Search Results (1,623)

Background: Disease-modifying drugs (DMDs) for multiple sclerosis (MS) slightly increase the risk of tuberculosis (TB) disease. The QuantiFERON-TB-Plus (QFT-Plus) test is approved for TB infection (TBI) screening. Currently, there are no data available regarding the characterization of QFT-Plus response in patients with MS. Objectives: This study aimed to compare the magnitude of QFT-Plus responses between patients with MS and TBI (MS-TBI) and TBI subjects without MS (NON-MS-TBI). Additionally, discordant responses to TB1/TB2 stimulation were documented. Results were evaluated considering demographic and clinical data, particularly the impact of DMDs and the type of TB exposure. Methods: Patients with MS (N = 810) were screened for TBI (2018–2023). Thirty (3.7%) had an MS-TBI diagnosis, and 20 were recruited for the study. As a control group, we enrolled 106 NON-MS-TBI. Results: MS-TBI showed significantly lower IFN-γ production in response to TB1 (p = 0.01) and TB2 stimulation (p = 0.02) compared to NON-MS-TBI. The 30% of TB2 results of MS-TBI fell into the QFT-Plus grey zone (0.2–0.7 IU/mL). Only 7% of NON-MS-TBI showed this profile (p = 0.002). Conclusions: MS-TBI had a lower QFT-Plus response and more borderline results compared to NON-MS-TBI. Future studies should clarify the significance of the borderline results in this vulnerable population to improve QFT-Plus accuracy regarding sensitivity, specificity, and TB prediction. Full article

Prostate cancer accounts for approximately 1.5 million new diagnoses and 400,000 deaths every year worldwide, and demographic projections indicate a near-doubling of both figures by 2040. Despite existing treatments, 10–20% of patients eventually progress to metastatic castration-resistant disease (mCRPC). The median overall survival (OS) after progression to mCPRC drops to 24 months, and efficacy drops severely after each additional line of treatment. Omics platforms have reached advanced levels and enable the acquisition of high-resolution large datasets that can provide insights into the molecular mechanisms underlying PCa pathology. Genomics, especially DDR (DNA damage response) gene alterations, detected via tissue and/or circulating tumor DNA, efficiently guides therapy in advanced prostate cancer. Given recent developments, we have performed a comprehensive literature search to cover recent research and clinical trial reports (over the last five years) that integrate omics along three converging trajectories in therapeutic development: (i) predicting response to approved agents with demonstrated survival benefits, (ii) stratifying patients to receive therapies in clinical trials, (iii) guiding drug development as part of drug repurposing frameworks. Collectively, this review is intended to serve as a comprehensive resource of recent advancements in omics-guided therapies for advanced prostate cancer, a clinical setting with existing clinical needs and poor outcomes. Full article

Background: Precision medicine refers to the formulation of personalized drug regimens according to the individual characteristics of patients to achieve optimal efficacy and minimize adverse reactions. Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as an optimal solution for precision drug delivery, enabling customizable and the fabrication of multifunctional structures with precise control over morphology and release behavior in pharmaceutics. However, the influence of 3D printing parameters on the printed tablets, especially regarding in vitro and in vivo performance, remains poorly understood, limiting the optimization of manufacturing processes for controlled-release profiles. Objective: To establish the fabrication process of 3D-printed controlled-release tablets via comprehensively understanding the printing parameters using fused deposition modeling (FDM) combined with hot-melt extrusion (HME) technologies. HPMC-AS/HPC-EF was used as the drug delivery matrix and carbamazepine (CBZ) was used as a model drug to investigate the in vitro drug delivery performance of the printed tablets. Methodology: Thermogravimetric analysis (TGA) was employed to assess the thermal compatibility of CBZ with HPMC-AS/HPC-EF excipients up to 230 °C, surpassing typical processing temperatures (160–200 °C). The formation of stable amorphous solid dispersions (ASDs) was validated using differential scanning calorimetry (DSC), hot-stage polarized light microscopy (PLM), and powder X-ray diffraction (PXRD). A 15-group full factorial design was then used to evaluate the effects of the fan speed (20–100%), platform temperature (40–80 °C), and printing speed (20–100 mm/s) on the tablet properties. Response surface modeling (RSM) with inverse square-root transformation was applied to analyze the dissolution kinetics, specifically t_50% (time for 50% drug release) and Q_4h (drug released at 4 h). Results: TGA confirmed the thermal compatibility of CBZ with HPMC-AS/HPC-EF, enabling stable ASD formation validated by DSC, PLM, and PXRD. The full factorial design revealed that printing speed was the dominant parameter governing dissolution behavior, with high speeds accelerating release and low speeds prolonging release through porosity-modulated diffusion control. RSM quadratic models showed optimal fits for t_50% (R² = 0.9936) and Q_4h (R² = 0.9019), highlighting the predictability of release kinetics via process parameter tuning. This work demonstrates the adaptability of polymer composite AM for tailoring drug release profiles, balancing mechanical integrity, release kinetics, and manufacturing scalability to advance multifunctional 3D-printed drug delivery devices in pharmaceutics. Full article

