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Introduction: Neuroendocrine neoplasms (NENs) represent a complex group of tumors arising from neuroendocrine cells, characterized by heterogeneous behavior and challenging diagnostics. Despite advancements in medical technology, NENs present a major challenge in early detection, often leading to delayed diagnosis and variable outcomes. This review aims to provide an in-depth analysis of current diagnostic methods as well as the evolving and future directions of diagnostic strategies for NENs. Area covered: The review extensively covers the evolution of diagnostic tools for NENs, from traditional imaging and biochemical tests to advanced genomic profiling and next-generation sequencing. The emerging role of technologies such as artificial intelligence, machine learning, and liquid biopsies could improve diagnostic precision, as could the integration of imaging modalities such as positron emission tomography (PET)/magnetic resonance imaging (MRI) hybrids and innovative radiotracers. Expert opinion: Despite progress, there is still a significant gap in the early diagnosis of NENs. Bridging this diagnostic gap and integrating advanced technologies and precision medicine are crucial to improving patient outcomes. However, challenges such as low clinical awareness, limited possibility of noninvasive diagnostic tools and funding limitations for rare diseases like NENs are acknowledged.

Artificial intelligence (AI) is of considerable interest in the healthcare community including its diagnostic applications for thyroid nodules in assisting both radiology and FNA assessment. Fine-needle aspiration (FNA) helps distinguishing benign from malignant thyroid nodules and is a crucial step in the initial diagnosis of cancer. The classification of some lesions can be challenging, and the use of AI in some cases may become essential in order not to give an indeterminate result to the lesion. In this review, we summarize the available evidence regarding the application of AI in thyroid imaging and cytopathology. There are now considerable applications in digital waiting to be approved that will save time and cut costs. The published literature to date has shown promising results. However, future work is required to better define how this technology can be exploited in routine cytopathology practice.

SETBP1 mutations are found in various clonal myeloid disorders. However, it is unclear whether they can initiate leukemia, because SETBP1 mutations typically appear as later events during oncogenesis. To answer this question, we generated a mouse model expressing mutated SETBP1 in hematopoietic tissue: this model showed profound alterations in the differentiation program of hematopoietic progenitors and developed a myeloid neoplasm with megakaryocytic dysplasia, splenomegaly, and bone marrow fibrosis, prompting us to investigate SETBP1 mutations in a cohort of 36 triple-negative primary myelofibrosis (TN-PMF) cases. We identified 2 distinct subgroups, one carrying SETBP1 mutations and the other completely devoid of somatic variants. Clinically, a striking difference in disease aggressiveness was noted, with patients with SETBP1 mutation showing a much worse clinical course. In contrast to myelodysplastic/myeloproliferative neoplasms, in which SETBP1 mutations are mostly found as a late clonal event, single-cell clonal hierarchy reconstruction in 3 patients with TN-PMF from our cohort revealed SETBP1 to be a very early event, suggesting that the phenotype of the different SETBP1+ disorders may be shaped by the opposite hierarchy of the same clonal SETBP1 variants.

ALK and ROS1 fusions are effectively targeted by tyrosine kinase inhibitors (TKIs), however patients inevitably relapse after an initial response, often due to kinase domain mutations. We investigated circulating DNA from TKI-relapsed NSCLC patients by deep-sequencing. New EML4::ALK substitutions, L1198R, C1237Y and L1196P, were identified in the plasma of NSCLC ALK patients and characterized in a Ba/F3 cell model. Variants C1237Y and L1196P demonstrated pan-inhibitor resistance across 5 clinical and 2 investigational TKIs.

The application of innovative spatial proteomics techniques, such as those based upon matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology, has the potential to impact research in the field of nephropathology. Notwithstanding, the possibility to apply this technology in more routine diagnostic contexts remains limited by the alternative fixatives employed by this ultraspecialized diagnostic field, where most nephropathology laboratories worldwide use bouin-fixed paraffin-embedded (BFPE) samples. Here, the feasibility of performing MALDI-MSI on BFPE renal tissue is explored, evaluating variability within the trypsin-digested proteome as a result of different preanalytical conditions and comparing them with the more standardized formalin-fixed paraffin-embedded (FFPE) counterparts. A large proportion of the features (270, 68.9%) was detected in both BFPE and FFPE renal samples, demonstrating only limited variability in signal intensity (10.22-10.06%). Samples processed with either fixative were able to discriminate the principal parenchyma regions along with diverse renal substructures, such as glomeruli, tubules, and vessels. This was observed when performing an additional "stress test", showing comparable results in both BFPE and FFPE samples when the distribution of several amyloid fingerprint proteins was mapped. These results suggest the utility of BFPE tissue specimens in MSI-based nephropathology research, further widening their application in this field.

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.

