Mitochondrial remodeling underlying age-induced skeletal muscle wasting: let's talk about sex

Sarcopenia is associated with reduced quality of life and premature mortality. The sex disparities in the processes underlying sarcopenia pathogenesis, which include mitochondrial dysfunction, are ill-understood and can be decisive for the optimization of sarcopenia-related interventions. To improve the knowledge regarding the sex differences in skeletal muscle aging, the gastrocnemius muscle of young and old female and male rats was analyzed with a focus on mitochondrial remodeling through the proteome profiling of mitochondria-enriched fractions. To the best of our knowledge, this is the first study analyzing sex differences in skeletal muscle mitochondrial proteome remodeling. Data demonstrated that age induced skeletal muscle atrophy and fibrosis in both sexes. In females, however, this adverse skeletal muscle remodeling was more accentuated than in males and might be attributed to an age-related reduction of 17beta-estradiol signaling through its estrogen receptor alpha located in mitochondria. The females-specific mitochondrial remodeling encompassed increased abundance of proteins involved in fatty acid oxidation, decreased abundance of the complexes subunits, and enhanced proneness to oxidative posttranslational modifications. This conceivable accretion of damaged mitochondria in old females might be ascribed to low levels of Parkin, a key mediator of mitophagy. Despite skeletal muscle atrophy and fibrosis, males maintained their testosterone levels throughout aging, as well as their androgen receptor content, and the age-induced mitochondrial remodeling was limited to increased abundance of pyruvate dehydrogenase E1 component subunit beta and electron transfer flavoprotein subunit beta. Herein, for the first time, it was demonstrated that age affects more severely the skeletal muscle mitochondrial proteome of females, reinforcing the necessity of sex-personalized approaches towards sarcopenia management, and the inevitability of the assessment of mitochondrion-related therapeutics.

Exploiting the therapeutic potential of contracting skeletal muscle-released extracellular vesicles in cancer: Current insights and future directions

The health benefits of exercise training in a cancer setting are increasingly acknowledged; however, the underlying molecular mechanisms remain poorly understood. It has been suggested that extracellular vesicles (EVs) released from contracting skeletal muscles play a key role in mediating the systemic benefits of exercise by transporting bioactive molecules, including myokines. Nevertheless, skeletal muscle-derived vesicles account for only about 5% of plasma EVs, with the immune cells making the largest contribution. Moreover, it remains unclear whether the contribution of skeletal muscle-derived EVs increases after physical exercise or how muscle contraction modulates the secretory activity of other tissues and thus influences the content and profile of circulating EVs. Furthermore, the destination of EVs after exercise is unknown, and it depends on their molecular composition, particularly adhesion proteins. The cargo of EVs is influenced by the training program, with acute training sessions having a greater impact than chronic adaptations. Indeed, there are numerous questions regarding the role of EVs in mediating the effects of exercise, the clarification of which is critical for tailoring exercise training prescriptions and designing exercise mimetics for patients unable to engage in exercise programs. This review critically analyzes the current knowledge on the effects of exercise on the content and molecular composition of circulating EVs and their impact on cancer progression.

Comprehensive characterization of protein modifications using mass spectrometry and dry blood spots

PURPOSE

The main objective of this study is to characterize and analyze modified peptides in DBS samples. This includes deciphering their specific PTMs and understanding their potential impact on the population or disease cohort under study.

EXPERIMENTAL DESIGN

Using mass spectrometry-based proteomic approaches, we performed a comprehensive analysis of DBS samples. Our focus was on the identification and quantification of modified peptides. We also took advantage of recent advances in DBS mass spectrometry to ensure accurate detection and quantification.

RESULTS

A comprehensive analysis identified 972 modified peptides in DBS samples. Of these, a subset of 211 peptides was consistently present in all samples, highlighting their potential biological importance and relevance. This indicates a diverse spectrum of PTMs in the proteome of DBS samples.

CONCLUSIONS AND CLINICAL RELEVANCE

Integration of mass spectrometry and proteomics has revealed a broad spectrum of modified peptides in DBS samples and highlighted their importance in biological processes and disease progression. Accurate detection of these PTMs may be critical for risk stratification and disease management. This study improves the understanding of molecular mechanisms underlying biological processes and disease development, providing important insights for clinical applications.

Shaping the future of oral cancer diagnosis: advances in salivary proteomics

INTRODUCTION

Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for the identification of oral cancer biomarkers. This is particularly important because oral cancer is often diagnosed at late stages with a poor prognosis.

AREAS COVERED

The review addresses the evolution of the experimental approaches used in salivary proteomics studies of oral cancer over the years and outlines advantages and pitfalls related to each one. In addition, examines the current landscape of oral cancer biomarker discovery and translation focusing on salivary proteomic studies. This discussion is based on an extensive literature search (PubMed, Scopus and Google Scholar).

EXPERT OPINION

The introduction of mass spectrometry has revolutionized the study of salivary proteomics. In the future, the focus will be on refining existing methods and introducing powerful experimental techniques such as mass spectrometry with selected reaction monitoring, which, despite their effectiveness, are still underutilized due to their high cost. In addition, conducting studies with larger cohorts and establishing standardized protocols for salivary proteomics are key challenges that need to be addressed in the coming years.

Prioritization of genes for translation: a computational approach

INTRODUCTION

Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation.

AREAS COVERED

In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes.

EXPERT OPINION

Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

Influenza A virus propagation requires the activation of the unfolded protein response and the accumulation of insoluble protein aggregates

Influenza A virus (IAV) employs multiple strategies to manipulate cellular mechanisms and support proper virion formation and propagation. In this study, we performed a detailed analysis of the interplay between IAV and the host cells' proteostasis throughout the entire infectious cycle. We reveal that IAV infection activates the inositol requiring enzyme 1 (IRE1) branch of the unfolded protein response, and that this activation is important for an efficient infection. We further observed the accumulation of virus-induced insoluble protein aggregates, containing both viral and host proteins, associated with a dysregulation of the host cell RNA metabolism. Our data indicate that this accumulation is important for IAV propagation and favors the final steps of the infection cycle, more specifically the virion assembly. These findings reveal additional mechanisms by which IAV disrupts host proteostasis and uncovers new cellular targets that can be explored for the development of host-directed antiviral strategies.

Acute and chronic effects of levosimendan in the ZSF1 obese rat model of heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) is a syndrome characterized by impaired cardiovascular reserve in which therapeutic options are scarce. Our aim was to evaluate the inodilator levosimendan in the ZSF1 obese rat model of HFpEF. Twenty-week-old male Wistar-Kyoto (WKY), ZSF1 lean (ZSF1 Ln) and ZSF1 obese rats chronically treated for 6-weeks with either levosimendan (1 mg/kg/day, ZSF1 Ob + Levo) or vehicle (ZSF1 Ob + Veh) underwent peak-effort testing, pressure-volume (PV) haemodynamic evaluation and echocardiography (n = 7 each). Samples were collected for histology and western blotting. In obese rats, skinned and intact left ventricular (LV) cardiomyocytes underwent in vitro functional evaluation. Seven additional ZSF1 obese rats underwent PV evaluation to assess acute levosimendan effects (10 μg/kg + 0.1 μg/kg/min). ZSF1 Ob + Veh presented all hallmarks of HFpEF, namely effort intolerance, elevated end-diastolic pressures and reduced diastolic compliance as well as increased LV mass and left atrial area, cardiomyocyte hypertrophy and increased interstitial fibrosis. Levosimendan decreased systemic arterial pressures, raised cardiac index, and enhanced LV relaxation and diastolic compliance in both acute and chronic experiments. ZSF1 Ob + Levo showed pronounced attenuation of hypertrophy and interstitial fibrosis alongside increased effort tolerance (endured workload raised 38 %) and maximum O2 consumption. Skinned cardiomyocytes from ZSF 1 Ob + Levo showed a downward shift in sarcomere length-passive tension relationship and intact cardiomyocytes showed decreased diastolic Ca2+ levels and enhanced Ca2+ sensitivity. On molecular grounds, levosimendan enhanced phosphorylation of phospholamban and mammalian target of rapamycin. The observed effects encourage future clinical trials with levosimendan in a broad population of HFpEF patients.

