Predictive value of α-synuclein expression in peripheral blood of multiple sclerosis patients: A two-dimensional assessment of a selected biomarker.

INTRODUCTION: Our study aimed to evaluate whether assessing α-synuclein expression levels in blood samples could provide a reliable and straightforward alternative to existing diagnostic and prognostic methods for neurodegenerative disorders, including multiple sclerosis (MS). We specifically investigated if α-synuclein and IL-6 expression levels from serum and peripheral blood mononuclear cells (PBMCs) could accurately predict MS severity in patients using a two-dimensional approach. METHODS: We designed a case-control study to analyze the expression of α-synuclein and IL-6 in the peripheral blood of an MS patient group (n = 51) and a control group (n = 51). We statistically evaluated the PBMCs and serum profiles of α-synuclein and IL-6 in MS patients, along with their age of onset, disease duration, tobacco exposure, and Expanded Disability Status Scale (EDSS) score, using SPSS V22.0 software and GraphPad Prism V9.0. RESULTS: Our findings indicate that α-synuclein production was significantly downregulated in MS patients. Principal component analysis also revealed distinct profiles between MS patients and controls. PBMCs and serum profiles of α-synuclein correlated with the EDSS score, suggesting that disease severity can be predicted using α-synuclein profiles. Moreover, α-synuclein showed a significant correlation with IL-6 and age of onset. Lastly, receiver operating characteristic curves of PBMCs and serum activity of α-synuclein profiles displayed discrimination with area under the curve values of 0.856 and 0.705, respectively. CONCLUSION: Our results imply that measuring α-synuclein levels in both serum and PBMCs could be a valuable method for diagnosing and predicting MS severity, potentially serving as a non-invasive biomarker for the disease.

Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma.

Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.

Mechanism underlying follicular hyperproliferation and oncogenesis in hidradenitis suppurativa.

Hidradenitis suppurativa (HS) is a skin disorder that causes chronic painful inflammation and hyperproliferation, often with the comorbidity of invasive keratoacanthoma (KA). Our research, employing high-resolution immunofluorescence and data science approaches together with confirmatory molecular analysis, has identified that the 5'-cap-dependent protein translation regulatory complex eIF4F is a key factor in the development of HS and is responsible for regulating follicular hyperproliferation. Specifically, eIF4F translational targets, Cyclin D1 and c-MYC, orchestrate the development of HS-associated KA. Although eIF4F and p-eIF4E are contiguous throughout HS lesions, Cyclin D1 and c-MYC have unique spatial localization and functions. The keratin-filled crater of KA is formed by nuclear c-MYC-induced differentiation of epithelial cells, whereas the co-localization of c-MYC and Cyclin D1 provides oncogenic transformation by activating RAS, PI3K, and ERK pathways. In sum, we have revealed a novel mechanism underlying HS pathogenesis of follicular hyperproliferation and the development of HS-associated invasive KA.

The analysis of dynamic gene expression patterns in peripheral blood of multiple sclerosis patients indicates possible diagnostic and prognostic biomarkers.

INTRODUCTION: Among numerous invasive procedures for the research of biomarkers, blood-based indicators are regarded as marginally non-invasive procedures in the diagnosis and prognosis of demyelinating disorders, including multiple sclerosis (MS). In this study, we looked into the blood-derived gene expression profiles of patients with multiple sclerosis to investigate their clinical traits and linked them with dysregulated gene expressions to establish diagnostic and prognostic indicators. METHODS: We included 51 patients with relapsing-remitting MS (RRMS, n = 31), clinically isolated syndrome (CIS, n = 12), primary progressive MS (PPMS, n = 8) and a control group (n = 51). Using correlational analysis, the transcriptional patterns of chosen gene panels were examined and subsequently related with disease duration and the expanded disease disability score (EDSS). In addition, principal component analysis, univariate regression, and logistic regression analysis were employed to highlight distinct profiles of genes and prognosticate the excellent biomarkers of this illness. RESULTS: Our findings demonstrated that neurofilament light (NEFL), tumor necrosis factor α (TNF-α), Tau, and clusterin (CLU) were revealed to be increased in recruited patients, whereas the presenilin-1 (PSEN1) and cell-surface glycoprotein-44 (CD44) were downregulated. Principal Component Analysis revealed distinct patterns between the MS and control groups. Correlation analysis indicated co-dependent dysregulated genes and their differential expression with clinical findings. Furthermore, logistic regression demonstrated that Clusterin (AUC=0.940), NEFL (AUC=0.775), TNF-α (AUC=0.817), Tau (AUC=0.749), PSEN1 (AUC=0.6913), and CD44 (AUC=0.832) had diagnostic relevance. Following the univariate linear regression, a significant regression equation was found between EDSS and IGF-1 (R2 adj = 0.10844; p= 0.0060), APP (R2 adj = 0.1107; p= 0.0098), and PSEN1 (R2 adj = 0.1266; p=0.0102). CONCLUSION: This study exhibits dynamic gene expression patterns that represent the significance of specified genes that are prospective diagnostic and prognostic biomarkers for multiple sclerosis.