Background. Three different histological scores—histopathologic classification (Berden), Renal Risk Score (RRS) and the Mayo Clinic Chronicity Score (MCCS)—for anti-neutrophil cytoplasmic antibody (ANCA)-associated glomerulonephritis (ANCA-GN) were compared to evaluate their association with patient and kidney prognosis of ANCA-GN. Methods. Patients aged >18 years with at least 1 year of follow-up and biopsy-proven ANCA-GN entered this retrospective study. Renal biopsies were classified according to Berden’s classification, RRS and MCCS. The first endpoint was end-stage kidney disease (ESKD), defined as chronic dialysis or estimated glomerular filtration rate <15 mL/min/1.73 m2. The second endpoint was ESKD or death. Results. Of 152 patients 84 were males, with median age of 63.8 years and followed for 46.9 (interquartile range 12.8–119) months, 59 (38.8%) reached the first endpoint and 20 died. The Kaplan–Meier curves showed that Berden and RRS were associated with first (Berden: P = .004, RRS: P < .001) and second (Berden: P = .001, RRS: P < .001) endpoint, MCCS with the first endpoint only when minimal + mild vs moderate + severe groups were compared (P = .017), and with the second endpoint (P < .001). Among the clinical/histological presentation features, arterial hypertension [odds ratio (OR) = 2.75, confidence interval (95% CI) 1.50–5.06; P = .0011], serum creatinine (OR = 1.17, 95% CI 1.09–1.25; P < .0001), and the percentage of normal glomeruli (OR = 0.97, 95% CI 0.96–0.99; P = .009) were the independent predictors of ESKD at multivariate analysis. When the three scores were included in multivariate analysis, RRS (OR = 2.21, 95% CI 1.15–4.24; P = .017) and MCCS (OR = 2.03, 95% CI 1.04–3.95; P = .037) remained predictive of ESKD, but Berden (OR = 1.17, 95% CI 0.62–2.22; P = .691) did not. Conclusion. RRS and MCCS scores were independent predictors of kidney survival together with high serum creatinine and arterial hypertension at diagnosis

Kidneys are often targets of systemic vasculitis (SVs), being affected in many different forms and representing a possible sentinel of an underlying multi-organ condition. Renal biopsy still remains the gold standard for the identification, characterization and classification of these diseases, solving complex differential diagnosis thanks to the combined application of light microscopy (LM), immunofluorescence (IF) and electron microscopy (EM). Due to the progressively increasing complexity of renal vasculitis classification systems (e.g. pauci-immune vs immune complex related forms), a clinico-pathological approach is mandatory and adequate technical and interpretative expertise in nephropathology is required to ensure the best standard of care for our patients. In this complex background, the present review aims at summarising the current knowledge and challenges in the world of renal vasculitis, unveiling the potential role of the introduction of digital pathology in this setting, from the creation of hub-spoke networks to the future application of artificial intelligence (AI) tools to aid in the diagnostic and scoring/classification process.

This article describes how the transcriptional alterations of the innate immune system divide dysplasias into aggressive forms that, despite the treatment, relapse quickly and more easily, and others where the progression is slow and more treatable. It elaborates on how the immune system can change the extracellular matrix, favoring neoplastic progression, and how infections can enhance disease progression by increasing epithelial damage due to the loss of surface immunoglobulin and amplifying the inflammatory response. We investigated whether these dysregulated genes were linked to disease progression, delay, or recovery. These transcriptional alterations were observed using the RNA-based next-generation sequencing (NGS) panel Oncomine Immune Response Research Assay (OIRRA) to measure the expression of genes associated with lymphocyte regulation, cytokine signaling, lymphocyte markers, and checkpoint pathways. During the analysis, it became apparent that certain alterations divide dysplasia into two categories: progressive or not. In the future, these biological alterations are the first step to provide new treatment modalities with different classes of drugs currently in use in a systemic or local approach, including classical chemotherapy drugs such as cisplatin and fluorouracile, older drugs like fenretinide, and new checkpoint inhibitor drugs such as nivolumab and pembrolizumab, as well as newer options like T cell therapy (CAR-T). Following these observed alterations, it is possible to differentiate which dysplasias progress or not or relapse quickly. This information could, in the future, be the basis for determining a close follow-up, minimizing surgical interventions, planning a correct and personalized treatment protocol for each patient and, after specific clinical trials, tailoring new drug treatments.

The diagnostic assessment of thyroid nodules is hampered by the persistence of uncertainty in borderline cases, and further complicated by the inclusion of non-invasive follicular tumor with papillary-like nuclear features (NIFTP) as a less aggressive alternative to papillary thyroid carcinoma (PTC). In this setting, computational methods might facilitate the diagnostic process by unmasking key nuclear characteristics of NIFTPs. The main aims of this work were to (1) identify morphometric features of NIFTP and PTC that are interpretable for the human eye, and (2) develop a deep learning model for multi-class segmentation as a support tool to reduce diagnostic variability. Our findings confirmed that nuclei in NIFTP and PTC share multiple characteristics, setting them apart from hyperplastic nodules (HP). The morphometric analysis identified 15 features that can be translated into nuclear alterations readily understandable by pathologists, such as a remarkable inter-nuclear homogeneity for HP in contrast to a major complexity in the chromatin texture of NIFTP, and to the peculiar pattern of nuclear texture variability of PTC. A few NIFTP cases with available NGS data were also analyzed to initially explore the impact of RAS-related mutations on nuclear morphometry. Finally, a pixel-based deep learning model was trained and tested on whole slide images (WSIs) of NIFTP, PTC, and HP cases. The model, named NUTSHELL (NUclei from Thyroid tumors Segmentation to Highlight Encapsulated Low-malignant Lesions), successfully detected and classified the majority of nuclei in all WSIs' tiles, showing comparable results with already well-established pathology nuclear scores. NUTSHELL provides an immediate overview of NIFTP areas and can be used to detect microfoci of PTC within extensive glandular samples or identify lymph node metastases. NUTSHELL can be run inside WSInfer with an easy rendering in QuPath, thus facilitating the democratization of digital pathology.

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.

Objectives: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine. Methods: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer. Results: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival. Conclusions: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

Kidney transplantation is the best treatment for end-stage renal disease since it offers the greatest survival benefit compared to dialysis. The gap between the number of renal transplants performed and the number of patients awaiting renal transplants leads to a steadily increasing pressure on the scientific community. Kidney preimplantation biopsy is used as a component of the evaluation of organ quality before acceptance for transplantation. However, the reliability and predictive value of biopsy data are controversial. Most of the previously proposed predictive models were not associated with graft survival, but what has to be reaffirmed is that histologic examination of kidney tissue can provide an objective window on the state of the organ that cannot be deduced from clinical records and renal functional studies. The balance of evidence indicates that reliable decisions about donor suitability must be made based on the overall picture. This work discusses recent trends that can reduce diagnostic timing and variability among players in the decision-making process that lead to kidney transplants, from the pathologist’s perspective.