Long-Term Exposure to Supraphysiological Levels of Testosterone Impacts Rat Submandibular Gland Proteome

The salivary glands play a central role in the secretion of saliva, whose composition and volume affect oral and overall health. A lesser-explored dimension encompasses the possible changes in salivary gland proteomes in response to fluctuations in sex hormone levels. This study aimed to examine the effects of chronic exposure to testosterone on salivary gland remodeling, particularly focusing on proteomic adaptations. Therefore, male Wistar rats were implanted with subcutaneous testosterone-releasing devices at 14 weeks of age. Their submandibular glands were histologically and molecularly analyzed 47 weeks later. The results underscored a significant increase in gland mass after testosterone exposure, further supported by histologic evidence of granular duct enlargement. Despite increased circulating sex hormones, there was no detectable shift in the tissue levels of estrogen alpha and androgen receptors. GeLC-MS/MS and subsequent bioinformatics identified 308 proteins in the submandibular glands, 12 of which were modulated by testosterone. Of note was the pronounced upregulation of Klk3 and the downregulation of Klk6 and Klk7 after testosterone exposure. Protein-protein interaction analysis with the androgen receptor suggests that Klk3 is a potential target of androgenic signaling, paralleling previous findings in the prostate. This exploratory analysis sheds light on the response of salivary glands to testosterone exposure, providing proteome-level insights into the associated weight and histological changes.

A two-pronged approach against glioblastoma: drug repurposing and nanoformulation design for in situ-controlled release

Glioblastoma (GB) is one of the most lethal types of neoplasms. Its biologically aggressive nature and the presence of the blood-brain barrier (BBB) limit the efficacy of standard therapies. Several strategies are currently being developed to both overcome the BBB and deliver drugs site specifically to tumor cells. This work hypothesizes a two-pronged approach to tackle GB: drug repurposing with celecoxib (CXB) and a nanoformulation using ultra-small nanostructured lipid carriers (usNLCs). CXB antitumor druggable activity was inspected bioinformatically and screened in four glioma cell lines aiming at the comparison with temozolomide (TMZ), as standard of care. Delving into formulation design, it was tailored aiming at (i) improving the drug solubility/loading properties, (ii) assigning a thermal-triggerable drug release based on a lipid matrix with a low melting point, and (iii) enhancing the cytotoxic effect by selecting a template targetable to tumor cells. For this purpose, an integrated analysis of the critical material attributes (CMAs), critical process parameters (CPPs), and critical quality attributes (CQAs) was conducted under the umbrella of a quality by design approach. CMAs that demonstrate a high-risk level for the final quality and performance of the usNLCs include the drug solubility in lipids (solid and liquid), the lipid composition (envisioning a thermoresponsive approach), the ratio between lipids (solid vs. liquid), and the surfactant type and concentration. Particle size was shown to be governed by the interaction lipid-surfactant followed by surfactant type. The drug encapsulation did not influence colloidal characteristics, making it a promising carrier for lipophilic drugs. In general, usNLCs exhibited a controlled drug release during the 72 h at 37 °C with a final release of ca. 25%, while at 45 °C this was doubled. The in vitro cellular performance depended on the surfactant type and lipid composition, with the formulations containing a sole solid lipid (Suppocire® NB) and Kolliphor® RH40 as surfactant being the most cytotoxic. usNLCs with an average diameter of ca. 70 nm and a narrow size distribution (PdI lower than 0.2) were yielded, exhibiting high stability, drug protection, sustained and thermo-sensitive release properties, and high cytotoxicity to glioma cells, meeting the suitable CQAs for parenteral administration. This formulation may pave the way to a multi-addressable purpose to improve GB treatment.

Empowering peptidomics: utilizing computational tools and approaches

Bioinformatics plays a critical role in the advancement of peptidomics by providing powerful tools for data analysis, interpretation and integration. Peptidomics is concerned with the study of peptides, short chains of amino acids with diverse biological functions. This area includes peptide identification and characterization, database construction, de novo sequencing, functional annotation, omics data integration and systems biology. Artificial intelligence techniques, such as machine learning and natural language processing, aid in the interpretation of peptide sequence data and the generation of biological insights. By using bioinformatics approaches, peptidomics researchers can accelerate peptide discovery, understand their functions and gain insights into complex molecular interactions.

Exercise training decreases the load and changes the content of circulating SDS-resistant protein aggregates in patients with heart failure with reduced ejection fraction

BACKGROUND

Heart failure (HF) often disrupts the protein quality control (PQC) system leading to protein aggregate accumulation. Evidence from tissue biopsies showed that exercise restores PQC system in HF; however, little is known about its effects on plasma proteostasis.

AIM

To determine the effects of exercise training on the load and composition of plasma SDS-resistant protein aggregates (SRA) in patients with HF with reduced ejection fraction (HFrEF).

METHODS

Eighteen patients with HFrEF (age: 63.4 ± 6.5 years; LVEF: 33.4 ± 11.6%) participated in a 12-week combined (aerobic plus resistance) exercise program (60 min/session, twice per week). The load and content of circulating SRA were assessed using D2D SDS-PAGE and mass spectrometry. Cardiorespiratory fitness, quality of life, and circulating levels of high-sensitive C-reactive protein, N-terminal pro-B-type natriuretic peptide (NT-proBNP), haptoglobin and ficolin-3, were also evaluated at baseline and after the exercise program.

RESULTS

The exercise program decreased the plasma SRA load (% SRA/total protein: 38.0 ± 8.9 to 36.1 ± 9.7%, p = 0.018; % SRA/soluble fraction: 64.3 ± 27.1 to 59.8 ± 27.7%, p = 0.003). Plasma SRA of HFrEF patients comprised 31 proteins, with α-2-macroglobulin and haptoglobin as the most abundant ones. The exercise training significantly increased haptoglobin plasma levels (1.03 ± 0.40 to 1.11 ± 0.46, p = 0.031), while decreasing its abundance in SRA (1.83 ± 0.54 × 1011 to 1.51 ± 0.59 × 1011, p = 0.049). Cardiorespiratory fitness [16.4(5.9) to 19.0(5.2) ml/kg/min, p = 0.002], quality of life, and circulating NT-proBNP [720.0(850.0) to 587.0(847.3) pg/mL, p = 0.048] levels, also improved after the exercise program.

CONCLUSION

Exercise training reduced the plasma SRA load and enhanced PQC, potentially via haptoglobin-mediated action, while improving cardiorespiratory fitness and quality of life of patients with HFrEF.

