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Malignant pleural mesothelioma (MPM) represents a significant health burden, with limited treatment options and poor prognosis. Despite advances in pharmacological and surgical interventions, the role of rehabilitation in MPM management remains underexplored. This study aims to assess the feasibility of a tailored pulmonary rehabilitation intervention addressing physical and respiratory function in MPM patients. A prospective pilot study was conducted on surgically treated MPM patients referred to a cardiopulmonary rehabilitation service. The intervention comprised multidisciplinary educational sessions, physical rehabilitation, and respiratory physiotherapy. Feasibility was evaluated based on dropout rates, adherence to the rehabilitation program, safety, and patient-reported outcomes. Twelve patients were initially enrolled, with seven completing the study. High adherence to physical (T1: 93.43%, T2: 82.56%) and respiratory (T1: 96.2%, T2: 92.5%) rehabilitation was observed, with minimal adverse events reported. Patient satisfaction remained high throughout the study (GPE scores at T1: 1.83 ± 1.17; T2: 2.0 ± 1.15), with improvements noted in physical function, pain management, and health-related quality of life. However, some issues, such as time constraints and lack of continuous supervision, were reported by participants. This pilot study demonstrates the feasibility and potential benefits of a tailored pulmonary rehabilitation intervention in MPM patients. Despite its promising outcomes, further research with larger samples is warranted to validate its efficacy and integrate rehabilitation as a component into the multidisciplinary management of MPM.

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., Competing Interests: M.I. received honoraria from Agilent Technologies Denmark ApS and Diaceutics PLC. C.S. received honoraria for consulting, advisory roles, speaker bureaus, and/or research grants from Bristol Myers Squibb, Astra Zeneca, Daiichi-Sankyo, Gilead, Roche SPA, Novartis, Menarini, Veracyte Inc. G.d.A. received honoraria for consulting, advisory roles, and speaker bureaus from Merck Sharp & Dohme (MSD), Novartis, AstraZeneca, Roche, and Daiichi Sankyo. G.C. received honoraria from Roche and others from Novartis, Lilly, Pfizer, Astra Zeneca, Daichii Sankyo, Ellipsis, Veracyte, Exact Science, Celcuity, Merck, BMS, Gilead, Sanofi, Menarini. N.F. received honoraria for consulting, advisory roles, speaker bureaus, travel, and/or research grants from Merck Sharp & Dohme (MSD), Merck, Novartis, AstraZeneca, Roche, Menarini, Daiichi Sankyo, GlaxoSmithKline (GSK), Gilead, Adicet Bio, Sermonix, Reply, Veracyte Inc., Leica Biosystems, and Lilly. These companies had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. All other authors have no relevant financial or non-financial interests to disclose.

Early breast cancer (BC) is the definition applied to breast-confined tumors with or without limited involvement of locoregional lymph nodes. While risk stratification is essential for guiding clinical decisions, it can be a complex endeavor in these patients due to the absence of comprehensive guidelines. Histopathological analysis and biomarker assessment play a pivotal role in defining patient outcomes. Traditional histological criteria such as tumor size, lymph node involvement, histological type and grade, lymphovascular invasion, and immune cell infiltration are significant prognostic indicators. In addition to the hormone receptor, HER2, and-in specific scenarios-BRCA1/2 testing, molecular subtyping through gene expression profiling provides valuable insights to tailor clinical decision-making. The emergence of "omics" technologies, applicable to both tissue and liquid biopsy samples, has broadened our arsenal for evaluating the risk of early BC. However, a pressing need remains for standardized methodologies and integrated pathological models that encompass multiple analytical dimensions. In this study, we provide a detailed examination of the existing strategies for early BC risk stratification, intending to serve as a practical guide for histopathologists and molecular pathologists.