BACKGROUND: Nephritis is a common manifestation of IgA vasculitis and is morphologically indistinguishable from IgA nephropathy. While MEST-C scores are predictive of kidney outcomes in IgA nephropathy, their value in IgA vasculitis nephritis has not been investigated in large multiethnic cohorts. METHODS: Biopsies from 262 children and 99 adults with IgA vasculitis nephritis ( N =361) from 23 centers in North America, Europe, and Asia were independently scored by three pathologists. MEST-C scores were assessed for correlation with eGFR/proteinuria at biopsy. Because most patients ( N =309, 86%) received immunosuppression, risk factors for outcomes were evaluated in this group using latent class mixed models to identify classes of eGFR trajectories over a median follow-up of 2.7 years (interquartile range, 1.2-5.1). Clinical and histologic parameters associated with each class were determined using logistic regression. RESULTS: M, E, T, and C scores were correlated with either eGFR or proteinuria at biopsy. Two classes were identified by latent class mixed model, one with initial improvement in eGFR followed by a late decline (class 1, N =91) and another with stable eGFR (class 2, N =218). Class 1 was associated with a higher risk of an established kidney outcome (time to ≥30% decline in eGFR or kidney failure; hazard ratio, 5.84; 95% confidence interval, 2.37 to 14.4). Among MEST-C scores, only E1 was associated with class 1 by multivariable analysis. Other factors associated with class 1 were age 18 years and younger, male sex, lower eGFR at biopsy, and extrarenal noncutaneous disease. Fibrous crescents without active changes were associated with class 2. CONCLUSIONS: Kidney outcome in patients with biopsied IgA vasculitis nephritis treated with immunosuppression was determined by clinical risk factors and endocapillary hypercellularity (E1) and fibrous crescents, which are features that are not part of the International Study of Diseases of Children classificatio

Transplantation of an organ from a donor carries an unavoidable risk of tumor transmission. The need to extend the donor pool increases the use of organs from donors with malignancies and potential disease transmission is a constant tension influencing donor suitability decisions. Current classification systems for the assessment of donor malignancy transmission risk have evolved from reports of potential transmission events in recipients to national donation and transplant surveillance agencies. Although the risk of malignancy transmission is very low in the general transplant setting it must constantly be balanced with the transplant benefits. Guidelines are mainly based on large registries and sparse case reports of transmission, so they cannot cover all the possible situations. For this reason, in 2004 in Italy, the National Transplant Center gave rise to the Second Opinion Service, charged by the Ministry of Health, by structuring expertise in diagnostic oncology and risk transmission and making it available to the Italian Transplant Centers. In this paper the registry of the Italian Oncological Second Opinion was reviewed, from 2016 to 2018, to detail the most frequent and problematic neoplastic topics addressed, those are separately reported and discussed. Furthermore, a review of the most recent strategies and risk stratification is provided, according to the most recent literature evidence and to the European Guidelines.

Background: Immunotherapy represented a turning point for treating extensive small-cell lung cancer (ES-SCLC). Although, many issues remain debated. Methods: A group of Italian medical and radiation oncologists with expertise in managing patients with ES-SCLC developed a list of statements divided in six areas of interest. The Delphi method was used to assess the consensus on the defined list of statements. Results: 32 statements were included in the final list to be voted by the Delphi panel, and 26 reached a consensus on the agreement. A prompt involvement of a multidisciplinary team is a priority to provide an integrated treatment strategy. First-line recommended treatment is immunotherapy in combination with platinum-based chemotherapy and etoposide for four cycles followed by maintenance immunotherapy. Conclusions: While awaiting new data from clinical trials and real-world studies, these recommendations can represent a useful tool to guide the management of ES-SCLC patients in daily practice.

Molecular biomarker testing is increasingly becoming standard of care for advanced non-small cell lung cancer (NSCLC). Tissue and liquid biopsy-based next-generation sequencing (NGS) is now highly recommended and has become an integral part of the routine management of advanced NSCLC patients. This highly sensitive approach can simultaneously and efficiently detect multiple biomarkers even in scant samples. However full optimization of NGS in clinical practice requires accurate reporting and interpretation of NGS findings. Indeed, as the number of NSCLC biomarkers continues to grow, clinical reporting of NGS data is becoming increasingly complex. In this scenario, achieving standardization, simplification, and improved readability of NGS reports is key to ensuring timely and appropriate treatment decisions. In an effort to address the complexity and lengthy reporting of NGS mutation results, an Italian group of 14 healthcare professionals involved in NSCLC management convened in 2023 to address the content, structure, and ease-of-use of NGS reporting practices and proposed a standard report template for clinical use This article presents the key discussion points addressed by the Italian working group and describes the essential elements of the report template.

Background: The molecular diagnostic and therapeutic pathway of Non-Small Cell Lung Cancer (NSCLC) stands as a successful example of precision medicine. The scarcity of material and the increasing number of biomarkers to be tested have prompted the routine application of next-generation-sequencing (NGS) techniques. Despite its undeniable advantages, NGS involves high costs that may impede its broad adoption in laboratories. This study aims to assess the detailed costs linked to the integration of NGS diagnostics in NSCLC to comprehend their financial impact. Materials and methods: The retrospective analysis encompasses 210 cases of early and advanced stages NSCLC, analyzed with NGS and collected at the IRCCS San Gerardo dei Tintori Foundation (Monza, Italy). Molecular analyses were conducted on FFPE samples, with an hotspot panel capable of detecting DNA and RNA variants in 50 clinically relevant genes. The economic analysis employed a full-cost approach, encompassing direct and indirect costs, overheads, VAT (Value Added Tax). Results: We estimate a comprehensive cost for each sample of €1048.32. This cost represents a crucial investment in terms of NSCLC patients survival, despite constituting only around 1% of the expenses incurred in their molecular diagnostic and therapeutic pathway. Conclusions: The cost comparison between NGS test and the notably higher therapeutic costs highlights that the diagnostic phase is not the limiting economic factor. Developing NGS facilities structured in pathology networks may ensure appropriate technical expertise and efficient workflows.