Expression of NORAD correlates with breast cancer aggressiveness and protects breast cancer cells from chemotherapy

The recently discovered human lncRNA NORAD is induced after DNA damage in a p53-dependent manner. It plays a critical role in the maintenance of genomic stability through interaction with Pumilio proteins, limiting the repression of their target mRNAs. Therefore, NORAD inactivation causes chromosomal instability and aneuploidy, which contributes to the accumulation of genetic abnormalities and tumorigenesis. NORAD has been detected in several types of cancer, including breast cancer, which is the most frequently diagnosed and the second-leading cause of cancer death in women. In the present study, we confirmed upregulated NORAD expression levels in a set of human epithelial breast cancer cell lines (MDA-MB-231, MDA-MB-436, and MDA-MB-468), which belong to the most aggressive subtypes (triple-negative breast cancer). These results are in line with previous data showing that high NORAD expression levels in basal-like tumors were associated with poor prognosis. Here, we demonstrate that NORAD downregulation sensitizes triple-negative breast cancer cells to chemotherapy, through a potential accumulation of genomic aberrations and an impaired capacity to signal DNA damage. These results show that NORAD may represent an unexploited neoadjuvant therapeutic target for chemotherapy-unresponsive breast cancer.

Ceramides and ceramide synthases in cancer: Focus on apoptosis and autophagy

Different studies corroborate a role for ceramide synthases and their downstream products, ceramides, in modulation of apoptosis and autophagy in the context of cancer. These mechanisms of regulation, however, appear to be context dependent in terms of ceramides' fatty acid chain length, subcellular localization, and the presence or absence of their downstream targets. Our current understanding of the role of ceramide synthases and ceramides in regulation of apoptosis and autophagy could be harnessed to pioneer the development of new treatments to activate or inhibit a single type of ceramide synthase, thereby regulating the apoptosis induction or cross talk of apoptosis and autophagy in cancer cells. Moreover, the apoptotic function of ceramide suggests that ceramide analogues can pave the way for the development of novel cancer treatments. Therefore, in the current review paper we discuss the impact of ceramide synthases and ceramides in regulation of apoptosis and autophagy in context of different types of cancers. We also briefly introduce the latest information on ceramide synthase inhibitors, their application in diseases including cancer therapy, and discuss approaches for drug discovery in the field of ceramide synthase inhibitors. We finally discussed strategies for developing strategies to use lipids and ceramides analysis in biological fluids for developing early biomarkers for cancer.

Bioinformatic analysis of the SPs and NFTs proteomes unravel putative biomarker candidates for Alzheimer's disease

Aging is the main risk factor for the appearance of age-related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks in AD brains. The core of these deposits are predominantly amyloid fibrils in SPs and hyperphosphorylated Tau protein in NFTs, but other molecular components can be found associated with these pathological lesions. Herein, an extensive literature review was carried out to obtain the SPs and NFTs proteomes, followed by a bioinformatic analysis and further putative biomarker validation. For SPs, 857 proteins were recovered, and, for NFTs, 627 proteins of which 375 occur in both groups and represent the common proteome. Gene Ontology (GO) enrichment analysis permitted the identification of biological processes and the molecular functions most associated with these lesions. Analysis of the SPs and NFTs common proteins unraveled pathways and molecular targets linking both histopathological events. Further, validation of a putative phosphotarget arising from the in silico analysis was performed in serum-derived extracellular vesicles from AD patients. This bioinformatic approach contributed to the identification of putative molecular targets, valuable for AD diagnostic or therapeutic intervention.

Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.

Special Issue: "Bioinformatics and Omics Tools"

With the rapid introduction of high-throughput omics approaches such as genomics, transcriptomics, proteomics and metabolomics, the generation of large amounts of data has become a fundamental aspect of modern biological research [...].

LSPR-Based Aptasensor for Rapid Urinary Detection of NT-proBNP

N-terminal pro-brain natriuretic peptide (NT-proBNP) is a myocardial stress biomarker that can be found in serum or plasma, saliva, and urine in the context of cardiovascular disease. In this study, we developed a rapid (~25 min) and straightforward localized surface plasmon resonance (LSPR)-based assay for detecting NT-proBNP in urine. The assay employs citrate-capped gold nanoparticles (AuNPs) and an aptamer specific for NT-proBNP, which initially interacts with NT-proBNP. The remaining unbound aptamer then interacts with the AuNPs, and the addition of NaCl induces the aggregation of the unprotected AuNPs, resulting in a decrease in absorbance at the LSPR band (A₅₂₁) and an increase in absorbance at 750 nm (A₇₅₀). The concentration of NT-proBNP showed a linear correlation with the aggregation ratio (A₅₂₁/A₇₅₀), and the assay demonstrated a limit of detection (LOD) of 0.303 µg·L^-1 and a detection range of 0.566-8 µg·L^-1. However, the presence of sulfur-containing proteins in saliva and fetal bovine serum hindered the detection of NT-proBNP in these biofluids. Nevertheless, the assay successfully detected NT-proBNP in diluted urine with an LOD of 0.417 µg·L^-1 and a detection range of 0.589-6 µg·L^-1. The observed values in urine samples from preterm infants with cardiovascular disease fell within this range, indicating the potential clinical relevance of the assay. The recovery percentages ranged from 92.3 to 116.3%. Overall, our findings suggest that the LSPR-based assay for NT-proBNP detection in urine can be a valuable tool for the diagnosis and treatment of cardiovascular disease.

Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maximally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7560 proteins related to GBM disease and 3860 proteins associated with signaling pathways involved in GBM. By integrating the results of the analyses mentioned above and again performing centrality analysis, eleven key genes involved in GBM disease were identified. ProteomicsDB and Gliovis databases were used for determining the gene expression in normal and tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of identified genes, miRNAs, and metabolites associated with GBM disease was performed using ExpressAnalyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was performed using pathway, joint pathway, and network analyses. The results of this study allowed us to identify 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, and hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose, and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in GBM disease development. The identified top genes, miRNAs, and metabolite signatures can be targeted to establish early diagnostic methods and plan personalized GBM treatment strategies.

Diagnostic and monitoring applications using Near infrared (NIR) Spectroscopy in cancer and other diseases

Early cancer diagnosis plays a critical role in improving treatment outcomes and increasing survival rates for certain cancers. NIR spectroscopy offers a rapid and cost-effective approach to evaluate the optical properties of tissues at the microvessel level and provides valuable molecular insights. The integration of NIR spectroscopy with advanced data-driven algorithms in portable instruments has made it a cutting-edge technology for medical applications. NIR spectroscopy is a simple, non-invasive and affordable analytical tool that complements expensive imaging modalities such as functional magnetic resonance imaging, positron emission tomography and computed tomography. By examining tissue absorption, scattering, and concentrations of oxygen, water, and lipids, NIR spectroscopy can reveal inherent differences between tumor and normal tissue, often revealing specific patterns that help stratify disease. In addition, the ability of NIR spectroscopy to assess tumor blood flow, oxygenation, and oxygen metabolism provides a key paradigm for its application in cancer diagnosis. This review evaluates the effectiveness of NIR spectroscopy in the detection and characterization of disease, particularly in cancer, with or without the incorporation of chemometrics and machine learning algorithms. The report highlights the potential of NIR spectroscopy technology to significantly improve discrimination between benign and malignant tumors and accurately predict treatment outcomes. In addition, as more medical applications are studied in large patient cohorts, consistent advances in clinical implementation can be expected, making NIR spectroscopy a valuable adjunct technology for cancer therapy management. Ultimately, the integration of NIR spectroscopy into cancer diagnostics promises to improve prognosis by providing critical new insights into cancer patterns and physiology.

