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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

Introduction: Digital pathology can improve the technical and interpretative workflows in nephropathology by creating hub-spoke networks and virtuous collaboration projects among centers in different geographical regions. New high-resolution fast-scanning instruments combined with currently existing equipment were tested in a nephropathology hub to evaluate possible upgrading in the routine processing phases. Methods: The scanning performance of two different instruments (Aperio vs hybrid MIDI II) was evaluated and a comparative quality control check was performed on obtained whole slide images. Results: Both with default and custom settings for light microscopy, MIDI II proved to be faster, with only slightly more time required to prepare the scan and larger final file size as compared to Aperio (p < 0.001). No differences were noted in the number of out-of-focus slides per case (p = 0.75). Regarding immunofluorescence, the new scanner required longer preparation time (p = 0.001) with comparable scanning times and final file size (p = 0.169 and p = 0.177, respectively). Quality control showed differences in 3 quality features related to white background and blurriness (p < 0.001). No major discordances in the final diagnosis were recorded after comparing the report obtained with slides scanned using the two instruments, with only one case (4%) showing minor disagreement. Conclusion: The present report describes the experience of a hub nephropathology center adopting next generation digital pathology tools for the routine assessment of renal biopsies, highlighting the need for a complementary approach towards a philosophy of interoperability.

Con la “Single Cell Biology”1 una nuova era è iniziata e con essa il nostro modo di di capire i processi biologici è stato rivoluzionato. In breve si tratta di misurare la stessa caratteristica in ogni singola cellula di un campione, non semplicemente estrarre il dato come una media fra tutte. Questa rivoluzione aggiunge un nuovo livello di risoluzione a quello che possiamo “vedere” e ci permette di comprendere meglio la complessità di un campione composto da diverse entità: le cellule. Caratterizzare singolarmente le cellule ci permette di approfondire la nostra conoscenza rispetto a fenotipo, sviluppo e network. Tutto questo è possibile grazie allo sviluppo di nuove tecnologie: le “single cell-omic technologies". Tra tutte queste novità la proteomica spaziale rappresenta un piccolo ma cruciale settore per diverse ragioni: la risoluzione a singola cellula è associata alla localizzazione spaziale, si misura la presenza di proteine e non RNA (quindi segnali dopo le modifiche trascrizionali), vengono analizzate tutte le cellule senza perderne determinati tipi come spesso succede nella disgregazione dei tessuti o in altre tecnologie a singola cellula, infine consente studi retrospettivi utilizzando campioni Fissati in Formalina e Inclusi in Paraffina (FFPE) ed è facilmente integrabile con altre tecnologie “-omiche”. Nel 2017 abbiamo sviluppato e pubblicato un lavoro metodologico chiamato Multiple Iterative Labeling by Antibody Neodeposition (MILAN technology) “che consiste nella colorazione multipla dello stesso campione di tessuto con diversi anticorpi..” 2 La tesi di dottorato si sviluppa in questo scenario. In pratica concerne l’analisi, con la tecnologia MILAN, di tessuti umani e murini, sani e patologici, a risoluzione cellulare, per classificare, quantificare e localizzare in situ le diverse popolazioni cellulari e per identificarne le specifiche interazioni e caratteristiche. Raccoglie gli articoli significativi di questi 3 anni di ricerca che hanno segu, The field of Single Cell biology 1 has revolutionized the way we understand biological processes and a new era is started. In a few words it can be explained as the detection of the same traits in every single cell inasample,notjustasthemeanvalueofthebulk.Thisrevolutionhasaddeda new level of resolution to what we can “see” and makes us better understand the complexity of a sample made of different entities: cells. Characterization of single cells has increased our understanding of cell phenotypes, the dynamics and trajectory of their development, and their network. All of this has been possible thanks to the fast development of a large group of technologies: “single-cell multi omic technologies”. Among all of these novelties high-plex spatial proteomic represents a small but crucial niche for many reasons: it has a single cell resolution associated with spatial localization, it evaluates the presence of protein and not RNA signal (bypassing post transcriptional modification), it analyses whole cells without losing any types of them as often happens in tissue disaggregation or other single cell technologies, it allows retrospective study on Formalin Fixed Paraffin Embedded (FFPE) sample collection, easily integrable with other -omic technologies. In 2017 we developed a method called Multiple Iterative Labeling by Antibody Neodeposition (MILAN technology) “Which implies multiple stainings of a tissue section with multiple antibodies..” 2 Within this scenario my PhD thesis develops. Briefly it concerns the analysis, with MILAN technology, of human or mouse, healthy or pathologic tissues, at single cell level in order to classify cell populations, quantify and localize them in situ and recognize their specific interaction and characteristics. It’s a selection of results of these 3 last years of research after the publication of the MILAN technology method. The first part is related to the application of MILAN methods to different types of tissue. This has allowed us to

