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Our knowledge regarding the role proteins play in the mutual relationship among oocytes, surrounding follicle cells, stroma, and the vascular network inside the ovary is still poor and obtaining insights into this context would significantly aid our understanding of folliculogenesis. Here, we describe a spatial proteomics approach to characterize the proteome of individual follicles at different growth stages in a whole prepubertal 25-day-old mouse ovary. A total of 401 proteins were identified by nano-scale liquid chromatography–electrospray ionization–tandem mass spectrometry (nLC-ESI-MS/MS), 69 with a known function in ovary biology, as demonstrated by earlier proteomics studies. Enrichment analysis highlighted significant KEGG and Reactome pathways, with apoptosis, developmental biology, PI3K-Akt, epigenetic regulation of gene expression, and extracellular matrix organization being well represented. Then, correlating these data with the spatial information provided by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) on 276 follicles enabled the protein profiles of single follicle types to be mapped within their native context, highlighting 94 proteins that were detected throughout the secondary to the pre-ovulatory transition. Statistical analyses identified a group of 37 proteins that showed a gradual quantitative change during follicle differentiation, comprising 10 with a known role in follicle growth (NUMA1, TPM2), oocyte germinal vesicle-to-metaphase II transition (SFPQ, ACTBL, MARCS, NUCL), ovulation (GELS, CO1A2), and preimplantation development (TIF1B, KHDC3). The proteome landscape identified includes molecules of known function in the ovary, but also those whose specific role is emerging. Altogether, this work demonstrates the utility of performing spatial proteomics in the context of the ovary and offers sound bases for more in-depth investigations that aim to further unravel its spatial proteome.

Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are low-risk thyroid lesions most often characterised by RAS-type mutations. The histological diagnosis may be challenging, and even immunohistochemistry and molecular approaches have not yet provided conclusive solutions. This study characterises a set of NIFTPs by Matrix-Assisted Laser Desorption/Ionisation (MALDI)–Mass Spectrometry Imaging (MSI) to highlight the proteomic signatures capable of overcoming histological challenges. Archived formalin-fixed paraffin-embedded samples from 10 NIFTPs (n = 6 RAS-mutated and n = 4 RAS-wild type) were trypsin-digested and analysed by MALDI–MSI, comparing their profiles to normal tissue and synchronous benign nodules. This allowed the definition of a four-peptide signature able to distinguish RAS-mutant from wild-type cases, the latter showing proteomic similarities to hyperplastic nodules. Moreover, among the differentially expressed signals, Peptidylprolyl Isomerase A (PPIA, 1505.8 m/z), which has already demonstrated a role in the development of cancer, was found overexpressed in NIFTP RAS-mutated nodules compared to wild-type lesions. These results underlined that high-throughput proteomic approaches may add a further level of biological comprehension for NIFTPs. In the future, thanks to the powerful single-cell detail achieved by new instruments, the complementary NGS–MALDI imaging sequence might be the correct methodological approach to confirm that the current NIFTP definition encompasses heterogeneous lesions that must be further characterised.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection leads to a wide range of clinical manifestations and determines the need for personalized and precision medicine. To better understand the biological determinants of this heterogeneity, we explored the plasma proteome of 43 COVID-19 patients with different outcomes by an untargeted liquid chromatography-mass spectrometry approach. The comparison between asymptomatic or pauci-symptomatic subjects (MILDs), and hospitalised patients in need of oxygen support therapy (SEVEREs) highlighted 29 proteins emerged as differentially expressed: 12 overexpressed in MILDs and 17 in SEVEREs. Moreover, a supervised analysis based on a decision-tree recognised three proteins (Fetuin-A, Ig lambda-2chain-C-region, Vitronectin) that are able to robustly discriminate between the two classes independently from the infection stage. In silico functional annotation of the 29 deregulated proteins pinpointed several functions possibly related to the severity; no pathway was associated exclusively to MILDs, while several only to SEVEREs, and some associated to both MILDs and SEVEREs; SARS-CoV-2 signalling pathway was significantly enriched by proteins up-expressed in SEVEREs (SAA1/2, CRP, HP, LRG1) and in MILDs (GSN, HRG). In conclusion, our analysis could provide key information for ‘proteomically’ defining possible upstream mechanisms and mediators triggering or limiting the domino effect of the immune-related response and characterizing severe exacerbations.

