The putative role of MALDI-MSI in the study of Membranous Nephropathy

Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions

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.

Congo Red Staining in Digital Pathology: The Streamlined Pipeline for Amyloid Detection Through Congo Red Fluorescence Digital Analysis

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 study has the potential to facilitate the integration of spatial omics and artificial intelligence tools for the diagnosis of amyloidosis, streamlining its detection process.

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Serum protein signatures using aptamer-based proteomics for minimal change disease and membranous nephropathy

Introduction

Minimal change disease (MCD) and membranous nephropathy (MN) are glomerular diseases (glomerulonephritis [GN]) that present with the nephrotic syndrome. Although circulating PLA2R antibodies have been validated as a biomarker for MN, the diagnosis of MCD and PLA2R-negative MN still relies on the results of kidney biopsy or empirical corticosteroids in children. We aimed to identify serum protein biomarker signatures associated with MCD and MN pathogenesis using aptamer-based proteomics.

Methods

Quantitative SOMAscan proteomics was applied to the serum of adult patients with MCD (n = 15) and MN (n = 37) and healthy controls (n = 20). Associations between the 1305 proteins detected with SOMAscan were assessed using multiple statistical tests, expression pattern analysis, and systems biology analysis.

Results

A total of 208 and 244 proteins were identified that differentiated MCD and MN, respectively, with high statistical significance from the healthy controls (Benjamin-Hochberg [BH] P < 0.0001). There were 157 proteins that discriminated MN from MCD (BH P < 0.05). In MCD, 65 proteins were differentially expressed as compared with MN and healthy controls. When compared with MCD and healthy controls, 44 discriminatory proteins were specifically linked to MN. Systems biology analysis of these signatures identified cell death and inflammation as key pathways differentiating MN from MCD and healthy controls. Dysregulation of fatty acid metabolism pathways was confirmed in both MN and MCD as compared with the healthy subjects.

Conclusion

SOMAscan represents a promising proteomic platform for biomarker development in GN. Validation of a greater number of discovery biomarkers in larger patient cohorts is needed before these data can be translated for clinical care.

Imaging the kidney: from light to super-resolution microscopy

The important achievements in kidney physiological and pathophysiological mechanisms can largely be ascribed to progress in the technology of microscopy. Much of what we know about the architecture of the kidney is based on the fundamental descriptions of anatomic microscopists using light microscopy and later by ultrastructural analysis provided by electron microscopy. These two techniques were used for the first classification systems of kidney diseases and for their constant updates. More recently, a series of novel imaging techniques added the analysis in further dimensions of time and space. Confocal microscopy allowed us to sequentially visualize optical sections along the z-axis and the availability of specific analysis software provided a three-dimensional rendering of thicker tissue specimens. Multiphoton microscopy permitted us to simultaneously investigate kidney function and structure in real time. Fluorescence-lifetime imaging microscopy allowed to study the spatial distribution of metabolites. Super-resolution microscopy increased sensitivity and resolution up to nanoscale levels. With cryo-electron microscopy, researchers could visualize the individual biomolecules at atomic levels directly in the tissues and understand their interaction at subcellular levels. Finally, matrix-assisted laser desorption/ionization imaging mass spectrometry permitted the measuring of hundreds of different molecules at the same time on tissue sections at high resolution. This review provides an overview of available kidney imaging strategies, with a focus on the possible impact of the most recent technical improvements.

Proteomics for the study of new biomarkers in Fabry disease: State of the art

Nephropathy represents a major complication of Fabry Disease and its accurate characterization is of paramount importance in predicting the disease progression and assessing the therapeutic responses. The diagnostic process still relies on performing renal biopsy, nevertheless many efforts have been made to discover early reliable biomarkers allowing us to avoid invasive procedures. In this field, proteomics offers a sensitive and fast method leading to an accurate detection of specific pathological proteins and the discovery of diagnostic and prognostic biomarkers that reflect disease progression and facilitate the evaluation of therapeutic responses. Here, we report a review of selected literature focusing on the investigation of several proteomic techniques highlighting their advantages, limitations and future perspectives in their application in the routine study of Fabry Nephropathy.

