Other Cancers

ALDH18A1 silencing inhibits lung adenocarcinoma progression through mitochondrial dysfunction and PPAR signaling pathway activation.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a prevalent malignant tumor characterized by a dismal prognosis. This study aimed to reveal potential mitochondria-related biomarkers and explore possible mechanisms. METHODS: Mitochondria-related differentially expressed genes (mitoDEGs) were identified by intersecting LUAD-associated DEGs with mitochondria-associated genes. Hub mitoDEGs were determi...

Predicting sentinel lymph node metastasis in breast cancer using an interpretable machine learning approach based on multi-domain clinical features.

BACKGROUND: Accurate identification of sentinel lymph node (SLN) status is essential for surgical and adjuvant therapy decisions in breast cancer. Although sentinel lymph node biopsy (SLNB) is less invasive than axillary lymph node dissection, it still exposes node-negative patients to unnecessary surgical risks. Most existing models predicting lymph node status in breast cancer rely on a limited ...

A multimodal deep learning classifier for prediction of HER2-low expression in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive molecular subtype. With the new definition of HER2-low status and the availability o...

Dismantling the TGF-β Axis: A Critical Transition from Occupancy-based Kinase Inhibitors to Event-driven Degraders.

The TGF-β signaling pathway plays a dual role in cancer, acting as both a tumor suppressor and a potent driver of metastasis and immune evasion. Tradi...

Interpretable machine learning model of contrast-enhanced CT radiomics for predicting post-BCG recurrence in high-grade non-muscle-invasive bladder cancer.

BACKGROUND AND PURPOSE: While intravesical Bacillus Calmette-Guérin Vaccine (BCG) instillation remains standard adjuvant therapy for high-grade non-mu...

Targeting galactose metabolic reprogramming overcomes immunotherapy resistance in KRAS-mutant lung adenocarcinoma: Integrative multi-omics and machine learning approaches.

BACKGROUND: KRAS-mutant lung adenocarcinoma (LUAD) is associated with aggressive phenotypes and therapy resistance, which highlights an urgent need to...

Precision lung cancer classification using convolutional neural networks with enhanced image pre-processing and model optimization.

Among various types of cancers, lung cancer causes the highest mortality globally, necessitating prompt diagnosis for effective treatment. Traditional...

Multiscale systems modelling of communication networks in brain metastasis.

Brain metastasis remains a major clinical challenge because intracranial progression and therapeutic resistance arise not only from tumour-intrinsic p...

AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.

BACKGROUND: Neoantigens-tumor-specific peptides generated by somatic mutations-are central targets of effective anticancer T cell immunity and underpi...

Artificial intelligence-detected HER2 strong-positive tumor proportion predicts FISH positivity and treatment response in breast cancer.

Human epidermal growth factor receptor 2 (HER2)-targeted therapies have revolutionized breast cancer treatment, necessitating standardized HER2 testin...

Machine Learning-Assisted SERS Quantification of Sialylated Alpha-Fetoprotein: From Single-Cell Analysis to Hepatocellular Carcinoma Risk Assessment.

Sialylated alpha-fetoprotein (sAFP) is a very potential marker for the pathogenesis exploration and clinical assessment of hepatocellular carcinoma (H...

Vascular reprogramming in cancer: engineering the tumor microenvironment.

Tumor vasculature has traditionally been viewed as structurally and functionally abnormal and, therefore, is primarily targeted for inhibition. Howeve...

From tumor-centric to ecosystem-based hypotheses in brain tumor research and care: Proceedings from The second Brain Tumor Meeting by the Sea organized by Julie Gavard and Eric Chevet, held in St Malo (France), 23-25 March 2026.

Brain tumors remain among the most lethal cancers, largely due to their remarkable heterogeneity, plasticity, and resistance to therapy. The second Br...

Integrative single-cell and multi-omics analysis of ZBTB21-mediated serine metabolism in colorectal cancer: from metabolic reprogramming to immune microenvironment modulation.

BACKGROUND: Colorectal cancer (CRC) exhibits pronounced biological diversity, a feature increasingly attributed to alterations in cellular metabolic r...

Macrophage heterogeneity in breast cancer microenvironment and development of a prognostic model: exploring TFF1 as a novel therapeutic target.

BACKGROUNDS: Breast cancer (BRCA) represents the most prevalent malignancy globally, with projections indicating 3.2 million new cases anticipated by ...

Intraoperative technological advances and new frontiers in precision glioma surgery.

BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by their infiltrative nature, proximity to eloquent bra...

Identification of exosome-related genes signature based on bioinformatics and machine learning for prognostic prediction in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory ves...

A novel prognostic zinc finger gene model for hepatocellular carcinoma via machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly lethal malignancy with poor prognosis, and effective biomarkers for predicting immunotherapy re...

Single-cell spatial landscape of aggrephagy activity stratifies hepatocellular carcinoma neutrophils and delivers a 5-gene diagnostic panel for patient stratification.

BACKGROUND: Hepatocellular carcinoma (LIHC) features a complex tumor microenvironment (TME) where tumor-associated neutrophils (TANs) show significant...

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Transarterial radioembolization (TARE) is increasingly used for patients with hepatocellular carcinoma (HCC) across Barcelon...