Gold nanoparticle probes for colorimetric detection of plasma galectin-3: a simple and rapid approach

Galectin-3 (Gal-3) is a carbohydrate-binding protein associated with the development and progress of heart failure. Here, we report the first colorimetric and low-cost approach for detecting and quantifying Gal-3 using gold nanoparticles (AuNPs) bioconjugated with Gal-3 antibody. The interaction of Gal-3 with the resulting nanoprobes led to a linear response of the absorbance ratio A_750nm/A_526nm to Gal-3 concentration, accompanied by a change in color intensity. The assay showed a linear optical response even in complex samples, such as saliva and fetal bovine serum (FBS), up to a concentration of 200 μg L^-1. The limit of detection (LOD) followed the trend LOD_PBS (10.0 μg L^-1) < LOD_saliva (22.6 μg L^-1) < LOD_FBS (25.3 μg L^-1). The potential applicability of this method to the analysis of human plasma samples was also demonstrated. Compared to conventional detection techniques, this colorimetric assay provides faster results (∼1 h) and is more cost-effective due to the use of simple and unexpensive equipment. This assay represents an exciting solution for the rapid screening of high risk for rapid progression of heart failure in patient samples (Gal-3 > 25.9 μg L^-1).

Salivary ATR-FTIR Spectroscopy Coupled with Support Vector Machine Classification for Screening of Type 2 Diabetes Mellitus

The blood diagnosis of diabetes mellitus (DM) is highly accurate; however, it is an invasive, high-cost, and painful procedure. In this context, the combination of ATR-FTIR spectroscopy and machine learning techniques in other biological samples has been used as an alternative tool to develop a non-invasive, fast, inexpensive, and label-free diagnostic or screening platform for several diseases, including DM. In this study, we used the ATR-FTIR tool associated with linear discriminant analysis (LDA) and a support vector machine (SVM) classifier in order to identify changes in salivary components to be used as alternative biomarkers for the diagnosis of type 2 DM. The band area values of 2962 cm^-1, 1641 cm^-1, and 1073 cm^-1 were higher in type 2 diabetic patients than in non-diabetic subjects. The best classification of salivary infrared spectra was by SVM, showing a sensitivity of 93.3% (42/45), specificity of 74% (17/23), and accuracy of 87% between non-diabetic subjects and uncontrolled type 2 DM patients. The SHAP features of infrared spectra indicate the main salivary vibrational modes of lipids and proteins that are responsible for discriminating DM patients. In summary, these data highlight the potential of ATR-FTIR platforms coupled with machine learning as a reagent-free, non-invasive, and highly sensitive tool for screening and monitoring diabetic patients.

Chemotherapy-Induced Molecular Changes in Skeletal Muscle

Paraneoplastic conditions such as cancer cachexia are often exacerbated by chemotherapy, which affects the patient’s quality of life as well as the response to therapy. The aim of this narrative review was to overview the body-composition-related changes and molecular effects of different chemotherapy agents used in cancer treatment on skeletal-muscle remodeling. A literature search was performed using the Web of Science, Scopus, and Science Direct databases and a total of 77 papers was retrieved. In general, the literature survey showed that the molecular changes induced by chemotherapy in skeletal muscle have been studied mainly in animal models and mostly in non-tumor-bearing rodents, whereas clinical studies have essentially assessed changes in body composition by computerized tomography. Data from preclinical studies showed that chemotherapy modulates several molecular pathways in skeletal muscle, including the ubiquitin–proteasome pathway, autophagy, IGF-1/PI3K/Akt/mTOR, IL-6/JAK/STAT, and NF-κB pathway; however, the newest chemotherapy agents are underexplored. In conclusion, chemotherapy exacerbates skeletal-muscle wasting in cancer patients; however, the incomplete characterization of the chemotherapy-related molecular effects on skeletal muscle makes the development of new preventive anti-wasting strategies difficult. Therefore, further investigation on molecular mechanisms and clinical studies are necessary.

Galectin-3 in prostate cancer and heart diseases: a biomarker for these two frightening pathologies?

Galectin-3 (Gal-3) belongs to galectin protein family, a type of β-galactose-binding lectin having more than one evolutionarily conserved domain of carbohydrate recognition. Gal-3 is mainly located in the cytoplasm, but it also enters the nucleus and is secreted into the extracellular environment and biological fluids such as urine, saliva, and serum. It plays an important role in many biological functions, such as angiogenesis, apoptosis, cell differentiation, cell growth, fibrosis, inflammation, host defense, cellular modification, splicing of pre-mRNA, and transformation. Many previous studies have shown that Gal-3 can be used as a diagnostic or prognostic biomarker for heart ailments, kidney diseases, and other major illnesses including cancer. Moreover, it may also play a major role in risk stratification in different diseases, and in this review, we have summarized the potential roles and application of Gal-3 as diagnostic, prognostic, and risk stratifying biomarker from previously reported studies in heart diseases and cancer, with special emphasis on prostate cancer.

Gal-3 Protein Expression and Localization in Prostate Tumours

Gal-3 plays an important role in cell survival, mRNA splicing, and cell–cell and cell–matrix interactions. Depending on its cellular localization and cancer type, Gal-3 may have tumour-suppressive or tumour-promoting activities. Given the promising diagnostic role of Gal-3 in the urine of PCa patients found in our previous study, its concordant gene and protein expression levels, and its involvement in PCa-related biological processes (e.g., morphogenesis of the prostate gland epithelium), we aimed to investigate this protein immunohistochemically in tumour and normal prostate tissues. Gal-3 protein expression was evaluated in 48 tumour prostate tissues, eight normal prostate tissues and 14 adjacent-normal prostate tissues. Decreased Gal-3 staining was detected in tumour tissues compared with normal tissues. Although Gal-3 staining was decreased in tumour tissues with GS 5-8 and pT2 and pT3 stages compared with normal prostate tissue, no correlation was found between Gal-3 expression and PCa progression. In the present study, the pattern of cellular localization differed between groups, as Gal-3 was predominantly excluded from the nucleus in tumour tissues. Furthermore, Gal-3 had no significant effect on survival and relapse in these PCa patients. This work confirms Gal-3 as a promising marker for PCa diagnosis.

Automatic Text-Mining Approach to Identify Molecular Target Candidates Associated with Metabolic Processes for Myotonic Dystrophy Type 1

Myotonic dystrophy type 1 (DM1) is an autosomal dominant hereditary disease caused by abnormal expansion of unstable CTG repeats in the 3' untranslated region of the myotonic dystrophy protein kinase (DMPK) gene. This disease mainly affects skeletal muscle, resulting in myotonia, progressive distal muscle weakness, and atrophy, but also affects other tissues and systems, such as the heart and central nervous system. Despite some studies reporting therapeutic strategies for DM1, many issues remain unsolved, such as the contribution of metabolic and mitochondrial dysfunctions to DM1 pathogenesis. Therefore, it is crucial to identify molecular target candidates associated with metabolic processes for DM1. In this study, resorting to a bibliometric analysis, articles combining DM1, and metabolic/metabolism terms were identified and further analyzed using an unbiased strategy of automatic text mining with VOSviewer software. A list of candidate molecular targets for DM1 associated with metabolic/metabolism was generated and compared with genes previously associated with DM1 in the DisGeNET database. Furthermore, g:Profiler was used to perform a functional enrichment analysis using the Gene Ontology (GO) and REAC databases. Enriched signaling pathways were identified using integrated bioinformatics enrichment analyses. The results revealed that only 15 of the genes identified in the bibliometric analysis were previously associated with DM1 in the DisGeNET database. Of note, we identified 71 genes not previously associated with DM1, which are of particular interest and should be further explored. The functional enrichment analysis of these genes revealed that regulation of cellular metabolic and metabolic processes were the most associated biological processes. Additionally, a number of signaling pathways were found to be enriched, e.g., signaling by receptor tyrosine kinases, signaling by NRTK1 (TRKA), TRKA activation by NGF, PI3K-AKT activation, prolonged ERK activation events, and axon guidance. Overall, several valuable target candidates related to metabolic processes for DM1 were identified, such as NGF, NTRK1, RhoA, ROCK1, ROCK2, DAG, ACTA, ID1, ID2 MYOD, and MYOG. Therefore, our study strengthens the hypothesis that metabolic dysfunctions contribute to DM1 pathogenesis, and the exploitation of metabolic dysfunction targets is crucial for the development of future therapeutic interventions for DM1.

