Yuri A. Piven¹, Danila V. Sorokin², Nastassia A. Varabyeva¹, Alexandra L. Mikhaylova², Fedor B. Bogdanov², Elena V. Shafranovskaya¹, Raman M. Puzanau³, Fedor A. Lakhvich¹, Alexander M. Scherbakov^2,4,*

Oncology Research, Vol.33, No.12, pp. 4049-4072, 2025, DOI:10.32604/or.2025.067832 - 27 November 2025

Abstract Background: The most aggressive forms of breast cancer are characterized by independence from steroid hormones but a strong dependence on growth factors. In such cancer cells, oncogenic receptors, including human epidermal growth factor receptor 2 (HER2), are activated, and their targeted inhibition represents an attractive therapeutic strategy. The study aimed to develop small-molecule potential dual heat shock protein 90 (HSP90)-HER2 inhibitors and evaluate them as anticancer agents in HER2-positive cells. Methods: The research project involved obtaining a series of compounds with potential dual inhibitory activity against HSP90 and HER2 by targeted organic synthesis, which was… More > Graphic Abstract

David Amilo^1,*, Khadijeh Sadri¹, Evren Hincal^1,2, Mohamed Hafez^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2189-2222, 2025, DOI:10.32604/cmes.2025.070298 - 26 November 2025

Abstract Breast cancer’s heterogeneous progression demands innovative tools for accurate prediction. We present a hybrid framework that integrates machine learning (ML) and fractional-order dynamics to predict tumor growth across diagnostic and temporal scales. On the Wisconsin Diagnostic Breast Cancer dataset, seven ML algorithms were evaluated, with deep neural networks (DNNs) achieving the highest accuracy (97.72%). Key morphological features (area, radius, texture, and concavity) were identified as top malignancy predictors, aligning with clinical intuition. Beyond static classification, we developed a fractional-order dynamical model using Caputo derivatives to capture memory-driven tumor progression. The model revealed clinically interpretable patterns: More >

Sihai Duan^1,2,#, Xiaoyan Li^3,#, Cailu Song³, Song Wu³, Yunyun Tang^3,4, Qing Bao^3,4, Na Li^3,*, Hailin Tang^3,*

Oncology Research, Vol.33, No.11, pp. 3543-3556, 2025, DOI:10.32604/or.2025.068292 - 22 October 2025

Abstract Objectives: Triple-negative breast cancer (TNBC) is the breast cancer subtype with the poorest prognosis. This study aimed to elucidate the molecular pathways through which isoliquiritigenin (ISL), a natural chalcone compound derived from licorice and other plant roots, targets interferon regulatory factor 5 (IRF5) in TNBC. Methods: TNBC cell lines were cultured and subjected to IRF5 knockdown using short hairpin RNA. Cell proliferation was assessed by cell counting kit-8 (CCK-8) assay and colony formation assays. Western blotting and quantitative reverse transcription polymerase chain reaction (RT-PCR) were employed to measure expression levels of IRF5, solute carrier family… More >

Botao Pan¹, Zirun Luo², Xiujuan Yang¹, Qingqing Liu³, Zhimin Yang^4,*, Chenglai Xia^1,3,*

Oncology Research, Vol.33, No.11, pp. 3557-3582, 2025, DOI:10.32604/or.2025.068119 - 22 October 2025

Abstract Objectives: Breast cancer is characterized by significant metabolic dysregulation, in which altered enzyme activity plays a central role. Malate dehydrogenase 2 (MDH2), a key enzyme in the tricarboxylic acid cycle, has been implicated in several malignancies, but its role in breast cancer tumorigenesis and progression remains unclear. We aimed to elucidate the oncogenic role of MDH2 in breast cancer and to evaluate its potential as a diagnostic, therapeutic, and prognostic biomarker. Methods: We combined in vitro cell-based assays with mouse xenograft models to systematically dissect how MDH2 governs breast cancer growth. In vitro, we assessed the effects… More >

Sudhakar Tummala^1,2,*, Sajjad Hussain Chauhdary³, Vikash Singh⁴, Roshan Kumar⁵, Seifedine Kadry⁶, Jungeun Kim^7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3585-3605, 2025, DOI:10.32604/cmes.2025.069731 - 30 September 2025

Abstract Lightweight deep learning models are increasingly required in resource-constrained environments such as mobile devices and the Internet of Medical Things (IoMT). Multi-head convolution with channel attention can facilitate learning activations relevant to different kernel sizes within a multi-head convolutional layer. Therefore, this study investigates the capability of novel lightweight models incorporating residual multi-head convolution with channel attention (ResMHCNN) blocks to classify medical images. We introduced three novel lightweight deep learning models (BT-Net, LCC-Net, and BC-Net) utilizing the ResMHCNN block as their backbone. These models were cross-validated and tested on three publicly available medical image datasets:… More >