Elaboration Pipeline for the Management of MALDI-MS Imaging Datasets

Matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-mass spectrometry imaging (MSI) enables the spatial localization of proteins to be mapped directly on tissue sections, simultaneously detecting hundreds in a single analysis. However, the large data size, as well as the complexity of MALDI-MSI proteomics datasets, requires the appropriate tools and statistical approaches in order to reduce the complexity and mine the dataset in a successful manner. Here, a pipeline for the management of MALDI-MSI data is described, starting with preprocessing of the raw data, followed by statistical analysis using both supervised and unsupervised statistical approaches and, finally, annotation of those discriminatory protein signals highlighted by the data mining procedure.

Mass Spectrometric (MS) Analysis of Proteins and Peptides

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

Detecting Proteomic Indicators to Distinguish Diabetic Nephropathy from Hypertensive Nephrosclerosis by Integrating Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging with High-Mass Accuracy Mass Spectrometry

INTRODUCTION

Diabetic nephropathy (DN) and hypertensive nephrosclerosis (HN) represent the most common causes of chronic kidney disease (CKD) and many patients progress to -end-stage renal disease. Patients are treated primarily through the management of cardiovas-cular risk factors and hypertension; however patients with HN have a more favorable outcome. A noninvasive clinical approach to separate these two entities, especially in hypertensive patients who also have diabetes, would allow for targeted treatment and more appropriate resource allocation to those patients at the highest risk of CKD progression. Meth-ods: In this preliminary study, high-spatial-resolution matrix-assisted laser desorption/ion-ization (MALDI) mass spectrometry imaging (MSI) was integrated with high-mass accuracy MALDI-FTICR-MS and nLC-ESI-MS/MS analysis in order to detect tissue proteins within kidney biopsies to discriminate cases of DN (n = 9) from cases of HN (n = 9).

RESULTS

Differences in the tryptic peptide profiles of the 2 groups could clearly be detected, with these becoming even more evident in the more severe histological classes, even if this was not evident with routine histology. In particular, 4 putative proteins were detected and had a higher signal intensity within regions of DN tissue with extensive sclerosis or fibrosis. Among these, 2 proteins (PGRMC1 and CO3) had a signal intensity that increased at the latter stages of the disease and may be associated with progression.

DISCUSSION/CONCLUSION

This preliminary study represents a valuable starting point for a future study employing a larger cohort of patients to develop sensitive and specific protein biomarkers that could reliably differentiate between diabetic and hypertensive causes of CKD to allow for improved diagnosis, fewer biopsy procedures, and refined treatment approaches for clinicians.

Chronic kidney disease: a review of proteomic and metabolomic approaches to membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy biomarkers

Chronic Kidney Disease (CKD) is a global health problem annually affecting millions of people around the world. It is a comprehensive syndrome, and various factors may contribute to its occurrence. In this study, it was attempted to provide an accurate definition of chronic kidney disease; followed by focusing and discussing on molecular pathogenesis, novel diagnosis approaches based on biomarkers, recent effective antigens and new therapeutic procedures related to high-risk chronic kidney disease such as membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy, which may lead to end-stage renal diseases. Additionally, a considerable number of metabolites and proteins that have previously been discovered and recommended as potential biomarkers of various CKD_s using ‘-omics-’ technologies, proteomics, and metabolomics were reviewed.

Matrix-assisted laser desorption/ionization mass spectrometry imaging to uncover protein alterations associated with the progression of IgA nephropathy

IgA nephropathy (IgAN) is one of the most diffuse glomerulonephrites worldwide, and many issues still remain regarding our understanding of its pathogenesis. The disease is diagnosed by renal biopsy examination, but potential pitfalls still persist with regard to discriminating its primary origin and, as a result, determining patient outcome remains challenging. In this pilot study, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) was performed on renal biopsies obtained from patients with IgAN (n = 11) and other mesangioproliferative glomerulonephrites (MesPGN, n = 6) in order to enlighten proteomic alterations that may be associated with the progression of IgAN. Differences in the proteomic profiles of IgAN and MesPGN tissue could clearly be detected using this approach and, furthermore, 14 signals (AUC ≥ 0.8) were observed to have an altered intensity among the different CKD stages within the IgAN group. In particular, large increases in the intensity of these signals could be observed at CKD stages II and above. These signals primarily corresponded to proteins involved in either inflammatory and healing pathways and their increased intensity was localized within regions of tissue with large amounts of inflammatory cells or sclerosis. Despite much work in recent years, our molecular understanding of IgAN progression remains incomplete. This pilot study represents a promising starting point in the search for novel protein markers that can assist clinicians in better understanding the pathogenesis of IgAN and highlighting those patients who may progress to end-stage renal disease.

