Jun He¹, Jianli Luo¹, Yanling Wang^1,*, Dai Zhou^1,*, Shuanglin Xiang^2,*

Congenital Heart Disease, Vol.20, No.5, pp. 613-623, 2025, DOI:10.32604/chd.2025.071773 - 30 November 2025

Abstract Pediatric congenital heart disease (CHD) pharmacotherapy faces three fundamental barriers: developmental pharmacokinetic complexity, anatomic-genetic heterogeneity, and evidence chain gaps. Traditional agents exhibit critical limitations: digoxin’s narrow therapeutic index (0.5–0.9 ng/mL) is exacerbated by ABCB1 mutations (toxicity risk increases 4.1-fold), furosemide efficacy declines by 35% in neonates due to NKCC2 immaturity, and β-blocker responses vary by CYP2D6 polymorphisms (poor metabolizers require 50–75% dose reduction). Novel strategies demonstrate transformative potential—CRISPR editing achieves 81% reversal of BMPR2-associated pulmonary vascular remodeling, metabolically matured cardiac organoids replicate adult myocardial energy metabolism for drug screening, and SGLT2 inhibitors activate triple mechanisms (calcium overload More >

Boxuan Han^1,2,#, Shaokun Liu^3,#, Ridhima Das³, Shiqian Liu⁴, Yang Zhang^1,2,*

Oncology Research, Vol.33, No.12, pp. 3633-3656, 2025, DOI:10.32604/or.2025.071296 - 27 November 2025

Abstract Organoid technology, characterized by high fidelity in mimicking the in vivo microenvironment, preservation of tumor heterogeneity, and capacity for high-throughput operations, has emerged as a critical tool in head and neck cancer research. To address clinical challenges in head and neck cancer management—including marked tumor heterogeneity, therapeutic resistance, and significant prognostic variability—this review focuses on four key translational applications of organoid technology: In mechanistic studies, organoid models provide a reliable platform for investigating tumorigenesis, progression, and drug resistance mechanisms. In personalized therapy, organoid-based drug sensitivity testing enables data-driven clinical decision-making. For biomarker discovery, organoids facilitate the More >

Sameera V Mohd Sagheer^1,*, Meghana K H², P M Ameer³, Muneer Parayangat⁴, Mohamed Abbas⁴

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4259-4297, 2025, DOI:10.32604/cmc.2025.063726 - 30 July 2025

Abstract Integrating multiple medical imaging techniques, including Magnetic Resonance Imaging (MRI), Computed Tomography, Positron Emission Tomography (PET), and ultrasound, provides a comprehensive view of the patient health status. Each of these methods contributes unique diagnostic insights, enhancing the overall assessment of patient condition. Nevertheless, the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution, data collection methods, and noise levels. While traditional models like Convolutional Neural Networks (CNNs) excel in single-modality tasks, they struggle to handle multi-modal complexities, lacking the capacity to model global relationships. This research presents a novel approach for… More >

Madeline Keane¹, Natalia Wojciechowska², Lindsay Zumwalt^1,*, Emilie Sandfeld³, Alejandra Dominguez¹, Jason Wang², Anish Ray²

Oncology Research, Vol.33, No.8, pp. 1895-1908, 2025, DOI:10.32604/or.2025.065547 - 18 July 2025

Abstract Background: Precision medicine is an emerging approach for treating pediatric cancer due to its ability to target tumor-specific genetic drivers rather than provide broad and aggressive treatments. The study aimed to outline the establishment and impact of a Precision Medicine Clinic (PMC) in the setting of pediatric oncology, with the objective of offering targeted treatment options within the institution and creating a scalable model for adoption by other healthcare systems to achieve a wider impact. Methods: Recognizing this need for an individualized approach to treating patients, Cook Children’s Medical Center (CCMC) established a multidisciplinary molecular… More >

