Skin Cancer

Explainable machine learning to predict immunotherapy outcomes in metastatic renal cell carcinoma - Meet-URO 15-AI study.

Metastatic renal cell carcinoma remains clinically challenging because of heterogeneous outcomes and limited predictive biomarkers for immunotherapy. We performed an explainable machine learning analysis using data from the multicenter retrospective Meet-URO 15 study, including 571 patients with metastatic renal cell carcinoma treated with second-line or later nivolumab. Clinical and inflammatory ...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell lung cancer (NSCLC). Their translation depends on reliable biomarker assessment, a task still dominated by subjective visual scoring and inconsistent reproducibility. EXPERIMENTAL DESIGN: We built a modular Artificial Intelligence (AI) pipeline that ...

AI in clinical diagnostics in dermatology: applications, validation, and real-world use cases.

Artificial intelligence (AI) has moved from proof-of-concept studies in dermatology to selective, real-world clinical use, particularly in image-based...

Preclinical and Virtual Models of Mucosal Melanoma: Bridging Translational Gaps in a Rare and Lethal Cancer.

Mucosal melanoma (MM) is a rare and lethal subtype of melanoma, disproportionately affecting Asian populations and exhibiting distinct clinicopatholog...

Metabolic reprogramming of myeloid cells in cancer: from lactate-NAMPT axis to AI-guided therapeutics.

Myeloid cells-including macrophages, monocytes, neutrophils and dendritic cells-are metabolically plastic sentinels that shape the tumor microenvironm...

APOBEC mutational signatures predict immune checkpoint inhibitor benefit in TMB-low metastatic NSCLC independent of PD-L1 status.

BACKGROUND: ∼60%-70% of patients with metastatic non-small cell lung cancer (NSCLC) have relatively low tumor mutational burden (TMB), with limited bi...

Artificial intelligence (AI)-assisted diagnosis of skin diseases: From image classification to dermatology-specific multimodal clinical reasoning.

Artificial intelligence (AI) in dermatology has moved beyond the early paradigm of single-image classification. Dermatological diagnosis is achieved b...

Integrative multi-omics and network toxicology reveal candidate molecular targets of deoxynivalenol in melanoma.

Deoxynivalenol (DON) has been reported to exhibit skin toxicity and carcinogenic potential; however, its effects on melanoma remain unclear. We integr...

Integrated multi-omics analysis reveals folate metabolism-related genes as prognostic markers and therapeutic targets in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is an aggressive tumor with high metastatic potential and therapeutic resistance, yet the role of ...

Integrating artificial intelligence and multi-omics data for precision oncology in endometrial cancer: a narrative review.

Endometrial cancer (EC) is the most common gynaecological malignancy worldwide, yet the prognosis for advanced and recurrent disease remains poor, hig...

Deciphering the Therapeutic and Preventive Potential of Dietary Tannins in Osteosarcoma: A Multi-Omics Approach Targeting TGFA and Immune Microenvironment Remodeling.

Malignant tumors, including osteosarcoma (OS), are major non-communicable chronic diseases driven by systemic inflammation and oxidative stress. While...

Elucidating the pathway activity and prognostic significance of diverse regulatory cell death patterns in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a five-year survival rate below 10%. Regulatory cell death (RCD) plays ...

Pan-cancer analysis identifies immunoproteasome as the predominant survival-associated component of antigen processing machinery.

Neoantigens are critical targets for cancer immunotherapy, yet the relationship between experimentally validated neoantigen burden and antigen process...

Disulfidptosis-related signatures identify SPARC+/CYR61+ stromal cells mediating immunosuppression in gastric cancer.

BACKGROUND: Disulfidptosis is a novel form of glucose starvation-induced cell death, yet its prognostic implications in gastric cancer (GC) remain lar...

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...

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...

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...

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...

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...