Other Cancers

Integrative multi-omics analysis reveals metabolic dysfunction signatures as critical determinants of prostate cancer prognosis and immunosuppressive microenvironments.

BACKGROUND: Metabolic reprogramming is a hallmark of cancer. However, the precise mechanisms by which specific metabolic pathways drive prostate cancer (PCa) progression and shape the tumor microenvironment remain poorly defined. METHODS: A machine learning-derived Metabolic Dysfunction Signature (MODS) was developed and validated as a prognostic model. Its clinical relevance was established throu...

Multi-omics profiling reveals cholic acid-mediated immunosuppression driven by peritumoral ductular reactions in hepatocellular carcinoma.

Hepatocellular carcinoma remains a leading cause of cancer mortality worldwide, with peritumoral microenvironment interactions playing a critical role in disease progression. This multi-omics study employed artificial intelligence-pathology, single-nucleus multi-omics, spatial transcriptomics, and metabolomics to characterize peritumoral ductular reactions. Ductular reaction scores strongly predic...

Di-(2-ethylhexyl) terephthalate promotes breast cancer progression: Multi-omics integrated experimental validation.

Di-(2-ethylhexyl) terephthalate (DOTP), as an alternative to phthalate plasticizers, has been widely used in sensitive fields such as food packaging a...

18F-FDG PET/CT and receptor-positive circulating tumor cells-based machine learning model for predicting poorly differentiated lung adenocarcinoma.

INTRODUCTION: This study aimed to develop and validate a machine learning model that integrates radiomic features from 2-[18F]fluoro-2-deoxy-D-glucose...

Application of a Natural Language Processing Framework for Data Extraction From Pathology Reports Across Multiple Cancer Types.

BACKGROUND: Pathological reports provide comprehensive insights into the clinical and pathological features of different cancer types. However, extrac...

Cluster-Based MR Radiomics Model for Predicting Induction Chemotherapy Response in Nasopharyngeal Carcinoma.

RATIONALE AND OBJECTIVES: To develop a cluster-specific magnetic resonance (MR) radiomics model for predicting induction chemotherapy (ICT) response i...

Prediction of Neoadjuvant Chemotherapy Efficacy for Locally Advanced Nasopharyngeal Carcinoma Using MRI-Based Deep Learning Features Combined with Vision Transformer.

RATIONALE AND OBJECTIVES: Predicting neoadjuvant chemotherapy (NACT) efficacy is vital for advanced nasopharyngeal carcinoma (LA-NPC) management. Exis...

A Deep Learning Framework Integrating Tumor Microenvironmental Features Accurately Predicts Multiple Driver Gene Mutations in Lung Cancer Pathology Images.

UNLABELLED: Deep learning (DL) has the potential to enable the prediction of gene mutations directly from routine histopathology slides in lung cancer...

Integration of Short- and Long-Read RNA Sequencing Enables the Discovery of Circular RNAs.

UNLABELLED: Circular RNAs (circRNA) are associated with crucial hallmarks of tumorigenesis. Select circRNAs contain circular open reading frames (cORF...

Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response.

UNLABELLED: Multiplexed imaging of tissues is an approach that holds promise for improving early detection, diagnosis, and treatment of cancer. In thi...

Deep Learning-Derived Sarcopenia Marker Predicts Benefit from Anti-EGFR Therapy in Patients with RAS Wild-type Metastatic Colorectal Cancer.

PURPOSE: The benefit of treatment intensification in metastatic colorectal cancer (mCRC) may be influenced by host-related factors that are not accoun...

Computational exploration and discovery of dual EGFR-CDK2 kinase inhibitors: AI-ML powered bioisosteric design, 3D QSAR, docking, DFT and ADMET analysis of novel phthalimide derivatives.

AI-ML approaches emerged as transformative technologies in cancer drug discovery by accelerating the target identification and lead optimization. EGFR...

Deep learning-based identification and maturation assessment of the zygomaticomaxillary suture in cone-beam computed tomography images.

OBJECTIVE: This study addresses maxillary deficiency management by developing a deep learning-based system for zygomaticomaxillary suture assessment. ...

A CT radiomics signature enables risk stratification and survival prediction in colorectal liver metastases.

Colorectal liver metastases (CRLM) represent a major clinical challenge because outcomes after hepatic resection vary widely between patients. Preoper...

Preoperative prediction of metachronous liver metastasis in colorectal cancer using a deep learning-based radiomics model with automatic segmentation: a multicenter study.

OBJECTIVES: To develop and validate an integrated clinical-radiomics nomogram predicting the risk of metachronous liver metastasis (MLM) in patients w...

Developing a Metabolic-Associated Prognostic Index for Risk Stratification and Therapeutic Guidance in Stage I Lung Adenocarcinoma via Multiomics Analysis.

PURPOSE: Early-stage lung adenocarcinoma (LUAD) exhibits substantial clinical heterogeneity that is not fully explained by TNM staging, highlighting t...

Machine Learning-Driven Risk Stratification and Adjuvant Treatment Guidance in Oral Cavity Cancer.

PURPOSE: To develop and validate machine learning (ML) models for postoperative risk stratification in oral cavity squamous cell carcinoma (OCSCC) and...

From imaging to omics: deep learning is bridging MRI and liquid biopsy in bone tumor diagnosis.

Bone tumors such as osteosarcoma and Ewing sarcoma remain among the most challenging cancers to diagnose and monitor because of their biological heter...

Machine Learning Reveals the Association Between Gene Expression and Immune Infiltration in Colorectal Cancer: A Comprehensive Study From Single-Cell to Survival Analysis.

Colorectal cancer (CRC) is one of the most common causes of cancer mortality globally. Analysis of immune cell infiltration patterns in the tumour mic...

Advanced Drug Delivery Strategies for Overcoming Biological Barriers: Tumor Microenvironment and Blood-Brain Barrier.

Therapeutic efficacy for malignancies and neurological disorders is fundamentally restricted by biological barriers, particularly the complex tumor mi...