Other Cancers

BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.

Brain metastasis (BM) is a major cause of mortality in limited-stage small-cell lung cancer (LS-SCLC). Prophylactic cranial irradiation (PCI) reduces BM incidence but carries neurotoxicity and lacks individualized risk assessment. Here, we developed BraMARS, an explainable deep learning model that estimates future BM risk from routine H&E-stained whole-slide images of resected LS-SCLC. BraMARS dem...

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption...

Transcriptomic Profiling of Mouse Mammary Tumors Enables Prognostic and Predictive Biomarker Discovery for Human Breast Cancer.

The development and validation of prognostic and predictive biomarkers in breast cancer is limited by the availability of well-annotated datasets link...

Deep learning-based automated identification of papillary bladder cancer from endoscopic still images using SE-ResNeXt-50.

Bladder cancer remains a major global health challenge, necessitating rigorous endoscopic surveillance and the precise identification of neoplastic le...

Radiomics for Prediction of Microsatellite Instability Status in Gastric Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND: Microsatellite instability (MSI) is a key biomarker for immunotherapy in gastric cancer (GC), but preoperative non-invasive prediction rem...

Impact of oncological biomarkers and clinical factors on survival outcomes in renal cell carcinoma with spinal metastasis: a retrospective analysis.

OBJECTIVE: Renal cell carcinoma (RCC) is a common malignancy that metastasizes to the spine, leading to complex treatment challenges and reduced survi...

NMR metabolomics and glycomics for cancer detection in patients with non-specific symptoms: a prospective observational cohort study.

BACKGROUND: Early cancer diagnosis in patients with non-specific symptoms is limited by the lack of discriminatory tests. Within the Oxfordshire Suspe...

PET/CT In paediatric lymphoma: Current role and advances.

Fluorine-18 fluorodeoxyglucose ([18F] FDG) PET/CT has become central to the management of paediatric lymphoma, providing critical information for stag...

Research progress of confocal laser endomicroscopy in malignant respiratory diseases: A review.

The diagnosis and monitoring of malignant respiratory diseases are heavily reliant on imaging techniques and tissue biopsies. Confocal laser endomicro...

Clinical value of artificial intelligence ultrasound-assisted diagnostic system in the differential diagnosis of benign and malignant thyroid nodules: A retrospective case-control study.

Accurately distinguishing the benign thyroid nodules (BTNs) and malignant thyroid nodules (MTNs) is crucial for treatment planning and prognosis. This...

A novel adrenomedullin receptor signaling-based prognostic model predicts immunosuppressive microenvironment and informs therapeutic stratification in hepatocellular carcinoma: A retrospective bioinformatics study.

The adrenomedullin receptor signaling pathway plays a crucial role in tumor progression, yet its comprehensive implication in hepatocellular carcinoma...

Construction of a prognostic model using lactylation-related genes for predicting the prognosis of glioma patients.

Gliomas are the most lethal malignant tumors of the central nervous system, and their treatment continues to face serious challenges. Increasing evide...

A continuous-space analytical framework for committor functions from molecular dynamics.

Many biomolecular processes are governed by rare transitions between metastable states on complex free-energy landscapes. The committor function, the ...

Machine-learning-based Phenomapping of Patients with Keratinocyte Carcinoma: Data-driven Subgrouping by Disease Burden, Comorbidities and Socioeconomic Status.

Keratinocyte carcinoma (KC) places a considerable and growing burden on healthcare systems. Given the KC population's heterogeneity, tailored clinical...

A Combined Chemoinformatics- and Machine Learning-Based Approach Identifies Chlormidazole as a Drug Repurposing Candidate against Aggressive Prostate Cancer.

Despite recent therapeutic advances, treatment options for advanced, therapy-resistant, and metastatic prostate cancer (PCa) remain limited. Here, we ...

VIGIL: Vision-Language Guided Multiple Instance Learning Framework for Ulcerative Colitis Histological Healing Prediction.

OBJECTIVE: Ulcerative colitis (UC) is characterized by chronic inflammation with alternating remission-relapse cycles, necessitating precise histologi...

Modeling microbiome modulation of tumor metabolic networks to predict synergistic therapies.

Differences in microbiome composition profoundly influence drug response, yet methods to model the metabolic impact of microbes on host cells and ther...

Artificial intelligence-driven transformation in the management of atypia of undetermined significance (AUS) thyroid nodules.

Atypia of undetermined significance (AUS) thyroid nodules account for 10-30% of thyroid fine-needle aspiration (FNA) cytology results, with a malignan...

Disarming cGAS-STING hyperactivation in autoimmune and inflammatory diseases: Pathogenic mechanisms and emerging therapeutic strategies.

Aberrant activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway has been increasingly recognized as a key dri...

Explainable dual-task deep learning model for recurrence prediction and dose-sensitive region identification in HNC radiotherapy.

PURPOSE: Accurate prediction of distant metastasis (DM) and locoregional recurrence (LR) in head and neck cancer (HNC) patients following radiotherapy...