Mammary Paget disease (MPD) is a rare condition primarily affecting adult women, characterized by unilateral skin changes in the nipple-areolar complex (NAC) and frequently associated with underlying breast carcinoma. Histologically, MPD is identified by large intraepidermal epithelial cells (Paget cells) with distinct characteristics. Immunohistochemical profiles aid in distinguishing MPD from other skin conditions. Clinical evaluation and imaging techniques, including magnetic resonance imaging (MRI), are recommended if MPD is suspected, although definitive diagnosis always requires histological examination. This review delves into the historical context, epidemiology, pathogenesis, clinical manifestations, and diagnosis of MPD, emphasizing the need for early detection. The classification of MPD based on pathogenesis is explored, shedding light on its varied presentations. Treatment options, including mastectomy and breast-conserving surgery, are discussed with clear guidelines for different scenarios. Adjuvant therapies are considered, particularly in cases with underlying breast cancer. Prognostic factors are outlined, underlining the importance of early intervention. Looking to the future, emerging techniques, like liquid biopsy, new immunohistochemical and molecular markers, and artificial intelligence-based image analysis, hold the potential to transform MPD diagnosis and treatment. These innovations offer hope for early detection and improved patient care, though validation through large-scale clinical trials is needed.

One of the most relevant prognostic factors in cancer staging is the presence of lymph node (LN) metastasis. Evaluating lymph nodes for the presence of metastatic cancerous cells can be a lengthy, monotonous, and error-prone process. Owing to digital pathology, artificial intelligence (AI) applied to whole slide images (WSIs) of lymph nodes can be exploited for the automatic detection of metastatic tissue. The aim of this study was to review the literature regarding the implementation of AI as a tool for the detection of metastases in LNs in WSIs. A systematic literature search was conducted in PubMed and Embase databases. Studies involving the application of AI techniques to automatically analyze LN status were included. Of 4584 retrieved articles, 23 were included. Relevant articles were labeled into three categories based upon the accuracy of AI in evaluating LNs. Published data overall indicate that the application of AI in detecting LN metastases is promising and can be proficiently employed in daily pathology practice.

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.

Incidental thyroid carcinomas (ITCs) are a fairly frequent finding in daily routine practice, with papillary thyroid microcarcinoma being the most frequent entity. In our work, we isolated incidental cases arising in thyroids removed for other cytologically indeterminate and histologically benign nodules. We retrospectively retrieved cases with available thyroid Fine Needle Aspiration (FNA, 3270 cases), selecting those with an indeterminate cytological diagnosis (Bethesda classes III−IV, 652 cases). Subsequently, we restricted the analysis to surgically treated patients (163 cases) finding an incidental thyroid carcinoma in 22 of them. We found a 13.5% ITC rate, with ITCs representing 46.8% of all cancer histologically diagnosed in this indeterminate setting. Patients received a cytological diagnosis of Bethesda class III and IV in 41% and 59% of cases, respectively. All ITC cases turned out to be papillary thyroid microcarcinomas; 36% of cases were multifocal, with foci bilaterally detected in 50% of cases. We found an overall ITC rate concordant with the literature and with our previous findings. The assignment of an indeterminate category to FNA did not increase the risk of ITCs in our cohort. Rather, a strong statistical significance (p < 0.01) was found comparing the larger size of nodules that underwent FNA and the smaller size of their corresponding ITC nodule.

Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision., Methods: A total of 3100 VABBs were retrospectively reviewed, among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients' features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate and multivariate analysis. Finally, we developed a nomogram for predicting the upstage at surgery, according to the multivariate logistic regression model., Results: The overall upgrade rate to invasive carcinoma was 10.8%. At univariate analysis, the risk of upgrade was significantly lower in patients with greater age ( p = 0.018), without post-biopsy residual lesion ( p < 0.001), with a smaller post-biopsy residual lesion size ( p < 0.001), and in the presence of low-grade DCIS only in specimens with microcalcifications ( p = 0.002). According to the final multivariable model, the predicted probability of upstage at surgery was lower than 2% in 58 patients; among these 58 patients, only one (1.7%) upstage was observed, showing a good calibration of the model., Conclusions: An easy-to-use nomogram for predicting the upstage at surgery based on radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.

