Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery.

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

Investigating alpha-synuclein co-pathology in Alzheimer's disease by means of cerebrospinal fluid alpha-synuclein seed amplification assay.

INTRODUCTION: Lewy body disease, a frequently observed co-pathology in Alzheimer's disease (AD), can be identified antemortem in cerebrospinal fluid (CSF) by α-synuclein seed amplification assay (αS-SAA). The prevalence and clinical impact of CSF αS-SAA positivity in AD are still unknown. METHODS: αS-SAA was performed on CSF samples from 240 AD patients (preclinical, prodromal, and dementia stages), 85 controls, 84 patients with Parkinson's disease (PD), and 21 patients with PD with dementia or dementia with Lewy bodies. In AD patients, associations between αS-SAA positivity and cognitive changes were also evaluated. RESULTS: In agreement with available neuropathological studies, αS-SAA positivity was observed in 30% of AD patients (vs 9% in controls), and was associated with cognitive decline, visuospatial impairment, and behavioral disturbances. DISCUSSION: αS-SAA positivity in AD patients reflects the prevalence observed in neuropathological series and is associated with a worse clinical outcome. These data confirm the validity of CSF αS-SAA positivity as biomarker of synucleinopathy.

Fully automated measurement of plasma Aß42/40 and p-tau181: Analytical robustness and concordance with cerebrospinal fluid profile along the Alzheimer's disease continuum in two independent cohorts.

INTRODUCTION: For routine clinical implementation of Alzheimer's disease (AD) plasma biomarkers, fully automated random-access platforms are crucial to ensure reproducible measurements. We aimed to perform an analytical validation and to establish cutoffs for AD plasma biomarkers measured with Lumipulse. METHODS: Two cohorts were included. UNIPG: n = 450 paired cerebrospinal fluid (CSF)/plasma samples from subjects along the AD-continuum, subjects affected by other neurodegenerative diseases, and controls with known CSF profile; AMS: n = 40 plasma samples from AD and n = 40 controls. Plasma amyloid ß (Aß)42, Aß40, and p-tau181 were measured with Lumipulse. We evaluated analytical and diagnostic performance. RESULTS: Lumipulse assays showed high analytical performance. Plasma p-tau181 levels accurately reflected CSF A+/T+ profile in AD-dementia and mild cognitive impairment (MCI)-AD, but not in asymptomatic-AD. Plasma and CSF Aß42/40 values were concordant across clinical AD stages. Cutoffs and probability-based models performed satisfactorily in both cohorts. DISCUSSION: The identified cutoffs and probability-based models represent a significant step toward plasma AD molecular diagnosis.

Kidney Fibrosis and Oxidative Stress: From Molecular Pathways to New Pharmacological Opportunities.

Kidney fibrosis, diffused into the interstitium, vessels, and glomerulus, is the main pathologic feature associated with loss of renal function and chronic kidney disease (CKD). Fibrosis may be triggered in kidney diseases by different genetic and molecular insults. However, several studies have shown that fibrosis can be linked to oxidative stress and mitochondrial dysfunction in CKD. In this review, we will focus on three pathways that link oxidative stress and kidney fibrosis, namely: (i) hyperglycemia and mitochondrial energy imbalance, (ii) the mineralocorticoid signaling pathway, and (iii) the hypoxia-inducible factor (HIF) pathway. We selected these pathways because they are targeted by available medications capable of reducing kidney fibrosis, such as sodium-glucose cotransporter-2 (SGLT2) inhibitors, non-steroidal mineralocorticoid receptor antagonists (MRAs), and HIF-1alpha-prolyl hydroxylase inhibitors. These drugs have shown a reduction in oxidative stress in the kidney and a reduced collagen deposition across different CKD subtypes. However, there is still a long and winding road to a clear understanding of the anti-fibrotic effects of these compounds in humans, due to the inherent practical and ethical difficulties in obtaining sequential kidney biopsies and the lack of specific fibrosis biomarkers measurable in easily accessible matrices like urine. In this narrative review, we will describe these three pathways, their interconnections, and their link to and activity in oxidative stress and kidney fibrosis.

CSF and plasma Aß42/40 across Alzheimer's disease continuum: comparison of two ultrasensitive Simoa® assays targeting distinct amyloid regions.

