Other Cancers

Repurposing Non-oncologic Drugs via Targeted Nanocarriers for Cancer Therapy: Mechanisms, Synergistic Combinations, and Clinical Translation.

The urgent need for innovative cancer therapies has driven increasing interest in repurposing drugs originally developed for non-oncological diseases. Several FDA-approved and clinically investigated agents, including mesalamine, celecoxib, gliclazide, metformin, itraconazole, and doxycycline, have shown anticancer potential through diverse mechanisms. However, despite their therapeutic potential,...

CT-based radiomics as a non-invasive virtual biopsy for high PD-L1 expression prediction in non-small cell lung cancer.

PURPOSE: Non-small cell lung cancer (NSCLC) remains a major clinical challenge, with Programmed death-ligand 1 (PD-L1) expression serving as a crucial biomarker to guide immunotherapy. However, its current assessment through invasive biopsies may not capture tumor heterogeneity. This study explores the feasibility of a CT-based radiomics approach, combined with machine learning (ML), as a potentia...

Identification and prognostic analysis of genes related to CTNNB1 mutations in hepatocellular carcinoma.

BACKGROUND: Mutations in CTNNB1 are recognized oncogenic drivers of hepatocellular carcinoma (HCC); however, the downstream effector molecules and the...

Tumor ablation: emerging uses, challenges, and strategic implementation. A green paper by the Network of Expertise in Cancer (JANE-2), High Tech Medical Resources, network on Physical Methods of Tumor Ablation.

The field of oncology has witnessed remarkable progress with the integration of high-tech innovations in tumor ablation. Tumor ablation therapies, suc...

Integrated single-cell RNA sequencing and Bulk-RNA technologies reveal the immunological characteristics of lactylation related-genes in glioblastoma.

OBJECTIVE: Glioblastoma (GBM) is the most aggressive type of intracranial malignant tumor, known for its extremely poor prognosis. Lactylation, a newl...

Corneal nerve regeneration: treatments and monitoring approaches.

BACKGROUND: Diagnostics and therapeutics for corneal nerve pathologies are rapidly evolving, with continual advancements in imaging, laser, machine le...

OpenIO: An open framework for AI-native immunotherapy.

We propose Open Immune Oncology (OpenIO), a framework integrating generative AI and omics to advance precision oncology. By leveraging biological scal...

[An auxiliary diagnosis system for cervical intraepithelial neoplasia based on colposcopic images].

Cervical intraepithelial neoplasia is the primary type of cervical precancerous lesion; however, manual clinical diagnosis is prone to bias and has li...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

Heterogeneity Analyzed by CT-Based Habitat Analysis for Clinical Management of Cancers: A Narrative Review.

Tumors are highly heterogeneous, and whole-lesion radiomics analysis is a popular method for extracting texture features that reflect this heterogenei...

AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.

Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-ma...

Development of a LASSO-based machine learning model for relapse prediction in lupus nephritis.

OBJECTIVE: To identify the predictors of renal relapse in patients with lupus nephritis (LN) and develop a predictive model. METHODS: The patients wit...

Value operating system: a practical framework to measure outcomes-per-cost at the episode level.

OBJECTIVE: To specify a value operating system (VOS) and its executable metric-the Value Index (VI)-that expresses risk-adjusted outcomes-per-episode-...

Prediction of cardiac arrest in patients with heart failure in Sweden: a registry study with development of a machine learning model.

OBJECTIVE: 30-day survival after cardiac arrest is low, 12.4% and 36% for out-of-hospital and in-hospital cardiac arrest, respectively. Heart failure ...

IL4Rα blockade inhibits proliferation of malignant lymphocytes and the immunosuppressive tumor microenvironment of mycosis fungoides.

BACKGROUND: Limited therapeutic options are available for patients with advanced-stage mycosis fungoides (MF), and the 5-year survival rate is 25%. Du...

Diagnosis of Small Focal Liver Lesions (≤2 cm): A Deep Learning Approach Based on B-Mode Ultrasound and Contrast-Enhanced Ultrasound.

BACKGROUND: To develop and validate a deep learning (DL) model based on feature fusion with B-mode ultrasound (BMUS) and contrast enhanced ultrasound ...

Oral cancer in the era of precision medicine: molecular targets and technological innovations.

This topical Collection presents a series of studies that examine molecular mechanisms, diagnostic approaches, and therapeutic strategies relevant to ...

A prediction model based on tumor immune microenvironment for immunotherapy response in gastric cancer.

This study aimed to develop a robust prediction model- using machine-learning algorithms based on the core indicators of the tumor immune microenviron...

Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling.

Immune-checkpoint inhibitors benefit a subset of patients with advanced cancer, and the metabolic determinants of response remain unclear. Here, using...