Macrophage Resistance to Ionizing Radiation Exposure Is Accompanied by Decreased Cathepsin D and Increased Transferrin Receptor 1 Expression

PURPOSE

To identify a molecular signature of macrophages exposed to clinically relevant ionizing radiation (IR) doses, mirroring radiotherapy sessions.

METHODS

Human monocyte-derived macrophages were exposed to 2 Gy/ fraction/ day for 5 days, mimicking one week of cancer patient's radiotherapy. Protein expression profile by proteomics was performed.

RESULTS

A gene ontology analysis revealed that radiation-induced protein changes are associated with metabolic alterations, which were further supported by a reduction of both cellular ATP levels and glucose uptake. Most of the radiation-induced deregulated targets exhibited a decreased expression, as was the case of cathepsin D, a lysosomal protease associated with cell death, which was validated by Western blot. We also found that irradiated macrophages exhibited an increased expression of the transferrin receptor 1 (TfR1), which is responsible for the uptake of transferrin-bound iron. TfR1 upregulation was also found in tumor-associated mouse macrophages upon tumor irradiation. In vitro irradiated macrophages also presented a trend for increased divalent metal transporter 1 (DMT1), which transports iron from the endosome to the cytosol, and a significant increase in iron release.

CONCLUSIONS

Irradiated macrophages present lower ATP levels and glucose uptake, and exhibit decreased cathepsin D expression, while increasing TfR1 expression and altering iron metabolism.

Interaction of Colloidal Gold Nanoparticles with Urine and Saliva Biofluids: An Exploratory Study

The use of gold nanoparticles for drug delivery, photothermal or photodynamic therapy, and biosensing enhances the demand for knowledge about the protein corona formed on the surface of nanoparticles. In this study, gold nanospheres (AuNSs), gold nanorods (AuNRs), and gold nanoflowers (AuNFs) were incubated with saliva or urine. After the interaction, the surface of gold nanoparticles was investigated using UV-VIS spectroscopy, zeta potential, and dynamic light scattering. The shifting of the localized surface plasmon resonance (LSPR) band, the increase in hydrodynamic diameter, and the changes in the surface charge of nanoparticles indicated the presence of biomolecules on the surface of AuNSs, AuNRs, and AuNFs. The incubation of AuNFs with saliva led to nanoparticle aggregation and minimal protein adsorption. AuNSs and AuNRs incubated in saliva were analyzed through liquid chromatography with tandem mass spectrometry (LC-MS/MS) to identify the 96 proteins adsorbed on the surface of the gold nanoparticles. Among the 20 most abundant proteins identified, 14 proteins were common in both AuNSs and AuNRs. We hypothesize that the adsorption of these proteins was due to their high sulfur content, allowing for their interaction with gold nanoparticles via the Au-S bond. The presence of distinct proteins on the surface of AuNSs or AuNRs was also investigated and possibly related to the competition between proteins present on the external layers of corona and gold nanoparticle morphology.

Re-analysis of published datasets in search of novel urogenital diseases biomarkers

Background:

Exosome research is a current trend in functional proteomics as it provides im-portant data on the pathophysiology and pathogenesis of diseases. The scientific outputs re-garding these topics often only approach disease-protein/peptide/exosome or mecha-nism-protein/peptide/exosome association. Approaching all three aspects could be the key to a better understanding of the pathophysiology and uncovering novel biomarkers for urogenital diseases. The focus of this work is to study exosome datasets to understand the possible role of underlying proteins in disease manifestation. We also attempt to link 4 different diseases that affect renal functions and are genetically inherited.

Methods:

For this purpose, the existing literature is consulted to understand the importance of exosomes in disease prediction, diagnosis and therapy. Available biotechnological methods of exosome analysis and the tools of proteomic analysis, data mining and visualization are dis-cussed. The database PRIDE is selected to query the information of several datasets related to urinary exosome analysis.

Results:

We have obtained a list of 19 proteins/genes involved in the mentioned diseases. On this list, we found a proteomic fingerprint consisting of Rab-7a, PDCD6, and CDC42, among others, and we are exploring their biological significance and underlying processes.

Conclusion:

APOA1, CD59, CD9, IGHG1, RAB7A, RAP1A, SEMG1 and SEMG2 are common in four urogenital diseases, and are involved in interactions with podosomes and endosomes, re-modeling of chylomicrons, regulation of interleukin production, regulation of endopeptidase activity, and establishment of apical/basal polarity of epithelial cells.

Optimization of a Protocol for Protein Extraction from Calcified Aortic Valves for Proteomics Applications: Development of a Standard Operating Procedure

The comprehension of the pathophysiological mechanisms, the identification of druggable targets, and putative biomarkers for aortic valve stenosis can be pursued through holistic approaches such as proteomics. However, tissue homogenization and protein extraction are made difficult by tissue calcification. The reproducibility of proteome studies is key in clinical translation of the findings. Thus, we aimed to optimize a protocol for aortic valve homogenization and protein extraction and to develop a standard operating procedure (SOP), which researchers can use to maximize protein yield while reducing inter-laboratory variability. We have compared the protein yield between conventional tissue grinding in nitrogen followed by homogenization with a Potter apparatus with a more advanced bead-beating system. Once we confirmed the superiority of the latter, we further optimized it by testing the effect of beads size, the number of homogenization cycles, tube capacity, lysis buffer/tissue mass ratio, and two different lysis buffers. Optimal protein extraction was achieved with 2.8 mm zirconium dioxide beads, in two homogenization cycles, in the presence of 20 µL RIPA buffer/mg tissue, using 2 mL O-ring cryotubes. As a proof of concept of the usefulness of this SOP for proteomics, the AV proteome of men and women with aortic stenosis was characterized, resulting in the quantification of proteins across six orders of magnitude and uncovering some putative proteins dysregulated by sex.

Tracking Prostate Carcinogenesis over Time through Urine Proteome Profiling in an Animal Model: An Exploratory Approach

Prostate cancer (PCa) is one of the most lethal diseases in men, which justifies the search for new diagnostic tools. The aim of the present study was to gain new insights into the progression of prostate carcinogenesis by analyzing the urine proteome. To this end, urine from healthy animals and animals with prostate adenocarcinoma was analyzed at two time points: 27 and 54 weeks. After 54 weeks, the incidence of pre-neoplastic and neoplastic lesions in the PCa animals was 100%. GeLC-MS/MS and subsequent bioinformatics analyses revealed several proteins involved in prostate carcinogenesis. Increased levels of retinol-binding protein 4 and decreased levels of cadherin-2 appear to be characteristic of early stages of the disease, whereas increased levels of enolase-1 and T-kininogen 2 and decreased levels of isocitrate dehydrogenase 2 describe more advanced stages. With increasing age, urinary levels of clusterin and corticosteroid-binding globulin increased and neprilysin levels decreased, all of which appear to play a role in prostate hyperplasia or carcinogenesis. The present exploratory analysis can be considered as a starting point for studies targeting specific human urine proteins for early detection of age-related maladaptive changes in the prostate that may lead to cancer.