OBJECTIVES: Decreased cerebrospinal fluid (CSF) amyloid beta 42/40 ratio (Aß42/40) is one of the core Alzheimer's disease (AD) biomarkers. Measurement of Aß42/40 in plasma has also been proposed as a surrogate marker for amyloidosis, however the validity and the diagnostic performance of this biomarker is still uncertain. Here we evaluated two immunoassays targeting distinct regions of the amyloid peptides by (a) performing a method comparison in both CSF and plasma, and (b) assessing the diagnostic performance across the AD continuum. METHODS: We used N4PE and N3PA Simoa® assays to measure Aß42/40 in CSF and plasma of 134 patients: preclinical AD (pre-AD, n=19), mild cognitive impairment due to AD (MCI-AD, n=41), AD at the dementia stage (AD-dem, n=35), and a control group (CTRL, n=39). The N4PE includes a detector antibody targeting the amyloid N-terminus, while the N3PA uses a detector targeting amyloid mid-region. RESULTS: Method comparison of N4PE and N3PA assays revealed discrepancies in assessment of plasma Aß42/Aß40. While the diagnostic performance of the two assays did not significantly differ in CSF, in plasma, N4PE assay provided better accuracy for AD discrimination than N3PA assay (AUC AD-dem vs. CTRL 0.77 N4PE, 0.68 N3PA). CONCLUSIONS: While both Aß42/40 assays allowed for an effective discrimination between CTRL and different AD stages, the assay targeting amyloid N-terminal region provided the best diagnostic performance in plasma. Differences observed in technical and diagnostic performance of the two assays may depend on matrix-specific amyloid processing, suggesting that further studies should be carried to standardize amyloid ratio measurement in plasma.

Trajectories of CSF and plasma biomarkers across Alzheimer's disease continuum: disease staging by NF-L, p-tau181, and GFAP.

CSF-to-plasma transition will open new avenues for molecular phenotyping of Alzheimer's disease (AD). Here we evaluated a panel of AD biomarkers in matched CSF and plasma samples across the AD continuum, from preclinical AD to dementia. The aims were to: 1) compare diagnostic performance of the two biofluids, 2) evaluate trajectories of the biomarkers along AD progression. We analyzed CSF and plasma Aß42/40, p-tau181, p-tau231, t-tau, NF-L, GFAP, UCHL-1 and CSF SNAP-25 in a cohort (n = 173) of preclinical AD, MCI-AD, AD dementia, frontotemporal dementia patients, and controls. We found a significant correlation between CSF and plasma levels of Aß42/40, p-tau181, p-tau231, NF-L, and GFAP, while no CSF-plasma correlation was observed for t-tau and UCHL-1. Next to the core CSF biomarkers (Aß42/40, p-tau181, t-tau), those providing the best discrimination between controls and preclinical AD were CSF p-tau231 and SNAP-25 and plasma Aß42/40, p-tau231, and GFAP. Among plasma biomarkers, we found Aß42/Aß40, GFAP, and p-tau231 to show the largest rate of change at the CSF biomarker-defined cut-offs for amyloidosis and tauopathy. Finally, we identified GFAP, NF-L, and p-tau181 as the biomarkers most significantly associated with disease progression in both CSF and plasma. We suggest that a well-standardized and validated panel of selected plasma markers can facilitate early AD diagnosis, even at the asymptomatic disease stage. We propose that both CSF and plasma measurement of NF-L, p-tau181, and GFAP may play a significant role in disease staging and monitoring.

Required improvements for cerebrospinal fluid-based biomarker tests of Alzheimer's disease.

INTRODUCTION: Cerebrospinal fluid (CSF) biomarkers represent a well-established tool for diagnosing Alzheimer's disease (AD), independently from the clinical stage, by reflecting the presence of brain amyloidosis (A+) and tauopathy (T+). In front of this important achievement, so far, (i) CSF AD biomarkers have not yet been adopted for routine clinical use in all Centers dedicated to AD, mainly due to inter-lab variation and lack of internationally accepted cutoff values; (ii) we do need to add other biomarkers more suitable to correlate with the clinical stage and disease monitoring; (iii) we also need to detect the co-presence of other 'non-AD' pathologies. AREAS COVERED: Efforts to establish standardized cutoff values based on large-scale multi-center studies are discussed. The influence of aging and comorbidities on CSF biomarker levels is also analyzed, and possible solutions are presented, i.e. complementing the A/T/(N) system with markers of axonal damage and synaptic derangement. EXPERT OPINION: The first, mandatory need is to reach common cutoff values and defined (automated) methodologies for CSF AD biomarkers. To properly select subjects deserving CSF analysis, blood tests might represent the first-line approach. In those subjects undergoing CSF analysis, multiple biomarkers, able to give a comprehensive and personalized pathophysiological/prognostic information, should be included.

Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias.

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Potential diagnostic value of CSF metabolism-related proteins across the Alzheimer's disease continuum.

BACKGROUND: Alzheimer's disease (AD) cerebrospinal fluid (CSF) core biomarkers (Aß42/40 ratio, p-tau, and t-tau) provide high diagnostic accuracy, even at the earliest stage of disease. However, these markers do not fully reflect the complex AD pathophysiology. Recent large scale CSF proteomic studies revealed several new AD candidate biomarkers related to metabolic pathways. In this study we measured the CSF levels of four metabolism-related proteins not directly linked to amyloid- and tau-pathways (i.e., pyruvate kinase, PKM; aldolase, ALDO; ubiquitin C-terminal hydrolase L1, UCHL1, and fatty acid-binding protein 3, FABP3) across the AD continuum. We aimed at validating the potential value of these proteins as new CSF biomarkers for AD and their possible involvement in AD pathogenesis, with specific interest on the preclinical phase of the disease. METHODS: CSF PKM and ALDO activities were measured with specific enzyme assays while UCHL1 and FABP3 levels were measured with immunoassays in a cohort of patients composed as follows: preclinical AD (pre-AD, n = 19, cognitively unimpaired), mild cognitive impairment due to AD (MCI-AD, n = 50), dementia due to AD (ADdem, n = 45), and patients with frontotemporal dementia (FTD, n = 37). Individuals with MCI not due to AD (MCI, n = 30) and subjective cognitive decline (SCD, n = 52) with negative CSF AD-profile, were enrolled as control groups. RESULTS: CSF UCHL1 and FABP3 levels, and PKM activity were significantly increased in AD patients, already at the pre-clinical stage. CSF PKM activity was also increased in FTD patients compared with control groups, being similar between AD and FTD patients. No difference was found in ALDO activity among the groups. UCHL1 showed good performance in discriminating early AD patients (pre-AD and MCI-AD) from controls (AUC ~ 0.83), as assessed by ROC analysis. Similar results were obtained for FABP3. Conversely, PKM provided the best performance when comparing FTD vs. MCI (AUC = 0.80). Combination of PKM, FABP3, and UCHL1 improved the diagnostic accuracy for the detection of patients within the AD continuum when compared with single biomarkers. CONCLUSIONS: Our study confirmed the potential role of UCHL1 and FABP3 as neurodegenerative biomarkers for AD. Furthermore, our results validated the increase of PKM activity in CSF of AD patients, already at the preclinical phase of the disease. Increased PKM activity was observed also in FTD patients, possibly underlining similar alterations in energy metabolism in AD and FTD.

Cerebrospinal fluid lipoproteins inhibit α-synuclein aggregation by interacting with oligomeric species in seed amplification assays.

BACKGROUND: Aggregation of α-synuclein (α-syn) is a prominent feature of Parkinson's disease (PD) and other synucleinopathies. Currently, α-syn seed amplification assays (SAAs) using cerebrospinal fluid (CSF) represent the most promising diagnostic tools for synucleinopathies. However, CSF itself contains several compounds that can modulate the aggregation of α-syn in a patient-dependent manner, potentially undermining unoptimized α-syn SAAs and preventing seed quantification. METHODS: In this study, we characterized the inhibitory effect of CSF milieu on detection of α-syn aggregates by means of CSF fractionation, mass spectrometry, immunoassays, transmission electron microscopy, solution nuclear magnetic resonance spectroscopy, a highly accurate and standardized diagnostic SAA, and different in vitro aggregation conditions to evaluate spontaneous aggregation of α-syn. RESULTS: We found the high-molecular weight fraction of CSF (> 100,000 Da) to be highly inhibitory on α-syn aggregation and identified lipoproteins to be the main drivers of this effect. Direct interaction between lipoproteins and monomeric α-syn was not detected by solution nuclear magnetic resonance spectroscopy, on the other hand we observed lipoprotein-α-syn complexes by transmission electron microscopy. These observations are compatible with hypothesizing an interaction between lipoproteins and oligomeric/proto-fibrillary α-syn intermediates. We observed significantly slower amplification of α-syn seeds in PD CSF when lipoproteins were added to the reaction mix of diagnostic SAA. Additionally, we observed a decreased inhibition capacity of CSF on α-syn aggregation after immunodepleting ApoA1 and ApoE. Finally, we observed that CSF ApoA1 and ApoE levels significantly correlated with SAA kinetic parameters in n = 31 SAA-negative control CSF samples spiked with preformed α-syn aggregates. CONCLUSIONS: Our results describe a novel interaction between lipoproteins and α-syn aggregates that inhibits the formation of α-syn fibrils and could have relevant implications. Indeed, the donor-specific inhibition of CSF on α-syn aggregation explains the lack of quantitative results from analysis of SAA-derived kinetic parameters to date. Furthermore, our data show that lipoproteins are the main inhibitory components of CSF, suggesting that lipoprotein concentration measurements could be incorporated into data analysis models to eliminate the confounding effects of CSF milieu on α-syn quantification efforts.

