Other Cancers

Deconstructing cancer in 3D: models, mechanisms, and personalized solutions.

Three-dimensional (3D) cancer models, notably patient-derived organoids (PDOs), address the critical limitations of traditional preclinical systems, including two-dimensional (2D) monolayer cultures and patient-derived xenografts (PDXs), by better recapitulating physiological tumor architecture and patient-specific heterogeneity, thereby revolutionizing oncology research. We chart the complementar...

Comprehensive benchmarking of deep learning architectures for multiclass histopathological classification of oral epithelial lesions.

BACKGROUND: Accurate histopathological differentiation of normal oral epithelium, oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC) is essential but remains time consuming and prone to inter-observer variability. Deep learning provides a powerful approach for automated analysis of histopathological images in digital pathology. This study comparatively evaluated multiple deep ...

Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases.

OBJECTIVE: The objective was to develop prognostic models that included convolutional neural networks (CNN) derived from 18F-DCFPyL (PSMA) PET imaging...

Integrating laboratory tests with FIGO staging using machine learning improves long-term prognostic assessment in endometrial cancer.

BACKGROUND: Limited access to robust biomarkers and regional disparities in standardized pathology and molecular profiling contribute to heterogeneous...

A decision-oriented framework for genomic testing across the prostate cancer continuum.

Genomic testing is now embedded in contemporary prostate cancer care, yet the clinical meaning of different genomic platforms varies substantially by ...

AI in esophageal cancer: advances, barriers to clinical translation, and perspectives for digital health.

BACKGROUND: Esophageal cancer (EC) remains one of the leading causes of cancer-related mortality worldwide. Accurate staging, treatment planning, and ...

A systemic immune signature stratifies early-stage breast cancer patients and reveals soluble IL-2RA and PD-1 as potential independent prognostic biomarkers.

BACKGROUND: Breast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. Systemic immune dysregulati...

Computational exploration of quercetin derivatives from Azadirachta indica leaf as threonine tyrosine kinase inhibitors for potential lung and pancreatic cancer treatment.

Lung and pancreatic adenocarcinomas account for substantial cancer-related mortality worldwide, with current therapeutic efficacy severely limited by ...

Understanding resistance in glioblastoma: insights into personalized and targeted therapeutic strategies.

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Despite combined treatments, including surgical removal...

Predicting Treatment Response After Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer.

OBJECTIVE: To develop a predictive model for pathological complete response (pCR) after total neoadjuvant therapy (TNT) to inform selection for watch-...

Decoding Occult Cervical Lymph Node Metastasis in Head and Neck Squamous Cell Carcinoma: From AI-Driven Multimodal Fusion to Clinical Translation.

PURPOSE OF REVIEW: This review examines the limitations of conventional macroscopic approaches in detecting occult cervical lymph node metastasis (OCL...

3D chromatin architecture-related genes orchestrate LUAD evolution and therapy resistance: insights from integrative machine learning and spatial single-cell mapping.

BACKGROUND: Lung adenocarcinoma (LUAD) is a prevalent and lethal malignancy. The three-dimensional (3D) chromatin architecture significantly influence...

Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial.

IMPORTANCE: Ocular surface malignancies pose risks to vision and survival yet are frequently misdiagnosed as benign lesions because of their subtle pr...

Advancing Gastrointestinal Cancer Risk Prediction With Patient-Centered Machine Learning: Machine Learning Modeling Study.

BACKGROUND: Gastrointestinal (GI) cancers are a significant health concern in South Korea. Recently, machine learning (ML) models have emerged as powe...

Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.

BACKGROUND: Severe COVID-19 is a global health concern despite continuous vaccination campaigns because current therapies, such as dexamethasone and r...

Novel technologies for gastrointestinal cancer detection: a systematic review and meta-analysis of diagnostic accuracy.

INTRODUCTION: Gastrointestinal (GI) cancers account for a quarter of all cancers and one-third of cancer-related deaths worldwide. Novel diagnostic ap...

Diagnostic yield and cost of three-level H&E sectioning in prostate biopsies.

AIM: The traditional three-level H&E sectioning protocol for prostate biopsies was developed for ultrasound-guided systematic sampling and predates le...

Multi-scale computational analysis of monoacylglycerol lipase inhibition as a new therapeutic strategy for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains one of the most critical global health challenges, particularly in connection to metabolically linked diseases ...

Comprehensive multi-omics analysis identifies cancer subtypes and prognostic signatures of hepatitis B virus-associated hepatocellular carcinoma.

Hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) is a heterogeneous malignancy with poor prognosis, necessitating refined classificatio...

Multi-omic biomarkers of neoadjuvant treatment response in rectal cancer: A narrative review.

BACKGROUND: Neoadjuvant treatment response in rectal cancer is highly heterogeneous, complicating patient selection for organ-preservation strategies....