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  • Open Access

    ARTICLE

    Identifying and validating MMP family members (MMP2, MMP9, MMP12, and MMP16) as therapeutic targets and biomarkers in kidney renal clear cell carcinoma (KIRC)

    KUNLUN LI1, DANDAN LI2, BARBOD HAFEZ3,*, MOUNIR M. SALEM BEKHIT4, YOUSEF A. BIN JARDAN4, FARS KAED ALANAZI4, EHAB I. TAHA4, SAYED H. AUDA4, FAIQAH RAMZAN5,*, MUHAMMAD JAMIL6

    Oncology Research, Vol.32, No.4, pp. 737-752, 2024, DOI:10.32604/or.2023.042925

    Abstract Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP… More >

  • Open Access

    ARTICLE

    Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

    LU ZHANG*, JINGUO CHU*, YUSHAN YU

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

    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 consensus clustering to identify subgroups… More >

  • Open Access

    ARTICLE

    Identification of prognostic molecular subtypes and model based on CD8+ T cells for lung adenocarcinoma

    HONGMIN CAO1,#,*, YING XUE2,#, FEI WANG1, GUANGYAO LI1, YULAN ZHEN1, JINGWEN GUO1

    BIOCELL, Vol.48, No.3, pp. 473-490, 2024, DOI:10.32604/biocell.2024.048946

    Abstract Background: Cytotoxic T lymphocytes (CD8+ T) cells function critically in mediating anti-tumor immune response in cancer patients. Characterizing the specific functions of CD8+ T cells in lung adenocarcinoma (LUAD) could help better understand local anti-tumor immune responses and estimate the effect of immunotherapy. Methods: Gens related to CD8+ T cells were identified by cluster analysis based on the single-cell sequencing data of three LUAD tissues and their paired normal tissues. Weighted gene co-expression network analysis (WGCNA), consensus clustering, differential expression analysis, least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were conducted to classify molecular subtypes for LUAD… More > Graphic Abstract

    Identification of prognostic molecular subtypes and model based on CD8+ T cells for lung adenocarcinoma

  • Open Access

    ARTICLE

    Bioinformatics analysis and experimental validation of cystathionine-gamma-lyase as a potential prognosis biomarker in hepatocellular carcinoma

    YANAN MA1, SHANSHAN WANG2,*, HUIGUO DING1,*

    BIOCELL, Vol.48, No.3, pp. 463-471, 2024, DOI:10.32604/biocell.2024.048244

    Abstract Background: Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis and high mortality worldwide. Although cystathionine-gamma-lyase (CSE) plays an important role in the development of multiple tumors, the clinical implication and potential mechanisms of CSE in HCC development remain elusive. Methods: In our study, the CSE expression in HCC was analyzed in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets and further confirmed by RT-qPCR and immunohistochemistry assays in HCC samples. Furthermore, the associations between CSE expression and HCC malignancy as well as survival were analyzed in GSE14520 and validated in HCC patients. Finally, the… More >

  • Open Access

    ARTICLE

    Cross-Dimension Attentive Feature Fusion Network for Unsupervised Time-Series Anomaly Detection

    Rui Wang1, Yao Zhou3,*, Guangchun Luo1, Peng Chen2, Dezhong Peng3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3011-3027, 2024, DOI:10.32604/cmes.2023.047065

    Abstract Time series anomaly detection is crucial in various industrial applications to identify unusual behaviors within the time series data. Due to the challenges associated with annotating anomaly events, time series reconstruction has become a prevalent approach for unsupervised anomaly detection. However, effectively learning representations and achieving accurate detection results remain challenging due to the intricate temporal patterns and dependencies in real-world time series. In this paper, we propose a cross-dimension attentive feature fusion network for time series anomaly detection, referred to as CAFFN. Specifically, a series and feature mixing block is introduced to learn representations in 1D space. Additionally, a… More >

  • Open Access

    ARTICLE

    A Normalizing Flow-Based Bidirectional Mapping Residual Network for Unsupervised Defect Detection

    Lanyao Zhang1, Shichao Kan2, Yigang Cen3, Xiaoling Chen1, Linna Zhang1,*, Yansen Huang4,5

