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  • Open Access

    ARTICLE

    Gastric cancer secreted miR-214-3p inhibits the anti-angiogenesis effect of apatinib by suppressing ferroptosis in vascular endothelial cells

    WEIXUE WANG#, TONGTONG WANG#, YAN ZHANG, TING DENG, HAIYANG ZHANG*, YI BA*

    Oncology Research, Vol.32, No.3, pp. 489-502, 2024, DOI:10.32604/or.2023.046676

    Abstract Different from necrosis, apoptosis, autophagy and other forms of cell death, ferroptosis is a mechanism that catalyzes lipid peroxidation of polyunsaturated fatty acids under the action of iron divalent or lipoxygenase, leading to cell death. Apatinib is currently used in the third-line standard treatment of advanced gastric cancer, targeting the anti-angiogenesis pathway. However, Apatinib-mediated ferroptosis in vascular endothelial cells has not been reported yet. Tumor-secreted exosomes can be taken up into target cells to regulate tumor development, but the mechanism related to vascular endothelial cell ferroptosis has not yet been discovered. Here, we show that exosomes secreted by gastric cancer… More >

  • Open Access

    ARTICLE

    High-throughput computational screening and in vitro evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl) phenyl]-1H-isoindole-1,3(2H)-dione (C3), as a novel EGFR—HER2 dual inhibitor in gastric tumors

    MESFER AL SHAHRANI, REEM GAHTANI, MOHAMMAD ABOHASSAN, MOHAMMAD ALSHAHRANI, YASSER ALRAEY, AYED DERA, MOHAMMAD RAJEH ASIRI, PRASANNA RAJAGOPALAN*

    Oncology Research, Vol.32, No.2, pp. 251-259, 2024, DOI:10.32604/or.2023.043139

    Abstract Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation, adhesion, angiogenesis, and metastasis. Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations. Hence, dual inhibition strategies are recommended to increase potency and reduce cytotoxicity. In this study, we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities. Diversity-based High-throughput Virtual Screening (D-HTVS) was used to screen the whole ChemBridge small molecular library against EGFR and… More > Graphic Abstract

    High-throughput computational screening and <i>in vitro</i> evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl) phenyl]-1H-isoindole-1,3(2H)-dione (C3), as a novel EGFR—HER2 dual inhibitor in gastric tumors

  • Open Access

    ARTICLE

    Advancing Brain Tumor Analysis through Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis

    S. Kannan1,*, S. Anusuya2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3835-3851, 2023, DOI:10.32604/cmc.2023.042465

    Abstract Gliomas, the most prevalent primary brain tumors, require accurate segmentation for diagnosis and risk assessment. In this paper, we develop a novel deep learning-based method, the Dynamic Hierarchical Attention for Improved Segmentation and Survival Prognosis (DHA-ISSP) model. The DHA-ISSP model combines a three-band 3D convolutional neural network (CNN) U-Net architecture with dynamic hierarchical attention mechanisms, enabling precise tumor segmentation and survival prediction. The DHA-ISSP model captures fine-grained details and contextual information by leveraging attention mechanisms at multiple levels, enhancing segmentation accuracy. By achieving remarkable results, our approach surpasses 369 competing teams in the 2020 Multimodal Brain Tumor Segmentation Challenge. With… More >

  • Open Access

    ARTICLE

    Classification of Brain Tumors Using Hybrid Feature Extraction Based on Modified Deep Learning Techniques

    Tawfeeq Shawly1, Ahmed Alsheikhy2,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 425-443, 2023, DOI:10.32604/cmc.2023.040561

    Abstract According to the World Health Organization (WHO), Brain Tumors (BrT) have a high rate of mortality across the world. The mortality rate, however, decreases with early diagnosis. Brain images, Computed Tomography (CT) scans, Magnetic Resonance Imaging scans (MRIs), segmentation, analysis, and evaluation make up the critical tools and steps used to diagnose brain cancer in its early stages. For physicians, diagnosis can be challenging and time-consuming, especially for those with little expertise. As technology advances, Artificial Intelligence (AI) has been used in various domains as a diagnostic tool and offers promising outcomes. Deep-learning techniques are especially useful and have achieved… More >

  • Open Access

    ARTICLE

    Liver Tumor Prediction with Advanced Attention Mechanisms Integrated into a Depth-Based Variant Search Algorithm

    P. Kalaiselvi1,*, S. Anusuya2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1209-1226, 2023, DOI:10.32604/cmc.2023.040264