C1q is increased in cerebrospinal fluid-derived extracellular vesicles in Alzheimer's disease: A multi-cohort proteomics and immuno-assay validation study.

INTRODUCTION: Extracellular vesicles (EVs) may propagate and modulate Alzheimer's disease (AD) pathology. We aimed to comprehensively characterize the proteome of cerebrospinal fluid (CSF) EVs to identify proteins and pathways altered in AD. METHODS: CSF EVs were isolated by ultracentrifugation (Cohort 1) or Vn96 peptide (Cohort 2) from non-neurodegenerative controls (n = 15, 16) and AD patients (n = 22, 20, respectively). EVs were subjected to untargeted quantitative mass spectrometry-based proteomics. Results were validated by enzyme-linked immunosorbent assay (ELISA) in Cohorts 3 and 4, consisting of controls (n = 16, n = 43, (Cohort3, Cohort4)), and patients with AD (n = 24, n = 100). RESULTS: We found > 30 differentially expressed proteins in AD CSF EVs involved in immune-regulation. Increase of C1q levels in AD compared to non-demented controls was validated by ELISA (∼ 1.5 fold, p (Cohort 3) = 0.03, p (Cohort 4) = 0.005). DISCUSSION: EVs may be utilized as a potential biomarker and may play a so far unprecedented role in immune-regulation in AD.

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women.

BACKGROUND: A non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls. METHODS: This was a prospective case-control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression. RESULTS: The top discriminatory proteins individually showed moderate accuracy (AUC > 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs > 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96-0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86-0.9)). CONCLUSION: A patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted.

Extracellular Vesicles in Aging: An Emerging Hallmark?

Extracellular vesicles (EVs) are membrane-enclosed particles secreted by cells and circulating in body fluids. Initially considered as a tool to dispose of unnecessary material, they are now considered an additional method to transmit cell signals. Aging is characterized by a progressive impairment of the physiological functions of tissues and organs. The causes of aging are complex and interconnected, but there is consensus that genomic instability, telomere erosion, epigenetic alteration, and defective proteostasis are primary hallmarks of the aging process. Recent studies have provided evidence that many of these primary stresses are associated with an increased release of EVs in cell models, able to spread senescence signals in the recipient cell. Additional investigations on the role of EVs during aging also demonstrated the great potential of EVs for the modulation of age-related phenotypes and for pro-rejuvenation therapies, potentially beneficial for many diseases associated with aging. Here we reviewed the current literature on EV secretion in senescent cell models and in old vs. young individual body fluids, as well as recent studies addressing the potential of EVs from different sources as an anti-aging tool. Although this is a recent field, the robust consensus on the altered EV release in aging suggests that altered EV secretion could be considered an emerging hallmark of aging.

Donor natural killer cells trigger production of ß-2-microglobulin to enhance post-bone marrow transplant immunity.