The assessment of programmed death-ligand 1 (PD-L1) combined positive scoring (CPS) in head and neck squamous cell carcinoma (HNSCC) is challenged by pre-analytical and inter-observer variabilities. An educational program to compare the diagnostic performances between local pathologists and a board of pathologists on 11 challenging cases from different Italian pathology centers stained with PD-L1 immunohistochemistry on a digital pathology platform is reported. A laboratory-developed test (LDT) using both 22C3 (Dako) and SP263 (Ventana) clones on Dako or Ventana platforms was compared with the companion diagnostic (CDx) Dako 22C3 pharm Dx assay. A computational approach was performed to assess possible correlations between stain features and pathologists’ visual assessments. Technical discordances were noted in five cases (LDT vs. CDx, 45%), due to an abnormal nuclear/cytoplasmic diaminobenzidine (DAB) stain in LDT (n = 2, 18%) and due to variation in terms of intensity, dirty background, and DAB droplets (n = 3, 27%). Interpretative discordances were noted in six cases (LDT vs. CDx, 54%). CPS remained unchanged, increased, or decreased from LDT to CDx in three (27%) cases, two (18%) cases, and one (9%) case, respectively, around relevant cutoffs (1 and 20, k = 0.63). Differences noted in DAB intensity/distribution using computational pathology partly explained the LDT vs. CDx differences in two cases (18%). Digital pathology may help in PD-L1 scoring, serving as a second opinion consultation platform in challenging cases. Computational and artificial intelligence tools will improve clinical decision-making and patient outcomes.

In the molecular era, proper archival conditions within pathology laboratories are crucial, especially for formalin-fixed paraffin-embedded (FFPE) tissue specimens retrieved years after the original diagnosis. Indeed, improper preservation can impact the integrity of nucleic acids and protein antigens. This study evaluates the quality status of stored FFPE blocks using multilevel omics approaches. FFPE blocks from 45 Non-Small Cell Lung Carcinoma (NSCLC) cases were analyzed. The blocks were collected from six different pathology archives across Italy with distinct environmental characteristics. Nucleic acids’ quantity and quality, as well as protein antigens, were assessed using various techniques, including MALDI-MSI. RNA was quantitatively higher, but more fragmented, compared to DNA. DNA quantity and quality were suitable for molecular analyses in 94.4% and 62.3% of samples, respectively. RNA quantity was adequate across all samples, but it was optimal only in 22.3% of cases. DNA quality started to deteriorate after 6–8 years, whereas RNA quality diminished only after 10 years of storage. These data might suggest a particular DNA susceptibility to FFPE blocks conservation. Immunohistochemical intensity decreased significantly after 6–8 years of storage, and MALDI-MSI analysis revealed that younger tissue blocks contained more unique proteomic signals than the older ones. This study emphasizes the importance of proper FFPE archiving conditions for molecular analyses. Governance should prioritize attention to pathology archives to ensure quality preservation and optimize predictive testing. By elucidating the nuances of FFPE block storage, this research paves the way for enhanced molecular diagnostics and therapeutic insights regarding oncology and beyond.

Aims: To date, precision medicine has revolutionized the clinical management of Non-Small Cell Lung Cancer (NSCLC). International societies approved a rapidly improved mandatory testing biomarkers panel for the clinical stratification of NSCLC patients, but harmonized procedures are required to optimize the diagnostic workflow. In this context a knowledge-based database (Biomarkers ATLAS, https://biomarkersatlas.com/) was developed by a supervising group of expert pathologists and thoracic oncologists collecting updated clinical and molecular records from about 80 referral Italian institutions. Here, we audit molecular and clinical data from n = 1100 NSCLC patients collected from January 2019 to December 2020. Methods: Clinical and molecular records from NSCLC patients were retrospectively collected from the two coordinating institutions (University of Turin and University of Naples). Molecular biomarkers (KRAS, EGFR, BRAF, ROS1, ALK, RET, NTRK, MET) and clinical data (sex, age, histological type, smoker status, PD-L1 expression, therapy) were collected and harmonized. Results: Clinical and molecular data from 1100 (n = 552 mutated and n = 548 wild-type) NSCLC patients were systematized and annotated in the ATLAS knowledge-database. Molecular records from biomarkers testing were matched with main patients’ clinical variables. Conclusions: Biomarkers ATLAS (https://biomarkersatlas.com/) represents a unique, easily managing, and reliable diagnostic tool aiming to integrate clinical records with molecular alterations of NSCLC patients in the real-word Italian scenario.

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.