    Abstract In recent days, Deep Learning (DL) techniques have become an emerging transformation in the field of machine learning, artificial intelligence, computer vision, and so on. Subsequently, researchers and industries have been highly endorsed in the medical field, predicting and controlling diverse diseases at specific intervals. Liver tumor prediction is a vital chore in analyzing and treating liver diseases. This paper proposes a novel approach for predicting liver tumors using Convolutional Neural Networks (CNN) and a depth-based variant search algorithm with advanced attention mechanisms (CNN-DS-AM). The proposed work aims to improve accuracy and robustness in diagnosing and treating liver diseases. The… More >

  • Open Access

    ARTICLE

    Early Diagnosis of Lung Tumors for Extending Patients’ Life Using Deep Neural Networks

    A. Manju1, R. kaladevi2, Shanmugasundaram Hariharan3, Shih-Yu Chen4,5,*, Vinay Kukreja6, Pradip Kumar Sharma7, Fayez Alqahtani8, Amr Tolba9, Jin Wang10

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 993-1007, 2023, DOI:10.32604/cmc.2023.039567

    Abstract The medical community has more concern on lung cancer analysis. Medical experts’ physical segmentation of lung cancers is time-consuming and needs to be automated. The research study’s objective is to diagnose lung tumors at an early stage to extend the life of humans using deep learning techniques. Computer-Aided Diagnostic (CAD) system aids in the diagnosis and shortens the time necessary to detect the tumor detected. The application of Deep Neural Networks (DNN) has also been exhibited as an excellent and effective method in classification and segmentation tasks. This research aims to separate lung cancers from images of Magnetic Resonance Imaging… More >

  • Open Access

    ARTICLE

    Liver Tumor Decision Support System on Human Magnetic Resonance Images: A Comparative Study

    Hiam Alquran1,2, Yazan Al-Issa3, Mohammed Alslatie4, Isam Abu-Qasmieh1, Amin Alqudah3, Wan Azani Mustafa5,7,*, Yasmin Mohd Yacob6,7

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861

    Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance of 3D features and 2D… More >

  • Open Access

    REVIEW

    Histone deacetylase inhibitors as a novel therapeutic approach for pheochromocytomas and paragangliomas

    ASPASIA MANTA1, SPYRIDON KAZANAS2, STEFANOS KARAMAROUDIS3, HELEN GOGAS2, DIMITRIOS C. ZIOGAS2,*

    Oncology Research, Vol.30, No.5, pp. 211-219, 2022, DOI:10.32604/or.2022.026913

    Abstract Epigenetic mechanisms, such as DNA methylation and histone modifications (e.g., acetylation and deacetylation), are strongly implicated in the carcinogenesis of various malignancies. During transcription, the expression and functionality of coding gene products are altered following the histone acetylation and deacetylation. These processes are regulated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), respectively. HDAC inhibitors (HDACis) have been developed as promising therapeutic agents, to limit exposure to traditional and toxic chemotherapies and offer more alternatives for some specific malignant diseases with limited options. Mechanistically, these agents affect many intracellular pathways, including cell cycle arrest, apoptosis and differentiation, and their mechanism… More >

  • Open Access

    REVIEW

    Research progress of TRIMs protein family in tumors

    YUANYUAN HUANG#, HONGMEI WU#, RUYUAN LIU, SONG JIN, WEILAI XIANG, CHANG YANG, LI XU, XIAONIAN ZHU*

    BIOCELL, Vol.47, No.3, pp. 445-454, 2023, DOI:10.32604/biocell.2023.025880

    Abstract The tripartite motif (TRIMs) protein family has E3 ubiquitin ligase activity among most of its members. They participate in multiple cellular processes and signaling pathways in living organisms, including cell cycle, growth, and metabolism, and mediate chromatin modification, transcriptional regulation, post-translational modification, and cellular autophagy. Previous studies have confirmed that the TRIMs protein family is involved in the development of various cancers and correlated with the prognosis of tumor patients. Here we summarize the biological roles of the TRIMs protein family in cancers. More >

  • Open Access

    ARTICLE

    Racial Disparities in Clinical Features and Survival Outcomes among Patients with Pancreatic Neuroendocrine Tumor: A Contemporary SEER Database Analysis

    Fei Wang1, Jihyun Ma2, Nan Zhao3, Chi Lin3,*, Haixing Jiang1,*

    Oncologie, Vol.24, No.4, pp. 865-895, 2022, DOI:10.32604/oncologie.2022.025447

    Abstract Objective: The characteristics of clinical features and prognoses among patients with different racial backgrounds have not been clearly studied. We thus investigated the clinical characteristics and overall survival (OS) differences among Asian, White, and Black patients with pancreatic neuroendocrine tumors (pNETs). Materials and Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried to identify patients with pNETs between 1983 and 2015. We performed univariable (UVA) and multivariable logistic regression (MVA) to assess the association between variables and race category. A Kaplan-Meier (KM) plot was used to calculate the OS rates. The Cox proportional hazard regression was used to… More >

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