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1631-1648, 2024, DOI:10.32604/cmc.2024.046924

    Abstract Unsupervised methods based on density representation have shown their abilities in anomaly detection, but detection performance still needs to be improved. Specifically, approaches using normalizing flows can accurately evaluate sample distributions, mapping normal features to the normal distribution and anomalous features outside it. Consequently, this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network (NF-BMR). It utilizes pre-trained Convolutional Neural Networks (CNN) and normalizing flows to construct discriminative source and target domain feature spaces. Additionally, to better learn feature information in both domain spaces, we propose the Bidirectional Mapping Residual Network (BMR), which maps sample features to these two spaces… More > Graphic Abstract

    A Normalizing Flow-Based Bidirectional Mapping Residual Network for Unsupervised Defect Detection

  • Open Access

    ARTICLE

    Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

    Ali Hamid Farea1,*, Omar H. Alhazmi1, Kerem Kucuk2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

    Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work. AI2AI employs AI techniques to… More >

  • Open Access

    REVIEW

    Stem cell technology for antitumor drug loading and delivery in oncology

    FRANCESCO PETRELLA*, ENRICO MARIO CASSINA, LIDIA LIBRETTI, EMANUELE PIRONDINI, FEDERICO RAVEGLIA, ANTONIO TUORO

    Oncology Research, Vol.32, No.3, pp. 433-437, 2024, DOI:10.32604/or.2023.046497

    Abstract The main aim of antineoplastic treatment is to maximize patient benefit by augmenting the drug accumulation within affected organs and tissues, thus incrementing drug effects and, at the same time, reducing the damage of non-involved tissues to cytotoxic agents. Mesenchymal stromal cells (MSC) represent a group of undifferentiated multipotent cells presenting wide self-renewal features and the capacity to differentiate into an assortment of mesenchymal family cells. During the last year, they have been proposed as natural carriers for the selective release of antitumor drugs to malignant cells, thus optimizing cytotoxic action on cancer cells, while significantly reducing adverse side effects… More >

  • Open Access

    REVIEW

    A review of the literature on the use of CRISPR/Cas9 gene therapy to treat hepatocellular carcinoma

    ELHAM AMJAD1, RAFFAELE PEZZANI2,3,*, BABAK SOKOUTI1,*

    Oncology Research, Vol.32, No.3, pp. 439-461, 2024, DOI:10.32604/or.2023.044473

    Abstract Noncoding RNAs instruct the Cas9 nuclease to site-specifically cleave DNA in the CRISPR/Cas9 system. Despite the high incidence of hepatocellular carcinoma (HCC), the patient’s outcome is poor. As a result of the emergence of therapeutic resistance in HCC patients, clinicians have faced difficulties in treating such tumor. In addition, CRISPR/Cas9 screens were used to identify genes that improve the clinical response of HCC patients. It is the objective of this article to summarize the current understanding of the use of the CRISPR/Cas9 system for the treatment of cancer, with a particular emphasis on HCC as part of the current state… More >

  • Open Access

    ARTICLE

    Low expression of fatty acid oxidation related gene ACADM indicates poor prognosis of renal clear cell carcinoma and is related to tumor immune infiltration

    JIECHUAN QIU1, TIANMIN YANG1, YANNING SUN2, KAI SUN2, YINGKUN XU3, QINGHUA XIA1,*

    Oncology Research, Vol.32, No.3, pp. 545-561, 2024, DOI:10.32604/or.2023.030462

    Abstract This research aims to identify the key fatty acid beta-oxidation (FAO) genes that are altered in kidney renal clear cell carcinoma (KIRC) and to analyze the role of these genes in KIRC. The Gene Expression Omnibus (GEO) and FAO datasets were used to identify these key genes. Wilcoxon rank sum test was used to assess the levels of acyl-CoA dehydrogenase medium chain (ACADM) between KIRC and non-cancer samples. The logistic regression and Wilcoxon rank sum test were used to explore the association between ACADM and clinical features. The diagnostic performance of ACADM for KIRC was assessed using a diagnostic receiver… More >

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