Idiopathic membranous nephropathy (IMN) is a pathologically defined disorder of the glomerulus, primarily responsible for nephrotic syndromes (NS) in nondiabetic adults. The underlying molecular mechanisms are still not completely clarified. To explore possible molecular and functional signatures, an optimised mass spectrometry (MS) method based on next-generation data-independent acquisition combined with ion-mobility was applied to serum of patients affected by IMN (n = 15) or by other glomerulopathies (PN) (n = 15). The statistical comparison highlighted a panel of 57 de-regulated proteins with a significant increase in lipoprotein-related proteins (APOC1, APOB, APOA1, APOL1 and LCAT) and a substantial quantitative alteration of key serpins (including A4, D1, A7, A6, F2, F1 and 1) possibly associated with IMN or NS and podocyte stress. A critical dysregulation in metabolisms of lipids (e.g., VLDL assembly and clearance) likely to be related to known hyperlipidemia in IMN, along with involvement of non-classical complement pathways and a putative enrolment of ficolin-2 in sustaining the activation of the lectin-mediated complement system have been pinpointed. Moreover, mannose receptor CD206 (MRC1-down in IMN) and biotinidase (BTD-up in IMN) are able alone to accurately distinguish IMN vs. PN. To conclude, our work provides key proteomic insights into the IMN complexity, opening the way to an efficient stratification of MN patients.

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.

The rising incidence of non-ST-segment elevation myocardial infarction (NSTEMI) and associated long-term high mortality constitutes an urgent clinical issue. Unfortunately, the study of possible interventions to treat this pathology lacks a reproducible pre-clinical model. Indeed, currently adopted small and large animal models of MI mimic only full-thickness, ST-segment-elevation (STEMI) infarcts, and hence cater only for investigation into therapeutics and interventions directed at this subset of MI. Thus, we developed an ovine model of NSTEMI by ligating the myocardial muscle at precise intervals parallel to the left anterior descending coronary artery. After validating the presented model both by histology and functional analysis with clinical data, further omics analyses highlighted the distinctive features of post-NSTEMI tissue remodelling. Here, by looking at the transcriptome and proteome-derived pathways emerging at acute (7 days) and late (28 days) post-surgery timepoints, we discovered specific alterations in cardiac post-ischaemic extracellular matrix (ECM). Together with the rise of well-known markers of inflammation and fibrosis, NSTEMI ischaemic regions showed distinctive patterns in the expression of complex N-glycans and glycosaminoglycans in cellular membranes and ECM. Identifying such changes in molecular moieties accessible to infusible and intra-myocardial injectable drugs sheds light on the development of targeted pharmacological solutions to contrast adverse fibrotic remodelling.

The podocyte injury, and consequent proteinuria, that characterize the pathology of idiopathic membranous nephropathy (IMN) is mediated by an autoimmune reaction against podocyte antigens. In particular, the activation of pathways leading to abundant renal deposits of complement is likely to involve the binding of mannose-binding lectin (MBL) to aberrant glycans on immunoglobulins. To obtain a landscape of circulatory IgG Fc glycosylation characterizing this disease, we conducted a systematic N-glycan profiling study of IgG1, 2, and 4 by mass spectrometry. The cohort included 57 IMN patients, a pathological control group with nephrotic syndrome (PN) (n = 20), and 88 healthy control subjects. The effect of sex and age was assessed in all groups and controlled by rigorous matching. Several IgG Fc glycan traits were found to be associated with IMN. Interestingly, among them, only IgG4-related results were specific for IMN and not for PN. Hypo-galactosylation of IgG4, already shown for IMN, was observed to occur in the absence of core fucose, in line with a probable increase of pro-inflammatory IgG. In addition, elevated levels of fucosylated IgG4, along with low levels of hybrid-type glycans, were detected. Some of these IgG4 alterations are likely to be more pronounced in high PLA2R (phospholipase A2 receptor) patients. IgG Fc glycosylation patterns associated with IMN warrant further studies of their role in disease mechanisms and may eventually enrich the diagnostic spectrum regarding patient stratification.