Immune checkpoint inhibitors for blocking the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis are now available for squamous cell carcinoma of the head and neck (HNSCC) in relapsing and/or metastatic settings. In this work, we compared the resulting combined positive score (CPS) of PD-L1 using alternative methods adopted in routine clinical practice and determined the level of diagnostic agreement and inter-observer reliability in this setting. The study applied 5 different protocols on 40 tissue microarrays from HNSCC. The error rate of the individual protocols ranged from a minimum of 7% to a maximum of 21%, the sensitivity from 79% to 96%, and the specificity from 50% to 100%. In the intermediate group (1 ≤ CPS < 20), the majority of errors consisted of an underestimation of PD-L1 expression. In strong expressors, 5 out of 14 samples (36%) were correctly evaluated by all the protocols, but no protocol was able to correctly identify all the "strong expressors". The overall inter-observer agreement in PD-L1 CPS reached 87%. The inter-observer reliability was moderate, with an ICC of 0.774 (95% CI (0.651; 0.871)). In conclusion, our study showed moderate interobserver reliability among different protocols. In order to improve the performances, adequate specific training to evaluate PD-L1 by CPS in the HNSCC setting should be coordinated.

A meeting among expert pathologists was held in 2019 in Rome to verify the results of the previous harmonization efforts on the PD-L1 immunohistochemical testing by scoring a representative series of non-small cell lung cancer (NSCLC) digital slides. The current paper shows the results of this digital experimental meeting and the expertise achieved by the community of Italian pathologists. PD-L1 protein expression was determined using tumor proportion score (TPS), i.e., the percentage of viable tumor cells showing partial or complete membrane staining at any intensity. The gold standard was defined as the final PD-L1 score formulated by a panel of seven lung committed pathologists. PD-L1 status was clustered in three categories, namely negative (TPS < 1), low (TPS 1-49%), and high (TPS ≥ 50%). In 23 cases (71.9%) PD-L1 staining was performed using the companion diagnostic 22C3 pharmDx kit on Dako Autostainer, while in nine (28.1%) cases it was performed using the SP263 Ventana kit on BenchMark platform. A complete PD-L1 scoring agreement between the panel of experts and the participants was reached in 57.1% of cases, whereas a minor disagreement in 16.1% of cases was recorded. Italian pathologists performed best in strong positive cases (i.e., tumor proportion score TPS > 50%), whereas only 10.8% of disagreement with the gold standard was observed, and 55.6% regarded a single challenging case. The worst performance was achieved in the negative cases, with 32.0% disagreement. A significant difference resulted from the analysis of the data separated by the different clones used: 22.3% and 38.1% disagreement ( p = 0.01) was found in the group of cases analyzed by 22C3 and SP263 antibody clones, respectively. In conclusion, this workshop record proposed the application of a digital pathology platform to share controversial cases in educational meetings as an alternative possibility for improving the interpretation and reporting of specific histological tools. Due to the crucial role of PD-L1 TPS for the selection of patients for immunotherapy, the identification of unconventional approaches as virtual slides to focus experiences and give more detailed practical verifications of the standard quality reached may be a considerable option.

E-cadherin (CDH1 gene) germline mutations are associated with the development of diffuse gastric cancer in the context of the so-called hereditary diffuse gastric syndrome, and with an inherited predisposition of lobular breast carcinoma. In 2019, the international gastric cancer linkage consortium revised the clinical criteria and established guidelines for the genetic screening of CDH1 germline syndromes. Nevertheless, the introduction of multigene panel testing in clinical practice has led to an increased identification of E-cadherin mutations in individuals without a positive family history of gastric or breast cancers. This observation motivated us to review and present a novel multidisciplinary clinical approach (nutritional, surgical, and image screening) for single subjects who present germline CDH1 mutations but do not fulfil the classic clinical criteria, namely those identified as-(1) incidental finding and (2) individuals with lobular breast cancer without family history of gastric cancer (GC).