SHUIZHONG CEN^1,#, XIAOJIE PENG^2,#, JIANWEN DENG^3,#, HAIYUN JIN⁴, ZHINAN DENG⁵, XIAOHUA LIN³, DI ZHU³, MING JIN⁶, YANWEN ZHU³, PUSHENG ZHANG³, YUNFENG LUO³, HONGYAN HUANG^3,*

Oncology Research, Vol.31, No.3, pp. 375-388, 2023, DOI:10.32604/or.2023.028256 - 22 May 2023

Abstract Triple-negative breast cancer (TNBC) is characterized by fast growth, high metastasis, high invasion, and a lack of therapeutic targets. Mitosis and metastasis of TNBC cells are two important biological behaviors in TNBC malignant progression. It is well known that the long noncoding RNA AFAP1-AS1 plays a crucial role in various tumors, but whether AFAP1-AS1 is involved in the mitosis of TNBC cells remains unknown. In this study, we investigated the functional mechanism of AFAP1-AS1 in targeting Polo-like Kinase 1 (PLK1) activation and participating in mitosis of TNBC cells. We detected the expression of AFAP1-AS1 in the TNBC… More > Graphic Abstract

FRANCISCO RAÚL BORZONE^1,*, MARÍA BELÉN GIORELLO¹, LEANDRO MARCELO MARTINEZ², MARÍA CECILIA SANMARTIN^1,3, LEONARDO FELDMAN⁴, FEDERICO DIMASE⁵, EMILIO BATAGELJ⁶, GUSTAVO YANNARELLI³, NORMA ALEJANDRA CHASSEING^1,*

Oncology Research, Vol.31, No.3, pp. 361-374, 2023, DOI:10.32604/or.2023.028104 - 22 May 2023

Abstract Breast cancer is the predominant form of carcinoma among women worldwide, with 70% of advanced patients developing bone metastases, with a high mortality rate. In this sense, the bone marrow (BM) mesenchymal stem/stromal cells (MSCs) are critical for BM/bone homeostasis, and failures in their functionality, transform the BM into a pre-metastatic niche (PMN). We previously found that BM-MSCs from advanced breast cancer patients (BCPs, infiltrative ductal carcinoma, stage III-B) have an abnormal profile. This work aims to study some of the metabolic and molecular mechanisms underlying MSCs shift from a normal to an abnormal profile… More >

KAIMIN FAN, JUNWEI WENG^*

BIOCELL, Vol.47, No.6, pp. 1199-1211, 2023, DOI:10.32604/biocell.2023.028516 - 19 May 2023

Abstract Immunotherapy targets the dysfunctional immune system to induce cancer cell killing by CD8-positive T cells. Immune checkpoint inhibitors (ICIs), specifically anti-PD-1 antibodies, anti-PD-L1 antibodies, and anti-CTLA4 antibodies, have revolutionized the management of many malignancies due to their significant role in generating a durable clinical response. However, clinical data suggest that response rates to ICI monotherapy are low due to the immunologically silent characteristics of breast cancer (BC). Chemotherapy, surgery, radiotherapy, and targeted therapy were recently reported to alter the tumor microenvironment and enhance the ICI response. Some clinical studies supported that ICIs, in combination with More >

Alia Alshehri, Duaa AlSaeed^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 939-970, 2023, DOI:10.32604/iasc.2023.037096 - 29 April 2023

Abstract One of the most prevalent cancers in women is breast cancer. Early and accurate detection can decrease the mortality rate associated with breast cancer. Governments and health organizations emphasize the significance of early breast cancer screening since it is associated to a greater variety of available treatments and a higher chance of survival. Patients have the best chance of obtaining effective treatment when they are diagnosed early. The detection and diagnosis of breast cancer have involved using various image types and imaging modalities. Breast “infrared thermal” imaging is one of the imaging modalities., a screening… More >

E. Jenifer Sweetlin^*, S. Saudia

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 343-367, 2023, DOI:10.32604/iasc.2023.036742 - 29 April 2023