Usual Interstitial Pneumonia (UIP) is characterized by progression of lung parenchyma that may be observed in various autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis and connective tissue diseases. From a diagnostic point of view, a UIP pattern related to ARDs may display imaging and pathological features able to distinguish it from that related to IPF, such as the "straight-edge" sign at HRCT and lymphoplasmacytic infiltrates at histologic specimens. Multidisciplinary approach (MDD), involving at least pulmonologist, rheumatologist and radiologist, is fundamental in the differential diagnosis process, but MDD is also required in the evaluation of severity, progression and response to treatment, that is based on the combination of changes in symptoms, pulmonary function trends, and, in selected patients, serial CT evaluation. Differently from IPF, in patients with ARDs both functional evaluation and patient-reported outcomes may be affected by systemic involvement and comorbidities, including musculoskeletal manifestations of disease. Finally, in regards to pharmacological treatment, immunosuppressants have been considered the cornerstone of therapy, despite the lack of solid evidence in most cases; recently, antifibrotic drugs were also proposed for the treatment of progressive fibrosing ILDs other than IPF. In ARD-ILD, the therapeutic choice should balance the need for the control of systemic and lung involvements with the risk of adverse events from multi-morbidities and -therapies. Purpose of this review is to summarize the definition, the radiological and morphological features of the UIP pattern in ARDs, together with risk factors, diagnostic criteria, prognostic evaluation, monitoring and management approaches of the UIP-ARDs.

Eosinophilic granulomatosis with polyangiitis (EGPA) is a necrotizing vasculitis, which typically affects small-to medium-sized blood vessels. It is characterized by the presence of tissue infiltrates rich in eosinophils, along with the formation of granulomatous lesions. About 40% of cases have positive anti-neutrophil cytoplasm antibodies (ANCA), with predominant perinuclear staining, and anti-myeloperoxidase (anti-MPO) specificity in about 65% of cases. Typical manifestations of EGPA include the late onset of asthma, nasal and sinus-related symptoms, peripheral neuropathy, and significant eosinophilia observed in the peripheral blood. In contrast to granulomatosis with polyangiitis and microscopic polyangiitis, renal involvement in EGPA is less frequent (about 25%) and poorly studied. Necrotizing pauci-immune crescentic glomerulonephritis is the most common renal presentation in patients with ANCA-positive EGPA. Although rarely, other forms of renal involvement may also be observed, such as eosinophilic interstitial nephritis, mesangial glomerulonephritis, membranous nephropathy, or focal sclerosis. A standardized treatment for EGPA with renal involvement has not been defined, however the survival and the renal outcomes are usually better than in the other ANCA-associated vasculitides. Nonetheless, kidney disease is an adverse prognostic factor for EGPA patients. Larger studies are required to better describe the renal involvement, in particular for patterns different from crescentic glomerulonephritis, and to favor the development of a consensual therapeutic approach. In this article, in addition to personal data, we will review recent findings on patient clinical phenotypes based on ANCA, genetics and the impact of biological drugs on disease management.

Introduction: Artificial intelligence (AI) integration in nephropathology has been growing rapidly in recent years, facing several challenges including the wide range of histological techniques used, the low occurrence of certain diseases, and the need for data sharing. This narrative review retraces the history of AI in nephropathology and provides insights into potential future developments. Methods: Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about automated image analysis or the application of an AI algorithm on non-neoplastic kidney histological samples were included and analyzed to extract information such as publication year, AI task, and learning type. Prepublication servers and reviews were not included. Results: Seventy-six (76) original research articles were selected. Most of the studies were conducted in the United States in the last 7 years. To date, research has been mainly conducted on relatively easy tasks, like single-stain glomerular segmentation. However, there is a trend towards developing more complex tasks such as glomerular multi-stain classification. Conclusion: Deep learning has been used to identify patterns in complex histopathology data and looks promising for the comprehensive assessment of renal biopsy, through the use of multiple stains and virtual staining techniques. Hybrid and collaborative learning approaches have also been explored to utilize large amounts of unlabeled data. A diverse team of experts, including nephropathologists, computer scientists, and clinicians, is crucial for the development of AI systems for nephropathology. Collaborative efforts among multidisciplinary experts result in clinically relevant and effective AI tools.

Introduction: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. Areas covered: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. Expert commentary: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Epidermal growth factor receptor (EGFR) exon 20 insertions occur rarely among different cancer types, with the highest frequency reported among non-small-cell lung cancer (NSCLC) patients, particularly adenocarcinomas (ADCs). Exon 20 insertions fall back in the tyrosine kinase domain, and can be clustered into two principal groups represented by in frame insertions and three to 21 bp (corresponding to 1–7 amino acids) duplications within amino acids 762 and 774. The identification of these alterations is key for an adequate management of NSCLC patients due to the possibility to treat these patients with specific targeted therapies. Next generation sequencing (NGS) technology, able to detect several hotspot gene mutations for different patients simultaneously, is the best detection approach due to its higher sensitivity and specificity compared to other techniques. Here we reviewed the principal biological characteristics, the main detection technologies and treatment options for NSCLC patients harbouring EGFR exon 20 insertions.

Background: Malignant pleural mesothelioma (MPM) is a cancer with a high mortality rate and few therapeutic options. After platinum–pemetrexed combination, no further promising drug seems to be effective. Immune checkpoint inhibitors may have some activity in pretreated patients and no data are available in this population about durvalumab. Materials and methods: DIADEM was a multicenter, open-label, single-arm, phase II trial aimed at evaluating the efficacy and safety of durvalumab. Patients with locally advanced/metastatic MPM who progressed after platinum–pemetrexed chemotherapy were enrolled to receive durvalumab (1500 mg, intravenously Q4W) for 12 months or until evidence of disease progression or unacceptable toxicity. The primary endpoint was the proportion of patients alive and free from progression at 16 weeks (PFS16wks) calculated from treatment initiation. Secondary endpoints were progression-free survival, overall survival, overall response rate, and safety. Results: Sixty-nine patients with a median age of 69 years (range 44-82 years) were enrolled; 62 patients (89.9%) had epithelioid histotype. As first-line treatment, all patients received platinum derivatives–pemetrexed combination (60.9% with carboplatin and 39.1% with cisplatin). As of March 2021, the median follow-up was 9.2 months (interquartile range 5.2-11.1 months). Six patients (8.7%) completed the 12-month treatment; 60 patients discontinued, of whom 42 for progressive disease, and 4 died. Seventeen patients (28.3%; 95% confidence interval 17.5% to 41.4%) were alive or free from progression at 16 weeks. Eleven patients (18.6%) had a grade 3 or 4 treatment-related adverse event (AE), and one (1.4%) had a grade ≥3 immune-related, treatment-related AE. There was one drug-related death. Conclusion: Durvalumab alone in pretreated non-selected MPM did not reach a meaningful clinical activity, showing any new major safety issue signals.