Objective: The International Society of Nephrology/Renal Pathology Society classification is the gold standard for the characterisation of lupus nephritis (LN) on renal biopsy, with therapeutic repercussions. Its recent revision simplified the current class subdivisions, eliminating the S/G forms of class IV, although data on a possible pathogenetic/clinical value of this subdivision are still contradictory. Methods: 353 renal biopsies from Belimumab International Study in LN were assessed through central pathology review. Univariate logistic models and a decision tree were performed on 314 adequate biopsies to evaluate the impact of histological features on focal/diffuse classes. Removing class I/II (n=6) and € pure' class V (n=34), principal component analysis (PCA) and heatmap were used to explore similarities among III, IVS and IVG biopsies either incorporating or not the mixed classes (+V, n=274). Finally, a method aimed at partitioning the cases into k clusters based on their similarity (KMeans), was used to study features from the cohort of € pure' class III/IVS/IVG cases (n=214) to determine alternative subdivisions based on phenotypic data. Results: Segmental endocapillary hypercellularity (EH) was prevalent in class III, global EH, wire loops, hyaline thrombi and double contours were hallmarks of class IVG, with IVS cases showing intermediate characteristics. Heatmap and PCA confirmed the segregation of these features among classes, showing better segregation for focal/diffuse LN as compared with the mixed classes (+V). KMeans revealed the presence of two main clusters, membranoproliferative-like (n=83) or vasculitis-like (n=131). Conclusions: This study reveals new phenotypic forms of LN surpassing the traditional classes as determined by the current classification. Future validation and confirmation are required to confirm these findings.

Dendritic cells (DC) (classic, plasmacytoid, inflammatory) are an intense focus of interest because of their role in inflammation, autoimmunity, vaccination and cancer. We present a tissue-based classification of human DC subsets in tonsils with a high-parameter (>40 markers) immunofluorescent approach, cell type-specific image segmentation and the use of bioinformatics platforms. Through this deep phenotypic and spatial examination, classic cDC1, cDC2, pDC subsets have been further refined and a novel subset of DC co-expressing IRF4 and IRF8 identified. Based on unique tissue locations within the tonsil, and close interactions with T cells (cDC1) or B cells (cDC2), DC subsets can be further subdivided by correlative phenotypic changes associated with these interactions. In addition, monocytes and macrophages expressing HLA-DR or S100AB are identified and localized in the tissue. This study thus provides a whole tissue in situ catalog of human DC subsets and their cellular interactions within spatially defined niches

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into ‘brisk’, ‘non-brisk’ and ‘absent’ entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single-cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns are heterogeneous functional categories that can be further sub-classified into active, transitional or exhausted. The classification of primary melanomas based on the functional paradigm also shows correlation with spontaneous regression, and an improved prognostic value when compared to that of the brisk classification. Finally, the main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis.

Multiplexing, labeling for multiple immunostains in the very same cell or tissue section in situ, has raised considerable interest. The methods proposed include the use of labeled primary antibodies, spectral separation of fluorochromes, bleaching of the fluorophores or chromogens, blocking of previous antibody layers, all in various combinations. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, and scarcity of specialized skills or facilities. We have validated a method based on common primary and secondary antibodies and diffusely available fluorescent image scanners. It entails rounds of four-color indirect immunofluorescence, image acquisition, and removal (stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulfide cleavage and a detergent or by a chaotropic salt treatment, this latter followed by antigen refolding. More than 30 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software. Multiplexing on routine tissue sections is a high throughput tool for in situ characterization of neoplastic, reactive, inflammatory, and normal cells.

Antigen masking in routinely processed tissue is a poorly understood process caused by multiple factors. We sought to dissect the effect on antigenicity of each step of processing by using frozen sections as proxies of the whole tissue. An equivalent extent of antigen masking occurs across variable fixation times at room temperature. Most antigens benefit from longer fixation times (>24 hr) for optimal detection after antigen retrieval (AR; for example, Ki-67, bcl-2, ER). The transfer to a graded alcohol series results in an enhanced staining effect, reproduced by treating the sections with detergents, possibly because of a better access of the polymeric immunohistochemical detection system to tissue structures. A second round of masking occurs upon entering the clearing agent, mostly at the paraffin embedding step. This may depend on the non-freezable water removal. AR fully reverses the masking due both to the fixation time and the paraffin embedding. AR itself destroys some epitopes which do not survive routine processing. Processed frozen sections are a tool to investigate fixation and processing requirements for antigens in routine specimens.