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.

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.

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.

A Lipidomics Approach to Determine the Role of Lipids and Its Crosstalk with Autophagy in Lung Cancer Metastasis.

Non-small cell lung cancer (NSCLC) is among the most malignant tumors with high propensity for metastasis and is the leading cause of cancer-related death globally. Most patients present with regional and distant metastasis, associated with poor prognosis. Lipids may play an essential role in either activating or inhibiting detachment-induced apoptosis (anoikis), where the latter is a crucial mechanism to prevent metastasis, and it may have a cross-talk with autophagy. Autophagy has been shown to be induced in various human cancer metastasis, modulating tumor cell motility and invasion, cancer cell differentiation, resistance to anoikis, and epithelial to mesenchymal transition. Hence, it may play a crucial role in the transition of benign to malignant phenotypes, the core of metastasis initiation. Here, we provide a method we have established in our laboratory for detecting lipids in attached and detached non-small lung cancer cells and show how to analyze lipidomics data to find its correlation with autophagy-related pathways.

Revisiting Multi-Omics Data to Unravel Galectins as Prognostic Factors in Head and Neck Squamous Cell Carcinoma.

Head and Neck Squamous Cell Carcinoma (HNSCC) is a malignant cancer with a poor prognosis. Galectins (Gal) have been the subject of intensive research, but the comparative prognostic value of each Gal type is not yet understood. Therefore, a literature search for evaluating galectins as prognostic biomarkers in HNSCC was conducted. The relationship between Gal expression in HNSCC with HPV and TP53 mutational status was assessed using the UALCAN database. The impact of these biomarkers on prognosis was analyzed using ToPP and CPPA web tools. The expression of galectins in the tumor microenvironment and the impact on prognosis depending on the cancer immune subtype were analyzed using single-cell RNA sequencing. Gal-1 and Gal-3BP were shown to be promising biomarkers with a triple function for the prediction of HPV and TP53 mutational status, stratification of the HNSCC prognosis, and prediction of the response to treatment. In addition, these two galectins have been shown to be most influenced by the tumor microenvironment of HNSCC. Gal-1 and Gal-3BP are the most promising galectins in HNSCC. Furthermore, this study highlights the need for further studies to evaluate galectins in HNSCC and clarify the role of individual Gals in the patient's stratification.

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.

Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review.

Bladder cancer (BCa) research relying on Omics approaches has increased over the last few decades, improving the understanding of BCa pathology and contributing to a better molecular classification of BCa subtypes. To gain further insight into the molecular profile underlying the development of BCa, a systematic literature search was performed in PubMed until November 2023, following the PRISMA guidelines. This search enabled the identification of 25 experimental studies using mass spectrometry or nuclear magnetic resonance-based approaches to characterize the metabolite signature associated with BCa. A total of 1562 metabolites were identified to be altered by BCa in different types of samples. Urine samples displayed a higher likelihood of containing metabolites that are also present in bladder tumor tissue and cell line cultures. The data from these comparisons suggest that increased concentrations of L-isoleucine, L-carnitine, oleamide, palmitamide, arachidonic acid and glycoursodeoxycholic acid and decreased content of deoxycytidine, 5-aminolevulinic acid and pantothenic acid should be considered components of a BCa metabolome signature. Overall, molecular profiling of biological samples by metabolomics is a promising approach to identifying potential biomarkers for early diagnosis of different BCa subtypes. However, future studies are needed to understand its biological significance in the context of BCa and to validate its clinical application.

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.

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.

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.

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.

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.

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.

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.

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.

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 [...].

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.

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.