Other Cancers

Development and validation of pathomics signature for predicting prognosis of advanced high-grade serous ovarian carcinoma patients after platinum-based chemotherapy.

In patients with advanced high-grade serous ovarian carcinoma (HGSOC), the standard treatment typically involves platinum-based chemotherapy after debulking surgery. However, the prognosis of patients following platinum-based chemotherapy varies, and known prognostic factors do not fully explain this variability. Therefore, developing an accurate and validated prognostic tool is essential. This st...

Ultrasound-based multiregional radiomics nomogram for predicting recurrence in HER2-positive breast cancer.

PURPOSE: Accurate prediction of recurrence risk is crucial for personalizing therapy in human epidermal growth factor receptor 2-positive (HER2-positive) breast cancer. We aimed to develop an interpretable machine learning model integrating multimodal data to address this need. METHODS: This retrospective study enrolled 148 patients with human epidermal growth factor receptor 2 (HER2)-positive bre...

Single-cell transcriptomics and machine learning unveil liquid-liquid phase separation-related biomarkers in HPV-positive cervical cancer.

BACKGROUND: Liquid-liquid phase separation (LLPS) dysregulation is a key driver of oncogenesis, yet its specific role in HPV-positive cervical cancer ...

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment options for resectable non-small cell lung cancer ...

Multimodal Artificial Intelligence Prediction of Abiraterone Efficacy in Two STAMPEDE Phase 3 Trials of Non-Metastatic Very High-Risk Prostate Cancer.

BACKGROUND: Long-term androgen deprivation therapy (LT-ADT) with radiotherapy is standard-of-care for high-risk localized prostate cancer, with abirat...

Machine Learning-Guided Survival Prediction and Treatment Sequencing in Advanced Soft Tissue Sarcoma Beyond Second-Line Therapy: A Retrospective Cohort Study.

INTRODUCTION: Evidence guiding the optimal sequencing of later-line systemic therapy in advanced soft tissue sarcoma (STS) remains limited. The aim of...

Artificial intelligence in prostate cancer imaging: A mini-review of current applications and future directions.

This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and fu...

Hyperspectral Imaging for Breast-Conserving Surgery Margin Assessment: A Systematic Review.

CONTEXT.—: Breast-conserving surgery (BCS) offers comparable overall survival rates to mastectomy. However, 14% to 37% of cases require re-excision ow...

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow.

Targeting the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) represents a promising strategy to overcome resistance in p...

Deep learning based on multiparametric MRI for differentiating benign from malignant PI-RADS 3 prostate lesions: a dual-center study.

To address the diagnostic challenge of indeterminate PI-RADS 3 prostate lesions, we developed a non-invasive deep learning radiomics model using multi...

The SALV-Dataset Registry: An Expertly Curated Digital Clinicopathological Dataset for Salivary Gland Tumor Research and AI-Assisted Diagnostic Tools.

UNLABELLED: Salivary gland tumors are rare and morphologically diverse, posing both diagnostic and scientific challenges. This study presents the firs...

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, i...

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 (OS...

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...

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-...