Background/Objectives: Androgen deprivation therapy (ADT) is widely used to manage prostate cancer (PC), but the emergence of treatment resistance remains a major clinical challenge. Although the GST family has been implicated in drug resistance, the specific role of GSTM5 remains poorly understood. This study investigates whether GSTM5, alone or in combination with clinical variables, can improve patient stratification based on the risk of early treatment resistance. Methods: In silico analyses were performed to examine GSTM5’s role in protein interactions, molecular pathways, and gene expression. The rs3768490 polymorphism was genotyped in 354 patients with PC, classified by ADT response. Descriptive analysis and logistic regression models were applied to evaluate associations between genotype, clinical variables, and ADT response. GSTM5 expression related to the rs3768490 genotype and ADT response was also analyzed in 129 prostate tissue samples. Results: The T/T genotype of rs3768490 was significantly associated with a lower likelihood of early ADT resistance in both individual (p = 0.0359, Odd Ratios (OR) = 0.18) and recessive models (p = 0.0491, OR = 0.21). High-risk classification according to D’Amico was strongly associated with early progression (p < 0.0004; OR > 5.4). Combining genotype and clinical risk improved predictive performance, highlighting their complementary value in stratifying patients by treatment response. Additionally, GSTM5 expression was slightly higher in T/T carriers, suggesting a potential protective role against ADT resistance. Conclusions: The T/T genotype of rs3768490 may protect against ADT resistance by modulating GSTM5 expression in PC. These preliminary findings highlight the potential of integrating genetic biomarkers into clinical models for personalized treatment strategies, although further studies are needed to validate these observations. Full article

Topical drug administration is a common method of delivering medications to the eye to treat various ocular conditions, including glaucoma, dry eye, and inflammation. Drug efficacy following topical administration, including the drug’s distribution within the eye, absorption and elimination rates, and physiological responses can be predicted using physiologically based pharmacokinetic (PBPK) modeling. High-resolution computational models of the eye are desirable to improve simulations of drug delivery; however, these approaches can have long run times. In this study, a fast-running computational quasi-3D (Q3D) model of the human tear film was developed to account for absorption, blinking, drainage, and evaporation. Visualization of blinking mechanics and flow distributions throughout the tear film were enabled using this Q3D approach. Average drug absorption throughout the tear film subregions was quantified using a high-resolution compartment model based on a system of ordinary differential equations (ODEs). Simulations were validated by comparing them with experimental data from topical administration of 0.1% dexamethasone suspension in the tear film (R² = 0.76, RMSE = 8.7, AARD = 28.8%). Overall, the Q3D tear film model accounts for critical mechanistic factors (e.g., blinking and drainage) not previously included in fast-running models. Further, this work demonstrated methods toward improved computational efficiency, where central processing unit (CPU) time was decreased while maintaining accuracy. Building upon this work, this Q3D approach applied to the tear film will allow for more seamless integration into full-body models, which will be an extremely valuable tool in the development of treatments for ocular conditions. Full article

Ulcerative colitis (UC), a subtype of inflammatory bowel disease (IBD), is a chronic, relapsing inflammatory condition that significantly impairs the patient’s quality of life. While biologics have transformed disease management, a substantial number of patients remain unresponsive or lose efficacy over time. Tofacitinib (TOFA), an oral Janus kinase (JAK) inhibitor, introduces a novel therapeutic class of small-molecule drugs with a unique oral administration route, offering enhanced patient convenience and broader accessibility compared to parenterally administered biologics. As the first oral treatment approved for moderate to severe UC in years, TOFA acts by modulating the JAK/STAT pathway, influencing critical inflammatory mediators such as IL-6, IL-17, and IFN-γ. However, response rates are variable and appear dose-dependent, with up to 60% of patients showing inadequate therapeutic outcomes. This review represents the first comprehensive synthesis focused specifically on biomarkers of TOFA response in UC. Drawing on multi-omics data—epigenomics, transcriptomics, proteomics, and cellular profiling, we highlight emerging predictors of responsiveness, including CpG methylation signatures (e.g., LRPAP1 and FGFR2), transcriptomic regulators (e.g., REG3A and CLDN3), immune and epithelial cell shifts, and the cationic transporter MATE1. TOFA demonstrates a dual mechanism by modulating immune responses while supporting epithelial barrier restoration. Despite being promising, TOFA’s dose-dependent efficacy and interpatient variability underscore the critical need for non-invasive, predictive biomarkers to guide personalized treatment. As the first review of its kind, this work establishes a basis for precision medicine approaches to optimize the clinical utility of TOFA in UC management. Full article

