Xiaoqing Jiang^1,2,#, Pengchong Li^1,2,#, Hongchuang Liu^1,2, Wenjie Dong^1,2, Wenjing Liu^1,2, Di Wu^1,2, Jianping Xue^1,2, Fenglan Zhao^1,2,*, Yongbo Duan^1,2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074434 - 30 January 2026

Abstract As its tuberous alkaloids induce valuable pharmacological effects, Pinellia ternata has considerable clinical value. However, its production currently fails to meet its demand. In vitro microtuber culture, combined with salicylic acid (SA) elicitation, may provide an effective alternative to traditional field production. In this study, an in vitro P. ternata microtuber induction system was developed and used to evaluate SA-induced elicitation of alkaloid accumulation. The quality of in vitro microtubers was assessed by total alkaloid measurement, a cytotoxicity assay, and transcriptomic analysis. With or without SA treatment, P. ternata microtuber induction was achieved within 60 d using petiole-derived explants, with… More >

Nuh Azginoglu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075834 - 29 January 2026

Abstract Breast cancer screening programs rely heavily on mammography for early detection; however, diagnostic performance is strongly affected by inter-reader variability, breast density, and the limitations of conventional computer-aided detection systems. Recent advances in deep learning have enabled more robust and scalable solutions for large-scale screening, yet a systematic comparison of modern object detection architectures on nationally representative datasets remains limited. This study presents a comprehensive quantitative comparison of prominent deep learning–based object detection architectures for Artificial Intelligence-assisted mammography analysis using the MammosighTR dataset, developed within the Turkish National Breast Cancer Screening Program. The dataset comprises… More >

Oncology Research Editorial Office

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.078459 - 19 January 2026

Abstract This article has no abstract. More >

Min Hee Kim¹, Boyoon Huh¹, Joo-Won Park^1,*, Woo-Jae Park^2,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.071523 - 19 January 2026

Abstract Breast cancer is one of the most prevalent malignancies among women and comprises a heterogeneous spectrum of molecular subtypes with distinct biological behaviors. Among various regulatory molecules, sphingolipids play pivotal roles in dynamically modulating fundamental cellular processes such as proliferation, apoptosis, and metastasis through metabolic interconversions, including phosphorylation, glycosylation, and the generation of sphingosine-1-phosphate. This review aims to elucidate the mechanisms through which sphingolipid metabolism orchestrates cancer cell fate and drives breast cancer progression. Particular emphasis is placed on the balance between proapoptotic ceramides and pro-survival metabolites, such as sphingosine-1-phosphate, which collectively influence tumor growth More >

Shail Rakesh Modi, Terrick Andey^*, George Acquaah-Mensah^*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070793 - 19 January 2026

Abstract Objectives: The current treatment options and therapeutic targets for triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer (BrCA), are limited. This study aimed to identify novel biomarkers and transcriptional regulatory networks (TRN) inherent in TNBC samples. Methods: We analyzed pan-cancer BrCA datasets from The Cancer Genome Atlas (TCGA) to compare triple-positive breast cancer (TPBC) with TNBC. TRN algorithms and virtual inference of protein-enriched regulon (VIPER) were used to identify master regulators and their target genes. Utilizing TNBC cells (MDA-MB-231 and MDA-MB-468), we validated the relationship of nuclear factor erythroid 2-like 3 (NFE2L3) and… More > Graphic Abstract

Hanifah Rahmi Fajrin^1,2, Se Dong Min^1,3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072609 - 12 January 2026

Abstract Accurate segmentation of breast cancer in mammogram images plays a critical role in early diagnosis and treatment planning. As research in this domain continues to expand, various segmentation techniques have been proposed across classical image processing, machine learning (ML), deep learning (DL), and hybrid/ensemble models. This study conducts a systematic literature review using the PRISMA methodology, analyzing 57 selected articles to explore how these methods have evolved and been applied. The review highlights the strengths and limitations of each approach, identifies commonly used public datasets, and observes emerging trends in model integration and clinical relevance. More >

Chee Chin Lim^1,2,*, Hui Wen Tiu¹, Qi Wei Oung^1,3, Chiew Chea Lau⁴, Xiao Jian Tan^2,5

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.070468 - 12 January 2026

Abstract Breast cancer remains one of the leading causes of cancer mortality world-wide, with accurate molecular subtyping is critical for guiding treatment and improving patient outcomes. Traditional molecular subtyping via immuno-histochemistry (IHC) test is invasive, time-consuming, and may not fully represent tumor heterogeneity. This study proposes a non-invasive approach using digital mammography images and deep learning algorithm for classifying breast cancer molecular subtypes. Four pretrained models, including two Convolutional Neural Networks (MobileNet_V3_Large and VGG-16) and two Vision Transformers (ViT_B_16 and ViT_Base_Patch16_Clip_224) were fine-tuned to classify images into HER2-enriched, Luminal, Normal-like, and Triple Negative subtypes. Hyperparameter tuning,… More >

Keiko Yanagihara^1,*, Masato Yoshida², Kensaku Awaji², Tamami Yamakawa¹, Sena Kato¹, Miki Tamura¹, Koji Nagata³

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.073891 - 30 December 2025

Abstract Background: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have transformed the management of hormone receptor–positive/HER2–negative (HR+/HER2–) advanced breast cancer, yet evidence for elderly or poor-performance patients remains limited. This study examined real-world outcomes of palbociclib plus endocrine therapy in Asian patients, with additional subgroup analyses by age and performance status. Methods: We retrospectively analyzed 46 consecutive Asian patients with recurrent or de novo HR+/HER2− breast cancer treated with first-line palbociclib plus ET between April 2021 and March 2025. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), disease control rate (DCR), and safety.… More >

Sarra B. Shakartalla^1,2,3, Iman M. Talaat^1,2,4,*, Nival Ali¹, Shahenaz S. Salih^1,5, Zainab M. Al Shareef^1,2, Noura Alkhayyal⁶, Riyad Bendardaf^2,7,*, Sameh S. M. Soliman^1,8,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070808 - 30 December 2025

Abstract Objectives: Breast cancer (BC) is the leading cause of cancer-related mortality in women, largely due to metastasis. This study aims to explore the role of purine nucleoside phosphorylase (PNP), a key enzyme in purine metabolism, in the aggressiveness and metastatic behavior of BC. Methods: A comprehensive analysis was performed using in silico transcriptomic data (n = 2509 patients), immunohistochemical profiling of BC tissues (n = 103), and validation through western blotting in multiple BC cell lines. Gene expression and survival analyses were conducted using Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and… More >

Jing Cai^1,#, Haoyun Zhu^1,#, Weiling Guo¹, Ting Huang¹, Pangzhou Chen^1,2, Wen Zhou¹, Ziyun Guan^1,3,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.069902 - 30 December 2025

Abstract Background: Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity. Current preclinical models, however, are inadequate for predicting individual patient responses towards different drugs. This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations. Methods: Tumor and adjacent tissues from female breast cancer patients were collected during surgery. Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models. The obtained patient-derived conditional reprogramming breast cancer (CRBC) cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres… More >