Other Cancers

Delta radiomics-based nomogram for preoperative prediction vessels encapsulating tumor clusters (VETC) and prognosis in hepatocellular carcinoma using dynamic contrast-enhanced CT.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) serve as a crucial adverse prognostic indicator in hepatocellular carcinoma (HCC). This study aimed to develop and validate a Delta radiomics-based nomogram model on dynamic contrast-enhanced CT (DCE-CT) to predict VETC status and patient prognosis in HCC. METHODS: A cohort of 222 patients from two centers with HCC undergoing DCE-CT scans and...

UHRF2 related to sumoylation : assessment of its role in immune suppression and therapeutic potential in colorectal cancer.

SUMOylation is a critical post-translational modification of proteins. However, the roles of SUMOylation-related genes in regulating the tumor immune microenvironment and their potential as therapeutic targets in CRC remain unclear. We integrated transcriptomic data from TCGA and GEO to identify 200 SUMOylation-related genes associated with prognosis. Among these, 58 genes exhibiting significant s...

Annotation-free prediction of immunotherapy response in melanoma using single-cell transcriptomic data.

Immune checkpoint inhibitors (ICIs) have transformed the advanced melanoma treatment landscape; however, a subset of patients achieve durable response...

Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease.

BACKGROUND: Radiation pneumonitis (RP) is a serious complication in lung cancer patients with pre-existing interstitial lung disease (ILD) undergoing ...

Computer-Aided Detection-Assisted Colonoscopy Teaches Gaze to Improve Adenoma Detection in First-Year Gastroenterology Fellows.

BACKGROUND AND AIMS: The impact of computer-aided detection (CADe)-assisted colonoscopy on gastroenterology fellow trainees remains incompletely defin...

Harnessing Hitchhikers: Outer Membrane Vesicles Leading the Way in Advanced Cancer Therapeutics and Diagnostic- A Review.

Cancer therapy is increasingly shaped by delivery platforms designed to overcome the limitations of conventional chemotherapy and radiotherapy. Among ...

Deep Learning-Enhanced Biomarker Interpretation on Cytology Cell Blocks - Foundations and Emerging Opportunities in Spatial Pathobiology.

Cytology cell block specimens are essential diagnostic materials in patients with advanced-stage malignancy and often represent the only available sub...

Synergizing Artificial Intelligence with In Vivo CAR-T Cell Generation: A New Paradigm for Democratized Immunotherapy.

In vivo CAR-T cell generation represents a paradigm shift in immunotherapy by transitioning the production of chimeric antigen receptor (CAR) T cells ...

Unlocking the Role of Exosomal ncRNAs in Colorectal Cancer: Molecular Insights and Clinical Promise.

Colorectal cancer (CRC) continues to be a substantial cause of cancer-related fatality globally, necessitating improved diagnostic and therapeutic str...

CXCL9 as a key feature for deep learning-based immune subtyping and prediction of immune checkpoint blockade response in triple-negative breast cancer.

BACKGROUND: Immune checkpoint blockade (ICB) therapy has provided a promising treatment option for patients with triple-negative breast cancer (TNBC)....

Current Status and Future Perspective for Bladder Cancer MR Imaging and the Vesical Imaging-Reporting and Data System (VI-RADS) in Japan: Challenges and Solutions.

Bladder cancer carries one of the highest lifetime costs among malignancies, and accurate distinction between non-muscle-invasive and muscle-invasive ...

CystoDS: a multiclass endoscopy image dataset for artificial intelligence-assisted bladder cancer detection.

Cystoscopy is a common endoscopic procedure used for the visual inspection of the lower urinary tract, particularly for the detection and surveillance...

Radiopharmaceuticals: Status, Regulatory Landscape and Future Perspective.

Radiopharmaceuticals are biologically active molecules labeled with radionuclides that have advanced the possibility of the nuclear medicine. They sup...

Unveiling the TP5 dual binding mechanism and structure-based search for potential dual inhibitors of tubulin and PD-L1.

The dual inhibition of microtubule dynamics and immune checkpoint signaling represents a promising strategy in cancer therapy by simultaneously disrup...

Research progress of machine learning applications in gastric cancer diagnosis and therapy.

Gastric cancer (GC), a malignant neoplasm originating from the gastric mucosal epithelium, represents one of the most prevalent cancers worldwide. Ear...

Identification of Gene Signatures Differentiating Cancer from Normal Tissues Across Histological Classifications of Gastric Adenocarcinoma via Machine Learning Methods.

Gastric adenocarcinoma is a significant global health concern. Among the myriad histologic classification methods for this cancer, the Lauren classifi...

Deep learning-assisted tumor radiomic dynamics on MRI predict pathological complete response in HCC undergoing immune-based therapy followed by hepatectomy.

BACKGROUND AIMS: Pathological complete response (pCR) following conversion therapy for initially unresectable hepatocellular carcinoma (uHCC) remains ...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key biomarker for assessing the risk of gastric cancer. H...

CMAF-Net: cross-modal attention fusion with information-theoretic regularization for imbalanced breast cancer histopathology.

Breast cancer diagnosis from histopathology images remains challenging due to two intertwined factors: severe class imbalance, where malignant cases r...

A Review on Image Processing and Fractal Analysis in Oral Potentially Malignant Disorders.

AIM: The clinical evaluation of patients with oral potentially malignant disorders is primarily based on physical examination and observable clinical ...