Abstract This paper proposes a hybrid feature selection sequence complemented with filter and wrapper concepts to improve the accuracy of Machine Learning (ML) based supervised classifiers for classifying the survivability of breast cancer patients into classes, living and deceased using METABRIC and Surveillance, Epidemiology and End Results (SEER) datasets. The ML-based classifiers used in the analysis are: Multiple Logistic Regression, K-Nearest Neighbors, Decision Tree, Random Forest, Support Vector Machine and Multilayer Perceptron. The workflow of the proposed ML algorithm sequence comprises the following stages: data cleaning, data balancing, feature selection via a filter and wrapper sequence, More >

JINGYUE FU, RUI CHEN, ZHIZHENG ZHANG, JIANYI ZHAO, TIANSONG XIA^*

Oncology Research, Vol.31, No.2, pp. 157-167, 2023, DOI:10.32604/or.2023.027972 - 10 April 2023

Abstract Background: Breast cancer has become the most common malignant tumor in the world. It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer, which causes the disparity in prognosis. Recently, inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer, so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies. Methods: We assessed the connection between Inflammatory-Related Genes (IRGs) and breast cancer by… More > Graphic Abstract

XI YANG^1,5,#, HUIXIAN WU^2,3,#, CHAO XIONG^4,#, BO ZHAO¹, MEILIAN LIU¹, JIE QIN⁶, MEI DENG^1,2,3,*

BIOCELL, Vol.47, No.5, pp. 1021-1037, 2023, DOI:10.32604/biocell.2023.027103 - 10 April 2023

Abstract Background: Cytochrome b561 (CYB561) plays a critical role in neuroendocrine function, cardiovascular regulation, and tumor growth; however, the prognostic value of CYB561 in patients with breast cancer and the relationship between CYB561 expression and immune infiltration in breast cancer remain unclear. Methods: The mRNA expression and clinical data of patients with breast cancer were obtained from The Cancer Genome Atlas database. Functional enrichment analysis was used to explore underlying biological functions associated with CYB561. The methylation status of CYB561 was analyzed using the MethSurv database. The enrichment score of immune cell infiltration for CYB561 in breast… More >

Manar Ahmed Hamza^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2879-2895, 2023, DOI:10.32604/iasc.2023.034719 - 15 March 2023

Abstract Breast Cancer (BC) is considered the most commonly scrutinized cancer in women worldwide, affecting one in eight women in a lifetime. Mammography screening becomes one such standard method that is helpful in identifying suspicious masses’ malignancy of BC at an initial level. However, the prior identification of masses in mammograms was still challenging for extremely dense and dense breast categories and needs an effective and automatic mechanisms for helping radiotherapists in diagnosis. Deep learning (DL) techniques were broadly utilized for medical imaging applications, particularly breast mass classification. The advancements in the DL field paved the… More >

Emad Abd Al Rahman¹, Nur Intan Raihana Ruhaiyem^1,*, Majed Bouchahma², Kamarul Imran Musa³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3007-3028, 2023, DOI:10.32604/iasc.2023.032580 - 15 March 2023

Abstract This study offers a framework for a breast cancer computer-aided treatment prediction (CATP) system. The rising death rate among women due to breast cancer is a worldwide health concern that can only be addressed by early diagnosis and frequent screening. Mammography has been the most utilized breast imaging technique to date. Radiologists have begun to use computer-aided detection and diagnosis (CAD) systems to improve the accuracy of breast cancer diagnosis by minimizing human errors. Despite the progress of artificial intelligence (AI) in the medical field, this study indicates that systems that can anticipate a treatment… More >

A. Selvi^*, S. Thilagamani

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2973-2987, 2023, DOI:10.32604/iasc.2022.029850 - 15 March 2023

Abstract Mammography is considered a significant image for accurate breast cancer detection. Content-based image retrieval (CBIR) contributes to classifying the query mammography image and retrieves similar mammographic images from the database. This CBIR system helps a physician to give better treatment. Local features must be described with the input images to retrieve similar images. Existing methods are inefficient and inaccurate by failing in local features analysis. Hence, efficient digital mammography image retrieval needs to be implemented. This paper proposed reliable recovery of the mammographic image from the database, which requires the removal of noise using Kalman More >