Allogeneic hematopoietic transplantation is a powerful treatment for hematologic malignancies. Posttransplant immune incompetence exposes patients to disease relapse and infections. We previously demonstrated that donor alloreactive natural killer (NK) cells ablate recipient hematopoietic targets, including leukemia. Here, in murine models, we show that infusion of donor alloreactive NK cells triggers recipient dendritic cells (DCs) to synthesize ß-2-microglobulin (B2M) that elicits the release of c-KIT ligand and interleukin-7 that greatly accelerate posttransplant immune reconstitution. An identical chain of events was reproduced by infusing supernatants of alloreactive NK/DC cocultures. Similarly, human alloreactive NK cells triggered human DCs to synthesize B2M that induced interleukin-7 production by thymic epithelial cells and thereby supported thymocyte cellularity in vitro. Chromatography fractionation of murine and human alloreactive NK/DC coculture supernatants identified a protein with molecular weight and isoelectric point of B2M, and mass spectrometry identified amino acid sequences specific of B2M. Anti-B2M antibody depletion of NK/DC coculture supernatants abrogated their immune-rebuilding effect. B2M knock-out mice were unable to undergo accelerated immune reconstitution, but infusion of (wild-type) NK/DC coculture supernatants restored their ability to undergo accelerated immune reconstitution. Similarly, silencing the B2M gene in human DCs, before coculture with alloreactive NK cells, prevented the increase in thymocyte cellularity in vitro. Finally, human recombinant B2M increased thymocyte cellularity in a thymic epithelial cells/thymocyte culture system. Our studies uncover a novel therapeutic principle for treating posttransplant immune incompetence and suggest that, upon its translation to the clinic, patients may benefit from adoptive transfer of large numbers of cytokine-activated, ex vivo-expanded donor alloreactive NK cells.

Phosphatidylethanolamine Binding Protein 1 (PEBP1) in Alzheimer's Disease: ELISA Development and Clinical Validation.

BACKGROUND: Phosphatidylethanolamine binding protein 1 (PEBP1) is a multifunctional protein, mainly known for its specific binding of phosphatidylethanolamine and the ability to suppress the Raf1-MAPK pathway. Its potential role as an Alzheimer's disease (AD) biomarker has been proposed in several studies. However, evaluation of its discriminative value in clinical cohorts is missing. OBJECTIVE: We aimed to develop a new immunoassay for the measurement of PEBP1 in cerebrospinal fluid (CSF) and assess the possible role of this protein as AD biomarker. METHODS: We developed a sandwich enzyme-linked immunosorbent assay (ELISA) for detection of PEBP1 in CSF and performed a technical and a clinical validation on two well-characterized cohorts. The first cohort included 14 mild cognitive impairment due to AD (MCI-AD) and 11 other neurological diseases (OND) patients. The second, larger cohort, included 25 MCI-AD, 29 AD dementia (AD-dem), and 21 OND patients. RESULTS: PEBP1 is highly sensitive to pre-analytical conditions, especially to prolonged storage at room temperature or 4°C. Analysis of the first cohort showed a trend of an increase of PEBP1 level in MCI-AD patients versus OND subjects. Analysis of the second cohort did not show significant differences among diagnostic groups. Weak, positive correlation was found between CSF PEBP1 and t-tau, p-tau, and Aß40 in the AD-dem group. CONCLUSION: A novel ELISA for the detection of PEBP1 in CSF was developed. Further research is needed to assess the potential of PEBP1 in AD diagnostics. The observed dependence of the PEBP1 signal on operating procedures encourages its potential application as CSF quality control.

Structural dynamics shape the fitness window of alanine:glyoxylate aminotransferase.

The conformational landscape of a protein is constantly expanded by genetic variations that have a minimal impact on the function(s) while causing subtle effects on protein structure. The wider the conformational space sampled by these variants, the higher the probabilities to adapt to changes in environmental conditions. However, the probability that a single mutation may result in a pathogenic phenotype also increases. Here we present a paradigmatic example of how protein evolution balances structural stability and dynamics to maximize protein adaptability and preserve protein fitness. We took advantage of known genetic variations of human alanine:glyoxylate aminotransferase (AGT1), which is present as a common major allelic form (AGT-Ma) and a minor polymorphic form (AGT-Mi) expressed in 20% of Caucasian population. By integrating crystallographic studies and molecular dynamics simulations, we show that AGT-Ma is endowed with structurally unstable (frustrated) regions, which become disordered in AGT-Mi. An in-depth biochemical characterization of variants from an anticonsensus library, encompassing the frustrated regions, correlates this plasticity to a fitness window defined by AGT-Ma and AGT-Mi. Finally, co-immunoprecipitation analysis suggests that structural frustration in AGT1 could favor additional functions related to protein-protein interactions. These results expand our understanding of protein structural evolution by establishing that naturally occurring genetic variations tip the balance between stability and frustration to maximize the ensemble of conformations falling within a well-defined fitness window, thus expanding the adaptability potential of the protein.

