Other Cancers

A metabolic-immune subtype of breast cancer defined by G6PD and SHMT2: From single‑cell dissection to dual-targeted therapy.

Breast cancer heterogeneity limits the precision of current prognostic and therapeutic strategies, underscoring the need for molecular frameworks that capture underlying metabolic drivers. Here, we systematically dissected the landscape of amino acid metabolism (AAM) in breast cancer through integrated bulk and single‑cell transcriptomics, machine learning, in silico knockout, and computational dr...

AI-driven identification of a selective dual function inhibitor blocking HK2 activity and HK2-VDAC1 interaction displaying enhanced anticancer efficacy under hypoxia.

Selective inhibition of hexokinase 2 (HK2) represents a promising therapeutic strategy due to the pivotal role of HK2 in the Warburg effect, enhancement of glycolysis and anti-apoptosis via HK2-Voltage-Dependent Anion Channel 1 (VDAC1) protein-protein interaction. Moreover, HK2 initiates glycolysis to generate lactate, hence this central enzyme can be pharmacologically targeted to enhance therapy ...

Endothelial SMAD1-MCAM axis facilitates sunitinib resistance and progression of clear cell renal cell carcinoma via LAMB1-ITGB1 signaling.

Clear cell renal cell carcinoma (ccRCC) is characterized by high metastatic potential and frequent resistance to conventional therapies, highlighting ...

IDH enzyme inhibition in cancer therapy: mechanisms, mutational insights, and effects of IDH inhibitors in glioma, acute myeloid leukemia and chondrosarcoma.

Isocitrate dehydrogenase (IDH) enzymes have recently emerged as a highly promising target for therapeutic intervention in cancer treatment. Mutations ...

Integrative spatial profiling pipeline for determining TME architectures in archival clinical specimens using CmTSA superplex technology.

The tumor microenvironment (TME) comprises diverse cellular components that spatially interact to form distinct functional niches (FNs). Profiling the...

A lightweight CNN for enhanced non-small cell lung cancer classification using CT scan image.

Lung cancer is a leading cause of cancer-related mortality worldwide, and its early and accurate detection is critical for improving patient outcomes....

Leveraging proteomics and machine learning for mechanism and biomarker discovery on glioma progression and transformation: from LGG to GBM.

BACKGROUND: Glioma was the most common malignant tumor of the central nervous system in adults. Low-grade gliomas (LGGs) have a potential of grade pro...

Intratumoral and peritumoral radiomics-based machine learning models for the postoperative survival prediction in esophageal squamous cell carcinoma.

OBJECTIVES: This study aimed to develop and validate machine learning (ML) models to predict survival following oesophagectomy in oesophageal squamous...

Deep learning with limited data: a transfer learning approach for transcriptomic survival prediction.

BACKGROUND: Deep neural networks (DNNs) are promising for analyzing high-dimensional transcriptomic data in cancer research but are limited by data sc...

Radiomics-Based machine learning for preoperative prediction of Large-Number central lymph node metastasis in papillary thyroid carcinoma.

Machine learning-based prognostic prediction for cutaneous malignant melanoma patient survival.

BACKGROUND: Cutaneous malignant melanoma (CMM) is a highly malignant tumor that necessitates early diagnosis and precise survival prediction. The deve...

Pediatric SleepNet: A Deep Learning Network for Reliable Pediatric Sleep Staging Across Developmental Stages.

STUDY OBJECTIVES: Manual sleep staging in pediatric populations is challenging due to developmental variability and limited scoring consistency, espec...

Clinical Validation of AI-assisted Evaluation of Indeterminate Biliary Strictures in Digital-Single Operator Cholangioscopy: a Transcontinental Multicentric Study.

INTRODUCTION: Biliary strictures (BS) are a significant challenge, with malignant strictures frequently diagnosed at advanced stages, limiting curativ...

Integrated and Ultrafast Multiomics Sample Preparation Workflow for Screening Biomarker Panel of Platelet Biomolecules for Early Diagnosis of HCC.

Early detection of hepatocellular carcinoma (HCC) remains a persistent worldwide challenge. Owing to its minimal invasiveness, liquid biopsy has emerg...

Deciphering lncRNA-disease associations based on multi-representation fusion and boosting with Gaussian process.

LncRNA-disease association (LDA) identification can provide valuable insights for understanding disease pathogenesis. Existing most deep learning-base...

Machine learning and logistic regression in estimating survival in patients with high-malignant deep-seated soft tissue sarcomas: development and analysis based on a population-based retrospective cohort.

BACKGROUND AND PURPOSE:  Soft tissue sarcomas are a heterogeneous group of malignant tumors with a high risk of metastasis, primarily to the lungs, ma...

Quantification of Ki-67 labeling index in pediatric brain tumor immunohistochemistry images.

Quantification of the Kiel 67 (Ki-67) labeling index (LI) is critical for assessing proliferation and prognosis in tumors but manual scoring remains a...

AGPAT3 reshapes tumor cell vulnerability to IFNγ-mediated ferroptosis and enhances immunotherapy efficacy through lipid remodeling.

BACKGROUND: Ferroptosis plays a critical role in immune regulation and tumor microenvironment remodeling. However, its therapeutic potential in enhanc...

[Discovery of multi-omics-based biomarkers for immune-related adverse events: precision management with 3D-SPACE].

This article provides a systematic review of the advances in the precise diagnosis and management of immune-related adverse events (irAEs) induced by ...

Accuracy and reproducibility of tumor size measurement using a deep-learning-based CDSS in resected lung cancer.

PURPOSE: MONCAD LCT is a commercially available deep-learning based clinical decision support system (CDSS) for lung screening CT. The aim of this mul...