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  • Open Access

    ARTICLE

    Methyltransferase 3A-mediated promoter methylation represses retinoic acid receptor responder 3 expression in basal-like breast cancer

    YOULIN TUO, XUBAO LIU*

    BIOCELL, Vol.47, No.2, pp. 319-328, 2023, DOI:10.32604/biocell.2023.025250

    Abstract Retinoic acid receptor responder 3 (RARRES3) has been characterized as a tumor suppressor in multiple types of cancer. This study aimed to examine the expression profile of RARRES3 across the PAM50 subtypes of breast cancer. The DNA methylation status of RARRES3 was checked in the basal-like subtype, and the underlying mechanisms of its dysregulation were explored. RNA-sequencing (seq) and methylation data from The Cancer Genome Atlas were used for in-silico analysis. Basal-like representative SUM149 and MDA-MB-468 cell lines were used for in vitro and in vivo studies. Compared to tumor-adjacent normal tissues, only the basal-like tumor tissues had significantly downregulated… More >

  • Open Access

    ARTICLE

    Breast Cancer Diagnosis Using Feature Selection Approaches and Bayesian Optimization

    Erkan Akkur1, Fuat TURK2,*, Osman Erogul1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1017-1031, 2023, DOI:10.32604/csse.2023.033003

    Abstract Breast cancer seriously affects many women. If breast cancer is detected at an early stage, it may be cured. This paper proposes a novel classification model based improved machine learning algorithms for diagnosis of breast cancer at its initial stage. It has been used by combining feature selection and Bayesian optimization approaches to build improved machine learning models. Support Vector Machine, K-Nearest Neighbor, Naive Bayes, Ensemble Learning and Decision Tree approaches were used as machine learning algorithms. All experiments were tested on two different datasets, which are Wisconsin Breast Cancer Dataset (WBCD) and Mammographic Breast Cancer Dataset (MBCD). Experiments were… More >

  • Open Access

    ARTICLE

    A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

    Muhammad Junaid Umer1, Muhammad Sharif1, Majed Alhaisoni2, Usman Tariq3, Ye Jin Kim4, Byoungchol Chang5,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1001-1016, 2023, DOI:10.32604/csse.2023.030463

    Abstract Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work proposed a deep learning-based (DL)… More >

  • Open Access

    ARTICLE

    Hybrid Models for Breast Cancer Detection via Transfer Learning Technique

    Sukhendra Singh1, Sur Singh Rawat, Manoj Gupta3, B. K. Tripathi4, Faisal Alanazi5, Arnab Majumdar6, Pattaraporn Khuwuthyakorn7, Orawit Thinnukool7,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3063-3083, 2023, DOI:10.32604/cmc.2023.032363

    Abstract Currently, breast cancer has been a major cause of deaths in women worldwide and the World Health Organization (WHO) has confirmed this. The severity of this disease can be minimized to the large extend, if it is diagnosed properly at an early stage of the disease. Therefore, the proper treatment of a patient having cancer can be processed in better way, if it can be diagnosed properly as early as possible using the better algorithms. Moreover, it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological images of breast tissues. To… More >

  • Open Access

    ARTICLE

    Pixel-Level Feature Extraction Model for Breast Cancer Detection

    Nishant Behar*, Manish Shrivastava

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3371-3389, 2023, DOI:10.32604/cmc.2023.031949

    Abstract Breast cancer is the most prevalent cancer among women, and diagnosing it early is vital for successful treatment. The examination of images captured during biopsies plays an important role in determining whether a patient has cancer or not. However, the stochastic patterns, varying intensities of colors, and the large sizes of these images make it challenging to identify and mark malignant regions in them. Against this backdrop, this study proposes an approach to the pixel categorization based on the genetic algorithm (GA) and principal component analysis (PCA). The spatial features of the images were extracted using various filters, and the… More >

  • Open Access

    ARTICLE

    Biological and molecular studies on specific immune cells treated with checkpoint inhibitors for the thera-personal approach of breast cancer patients (ex-vivo study)

    MOTAWA E. EL-HOUSEINI1, MOSTAFA S. ARAFAT2, AHMED M. EL-HUSSEINY3, ISLAM M. KASEM2, MAHMOUD M. KAMEL4, AHMED H. EL-HABASHY5, MEDHAT M. KHAFAGY6, ENAS M. RADWAN4, MAHA H. HELAL7, MONA S. ABDELLATEIF1,*

    Oncology Research, Vol.29, No.5, pp. 319-329, 2021, DOI:10.32604/or.2022.025249

    Abstract Immunotherapy becomes a promising line of treatment for breast cancer (BC) however, its success rate is still limited. Methods: The study was designed to optimize the condition for producing an effective dendritic cell (DCs) based immunotherapy by using DCs and T lymphocytes together with tumor-infiltrating lymphocytes (TILs) and tumor-infiltrating DCs (TIDCs), treated with anti-PD1 and anti-CTLA4 monoclonal antibodies. This mixture of immune cells was co-cultured with autologous breast cancer cells (BCCs) isolated from 26 BC females. Results: There was a significant upregulation of CD86 and CD83 on DCs (P = 0.001 and 0.017, respectively), similarly upregulation of CD8, CD4 and… More >