O-255 Clinical and laboratory factors associated with pregnancy outcomes in patients undergoing frozen euploid blastocyst transfer

Study question

Which variables do have an impact on the pregnancy and live birth rates (LBR) when euploid frozen embryo transfers (FET) are performed?

Summary answer

Day of trophectoderm biopsy, Body Mass Index (BMI) and endometrial preparation protocol have an impact on pregnancy rate (PR) and LBR in FET cycles.

What is known already

Preimplantation genetic testing for aneuploidy (PGT-A) and morphological grading of embryos are the two main criteria to select a blastocyst from a pool of embryos, having the highest implantation potential. However, other clinical and laboratory variables might play a crucial role for a successful outcome when top quality euploid embryos are transferred in a FET cycle. It has been described that higher BMI increases the odds for miscarriage when compared with non-obese women.

Study design, size, duration

This analysis includes 1660 FET cycles with data from of pregnancy rates, miscarriage rate and LBR. Embryos were obtained from 2564 IVF/ICSI cycles of couples with primary or secondary infertility at ART Fertility Clinics UAE, from November 2016 to December 2020.

Participants/materials, setting, methods

A total of 1660 FET cycles with 2439 euploid blastocysts were included. FET cycles with mosaic or segmental aneuploid embryos were excluded. PGT-A was performed on trophectoderm cells, using Next Generation Sequencing (NGS). Biopsy was performed on day 5, 6 or 7 blastocysts. Endometrial preparation included ovulatory natural cycles (NC) and hormone replacement therapy (HRT) cycles, chosen according to physician’s discretion. Ethical approval was obtained from the Research Ethics Committee (REFA023b).

Main results and the role of chance

Patients’ characteristics are described as mean±SD (min-max): age: 33.5±5.43(19-47), AMH: 3.30±3.05ng/mL(0.01-23.00), BMI: 27.1±4.87Kg/m2(13.1-43.90), mean number of blastocysts transferred: 1.4±0.49(1-3). Patients were categorized according to age (years) in 4 categories (&lt;30,n=404; 30-34,n=487; 35-40,n=595; &gt;40,n=174) and no association with pregnancy rate (PR, p = 0.856), biochemical miscarriage rate (BMR, p = 0.940), clinical miscarriage rate (CMR, p = 0.06) nor LBR (p = 0.154) was found. BMI (kg/m2) was divided into four groups according to World Health Organization: underweight (&lt;18.5;n=32), normal weight (18.5–24.9;n=555), overweight (25–29.9;n=622), and obese (≥30;n=426). Although no differences were seen for PR or BMR between groups (p = 0.507 and p = 0.343, respectively), CMR was significantly lower for normal BMI group (p &lt; 0.001) and LBR significantly higher when compared to the overweight and obese group (&lt;18.5kg/m2=68.42%; 18.5–24.9kg/m2=68.35%; 25–29.9kg/m2=60.14%; ≥30kg/m2=53.29%; p &lt; 0.001). No differences were observed on the outcomes when AMH was sub-divided as per Bologna Criteria (&lt;1.3ng/mL,n=327; ≥1.3ng/mL,n=1090). Regarding endometrial preparation, NC protocol showed significantly lower BMR and CMR (7.93% vs 12.27%,p=0.026; 8.44% vs 17.97%,p&lt;0.001), and higher LBR (70.33% vs 55.06%,p&lt;0.001) compared to HRT. Day of trophectoderm biopsy had a significant higher PR for day 5 (day 5=75.58% vs day 6=61.1% and day 7=23.81%, p &lt; 0.0001), yet no differences were observed for BMR, CMR nor LBR.

Limitations, reasons for caution

Although the large number of FET included, performed in the same centre with same methodology, the retrospective study design is a limitation. We could not discard other hypothetical variables contributing to miscarriage such as KIR-HLA discrepancies, or other obstetric factors affecting late miscarriage and live birth.

Wider implications of the findings

Evaluating the factors associated with pregnancy outcomes should be considered prior to euploid frozen embryo transfer for personalized treatment approach and adequate blastocyst selection. Women with higher BMI should be aware of higher risk of miscarriage and lower LBR although an euploid blastocyst is transferred.

Trial registration number

not applicable

Evolution of serum progesterone levels in the very early luteal phase of stimulated IVF/ICSI cycles post hCG trigger: a proof of concept study

BACKGROUND

Studies have suggested that controlled ovarian hyperstimulation adversely affects endometrial receptivity due to advanced endometrial maturation. This adverse effect is mainly attributed to supraphysiological levels of both estrogen and progesterone identified in stimulated cycles. There is a paucity of published data investigating the very early luteal steroid profile following hCG trigger.

AIM OF THE STUDY

This prospective, observational study was undertaken to determine the increase in serum progesterone levels after human chorionic gonadotrophin (hCG) trigger in stimulated IVF/ICSI cycles.

MATERIALS AND METHODS

This proof-of-concept study included 11 patients requiring ovarian stimulation for IVF/ICSI and who planned to avail of pre-implantation genetic screening with embryo vitrification of their biopsied embryos at blastocyst stage. For each study participant, five additional blood samples were drawn at the following specific times in the stimulation cycle, on the morning (10.00-12.00) of the assigned day to induce final oocyte maturation with hCG trigger, immediately prior to administration of hCG for final oocyte maturation, 1 h, 2 h, and 36 h post hCG trigger. A prediction model, the Gompertz curve, was used to determine serum progesterone levels at intervals between the 2 h post hCG trigger sample and the day of oocyte retrieval.

RESULTS

Statistically significant increases in serum progesterone levels were identified following hCG administration as early as 1 h following trigger (P4 0.57 ng/ml, p < 0.05), 2 h following trigger (P4 0.88 ng/ml, p < 0.001) and on the day of oocyte retrieval (P4 9.68 ng/ml, p < 0.001). According to our prediction model, the Gompertz curve, the projected serum progesterone level at 4 h post trigger would have achieved a level of 1.45 ng/ml, 8 h post trigger of 3.04 ng/ml, and 12 h post trigger of 4.8 ng/ml. The very early and significant increases in serum progesterone following hCG trigger are clearly demonstrated in this study.

CONCLUSION

The endometrium is undoubtedly exposed to rapidly increasing serum progesterone levels post hCG trigger that would not be identified until much later in natural menstrual cycles.

TRIAL REGISTRATION NUMBER

This study is registered with clinicaltrials.gov under the identifier NCT04417569.

Pericardial Fluid Annexin A1 Is a Marker of Atrial Fibrillation in Aortic Stenosis: A Proteomics Analysis

Atrial fibrillation (AF) is the most common arrhythmia with adverse clinical outcomes. Pericardial fluid (PF) mirrors the heart’s pathophysiological status due to its proximity. This study aimed to characterise the PF proteome to identify new biomarkers of disease. Eighty-three patients submitted to aortic valve replacement surgery with severe aortic stenosis were selected, and their baseline echocardiographic and clinical variables were documented. Thirteen samples were selected blindly for proteome characterisation following a shotgun (GeLC–MS/MS) and a label-free quantification approach (LFQ). According to previous AF history, a partial least squares discriminant analysis (PLS-DA) was conducted, and the top 15 variables important in projection were identified. To inquire potential biomarkers, ROC curves were designed using LFQ data. Target proteins were further validated by ELISA, in both pericardial fluid and serum. Proteome analysis uncovered nine proteins up- and downregulated ≥2-fold. Annexin A1, annexin A2, and vimentin were among the top 15 most important variables for group discrimination in PLS-DA. Protein—protein interaction and gene ontology enrichment analysis presented functional interaction among identified proteins, which were all part of focal adhesion sites. Annexin A1 was increased in the pericardial fluid of AF patients but not in serum when quantified by ELISA. Annexin A1 is a novel pericardial fluid biomarker of AF in patients with severe aortic stenosis.