MALDI imaging in Fabry nephropathy: a multicenter study

BACKGROUND

The current study evaluates the application of histology and in situ proteomics (MALDI-MSI) in Fabry nephropathy (FN), showing investigative and classification role for this coupled approach.

METHODS

A retrospective series of 14 formalin fixed paraffin embedded (FFPE) renal biopsies with diagnosis of FN and 1 biopsy from a patient bearing a galactosidase-α (GLA) genetic variant of unknown significance (GVUS, c.376A>G) have been classified for clinical characteristics. Groups were compared for histological differences (following the ISGFN scoring system). Moreover, renal biopsies from these cases have been analyzed with MALDI-MSI as previously described to find proteomic signatures among different mutations and phenotypes.

RESULTS

Comparison of clinical features revealed lower mean 24 h proteinuria in females (225 mg/24 h) than in males (1477.5 mg/24 h, p = 0.006). As for clinical characteristics, females significantly differed from males only for lower arterial sclerosis, with a mean value of 0.82 vs. 1.05 (p = 0.001). Proteomic analysis demonstrated specific signatures in different subgroups of FN patients. Moreover, MALDI correctly classified cases with undetermined mutation or GVUS.

CONCLUSIONS

The present study demonstrated the feasible application of MALDI-MSI in the analysis of FN FFPE renal biopsies, allowing the detection of putative signatures for phenotypic distinction and demonstrating genetic classification capabilities.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

High Spatial Resolution MALDI-MS Imaging in the Study of Membranous Nephropathy

PURPOSE

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology has advanced rapidly during recent years with the development of instruments equipped with low-diameter lasers that are suitable for high spatial resolution imaging. This may provide significant advantages in certain fields of molecular pathology where more specific protein fingerprints of individual cell types are required, such as renal pathology.

EXPERIMENTAL DESIGN

Here MALDI-MSI analysis of a cohort of membranous nephropathy (MN) patients is performed among which patients either responded favorably (R; n = 6), or unfavorably (NR; n = 4), to immunosuppressive treatment (Ponticelli Regimen), employing a 10 µm laser spot diameter.

RESULTS

Specific tryptic peptide profiles of the different cellular regions within the glomerulus can be generated, similarly for the epithelial cells belonging to the proximal and distal tubules. Conversely, specific glomerular and sub-glomerular profiles cannot be obtained while using the pixel size performed in previous studies (50 µm). Furthermore, two proteins are highlighted, sonic hedgehog and α-smooth muscle actin, whose signal intensity and spatial localization within the sub-glomerular and tubulointerstitial compartments differ between treatment responders and non-responders.

CONCLUSIONS AND CLINICAL RELEVANCE

The present study exemplifies the advantage of using high spatial resolution MALDI-MSI for the study of MN and highlights that such findings have the potential to provide complementary support in the routine prognostic assessment of MN patients.

MALDI-MSI Pilot Study Highlights Glomerular Deposits of Macrophage Migration Inhibitory Factor as a Possible Indicator of Response to Therapy in Membranous Nephropathy

PURPOSE

Membranous nephropathy (MN) is the most frequent cause of nephrotic syndrome in adults and the disease course is characterized by the "rule of third", with one-third of patients experiencing complete remission and the remaining experiencing relapses or progression of the disease. Additionally, the therapeutic approach is not standardized, leading to further heterogeneity in terms of response and outcome.

EXPERIMENTAL DESIGN

In this pilot study, MALDI-MSI analysis is performed on renal biopsies (n = 13) obtained from two homogeneous groups of patients, which differentially responded to the immunosuppressive treatments (Ponticelli regimen).

RESULTS

A signal at m/z 1303 displays the greatest discriminatory power when comparing the two groups and is observed to be of higher intensity in the glomeruli of the non-responding patients. The corresponding tryptic peptide is identified as macrophage migration inhibitory factor (MIF).

CONCLUSIONS AND CLINICAL RELEVANCE

Despite much effort being made in recent years to understand the pathogenesis of MN, a biomarker able to predict the outcome of these patients following therapeutic treatment is still lacking. Here, a protein (MIF), verified by immunohistochemistry, that can differentiate between these MN patients and could be a valuable starting point for a further study focused on verifying its predictive role in therapy response is highlighted.