  • Open Access

    ARTICLE

    Comparison of Time-Varying Pattern of Recurrence in Chinese Breast Cancer Patients with Different Molecular Subtypes: A Single-Center Retrospective Study

    Xujie Zhou1,2,3,#, Yuting Sang1,3,#, Jiajian Chen1,3, Miao Mo3,4, Jianjing Hou1,3, Benlong Yang1,3,*, Jiong Wu1,2,3,*

    Oncologie, Vol.24, No.3, pp. 451-469, 2022, DOI:10.32604/oncologie.2022.025226

    Abstract Background: To compare the time-varying recurrence patterns of different molecular subtypes of breast cancer in the contemporary era with those in the past era. Patients and Methods: This retrospective study included 14627 consecutive invasive breast cancer patients who underwent surgery from 2008 to 2016 at Fudan University Shanghai Cancer Center. We defined the period from 2013 to 2016 as the contemporary era and that from 2008 to 2012 as the past era. Five subtypes were defined according to the immunohistochemistry results. Emphasis was made on the changing patterns of recurrence for patients with different molecular subtypes changed between the two… More >

  • Open Access

    ARTICLE

    Ampelopsin Inhibits Breast Cancer Glucose Metabolism Reprogramming Based on Network Pharmacology and Molecular Docking

    Rong Zeng1,#, Lin Liu1,2,#, Jingshan Zhao1,2,3,#, Wenmei Zhang3, Guohong Zhang1, Yunfeng Li1,2,*

    Oncologie, Vol.24, No.3, pp. 483-498, 2022, DOI:10.32604/oncologie.2022.025148

    Abstract Background: Breast cancer (BC) is the most frequent type of gynecology tumors with high morbidity and mortality. Ampelopsin, the main active compound of Ampelopsis grossedentata, exerts an anti-tumor effect on a variety of cancers. However, the anti-cancer role of ampelopsin in BC remains unclear. The aim of this study is to explore the mechanism of ampelopsin against breast cancer. Materials and Methods: The target genes of ampelopsin in the treatment of breast cancer were determined and analyzed by network pharmacology and molecular docking. Cytoscape software was used to identify the core target genes and construct a protein–protein interaction (PPI) network.… More >

  • Open Access

    STUDY PROTOCOL IN FRENCH

    Impact of Adapted Physical Activity on Joint Pain Induced by Hormonotherapy in Adjuvant Breast Cancer Treatment: APAISE Study Protocol
    Impact de l’Activité Physique Adaptée sur les Douleurs Articulaires Induites sous Hormonothérapie en Traitement Adjuvant du Cancer : Protocole de l’Etude APAISE

    Virginie Prevost1,2,#,*, Pauline Drillon3,#, Antoine Desvergée4, Corinne Delcambre2, Claire Delorme2, Anne Besnier5, Kévin Lecaplain6, Charline Frandemiche7, Anaïs Briant7, Rémy Morello4, Xavier Blaizot7

    Oncologie, Vol.24, No.3, pp. 357-369, 2022, DOI:10.32604/oncologie.2022.025107

    Abstract Breast cancer is the most common cancer in women and approximately 80% of patients will receive hormone therapy. If survival rate after breast cancer patients is the most important, their treatment, induces strong side effects on quality of life, including joint pain which is encountered by one woman in two. These joint pains are likely to reduce compliance with the treatment and consequently impact survival. In this context, this work aims to evaluate the potential benefit of adapted physical activity to relieve pain and its impact on daily functions. The APAISE protocol, described in this article, is a prospective observational… More >

  • Open Access

    ARTICLE

    G-Protein-Coupled Estrogen Receptor Enhances the Stemness of Triple-Negative Breast Cancer Cells and Promotes Malignant Characteristics

    Dongliang Zhu1,*, Jun Yang2, Jiaxin Xu3

    Oncologie, Vol.24, No.3, pp. 471-482, 2022, DOI:10.32604/oncologie.2022.024062

    Abstract G-protein coupled estrogen receptor (GPER) is a transmembrane receptor that mediates non-genomic effects of estrogen. This study aimed to investigate the role of GPER in the stemness formation and malignancies in triple negative breast cancer (TNBC) cells. Spheroids of MDA-MB-468 cells were induced by mammosphere culture, and the proportion of the CD44+ /CD24−/low stem cell subpopulation was detected. Malignant characteristics, expression of GPER and stemness-related markers, and tumorigenesis in a xenograft assay were compared between the mammospheres and adherent cultured cells. The impacts of 17β-estradiol (E2) and the GPER-specific antagonist G15 were studied in in vitro assays. The proportion of… More >

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