Neha Raina¹, Radha Rani², Mahika Kanojia², Avril Mathias³, Keshav Raj Paudel^4,*, Ashish Garg⁵, Hardeep Singh Tuli⁶, A. T. M. Mijanur Rahman⁷, Vetriselvan Subramaniyan⁸, Madhu Gupta^2,*

Oncology Research, Vol.33, No.10, pp. 2787-2831, 2025, DOI:10.32604/or.2025.066624 - 26 September 2025

Abstract Breast cancer is among the most prevalent cancers in females globally and has the highest mortality rate. The emergence of pharmacologic resistance in breast cancer is a significant challenge for researchers in the pursuit of effective treatment. Investigations in cancer nanotechnology have been transformed by the advancement of smart polymers, lipids, and inorganic materials. Research is now being conducted in the field of innovative nano-pharmaceutical formulations aimed at enhancing the efficacy and durability of chemotherapy. Nanotechnology-based delivery systems are beneficial for combating breast cancer due to theranostic applications, augmented drug encapsulation, decreased degradation, and minimal… More >

Chuansheng Yang¹, Xiaoling Zhou^2,3, Ling Luo³, Zirun Luo⁴, Kaiming Fan^5,*, Chenglai Xia^2,3,*

Oncology Research, Vol.33, No.10, pp. 3065-3076, 2025, DOI:10.32604/or.2025.066058 - 26 September 2025

Abstract Objectives: Novel drug delivery systems have been designed to enhance local drug concentrations while reducing side effects conducive to improved breast cancer treatment outcomes. This study aimed to identify the anti-cancer function of zeolite imidazole ester-based material loaded with camptothecin nanoparticles. Methods: We utilized a zeolitic imidazolate backbone material to fabricate 9-hydroxycamptothecin nanoparticles and investigated their impact on breast cancer cell proliferation. Scanning electron microscopy and Fourier-transform infrared spectroscopy revealed changes in the carrier skeleton of the loaded 9-hydroxyl camptothecin, characterized by a reduction in surface smoothness, accompanied by slight collapses and folds on the… More >

Hailong Li^1,#, Wen Ouyang^2,#, Yiyin Long¹, Yun Peng¹, Ziyi Liu¹, Qi Zhou¹, Rong Xu^1,*, Wei Du^1,*

Oncology Research, Vol.33, No.9, pp. 2549-2571, 2025, DOI:10.32604/or.2025.065050 - 28 August 2025

Abstract Background: The study aimed to explore the clinical value of mitochondrial ribosomal protein L18 (MRPL18) in breast cancer. Methods: Multiple databases were used to validate the expression of MRPL18. The prognostic impact and predictive value of MRPL18 were evaluated by using predictive models. Protein-protein interaction (PPI) networks were constructed by using GeneMANIA. Enrichment analysis is used to explore the signaling pathway regulated by MRPL18. Cell counting kit-8 (CCK-8) assays, colony formation, migration assays, flow cytometry, and xenograft models were employed to evaluate the role of MRPL18 in tumor progression. The immune response of MRPL18 was More >

Xizhou Zhang^1,#, Zetao Zhang^1,#, Jianguang Lin², Jiarong Yi³, Xuxiazi Zou³, Jikun Feng³, Guangsheng Huang¹, Bingfeng Chen¹, Junxi Long¹, Fengjia Wu³, Feng Ye^3,*, Haoming Wu^1,*

Oncology Research, Vol.33, No.9, pp. 2529-2547, 2025, DOI:10.32604/or.2025.065029 - 28 August 2025

Abstract Background: Breast cancer remains a leading cause of morbidity and mortality among women worldwide, with significant geographic disparities in its impact. While human epidermal growth factor receptor 2 (HER2)-targeted therapies, such as trastuzumab, have improved outcomes for HER2-positive breast cancer, challenges like therapy resistance persist, highlighting the need for novel treatments. Recent developments in antibody-drug conjugates (ADCs), particularly disitamab vedotin (RC48), show promising efficacy in targeting both HER2-positive and HER2-low expression tumors, warranting further investigation through real-world studies to assess its broader clinical applicability. Method: This retrospective, multicenter observational study evaluated the real-world efficacy and… More >

Akari Fukumoto, Satoru Matsuda^*

Oncology Research, Vol.33, No.9, pp. 2205-2219, 2025, DOI:10.32604/or.2025.062810 - 28 August 2025

Abstract The non-coding RNAs (ncRNAs) are a family of single-stranded RNAs that have become recognized as crucial gene expression regulators in normal and cancer cell biology. The gut microbiota, which consists of several different bacteria, can actively contribute to the regulation of host metabolism, immunity, and inflammation. Roles of ncRNAs and gut microbiota could significantly interact with each other to regulate the growth of various types of cancer. In particular, a causal relationship among ncRNAs, gut microbiota, and immune cells has been shown for their potential importance in the development of breast cancer. Alteration of ncRNA More >