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by the aberrant accumulation of extracellular matrix in the lungs. nintedanib is one of the two FDA-approved drugs for IPF treatment; however, the exact pathophysiological mechanisms of fibrosis progression and response to therapy are still poorly understood. In this work, the molecular fingerprint of fibrosis progression and response to nintedanib treatment have been investigated by mass spectrometry-based bottom-up proteomics in paraffin-embedded lung tissues from bleomycin-induced (BLM) pulmonary fibrosis mice. Our proteomics results unveiled that (i) samples clustered depending on the tissue fibrotic grade (mild, moderate, and severe) and not on the time course after BLM treatment; (ii) the dysregulation of different pathways involved in fibrosis progression such as the complement coagulation cascades, advanced glycation end products (AGEs) and their receptors (RAGEs) signaling, the extracellular matrix-receptor interaction, the regulation of actin cytoskeleton, and ribosomes; (iii) Coronin 1A (Coro1a) as the protein with the highest correlation when evaluating the progression of fibrosis, with an increased expression from mild to severe fibrosis; and (iv) a total of 10 differentially expressed proteins (padj-value ≤ 0.05 and Fold change ≤−1.5 or ≥1.5), whose abundance varied in the base of the severity of fibrosis (mild and moderate), were modulated by the antifibrotic treatment with nintedanib, reverting their trend. Notably, nintedanib significantly restored lactate dehydrogenase B (Ldhb) expression but not lactate dehydrogenase A (Ldha). Notwithstanding the need for further investigations to validate the roles of both Coro1a and Ldhb, our findings provide an extensive proteomic characterization with a strong relationship with histomorphometric measurements. These results unveil some biological processes in pulmonary fibrosis and drug-mediated fibrosis therapy.

AimsIdentification and characterisation of monoclonal gammopathies of renal significance (MGRS) is critical for therapeutic purposes. Amyloidosis represents one of the most common forms of MGRS, and renal biopsy remains the gold standard for their classification, although mass spectrometry has shown greater sensitivity in this area.MethodsIn the present study, a new in situ proteomic technique, matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), is investigated as an alternative to conventional laser capture microdissection MS for the characterisation of amyloids. MALDI-MSI was performed on 16 cases (3 lambda light chain amyloidosis (AL), 3 AL kappa, 3 serum amyloid A amyloidosis (SAA), 2 lambda light chain deposition disease (LCDD), 2 challenging amyloid cases and 3 controls). Analysis began with regions of interest labelled by the pathologist, and then automatic segmentation was performed.ResultsMALDI-MSI correctly identified and typed cases with known amyloid type (AL kappa, AL lambda and SAA). A ‘restricted fingerprint’ for amyloid detection composed of apolipoprotein E, serum amyloid protein and apolipoprotein A1 showed the best automatic segmentation performance (area under the curve >0.7).ConclusionsMALDI-MSI correctly assigned minimal/challenging cases of amyloidosis to the correct type (AL lambda) and identified lambda light chains in LCDD cases, highlighting the promising role of MALDI-MSI for amyloid typing.

Ovarian cancer is a highly lethal gynecological malignancy. Drug resistance rapidly occurs, and different therapeutic approaches are needed. So far, no biomarkers have been discovered to predict early response to therapies in the case of multi-treated ovarian cancer patients. The aim of our investigation was to identify a protein panel and the molecular pathways involved in chemotherapy response through a combination of studying proteomics and network enrichment analysis by considering a subset of samples from a clinical setting. Differential mass spectrometry studies were performed on 14 serum samples from patients with heavily pretreated platinum-resistant ovarian cancer who received the FOLFOX-4 regimen as a salvage therapy. The serum was analyzed at baseline time (T0) before FOLFOX-4 treatment, and before the second cycle of treatment (T1), with the aim of understanding if it was possible, after a first treatment cycle, to detect significant proteome changes that could be associated with patients responses to therapy. A total of 291 shared expressed proteins was identified and 12 proteins were finally selected between patients who attained partial response or no-response to chemotherapy when both response to therapy and time dependence (T0, T1) were considered in the statistical analysis. The protein panel included APOL1, GSN, GFI1, LCATL, MNA, LYVE1, ROR1, SHBG, SOD3, TEC, VPS18, and ZNF573. Using a bioinformatics network enrichment approach and metanalysis study, relationships between serum and cellular proteins were identified. An analysis of protein networks was conducted and identified at least three biological processes with functional and therapeutic significance in ovarian cancer, including lipoproteins metabolic process, structural component modulation in relation to cellular apoptosis and autophagy, and cellular oxidative stress response. Five proteins were almost independent from the network (LYVE1, ROR1, TEC, GFI1, and ZNF573). All proteins were associated with response to drug-resistant ovarian cancer resistant and were mechanistically connected to the pathways associated with cancer arrest. These results can be the basis for extending a biomarker discovery process to a clinical trial, as an early predictive tool of chemo-response to FOLFOX-4 of heavily treated ovarian cancer patients and for supporting the oncologist to continue or to interrupt the therapy.