Natural products demonstrate potent immunomodulatory properties through checkpoint modulation, macrophage polarization, and T cell/natural killer (NK) cell activation. While cancer organoid-immune co-culture platforms enable physiologically relevant modeling of tumor–immune interactions, systematic investigation of natural product immunomodulation in these systems remains entirely unexplored. We conducted a comprehensive literature analysis examining natural products tested in cancer organoids, immunomodulatory mechanisms from traditional models, technical advances in organoid-immune co-cultures, and standardization requirements for clinical translation. Our analysis reveals a critical research gap: no published studies have investigated natural product-mediated immunomodulation using organoid-immune co-culture systems. Even though compounds like curcumin, resveratrol, and medicinal mushroom polysaccharides show extensive immunomodulatory effects in two-dimensional (2D) cultures, and organoid technology achieves high clinical correlation for drug response prediction, all existing organoid studies focus exclusively on direct cytotoxicity. Technical challenges include compound stability, limited matrix penetration requiring substantially higher concentrations than 2D cultures, and maintaining functional immune populations in three-dimensional (3D) systems. The convergence of validated organoid-immune co-culture platforms, Food and Drug Administration (FDA) regulatory support through the Modernization Act 2.0, and extensive natural product knowledge creates unprecedented opportunities. Priority research directions include systematic screening of immunomodulatory natural products in organoid-immune co-cultures, development of 3D-optimized delivery systems, and clinical validation trials. Success requires moving beyond cytotoxicity-focused studies to investigate immunomodulatory mechanisms in physiologically relevant 3D systems, potentially unlocking new precision cancer immunotherapy approaches. Full article

Docetaxel is a chemotherapeutic agent widely used for breast cancer treatment; however, its efficacy is often limited by drug resistance and associated toxicity. This review examines the molecular mechanisms of docetaxel resistance in breast cancer and discusses research advances and future directions for overcoming this challenge. Key resistance mechanisms include alterations in drug targets (microtubules), increased drug efflux, suppression of apoptosis, activation of survival signalling pathways, epithelial-to-mesenchymal transition (EMT), and cancer stem cell enrichment. An evolutionary perspective distinguishes between intrinsic and acquired resistance, emphasising the need for adaptive therapeutic strategies. Recent advances in genomic profiling, non-coding RNA research, novel drug combinations, and biomarker-guided therapies have also been reviewed. Emerging approaches, such as targeting the tumour microenvironment, harnessing immunotherapy, and implementing adaptive dosing schedules, have been discussed. This review emphasises the understanding of resistance as a multifactorial phenomenon that requires multipronged interventions. Research has aimed to identify predictive biomarkers, develop targeted agents to reverse resistance, and design rational combination strategies to improve patient outcomes. Progress in deciphering and targeting docetaxel resistance mechanisms holds promise for enhancing treatment responses and extending survival in patients with breast cancer. Full article

Background/Objectives: Anti-drug antibody (ADA) formation can impact the safety, pharmacokinetics, and/or efficacy of biotherapeutics, including monoclonal antibodies (mAbs). Current strategies for ADA/immunogenicity risk prediction of mAbs include in silico algorithms, T cell proliferation assays, MHC-associated peptide proteomics assays (MAPPs), and dendritic cell internalization assays. However, B cell-mediated responses are not assessed in these assays. B cells are professional antigen-presenting cells (APCs) and secrete antibodies toward immunogenic mAbs. Therefore, methods to determine B cell responses would be beneficial for immunogenicity risk prediction and may provide a more comprehensive assessment of risk. Methods: We used a PBMC culture method with the addition of IL-4, IL-21, B cell activating factor (BAFF), and an anti-CD40 agonist mAb to support B cell survival and activation. Results: B cells in this assay format become activated, proliferate, and secrete IgG. A panel of 51 antibodies with varying clinical immunogenicity rates were screened in this assay with IgG secretion used as a readout for immunogenicity risk. IgG secretion differed among test articles but did not correlate with the clinical immunogenicity rating. Conclusions: This dataset highlights the challenges of developing a B cell assay for immunogenicity risk prediction and provides a framework for further refinement of a B cell-based assay for immunogenicity risk prediction of mAbs. Full article