Fixed Dose Single Tablet Formulation with Differential Release of Amlodipine Besylate and Simvastatin and Its Pharmacokinetic Profile: QbD and Risk Assessment Approach.

PURPOSE: A differential release fixed dose matrix tablet of amlodipine besylate (AML-B) and simvastatin (SIM) was formulated to enhance patient compliance. MATERIAL AND METHOD: In the first phase, release controlling parameters of AML-B and SIM granules were identified and in the second phase a fixed dose AML-B and SIM tablet formulation was prepared and optimized for a differential release of the drugs using a quality by design (QbD) and risk assessment approach. A validated HPLC method was employed for simultaneous determination of AML-B and SIM for FDC formulation. A pharmacokinetics of the above drugs was studied in healthy dogs in the third phase. RESULTS: In QbD-based optimized formulation, Eudragit® RSPO-dicalcium phosphate (DCP) blend controlled the release of AML-B over 8 h, though this diffusion-controlled release assumed first order kinetics. DCP and Eudragit® RS 100 also retarded release of SIM causing SIM release over 8 h after AML-B release from the optimized FDC tablet formulation. The HPLC retention times of AML-B and SIM were 2.10 and 15.52 min, respectively. Linearity for AML-B was 5.0-50 ng/mL and 0.01-2.0 µg/mL for SIM with percent recoveries of 92.85-101.53% and 94.51-117.75% for AML-B and SIM. AUC0-∞ of AML-B was increased 3 fold, while AUC0-∞ of SIM was decreased 2 fold. The tmax values for AML-B and SIM were 12 and 6 h, respectively. AML-B was absorbed without any lag time (tlag) while tlag was 6.33 ± 0.81 h for SIM, thus met the study objective. CONCLUSION: The pharmacokinetic study showed an immediate absorption of AML-B while that of SIM was withheld for 6 h, close to the desired delay time of 8 h.

Patched1 haploinsufficiency severely impacts intermediary metabolism in the skin of Ptch1+/-/ODC transgenic mice.

The study of dominantly heritable cancers has provided insights about tumor development. Gorlin syndrome (GS) is an autosomal dominant disorder wherein affected individuals develop multiple basal cell carcinomas (BCCs) of the skin. We developed a murine model of Ptch1 haploinsufficiency on an ornithine decarboxylase (ODC) transgenic background (Ptch1+/-/ODCt/C57BL/6) that is more sensitive to BCCs growth as compared with Ptch1+/+/ODCt/C57BL/6 littermates. Ptch1+/-/ODCt/C57BL/6 mice show an altered metabolic landscape in the phenotypically normal skin, including restricted glucose availability, restricted ribose/deoxyribose flow and NADPH production, an accumulation of α-ketoglutarate, aconitate, and citrate that is associated with reversal of the tricarboxylic acid cycle, coupled with increased ketogenic/lipogenic activity via acetyl-CoA, 3-hydroybutyrate, and cholesterol metabolites. Also apparent was an increased content/acetylation of amino-acids, glutamine and glutamate, in particular. Accordingly, metabolic alterations due to a single copy loss of Ptch1 in Ptch1+/-/ODCt/C57BL/6 heterozygous mice may provide insights about the cancer prone phenotype of BCCs in GS patients, including biomarkers/targets for early intervention.