Mastocytosis is a rare and heterogeneous disease characterized by various clinical and biological features that affect different prognoses and treatments. The disease is usually divided into 2 principal categories: cutaneous and systemic disease (SM). Clinical features can be related to mast cell (MC) mediator release or pathological MC infiltration. SM is a disease often hard to identify, and the diagnosis is based on clinical, biological, histological, and molecular criteria with different specialists involved in the patient’s clinical work-up. Among all manifestations of the disease, gastrointestinal (GI) symptoms are common, being present in 14%-85% of patients, and can significantly impair the quality of life. Here we review the data regarding GI involvement in SM, in terms of clinical presentations, histological and endoscopic features, the pathogenesis of GI symptoms, and their treatment.

Aim: ALK, ROS1, NTRK and RET gene fusions and MET exon 14 skipping alterations represent novel predictive biomarkers for advanced non-small-cell lung cancer (NSCLC). Therefore, testing patients for these genetic variants is crucial for choosing the best selective treatment. Over the last couple of decades, next-generation sequencing (NGS) platforms have emerged as an extremely useful tool for detecting these variants. Materials & methods: In the present study, we report our NGS molecular records produced during a year of diagnostic activity. Results: Overall, our in-house developed NGS workflow successfully analyzed n = 116/131 (88.5%) NSCLC samples. Of these, eight (6.8%) and five (4.3%) out of 116 patients harbored ALK and RET gene rearrangements, respectively: one case harbored ROS1 gene fusion (0.7%). Conclusion: Our results highlight that an RNA-based NGS analysis can reliably detect gene fusion alterations, thereby playing a pivotal role in the management of NSCLC patients.

Introduction: Freehand renal biopsy represents a valid alternative to the most widespread ultrasonography-guided technique, although some concerns can derive from the possible increased complication rate and lower adequacy rate. Objectives: In the present audit study, efficacy of freehand method have been established through the analysis of 328 consecutive renal biopsies in 322 patients, instead the safety of the procedure was assessed in 196 patients. Patients and Methods: We retrospectively reviewed hospital databases of all patients who underwent a percutaneous renal biopsy over an 18 years’ period at Santa Marta and Santa Venera hospital in Acireale. Results: The procedure led to a definitive diagnosis in the majority of cases (98.48%), being uninformative only in 5 out of 328 cases (1.52%). Comparing these results against a Proforma, resulting from analysis of best literature reports for the items studied, adverse event rates were similar. Conclusion: Freehand renal biopsy resulted a good option to obtain renal tissue, without serious side effects. We argue about safety and we prefer to reserve this invasive procedure to selected cases, avoiding renal biopsy if biochemical and instrumental data allow a definitive diagnosis as well as in high risk patients. Our policy protects patients from the adverse effects that can result from kidney biopsy.

The introduction of next-generation sequencing (NGS) in the molecular diagnostic arma-mentarium is deeply changing pathology practice and laboratory frameworks. NGS allows for the comprehensive molecular characterization of neoplasms, in order to provide the best treatment to oncologic patients. On the other hand, NGS raises technical issues and poses several challenges in terms of education, infrastructures and costs. The aim of this review is to give an overview of the main NGS sequencing platforms that can be used in current molecular diagnostics and gain insights into the clinical applications of NGS in precision oncology. Hence, we also focus on the preanalytical, analytical and interpretative issues raised by the incorporation of NGS in routine pathology diagnostics.

Aims: The KWAY project aims to investigate the economic sustainability of the up-front NGS technologies adoption in the analysis of clinically relevant molecular alterations in NSCLC patients. Methods: The diagnostic workflow and the related sustained costs of five Italian referral centers were assessed in four different evolving scenarios were analyzed. For each scenario, two alternative testing strategies were evaluated: the Maximized Standard strategy and the Maximized NGS strategy. Results: For each center, the robustness of obtained results was verified through a deterministic sensitivity analysis, observing the variation of total costs based on a variation of ±20 % of the input parameters and ensuring that results would present a consistent behavior compared to the original ones. Conclusions: our project, highlighted that the adoption of NGS allows to save personnel time dedicated to testing activities and to reduce the overall cost of testing per patient.

Background and Objective: Digital pathology represents an invaluable source of information and a long-term investment with high returns, with the possible deployment of artificial intelligence (AI) tools for both the clinical and research activity. Moreover, the rising nosological complexity of the oncologic diseases, e.g., lung cancer, is stressing the need of integration among different subspecialities (e.g., radiology, molecular biology, and immuno-oncology) for the final characterization of cancer. In this setting, digital pathology can play a pivotal role in the "integration" of these different competencies, and the application of AI for prognostic/predictive purposes can represent a further "third" revolution in pathology. The objective of the present review is to provide an updated overview of the possible role of digital and integrative pathology in detecting gene mutations and, especially, translocations in different types of tumors, focusing on the promising implications that this advancement can have in lung cancer characterization. Methods: A systematic literature search was conducted on different research engines (PubMed, IEEE Xplore, dblp, ACM digital library, Inspec) over a 15-year interval from January 1, 2006 to October 31, 2021 selecting only English-language articles to highlight the possible diagnostic and prognostic role of digital pathology tools in detecting gene mutations and, especially, translocations in different types of tumors. Key Content and Findings: Digital pathology tools already demonstrated a role in the detection of specific mutations and translocations in different types of cancer, both in a targeted (e.g., liver/thyroid carcinoma) and in an agnostic (e.g., MSI) setting. In lung cancer, AI showed the capability of highlighting specific subset of mutations (STK11, EGFR, FAT1, SETBP1, KRAS, and TP53) from whole slide imaging (WSI), with the translocation field representing a promising frontier, with some gene rearrangement (e.g.