Oral administration remains the preferred drug delivery route but faces formidable gastrointestinal barriers, including enzymatic degradation, solubility limitations, and poor epithelial absorption. Zein-based nanocarriers (ZBNs), derived from maize prolamin, provide a transformative platform to address these challenges. This review synthesizes recent advances in ZBNs’ design, highlighting their intrinsic advantages: structural stability across pH gradients, self-assembly versatility, and a surface functionalization capacity. Critically, we detail how engineered ZBNs overcome key barriers, such as enzymatic/chemical protection via hydrophobic encapsulation, the enhanced mucus penetration or adhesion through surface engineering, and improved epithelial transport via ligand conjugation. Applications demonstrate their efficacy in stabilizing labile therapeutics, enhancing the solubility of BCS Class II/IV drugs, enabling pH-responsive release, and significantly boosting oral bioavailability. Remaining challenges in scalability and translational predictability warrant future efforts toward multifunctional systems, bio-interfacial modeling, and continuous manufacturing. This work positions ZBNs as a potential platform for the oral delivery of BCS Class II–IV drugs’ in the biopharmaceutics classification system. Full article

This paper compares two methods, inferential statistics and Systems Dynamics, to study the evolution of individual happiness after a single dose of drug consumption. In an application case, the effect of alcohol and caffeine on happiness is analyzed through a single-case experimental design, with replication, involving two participants. Both inferential statistical analysis and Systems Dynamics methods have been used to analyze the results. Two scales were used to measure happiness—the Euphoria Scale (ES) and the Smiling Face Scale (SFS)—in trait and state format. A single-case experimental ABC design was used. Phase A had no treatment, and Phases B and C saw both subjects receiving 26.51 mL of alcohol and 330 mg of caffeine, respectively. The participants filled in a form with both scales in a state format every 10 min over a 3 h period, operating in each one of the three phases A, B and C. The main conclusion of the analysis performed is that both methods provide similar results about the evolution of individual happiness after single dose consumption. Therefore, the article shows that inferential statistics and the stimulus response model derived from the Systems Dynamics approach can be used in a complementary and enriching way to obtain prediction results. Full article

Background: Methotrexate (MTX) remains the most commonly prescribed drug used to treat rheumatoid arthritis (RA). Polymorphisms in solute carrier organic anion transporter family member 1B3 (SLCO1B3) and SLCO1B1 may play a critical role in MTX pharmacokinetics and patient outcomes. However, research on these polymorphisms in Saudi Arabia remains limited. We evaluated the association of SLCO1B3 (rs4149117, rs7311358) and SLCO1B1 (rs2306283, rs4149056) polymorphisms with MTX efficacy and safety in Saudi patients with RA. Methods: This multicenter, case-control study included patients diagnosed with RA in Jeddah and Taif. Demographic and clinical data were collected and analyzed. Genotyping of SLCO1B3 (rs4149117, rs7311358) and SLCO1B1 (rs2306283, rs4149056) polymorphisms was performed using Sanger sequencing. Statistical analyses, including logistic regression and haplotype analysis, were conducted to evaluate associations between these polymorphisms, MTX efficacy, and toxicity. Results: The study cohort comprised 100 patients with RA, with 46 showing a good response to MTX and 54 showing a poor response. Clinical predictors of MTX response were significantly higher in patients with poor response. Both SLCO1B3 polymorphisms (rs4149117, rs7311358) were significantly associated with anemia. Significant associations were found between SLCO1B1 (rs2306283) and gastrointestinal disturbances and anemia. The GAAT haplotype was significantly more prevalent among good responders, while the TGGT haplotype was significantly associated with poor responders. Conclusions: These results highlight the importance of genetic testing in predicting MTX treatment outcomes and tailoring personalized treatment plans for patients with RA to improve efficacy and minimize adverse effects. Full article