3D-MSCs A151 ODN-Loaded Exosomes Are Immunomodulatory And Reveal A Proteomic Cargo That Sustains Wound Resolution

•

The MSC-derived secretome from 3D cultures enhances fibroblast and keratinocyte mitogenic and motogenic capacity in vitro, respectively.

•

The cargo of the 3D MSC-derived exosomes (Exo3D) reveals wound healing-related proteins and promotes wound resolution in a wound healing in vivo model.

•

Loading MSC-derived exosomes with A151 ODN further reduces the systemic levels of IL-6 and TNF-α pro-inflammatory cytokines at the late stage of wound healing in vivo, crucial for a full regenerated tissue.

•

A151-loaded Exo3D have a great potential as a noncellular off-the-shelf therapy for non-healing wound treatment.

Introduction

Non-healing wounds remain a major burden due to the lack of effective treatments. Mesenchymal stem cell-derived exosomes (MSC-Exo) have emerged as therapeutic options given their pro-regenerative and immunomodulatory features. Still, little is known on the exact mechanisms mediated by MSC-Exo. Importantly, modulation of their efficacy through 3D-physiologic cultures together with loading strategies continues underexplored.

Objectives

To uncover the MSC-Exo-mediated mechanism via proteomic analyses, and to use 3D-culture and loading technologies to expand MSC-Exo efficacy for cutaneous wound healing.

Methods

MSC-Exo were produced in either 3D or 2D cultures (Exo3D/Exo2D) and loaded with an exogenous immunosuppressive oligodeoxynucleotide (A151 ODN). Both, loaded and naïve exosomes were characterised regarding size, morphology and the presence of specific protein markers; while IPA analyses enabled to correlate their protein content with the effects observed in vitro and in vivo. The Exo3D/Exo2D regenerative potential was evaluated in vitro by assessing keratinocyte and fibroblast mitogenicity, motogenicity, and cytokine secretion as well as using an in vivo wound splinting model. Accordingly, the modulation of inflammatory and immune responses by A151-loaded Exo3D/Exo2D was also assessed.

Results

Exo3D stimulated mitogenically and motogenically keratinocytes and fibroblasts in vitro, with upregulation of IL-1α and VEGF-α or increased secretion of TGF-β, TNF-α and IL-10. In vivo, Exo3D reduced the granulation tissue area and promoted complete re-epithelization of the wound. These observations were sustained by the proteomic profiling of the Exo3D cargo that identified wound healing-related proteins, such as TGF-β, ITGA1-3/5, IL-6, CDC151, S100A10 and Wnt5α. Moreover, when loaded with A151 ODN, Exo3D differentially mediated wound healing-related trophic factors reducing the systemic levels of IL-6 and TNF-α at the late stage of wound healing in vivo.

Conclusion

Our results support the potential of A151-loaded Exo3D for the treatment of chronic wounds by promoting skin regeneration, while modulating the systemic levels of the pro-inflammatory cytokines.

The Secretome of Human Neonatal Mesenchymal Stem Cells Modulates Doxorubicin-Induced Cytotoxicity: Impact in Non-Tumor Cells

Doxorubicin (Dox) is one of the most widely used treatments for breast cancer, although limited by the well-documented cardiotoxicity and other off-target effects. Mesenchymal stem cell (MSC) secretome has shown immunomodulatory and regenerative properties, further potentiated under 3D conditions. This work aimed to uncover the effect of the MSC-derived secretome from 3D (CM3D) or 2D (CM2D) cultures, in human malignant breast cells (MDA-MB-231), non-tumor breast epithelial cells (MCF10A) and differentiated AC16 cardiomyocytes, co-treated with Dox. A comprehensive proteomic analysis of CM3D/CM2D was also performed to unravel the underlying mechanism. CM3D/CM2D co-incubation with Dox revealed no significant differences in MDA-MB-231 viability when compared to Dox alone, whereas MCF10A and AC16 viability was consistently improved in Dox+CM3D-treated cells. Moreover, neither CM2D nor CM3D affected Dox anti-migratory and anti-invasive effects in MDA-MB-231. Notably, Ge-LC-MS/MS proteomic analysis revealed that CM3D displayed protective features that might be linked to the regulation of cell proliferation (CAPN1, CST1, LAMC2, RANBP3), migration (CCN3, MMP8, PDCD5), invasion (TIMP1/2), oxidative stress (COX6B1, AIFM1, CD9, GSR) and inflammation (CCN3, ANXA5, CDH13, GDF15). Overall, CM3D decreased Dox-induced cytotoxicity in non-tumor cells, without compromising Dox chemotherapeutic profile in malignant cells, suggesting its potential use as a chemotherapy adjuvant to reduce off-target side effects.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

How can artificial intelligence be used for peptidomics?

INTRODUCTION

Peptidomics is an emerging field of omics sciences using advanced isolation, analysis, and computational techniques that enable qualitative and quantitative analyses of various peptides in biological samples. Peptides can act as useful biomarkers and as therapeutic molecules for diseases.

AREAS COVERED

The use of therapeutic peptides can be predicted quickly and efficiently using data-driven computational methods, particularly artificial intelligence (AI) approach. Various AI approaches are useful for peptide-based drug discovery, such as support vector machine, random forest, extremely randomized trees, and other more recently developed deep learning methods. AI methods are relatively new to the development of peptide-based therapies, but these techniques already become essential tools in protein science by dissecting novel therapeutic peptides and their functions (Figure 1).[Figure: see text].

EXPERT OPINION

Researchers have shown that AI models can facilitate the development of peptidomics and selective peptide therapies in the field of peptide science. Biopeptide prediction is important for the discovery and development of successful peptide-based drugs. Due to their ability to predict therapeutic roles based on sequence details, many AI-dependent prediction tools have been developed (Figure 1).

Bioinformatic analysis of the human brain extracellular matrix proteome in neurodegenerative disorders

Alzheimer's, Parkinson's, and Huntington's diseases are characterized by selective degeneration of specific brain areas. Although increasing number of studies report alteration of the extracellular matrix on these diseases, an exhaustive characterization at the brain's matrix level might contribute to the development of more efficient cell restoration therapies. In that regard, proteomics-based studies are a powerful approach to uncover matrix changes. However, to date, the majority of proteomics studies report no or only a few brain matrix proteins with altered expression. This study aims to reveal the changes in the brain extracellular matrix by integrating several proteomics-based studies performed with postmortem tissue. In total, 67 matrix proteins with altered expression were collected. By applying a bioinformatic approach, we were able to reveal the dysregulated biological processes. Among them are processes related to the organization of the extracellular matrix, glycosaminoglycans and proteoglycans' metabolism, blood coagulation, and response to injury and oxidative stress. In addition, a protein was found altered in all three diseases-collagen type I alpha 2-and its binding partners further identified. A ClueGO network was created, depicting the GO groups associated with these binding partners, uncovering the processes that may consequently be affected. These include cellular adhesion, cell signaling through membrane receptors, inflammatory processes, and apoptotic cell death in response to oxidative stress. Overall, we were able to associate the contribution of the modification of extracellular matrix components to essential biological processes, highlighting the investment needed on proteomics studies with specific focus on the extracellular matrix in neurodegeneration.

Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases

Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.

Effect of exercise training on amyloid-like protein aggregates among patients with heart failure

Funding Acknowledgements

Type of funding sources: Other. Main funding source(s): MG and CS were supported by a PhD FCT grant (SFRH/BD/128893/2017) and by an individual grant from CAPES [BEX 0554/14-6], respectively. This work was financially supported by the project POCI-01-0145-FEDER-030011, funded by FEDER, through COMPETE2020-POCI, and by national funds, through FCT/MCTES (PTDC/MEC-CAR/30011/2017). iBiMED is a research unit supported by the Portuguese Foundation for Science and Technology (REF: UID/BIM/04501/2020) and FEDER/Compete2020 funds).

Introduction

Amyloid-like protein aggregates play a decisive role in the pathology of heart failure. Alterations in protein homeostasis, in particular, the clearance of toxic amyloid-like aggregates are emerging therapeutic targets in cardiovascular medicine. The clinical benefits of cardiac rehabilitation and exercise training are widely accepted in heart failure; however, little is known about the potential benefit of exercise training in amyloid-like protein aggregates.

Purpose

To assess the effects of a moderate-intensity exercise training program on amyloid-like protein aggregates levels among patients with heart failure with reduced ejection fraction.

Methods

Eighteen subjects participated in the study; eight patients (age: 66.6 ± 5.9 years; FEVE: 38.4 ± 8.9%) with heart failure with reduced ejection fraction participated in a 3-month exercise training program (2 x 60 min sessions per week of moderate-intensity aerobic and resistance exercise). Ten healthy subjects (age: 68. 4 ± 3.1 years) were recruited to an age-matched reference group.  Amyloid-like protein aggregates were assessed before and after 3 months of exercise training. Clinical data, medication, anthropometrics, and cardiorespiratory fitness were also assessed. Thioflavin T (ThT) dye fluorescence was used to quantify the plasma levels of amyloid-like aggregates and the Fourier transform infrared spectroscopy (FTIR) was applied to evaluate the conformation of cross-β-sheet structures characteristic of amyloid protein aggregates.

Results

Exercise program improved cardiorespiratory fitness by 14.0 ± 17.1% (17.4 ± 3.2 to 19.7 ± 2.9 ml/kg/min) and reduced NT-proBNP levels by 16.5% (34.2) (median concentration of 632 pg/mL (720.8) to 517.5 pg/mL (707.0)) in the heart failure patients. A slight decrease of amyloid-like aggregates levels was observed in post-exercise training samples (a reduction of 3.1%); interestingly, after the exercise training program, the heart failure patients showed levels of amyloid-like aggregates similar to the reference group (1132.0 ± 114.2 vs. 1094.8 ± 132.9 a.u.). Additionally, the PLS-R multivariate analysis of the amide I region of the FTIR spectra revealed enrichment of antiparallel β-sheets (1693 cm-1) assigned to amyloid-like oligomers in the samples of heart failure patients before, but not after, the exercise program. Of note, oligomeric species, as intermediates of amyloid assembly, can contribute to the increase of amyloid burden, but also, some have been reported to be highly reactive and toxic to cells, being key elements of amyloid pathogenesis.

Conclusions

 Our preliminary results indicate that 3 months of exercise training may have significant effects on amyloid-like oligomers, and start hindering the formation of the larger ThT-positive aggregates among patients with heart failure.

Abstract Figure.

Microfluidics for Peptidomics, Proteomics, and Cell Analysis

Microfluidics is the advanced microtechnology of fluid manipulation in channels with at least one dimension in the range of 1-100 microns. Microfluidic technology offers a growing number of tools for manipulating small volumes of fluid to control chemical, biological, and physical processes relevant to separation, analysis, and detection. Currently, microfluidic devices play an important role in many biological, chemical, physical, biotechnological and engineering applications. There are numerous ways to fabricate the necessary microchannels and integrate them into microfluidic platforms. In peptidomics and proteomics, microfluidics is often used in combination with mass spectrometric (MS) analysis. This review provides an overview of using microfluidic systems for peptidomics, proteomics and cell analysis. The application of microfluidics in combination with MS detection and other novel techniques to answer clinical questions is also discussed in the context of disease diagnosis and therapy. Recent developments and applications of capillary and microchip (electro)separation methods in proteomic and peptidomic analysis are summarized. The state of the art of microchip platforms for cell sorting and single-cell analysis is also discussed. Advances in detection methods are reported, and new applications in proteomics and peptidomics, quality control of peptide and protein pharmaceuticals, analysis of proteins and peptides in biomatrices and determination of their physicochemical parameters are highlighted.

The potential impact of salivary peptides in periodontitis

Periodontitis is a complex immune-inflammatory condition characterized by the disruption of the periodontal ligament and subsequent formation of periodontal pockets, and by alveolar bone loss, often resulting in tooth loss. A myriad of factors, namely, genetic, metabolic, immunological, and inflammatory, is associated with progression of periodontitis. Periodontitis is also associated with systemic conditions such as neoplastic disorders, obesity, and diabetes. The current diagnosis of this disease relies on clinical measurements such as clinical attachment loss and probing depth, which have poor precision due to patient, operator and probe-related factors. Thus, there is a need to develop reliable, objective, and reproducible biomarkers for early diagnosis of periodontitis. In this regard, saliva, with contributions from the gingival crevicular fluid, holds great potential. However, most of the information on biomarkers of periodontium-related salivary proteins has come from studies on the molecular pathogenesis of periodontitis. In periodontitis, a more holistic approach, such as the use of -omics technologies, for biomarker discovery, is needed. Herein, we review the biomarkers proposed to date for the assessment of periodontitis, with emphasis on the role of salivary peptides in periodontitis and their assessment by high-throughput saliva proteomics. We also discuss the challenges pertaining to the identification of new periodontitis biomarkers in saliva.

Automatic text-mining as an unbiased approach to uncover molecular associations between periodontitis and coronary artery disease

The increasing prevalence of periodontal and cardiovascular diseases is the result of a sedentary lifestyle associated with poor diet, obesity, hypercholesterolaemia, smoking habits, alcohol consumption and stress. The present study aims to uncover molecular associations between periodontitis and coronary heart disease using an unbiased strategy of automatic text mining traditionally applied to bibliometric studies. A total of 1590 articles on these diseases were retrieved from the Web of knowledge database and searched using the VOS viewer to create a network of keywords associated with both diseases. These data were supplemented with data from DisGeNET, which stores known associations to either periodontitis or coronary heart disease. Overall, the automated text mining approach presented here highlighted inflammatory molecules as common associations between periodontitis and coronary heart disease. Specifically, this study showed that molecules such as C-reactive protein, interleukins 6 and 1-β, myeloperoxidase, and matrix metalloproteinase 9 are simultaneously associated with periodontitis and coronary artery disease by both text mining and DisGeNET analyses. This association validates the multiplex assessment of salivary inflammatory markers as a tool to assess cardiovascular disease risk and could become an important tool to identify common molecular targets to monitor both diseases simultaneously. In addition, the text mining protocol and subsequent data processing and methods using bioinformatics tools could be useful to uncover links between other diseases.