Interleukin-17 affects synaptic plasticity and cognition in an experimental model of multiple sclerosis.

Cognitive impairment (CI) is a disabling concomitant of multiple sclerosis (MS) with a complex and controversial pathogenesis. The cytokine interleukin-17A (IL-17A) is involved in the immune pathogenesis of MS, but its possible effects on synaptic function and cognition are still largely unexplored. In this study, we show that the IL-17A receptor (IL-17RA) is highly expressed by hippocampal neurons in the CA1 area and that exposure to IL-17A dose-dependently disrupts hippocampal long-term potentiation (LTP) through the activation of its receptor and p38 mitogen-activated protein kinase (MAPK). During experimental autoimmune encephalomyelitis (EAE), IL-17A overexpression is paralleled by hippocampal LTP dysfunction. An in vivo behavioral analysis shows that visuo-spatial learning abilities are preserved when EAE is induced in mice lacking IL-17A. Overall, this study suggests a key role for the IL-17 axis in the neuro-immune cross-talk occurring in the hippocampal CA1 area and its potential involvement in synaptic dysfunction and MS-related CI.

A Prostate Cancer Proteomics Database for SWATH-MS Based Protein Quantification.

Prostate cancer is the most frequent form of cancer in men, accounting for more than one-third of all cases. Current screening techniques, such as PSA testing used in conjunction with routine procedures, lead to unnecessary biopsies and the discovery of low-risk tumours, resulting in overdiagnosis. SWATH-MS is a well-established data-independent (DI) method requiring prior knowledge of targeted peptides to obtain valuable information from SWATH maps. In response to the growing need to identify and characterise protein biomarkers for prostate cancer, this study explored a spectrum source for targeted proteome analysis of blood samples. We created a comprehensive prostate cancer serum spectral library by combining data-dependent acquisition (DDA) MS raw files from 504 patients with low, intermediate, or high-grade prostate cancer and healthy controls, as well as 304 prostate cancer-related protein in silico assays. The spectral library contains 114,684 transitions, which equates to 18,479 peptides translated into 1227 proteins. The robustness and accuracy of the spectral library were assessed to boost confidence in the identification and quantification of prostate cancer-related proteins across an independent cohort, resulting in the identification of 404 proteins. This unique database can facilitate researchers to investigate prostate cancer protein biomarkers in blood samples. In the real-world use of the spectrum library for biomarker detection, using a signature of 17 proteins, a clear distinction between the validation cohort's pre- and post-treatment groups was observed. Data are available via ProteomeXchange with identifier PXD028651.

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

Cerebrospinal fluid hemoglobin levels as markers of blood contamination: relevance for α-synuclein measurement.

OBJECTIVES: Cerebrospinal fluid α-synuclein (CSF α-syn) represents a possible biomarker in Parkinson's disease (PD) diagnosis. CSF blood contamination can introduce a bias in α-syn measurement. To date, CSF samples with a red blood cells (RBC) count >50 RBC × 106/L or haemoglobin (Hb) concentration >200 µg/L are excluded from biomarker studies. However, investigations for defining reliable cut-off values are missing. METHODS: We evaluated the effect of blood contamination on CSF α-syn measurement by a systematic approach in a cohort of 42 patients with different neurological conditions who underwent lumbar puncture (LP) for diagnostic reasons. CSF samples were spiked with whole blood and serially diluted to 800, 400, 200, 100, 75, 50, 25, 5, 0 RBC × 106/L. CSF α-syn and Hb levels were measured by ELISA. RESULTS: In neat CSF, the average concentration of α-syn was 1,936 ± 636 ng/L. This value increased gradually in spiked CSF samples, up to 4,817 ± 1,456 ng/L (+149% α-syn variation) in samples with 800 RBC × 106/L. We established different cut-offs for discriminating samples with α-syn level above 5, 10, and 20% variation, corresponding to a Hb (RBC) concentration of 1,569 µg/L (37 RBC × 106/L), 2,082 µg/L (62 RBC × 106/L), and 3,118 µg/L (87 RBC × 106/L), respectively. CONCLUSIONS: Our data show the high impact of CSF blood contamination on CSF α-syn levels, highlighting the measurement of Hb concentration as mandatory when assessing CSF α-syn. The thresholds we calculated are useful to classify CSF samples for blood contamination, considering as reliable only those showing a Hb concentration <1,569 µg/L.