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 >

Zhun Yu^1,2, Jie Wang^1,2, Guoping Xu^1,2,*

Oncology Research, Vol.33, No.8, pp. 2013-2035, 2025, DOI:10.32604/or.2025.061757 - 18 July 2025

Abstract Objectives: Triple-negative breast cancer (TNBC) presents a major treatment challenge due to its aggressive behavior. The dysfunction of the Golgi apparatus (GA) contributes to the development of various cancers. This study aimed to utilize GA-related genes (GARGs) to forecast the prognosis and immune profile of TNBC. Methods: The data were downloaded from The Cancer Genome Atlas (TCGA) database, including 175 TNBC and 99 healthy samples. The differentially expressed GARGs (DEGARGs) were analyzed using the TCGA biolinks package. The patients with TNBC were classified into two clusters utilizing the ConsensusClusterPlus package according to prognosis-related DEGARGs, followed by… More >

Isra Mohammed¹, Mohamed Elhafiz M. Musa², Murtada K. Elbashir^3,*, Ayman Mohamed Mostafa³, Amin Ibrahim Adam⁴, Mahmood A. Mahmood³, Areeg S. Faggad⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3749-3763, 2025, DOI:10.32604/cmc.2025.063880 - 03 July 2025

Abstract Sonic Hedgehog Medulloblastoma (SHH-MB) is one of the four primary molecular subgroups of Medulloblastoma. It is estimated to be responsible for nearly one-third of all MB cases. Using transcriptomic and DNA methylation profiling techniques, new developments in this field determined four molecular subtypes for SHH-MB. SHH-MB subtypes show distinct DNA methylation patterns that allow their discrimination from overlapping subtypes and predict clinical outcomes. Class overlapping occurs when two or more classes share common features, making it difficult to distinguish them as separate. Using the DNA methylation dataset, a novel classification technique is presented to address… More >

HONGMIN CAO^1,#,*, YING XUE^2,#, FEI WANG¹, GUANGYAO LI¹, YULAN ZHEN¹, JINGWEN GUO¹

BIOCELL, Vol.48, No.3, pp. 473-490, 2024, DOI:10.32604/biocell.2024.048946 - 15 March 2024

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… More > Graphic Abstract

XUEFENG WANG^1,#, SICONG JIANG^2,#, XINHONG ZHOU³, XIAOFENG WANG⁴, LAN LI⁵, JIANJUN TANG^1,*

Oncology Research, Vol.31, No.5, pp. 697-714, 2023, DOI:10.32604/or.2023.029458 - 21 July 2023

Abstract Background: Pancreatic cancer is associated with high mortality and is one of the most aggressive of malignancies, but studies have not fully evaluated its molecular subtypes, prognosis and response to immunotherapy of different subtypes. The purpose of this study was to explore the molecular subtypes and the key genes associated with the prognosis of pancreas cancer patients and study the clinical phenotype, prognosis and response to immunotherapy using single-cell seq data and bulk RNA seq data, and data retrieved from GEO and TCGA databases. Methods: Single-cell seq data and bioinformatics methods were used in this… More >

Xujie Zhou^1,2,3,#, Yuting Sang^1,3,#, Jiajian Chen^1,3, Miao Mo^3,4, Jianjing Hou^1,3, Benlong Yang^1,3,*, Jiong Wu^1,2,3,*

Oncologie, Vol.24, No.3, pp. 451-469, 2022, DOI:10.32604/oncologie.2022.025226 - 19 September 2022

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… More >