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.

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-alpha (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.

Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC.

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.

Gelatin–dextran hydrogel scaffolds (G-PEG-Dx) were evaluated for their ability to activate the bone marrow human mesenchymal stromal cells (BM-hMSCs) towards mineralization. G-PEG-Dx1 and G-PEG-Dx2, with identical composition but different architecture, were seeded with BM-hMSCs in presence of fetal bovine serum or human platelet lysate (hPL) with or without osteogenic medium. G-PEG-Dx1, characterized by a lower degree of crosslinking and larger pores, was able to induce a better cell colonization than G-PEG-Dx2. At day 28, G-PEG-Dx2, with hPL and osteogenic factors, was more efficient than G-PEG-Dx1 in inducing mineralization. Scanning electron microscopy (SEM) and Raman spectroscopy showed that extracellular matrix produced by BM-hMSCs and calcium-positive mineralization were present along the backbone of the G-PEG-Dx2, even though it was colonized to a lesser degree by hMSCs than G-PEG-Dx1. These findings were confirmed by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), detecting distinct lipidomic signatures that were associated with the different degree of scaffold mineralization. Our data show that the architecture and morphology of G-PEG-Dx2 is determinant and better than that of G-PEG-Dx1 in promoting a faster mineralization, suggesting a more favorable and active role for improving bone repair.

Ischemic heart disease is a leading cause of mortality due to irreversible damage to cardiac muscle. Inspired by the post-ischemic microenvironment, we devised an extracellular matrix (ECM)-mimicking hydrogel using catalyst-free click chemistry covalent bonding between two elastin-like recombinamers (ELRs). The resulting customized hydrogel included functional domains for cell adhesion and protease cleavage sites, sensitive to cleavage by matrix metalloproteases overexpressed after myocardial infarction (MI). The scaffold permitted stromal cell invasion and endothelial cell sprouting in vitro. The incidence of non-transmural infarcts has increased clinically over the past decade, and there is currently no treatment preventing further functional deterioration in the infarcted areas. Here, we have developed a clinically relevant ovine model of non-transmural infarcts induced by multiple suture ligations. Intramyocardial injections of the degradable ELRs-hydrogel led to complete functional recovery of ejection fraction 21 days after the intervention. We observed less fibrosis and more angiogenesis in the ELRs-hydrogel-treated ischemic core region compared to the untreated animals, as validated by the expression, proteomic, glycomic, and histological analyses. These findings were accompanied by enhanced preservation of GATA4+ cardiomyocytes in the border zone of the infarct. We propose that our customized ECM favors cardiomyocyte preservation in the border zone by modulating the ischemic core and a marked functional recovery. The functional benefits obtained by the timely injection of the ELRs-hydrogel in a clinically relevant MI model support the potential utility of this treatment for further clinical translation.

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.

Fine needle aspiration (FNA) is the reference standard for the diagnosis of thyroid nodules. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been successfully used to discriminate the proteomic profiles of benign and malignant thyroid FNAs within the scope of providing support to pathologists for the classification of morphologically borderline cases. However, real FNAs provide a limited amount of material due to sample collection restrictions. Ex vivo FNAs could represent a valuable alternative, increasing sample size and the power of statistical conclusions. In this study, we compared the real and ex vivo MALDI-MSI proteomic profiles, extracted from thyrocyte containing regions of interest, of 13 patients in order to verify their similarity. Statistical analysis demonstrated the mass spectra similarity of the proteomic profiles by performing intra-patient comparison, using statistical similarity systems. In conclusion, these results show that post-surgical FNAs represent a possible alternative source of material for MALDI-MSI proteomic investigations in instances where pre-surgical samples are unavailable or the number of cells is scarce. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-020-03088-4.