Oncology/Hematology

Integrated multi-omics analysis of prognostic model and immune microenvironment in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive malignancy originating from the epithelial lining of second-order bile ducts. Despite advances in immunotherapy, which underscore the pivotal roles of T-cell dynamics and tumor microenvironment (TME) remodeling in anti-tumor immunity, iCCA remains a clinical challenge due to its rapid progression. Consequently, there is a pressing...

Comment on "leveraging readily available clinical data with machine learning to predict first-line immunotherapy outcomes in non-small cell lung Cancer".

Transformer-based feature extraction approach for hematopoietic cancer subtype classification.

Accurate classification of hematopoietic cancer subtypes remains challenging due to the multipotent nature of hematopoietic cells and the absence of d...

Peripheral Nerves in Cancer: Regulatory Roles and Therapeutic Strategies.

Cancer neuroscience has emerged as a transformative frontier in oncology research, focusing on the interplay between cancer cells and the nervous syst...

Clinical validation of a unified data-driven respiratory motion correction technique in 18F-FDG PET/CT imaging of upper abdominal lesions: a real-world study.

PURPOSE: Respiratory motion (RM)-related artifacts significantly impact image quality and diagnostic accuracy in PET/CT imaging. This study aimed to p...

Deciphering the molecular landscape of Sjögren's disease, mucosa-associated lymphoid tissue lymphoma, and thyroid cancer: unraveling the complexities of disease mechanisms and diagnostic biomarkers.

BACKGROUND: Sjögren's disease (SjD), mucosa-associated lymphoid tissue lymphoma (MALT lymphoma), and thyroid cancer (THCA) are clinically distinct yet...

Machine learning integrating MRI and clinical features predicts early recurrence of hepatocellular carcinoma after resection.

This study aims to construct a robust artificial intelligence (AI) model to predict early recurrence of hepatocellular carcinoma (HCC) following surgi...

SERS-enabled immune monitoring: Decoding the tumor microenvironment for precision Cancer immunotherapy.

The tumor immune microenvironment (TME) is pivotal in regulating cancer initiation, progression, and therapeutic response. Despite major advances in i...

Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.

BACKGROUND: Precancerous gastric lesions (PLGC) are a critical stage in gastric cancer progression, where timely intervention can substantially reduce...

Smart Designer Nanozymes for Precision Cancer Therapy: Recent Advances and Prospects.

Nanozymes are enzyme-mimicking nanomaterials that are promising for diverse biomedical applications; they enable stable, tunable, and multifunctional ...

A prognostic signature of ferroptosis and lipid metabolism related genes predicts survival and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. There is an interplay between ferroptosis and lipid metabolism i...

Diagnostic performance of radiomics for detecting and characterising upper tract urothelial carcinoma (UTUC): a systematic review.

PURPOSE: Upper tract urothelial carcinoma (UTUC) is a rare but aggressive malignancy where accurate preoperative assessment of tumour grade and stage ...

Accessible cartilage tumor malignancy prediction via vision-language foundation model adaptation.

OBJECTIVE: To predict cartilage tumor malignancy from radiographic images combined with readily available non-imaging information based on a vision-la...

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite rising risks from metabolic and alcohol-related l...

Lactylation-driven gene signatures define breast cancer prognosis: a predictive model and insights into immune microenvironment dynamics.

BACKGROUND: Breast cancer is a leading cause of cancer-related mortality worldwide, with poor prognosis largely due to its invasive and metastatic nat...

Machine learning-based prediction of progression from idiopathic cytopenia of undetermined significance to myeloid malignancies.

Although the risk of progression varies, a subset of patients with idiopathic cytopenia of undetermined significance (ICUS) eventually develop myeloid...

Multiomics Profiling of T-cell Leukemia and Lymphoma Enables Targeted Therapeutic Discovery.

UNLABELLED: T-cell leukemias and lymphomas (TCL) form a heterogeneous group of rare and often aggressive malignancies. Because of the rarity and heter...

Cancer genome profiling in sarcomas: current status and future perspectives in Japan.

INTRODUCTION: Sarcomas are rare, molecularly diverse malignancies that challenge accurate diagnosis and effective therapy. Japan has implemented natio...

Single-cell profiling of immunogenic cell death in melanoma reveals prognostic signatures and therapeutic targets.

BACKGROUND: Cutaneous melanoma is one of the most aggressive forms of skin cancer, marked by rapid progression, early metastasis, and high resistance ...

Integrating multiomics data using a correlation based graph attention network for subtype classification in lower grade glioma.

Accurate classification of cancer subtypes is crucial for personalised therapies and targeted interventions. In this study, we propose BioGAT-LGG, a d...