Background: Rearranged during transfection (RET) gene fusions are detected in 10–20% of thyroid cancer patients. Recently, RET fusion-positive metastatic thyroid cancers have attracted much attention owing to the FDA approval of two highly selective anti-RET tyrosine kinase inhibitors, namely, selpercatinib, and pralsetinib. Areas covered: This review summarizes the available evidence on the biological and predictive role of RET gene fusions in thyroid carcinoma patients and the latest screening assays currently used to detect these genomic alterations in histological and cytological specimens. Expert opinion: Management of advanced thyroid carcinoma has significantly evolved over the last decade thanks to the approval of three multikinase inhibitors, i.e. sorafenib, lenvatinib, cabozantinib, and of two selective RET-tyrosine inhibitors, i.e. selpercatinib and pralsetinib. In this setting, the detection of RET-fusions in advanced thyroid cancer specimens through the use of next-generation sequencing has become a commonly used strategy in clinical practice to select the best treatment options.

Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20–30% of cases are deemed “indeterminate for malignancy” and undergo surgery. However, after thyroidectomy, 70–80% of these nodules are benign. The identification of tools for improving FNA’s diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (n = 70), with 100.0% (95% CI = 83.2–100.0%) sensitivity and 96.0% (95% CI = 86.3–99.5%) specificity. The external validation (n = 170) showed a specificity of 82.9% (95% CI = 74.3–89.5%) and a sensitivity of 43.1% (95% CI = 30.9–56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8–89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up.

Importance: Identifying new prognostic features in colon cancer has the potential to refine histopathologic review and inform patient care. Although prognostic artificial intelligence systems have recently demonstrated significant risk stratification for several cancer types, studies have not yet shown that the machine learning-derived features associated with these prognostic artificial intelligence systems are both interpretable and usable by pathologists. Objective: To evaluate whether pathologist scoring of a histopathologic feature previously identified by machine learning is associated with survival among patients with colon cancer. Design, Setting, and Participants: This prognostic study used deidentified, archived colorectal cancer cases from January 2013 to December 2015 from the University of Milano-Bicocca. All available histologic slides from 258 consecutive colon adenocarcinoma cases were reviewed from December 2021 to February 2022 by 2 pathologists, who conducted semiquantitative scoring for tumor adipose feature (TAF), which was previously identified via a prognostic deep learning model developed with an independent colorectal cancer cohort. Main Outcomes and Measures: Prognostic value of TAF for overall survival and disease-specific survival as measured by univariable and multivariable regression analyses. Interpathologist agreement in TAF scoring was also evaluated. Results: A total of 258 colon adenocarcinoma histopathologic cases from 258 patients (138 men [53%]; median age, 67 years [IQR, 65-81 years]) with stage II (n = 119) or stage III (n = 139) cancer were included. Tumor adipose feature was identified in 120 cases (widespread in 63 cases, multifocal in 31, and unifocal in 26). For overall survival analysis after adjustment for tumor stage, TAF was independently prognostic in 2 ways: TAF as a binary feature (presence vs absence: hazard ratio [HR] for presence of TAF, 1.55 [95% CI, 1.07-2.25]; P = .02) and TAF as a semiquantitative categorica

Objective. The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods. Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results. The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions. AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports.

One of the goals of pathology is to standardize laboratory practices to increase the precision and effectiveness of diagnostic testing, which will ultimately enhance patient care and results. Standardization is crucial in the domains of tissue processing, analysis, and reporting. To enhance diagnostic testing, innovative technologies are also being created and put into use. Furthermore, although problems like algorithm training and data privacy issues still need to be resolved, digital pathology and artificial intelligence are emerging in a structured manner. Overall, for the field of pathology to advance and for patient care to be improved, standard laboratory practices and innovative technologies must be adopted. In this paper, we describe the state-of-the-art of automation in pathology laboratories in order to lead technological progress and evolution. By anticipating laboratory needs and demands, the aim is to inspire innovation tools and processes as positively transformative support for operators, organizations, and patients.

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.

The number of patients awaiting a kidney transplant is constantly rising but lack of organs leads kidneys from extended criteria donors (ECD) to be used to increase the donor pool. Pre-transplant biopsies are routinely evaluated through the Karpinski-Remuzzi score but consensus on its correlation with graft survival is controversial. This study aims to test a new diagnostic model relying on digital pathology to evaluate pre-transplant biopsies and to correlate it with graft outcomes. Pre-transplant biopsies from 78 ECD utilized as single kidney transplantation were scanned, converted to whole-slide images (WSIs), and reassessed by two expert nephropathologists using the Remuzzi-Karpinski score. The correlation between graft survival at 36 months median follow-up and parameters assigned by either WSI or glass slide score (GSL) by on-call pathologists was evaluated, as well as the agreement between the GSL and the WSIs score. No relation was found between the GSL assessed by on-call pathologists and graft survival (P = 0.413). Conversely, the WSI score assigned by the two nephropathologists strongly correlated with graft loss probability, as confirmed by the ROC curves analysis (DeLong test P = 0.046). Digital pathology allows to share expertise in the transplant urgent setting, ensuring higher accuracy and favoring standardization of the process. Its employment may significantly increase the predictive capability of the pre-transplant biopsy evaluation for ECD, improving the quality of allocation and patient safety.