Background and Objectives: The Hippo pathway, via Yes-associated protein 1 (YAP1), regulates cell proliferation, apoptosis, and tissue regeneration. Aberrant YAP1 activation is linked to tumor progression and immune evasion in various cancers, including breast carcinoma, despite conflicting evidence on its prognostic value. Preclinical studies have explored drugs targeting YAP1–TEAD interactions, but therapeutic application is limited. Materials and Methods: This study included 50 patients with locally advanced breast cancer, who were assessed by a multidisciplinary tumor board and underwent neoadjuvant treatment per tumor subtype and clinical guidelines. Eligibility required both pre-treatment core biopsy and post-treatment surgical resection samples. Due to the absence of residual tumor in some patients achieving complete pathological response, post-treatment tissue was available and analyzable in 30 patients. YAP1 expression was evaluated immunohistochemically for nuclear and cytoplasmic staining patterns. ROC analysis identified a cutoff for YAP1 expression, defining tumors with ≥70% nuclear and ≥80% cytoplasmic staining. Results: YAP1 expression had a significant relationship with tumor subtype (p = 0.001), being most frequent in HER-2-positive tumors (55.6%) and least frequent in luminal tumors (11.1%). YAP1 positivity significantly predicted axillary pathological complete response (pCR) (p = 0.01). In YAP1-positive patients, 77.8% achieved axillary pCR compared to 31.7% in YAP1-negative patients, though the YAP1 status and breast pCR association were insignificant (p = 0.07). The Mann–Whitney U test indicated that higher Ki-67 values were significantly associated with positive YAP1 expression (p = 0.028). In contrast, there was no association between ER, PR status, age, and tumor size. Following treatment, there was a statistically significant change in YAP1 expression, with nuclear staining decreasing (p = 0.004) while cytoplasmic staining increased (p = 0.002). YAP1 was significantly linked to axillary pCR, HER-2 status, and Ki-67. Conclusions: Post treatment, nuclear YAP1 decreased, whereas cytoplasmic expression increased, showing a localization shift. These results suggest that YAP1 may predict treatment response and become a future therapeutic target. Full article

(1) Background: Overexpression of P-glycoprotein (P-gp) is one mediator of multidrug resistance in cancer. While many studies demonstrate the efficacy of modulating P-glycoprotein expression to increase drug response in cancer cells, the nature of the mathematical relationship between drug sensitivity and P-glycoprotein surface density is not yet characterized. (2) Methods: In this study, we employ siRNA to modulate P-gp expression in two model cell lines and evaluate their steady-state response to three common chemotherapeutics in vitro. Additionally, we model the kinetics of calcein-AM, a P-gp substrate, as a function of P-gp expression. (3) Results: For both cell lines, a robust linear relationship governs chemotherapeutic sensitivity as a function of P-gp expression, demonstrating that characterization of P-gp surface density is a strong indicator of drug response in drug-resistant cells. Furthermore, calcein accumulation and initial influx rate exhibit first-order kinetics with respect to P-gp density, further elucidating the nature of substrate interactions with P-gp-overexpressing cells. When transport kinetics are evaluated using a Michaelis–Menten model, V_max varies with P-gp density according to a first-order relationship. (4) Conclusions: These results establish the mathematical relationships between chemotherapeutic response and substrate influx as a function of P-gp expression and suggest that rational changes in P-gp expression could be used as a predictive measure of drug sensitivity in model cell lines. Full article

Background: Epigenomic instability accelerates mutations in tumor suppressor genes and oncogenes, contributing to malignant transformation. Histone modifications, particularly methylation and acetylation, significantly influence tumor biology, with chromo-, bromo-, and Tudor domain-containing proteins mediating these changes. This study investigates how genes encoding these domain-containing proteins affect colorectal cancer (CRC) prognosis. Methods: Using CRC data from the GSE39582 and TCGA datasets, we identified domain-related genes via GeneCards and developed a prognostic signature using LASSO-COX regression. Patients were classified into high- and low-risk groups, and comparisons were made across survival, clinical features, immune cell infiltration, immunotherapy responses, and drug sensitivity predictions. Single-cell analysis assessed gene expression in different cell subsets. Results: Four domain-related genes (AKAP1, ORC1, CHAF1A, and UHRF2) were identified as a prognostic signature. Validation confirmed their prognostic value, with significant differences in survival, clinical features, immune patterns, and immunotherapy responses between the high- and low-risk groups. Drug sensitivity analysis revealed top candidates for CRC treatment. Single-cell analysis showed varied expression of these genes across cell subsets. Conclusions: This study presents a novel prognostic signature based on domain-related genes that can predict CRC severity and offer insights into immune dynamics, providing a promising tool for personalized risk assessment in CRC. Full article