) and HER2 status did not show significant changes across different pregnancy trimesters. In the HR+/HER2- subtype, there was a higher proportion of tumors with high/moderate TILs in the early phases of pregnancy, similar to FOXP3 expression (TILs: first trimester, n = 10, 35.7%; second trimester, n = 2, 10.5%; third trimester, n = 0; p = 0.02; FOXP3: first trimester, n = 10, 40%; second trimester, n = 3, 15.8%; third trimester, n = 0; p = 0.03). The median follow-up for our cohort was 81 months. Patients who relapsed after a breast cancer diagnosis during the first trimester were more frequently PD-L1-negative, unlike those with no disease recurrence (n = 9, 100% vs. n = 9, 56.3%; p = 0.03; hormone therapy and n = 9, 100% vs. n = 7, 53.9%; p = 0.02; chemotherapy). No statistically significant differences were seen among the three trimesters in terms of survival outcome. Conclusion: The TME dynamics of HR+/HER2- PrBC vary based on gestational age, suggesting that immune tolerance expression during later gestational age could explain the increased aggressiveness of tumors diagnosed at that stage.

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.

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.

Characterization of the immune environment in pregnancy-associated breast cancer.

Pregnancy-associated breast cancer (PrBC) is a rare and clinically challenging condition. Specific immune mechanisms and pathways are involved in maternal-fetal tolerance and tumor-host immunoediting. The comprehension of the molecular processes underpinning this immune synergy in PrBC is needed to improve patients' clinical management. Only a few studies focused on the immune biology of PrBC and attempted to identify bona fide biomarkers. Therefore, clinically actionable information remains extremely puzzling for these patients. In this review article, we discuss the current knowledge on the immune environment of PrBC, in comparison with pregnancy-unrelated breast cancer and in the context of maternal immune changes during pregnancy. A particular emphasis is given to the actual role of potential immune-related biomarkers for PrBC clinical management.

Pregnancy-associated breast cancer (PrBC) affects about 4% of women with breast cancer who are of childbearing age. Managing these tumors is difficult due to interactions between the mother, fetus and tumor. These interactions cause changes in the immune system of patients with PrBC. Understanding how the immune system responds to PrBC may lead to better ways of managing the disease. This review focuses on the current knowledge of the immune system in PrBC, including which components can be used as biomarkers to improve clinical management.

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.

Pathological identification of HER2-low breast cancer: Tips, tricks, and troubleshooting for the optimal test.

The introduction of novel anti-HER2 antibody-drug conjugates (ADC) for the treatment of HER2-low breast cancers has transformed the traditional dichotomy of HER2 status to an expanded spectrum. However, the identification of HER2-low (i.e., immunohistochemistry (IHC) score 1 + or IHC score 2+, without gene amplification) tumors is challenged by methodological and analytical variables that might influence the sensitivity and reproducibility of HER2 testing. To open all possible therapeutic opportunities for HER2-low breast cancer patients the implementation of more accurate and reproducible testing strategies is mandatory. Here, we provide an overview of the existing barriers that may trouble HER2-low identification in breast cancer and discuss practical solutions that could enhance HER-low assessment.

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.

The molecular landscape of breast mucoepidermoid carcinoma.

Mucoepidermoid carcinoma (MEC) of the breast is an extremely rare salivary gland-type tumor characterized by epidermoid, basaloid, intermediate, and/or mucinous cells arranged in solid and cystic patterns. Despite their triple-negative phenotype, breast MECs are generally considered low-risk malignancies but their biology is largely unexplored; therefore, guidelines for clinical management are lacking. Here, we sought to characterize the molecular landscape of breast MECs. Thirteen cases were histologically reviewed, characterized for tumor-infiltrating lymphocytes (TILs), and were subjected to immunohistochemistry for programmed death-ligand 1 (PD-L1, clone 22C3), EGFR, and amphiregulin (AREG). Rearrangements in MAML2 and EWSR1 were investigated by fluorescent in situ hybridization. Targeted next-generation sequencing of 161 genes was performed on eight cases. Most MECs had low histological grade (n = 10, 77%), with the presence of TILs (n = 9/12; 75%) and PD-L1 combined positive score ranging from 10 to 20 (n = 4/6; 67%). All cases showed EGFR and AREG overexpression and were fusion negative. Enrichment of genetic alterations was observed in PI3K/AKT/mTOR and cell cycle regulation pathways, while only one case harbored TP53 mutations. This is the first study providing extensive molecular data on breast MECs and the largest collection of cases available to date in the literature. Breast MECs lack TP53 mutations found in high-grade forms of triple-negative breast cancers and MAML2 or EWSR1 rearrangements pathognomonic of salivary MECs. Triple-negativity and PD-L1 positivity suggest a window of opportunity for immunotherapy in these patients. The EGFR/AREG axis activation, coupled with the mutational patterns in PI3K/AKT/mTOR and cell cycle pathways warrants caution in considering MECs as low-risk neoplasms.

Unlocking the Resistance to Anti-HER2 Treatments in Breast Cancer: The Issue of HER2 Spatial Distribution.

Approximately 15% of breast cancers are classified as HER2-positive, with an amplification of the ERBB2 gene and/or an overexpression of the HER2 protein. Up to 30% of HER2-positive breast cancers shows heterogeneity in HER2 expression and different patterns of spatial distribution, i.e., the variability in the distribution and expression of the HER2 protein within a single tumour. Spatial heterogeneity may potentially affect treatment, response, assessment of HER2 status and consequently, may impact on the best treatment strategy. Understanding this feature can help clinicians to predict response to HER2-targeted therapies and patient outcomes, and to fine tune treatment decisions. This review summarizes the available evidence on HER2 heterogeneity and spatial distribution and how this may affect current available treatment choices, exploring possible opportunities for overcoming this issue, such as novel pharmacological agents, belonging to the group of antibody-drug conjugates.

Malignancies in Patients with Celiac Disease: Diagnostic Challenges and Molecular Advances.

Celiac disease (CD) is a multiorgan autoimmune disorder of the chronic intestinal disease group characterized by duodenal inflammation in genetically predisposed individuals, precipitated by gluten ingestion. The pathogenesis of celiac disease is now widely studied, overcoming the limits of the purely autoimmune concept and explaining its hereditability. The genomic profiling of this condition has led to the discovery of numerous genes involved in interleukin signaling and immune-related pathways. The spectrum of disease manifestations is not limited to the gastrointestinal tract, and a significant number of studies have considered the possible association between CD and neoplasms. Patients with CD are found to be at increased risk of developing malignancies, with a particular predisposition of certain types of intestinal cancer, lymphomas, and oropharyngeal cancers. This can be partially explained by common cancer hallmarks present in these patients. The study of gut microbiota, microRNAs, and DNA methylation is evolving to find the any possible missing links between CD and cancer incidence in these patients. However, the literature is extremely mixed and, therefore, our understanding of the biological interplay between CD and cancer remains limited, with significant implications in terms of clinical management and screening protocols. In this review article, we seek to provide a comprehensive overview of the genomics, epigenomics, and transcriptomics data on CD and its relation to the most frequent types of neoplasms that may occur in these patients.