Renal amyloidosis is a rare condition caused by the progressive accumulation of misfolded proteins within glomeruli, vessels, and interstitium, causing functional decline and requiring prompt treatment due to its significant morbidity and mortality. Congo red (CR) stain on renal biopsy samples is the gold standard for diagnosis, but the need for polarized light is limiting the digitization of this nephropathology field. This study explores the feasibility and reliability of CR fluorescence on virtual slides (CRFvs) in evaluating the diagnostic accuracy and proposing an automated digital pipeline for its assessment. Whole-slide images from 154 renal biopsies with CR were scanned through a Texas red fluorescence filter (NanoZoomer S60, Hamamatsu) at the digital Nephropathology Center of the Istituto di Ricovero e Cura a Carattere Scientifico San Gerardo, Monza, Italy, and evaluated double-blinded for the detection and quantification through the amyloid score and a custom ImageJ pipeline was built to automatically detect amyloid-containing regions. Interobserver agreement for CRFvs was optimal (k = 0.90; 95% CI, 0.81-0.98), with even better concordance when consensus-based CRFvs evaluation was compared to the standard CR birefringence (BR) (k = 0.98; 95% CI, 0.93-1). Excellent performance was achieved in the assessment of amyloid score overall by CRFvs (weighted k = 0.70; 95% CI, 0.08-1), especially within the interstitium (weighted k = 0.60; 95% CI, 0.35-0.84), overcoming the misinterpretation of interstitial and capsular collagen BR. The application of an automated digital pathology pipeline (Streamlined Pipeline for Amyloid detection through CR fluorescence Digital Analysis, SPADA) further increased the performance of pathologists, leading to a complete concordance with the standard BR. This study represents an initial step in the validation of CRFvs, demonstrating its general reliability in a digital nephropathology center. The computational method used in this stu

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.

Context Despite the reluctance to invest and the challenging estimation of necessary supporting costs, optimising the archives seems to be one of the hottest topics in the future management of the pathology laboratories. Historically, archives were only partially designed to securely store and organise tissue specimens, and tracking systems were often flawed, posing significant risks to patients' health and legal ramifications for pathologists. Objective The current review explores the available data from the literature on archives' management in pathology, including comprehensive business plans, structure setup, outfit, inventories, ongoing conservation and functional charges. Data sources Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about the archiving process and storage were included and analysed to extract information. Prepublication servers were ignored. Italian Institutional Regional databases for public competitive bidding processes were queried too. Conclusions A new emergent feeling in the pathology laboratory is growing for archives management; the digital pathology era is a great opportunity to apply innovation to tracking systems and samples preservation. The main aim is a critical evaluation of the return of investment in developing automatic and tracked archiving processes for improving not only quality, efficacy and efficiency of the labs but also patients' healthcare.

Objective: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered. Methods: On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education. Results: Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides. Conclusion: Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care.

Objective: Despite an increase in thyroid fine needle aspiration (FNA) and advances in whole slide imaging (WSI) adoption, digital pathology is still considered inadequate for primary diagnosis of these cases. Herein, we aim to validate the utility of WSI in thyroid FNAs employing the Delphi method strategy. Methods: A panel of experts from seven reference cytology centres was recruited. The study consisted of two consecutive rounds: (1) an open-ended, free-response questionnaire generating a list of survey items; and (2) a consensus analysis of 80 selected shared WSIs from 80 cases by six investigators answering six morphological questions utilising a 1 to 5 Likert scale. Results: High consensus was achieved for all parameters, with an overall average score of 4.27. The broad majority of items (84%) were ranked either 4 or 5 by each physician. Two badly scanned cases were responsible for more than half of the low-ranked (≤2) values (57%). Good to excellent (≥3) diagnostic confidence was reached in more than 95.2% of cases. For most cases (78%) WSI assessment was not limited by technical issues linked to the image acquisition process. Conclusion: This systematic Delphi study indicates broad consensus among participating physicians on the application of DP to thyroid cytopathology, supporting expert opinion that WSI is reliable and safe for primary diagnostic purposes.

Aims: Diabetic nephropathy is a major consequence of inflammation developing in type 1 diabetes, with interleukin-8 (IL-8)-CXCR1/2 axis playing a key role in kidney disease progression. In this study, we investigated the therapeutic potential of a CXCR1/2 non-competitive allosteric antagonist (Ladarixin) in preventing high glucose-mediated injury in human podocytes and epithelial cells differentiated from renal stem/progenitor cells (RSC) cultured as nephrospheres. Materials and Methods: We used human RSCs cultured as nephrospheres through a sphere-forming functional assay to investigate hyperglycemia-mediated effects on IL-8 signalling in human podocytes and tubular epithelial cells. Results: High glucose impairs RSC self-renewal, induces an increase in IL-8 transcript expression and protein secretion and induces DNA damage in RSC-differentiated podocytes, while exerting no effect on RSC-differentiated epithelial cells. Accordingly, the supernatant from epithelial cells or podocytes cultured in high glucose was able to differentially activate leucocyte-mediated secretion of pro-inflammatory cytokines, suggesting that the crosstalk between immune and non-immune cells may be involved in disease progression in vivo. Conclusions: Treatment with Ladarixin during RSC differentiation prevented high glucose-mediated effects on podocytes and modulated either podocyte or epithelial cell-dependent leucocyte secretion of pro-inflammatory cytokines, suggesting CXCR1/2 antagonists as possible pharmacological approaches for the treatment of diabetic nephropathy.