Anandhavalli Muniasamy^1,*, Ashwag Alasmari²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 569-592, 2025, DOI:10.32604/cmes.2025.060484 - 11 April 2025

Abstract The effective and timely diagnosis and treatment of ocular diseases are key to the rapid recovery of patients. Today, the mass disease that needs attention in this context is cataracts. Although deep learning has significantly advanced the analysis of ocular disease images, there is a need for a probabilistic model to generate the distributions of potential outcomes and thus make decisions related to uncertainty quantification. Therefore, this study implements a Bayesian Convolutional Neural Networks (BCNN) model for predicting cataracts by assigning probability values to the predictions. It prepares convolutional neural network (CNN) and BCNN models. More > Graphic Abstract

GUANTING PANG^1,5,#, YAOHAN LI^2,5,#, QIWEN SHI³, JINGKUI TIAN⁵, HANMEI LOU^4,5,*, YUE FENG^4,5,*

Oncology Research, Vol.33, No.4, pp. 821-836, 2025, DOI:10.32604/or.2024.053772 - 19 March 2025

Abstract Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer (CC). However, the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment (TIME). Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME. Furthermore, integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior. In this review, we present advanced omics technologies that More >

IOANA MARIA MIHAI¹, GANG WANG^1,2,*

Oncology Research, Vol.33, No.3, pp. 533-547, 2025, DOI:10.32604/or.2024.055155 - 28 February 2025

Abstract The advent of precision medicine has underscored the importance of biomarkers in predicting therapy response for bladder cancer, a malignancy marked by considerable heterogeneity. This review critically examines the current landscape of biomarkers to forecast treatment outcomes in bladder cancer patients. We explore a range of biomarkers, including genetic, epigenetic, proteomic, and transcriptomic indicators, from multiple sample sources, including urine, tumor tissue and blood, assessing their efficacy in predicting responses to chemotherapy, immunotherapy, and targeted therapies. Despite promising developments, the translation of these biomarkers into clinical practice faces significant challenges, such as variability in biomarker More >

AHMAD SHAHIR MOHAMAD NAZRI, NAZIHAH MOHD YUNUS, MARAHAINI MUSA^*

BIOCELL, Vol.49, No.1, pp. 149-160, 2025, DOI:10.32604/biocell.2024.057352 - 24 January 2025

Abstract Pediatric inflammatory bowel disease (IBD) is a chronic and heterogeneous disease. IBD is commonly classified into Crohn’s disease and ulcerative colitis. It is linked to serious symptoms and complications. The onset of IBD commonly occurs during adolescence. Despite the significant number of cases globally (~5 million), the causes of pediatric IBD, which constitutes 25% of IBD patients, are not yet fully understood. Apart from environmental factors, genetic factors contribute to a higher risk of developing IBD. The predisposition risk of IBD can be investigated using genetic testing. Genetic mechanisms of pediatric IBD are highly complex More >

MERYEM A. ABDESSALEM, SIRIN A. ADHAM^*

Oncology Research, Vol.33, No.1, pp. 27-44, 2025, DOI:10.32604/or.2024.056955 - 20 December 2024

Abstract Nanotechnology in cancer therapy has significantly advanced treatment precision, effectiveness, and safety, improving patient outcomes and personalized care. Engineered smart nanoparticles and cell-based therapies are designed to target tumor cells, precisely sensing the tumor microenvironment (TME) and sparing normal cells. These nanoparticles enhance drug accumulation in tumors by solubilizing insoluble compounds or preventing their degradation, and they can also overcome therapy resistance and deliver multiple drugs simultaneously. Despite these benefits, challenges remain in patient-specific responses and regulatory approvals for cell-based or nanoparticle therapies. Cell-based drug delivery systems (DDSs) that primarily utilize the immune-recognition principle between… More > Graphic Abstract

LU ZHANG^*, JINGUO CHU^*, YUSHAN YU

Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988 - 20 March 2024

Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using… More >