Skin Cancer

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, and the mesenchymal type is the most aggressive form with the worst prognosis. GBM undergoes proneural-mesenchymal transition (PMT) during its evolution or in response to changes in the microenvironment or therapeutic interventions. PMT is accompanied...

AI-Driven Biomarker Discovery and Personalized Allergy Treatment: Utilizing Machine Learning and NGS.

PURPOSE OF REVIEW: This review explores the transformative potential of artificial intelligence (AI) and next-generation sequencing (NGS) in allergy diagnostics and treatment. It focuses on leveraging these technologies to enhance precision in biomarker discovery, patient stratification, and personalized management strategies for allergic diseases. RECENT FINDINGS: AI-driven algorithms, particular...

Skin cancer segmentation and classification by implementing a hybrid FrCN-(U-NeT) technique with machine learning.

Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infect...

Tumor-specific draining lymph node CD8 T cells orchestrate an anti-tumor response to neoadjuvant PD-1 immune checkpoint blockade.

Elucidating the anti-tumor role of tumor-draining lymph nodes (tdLNs) in patients could offer critical mechanistic insight and shift therapeutic strat...

From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.

Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies. Bispecific antibodies (BsAbs), which redirect cyt...

NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.

BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy re...

Development and interpretation of a pathomics-based model for the prediction of immune therapy response in colorectal cancer.

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related deaths worldwide, with a 5-year survival ra...

Mechanical Modulation, Physiological Roles, and Imaging Innovations of Intercellular Calcium Waves in Living Systems.

Long-range intercellular communication is essential for multicellular biological systems to regulate multiscale cell-cell interactions and maintain li...

Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.

Breast cancer (BC) is still the most diagnosed cancer for females with an increased focus on immunotherapy as a promising precise treatment. Selecting...

Integrated Single-Cell and Bulk RNA Sequencing Analysis Identifies a Regulated Cell Death-Related Gene Signature for Predicting Prognosis and Therapeutic Responses in Cutaneous Melanoma.

Regulated cell death (RCD) is crucial for the advancement of cancers, and providing opportunities as prognostic indicators and immunotherapy markers f...

Unraveling the TEC-associated landscape in hepatocellular carcinoma: a comprehensive study based on multi-omics analyses.

The tumor microenvironment (TME) plays a pivotal role in tumor progression, immune evasion, and therapeutic responses. Among its key components, endot...

Development of an immune scoring system based on exosome-related gene expression for prognosis and treatment response prediction in breast cancer.

Breast cancer (BC) is a heterogeneous disease with diverse subtypes that influence prognosis and treatment outcomes. While advances have been made in ...

A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning.

Cancer has increasingly been recognized as a genetic disease, influenced by lifestyle changes, dietary patterns, and environmental pollutants. Lung ca...

Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis.

Sepsis is a systemic inflammatory response syndrome that predisposes to severe lung infections (SeALAR) such as sepsis-associated acute lung injury (S...

Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization.

Bladder cancer is the fourth most common malignant tumor in men, with limited therapeutic biomarkers and heterogeneous responses to immunotherapy. Dis...

CT-Based Radiomics for Predicting PD-L1 Expression in Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis.

BACKGROUND AND PURPOSE: The efficacy of immunotherapy in non-small cell lung cancer (NSCLC) is intricately associated with baseline PD-L1 expression r...

Non-invasive diagnosis of melanoma using machine learning and reflectance confocal microscopy.

Machine learning prediction for early-stage melanoma outcomes: recurrence-free survival, disease-specific survival, and overall survival.

This study compared machine-learning models for predicting recurrence-free survival (RFS), disease-specific survival (DSS), and overall survival (OS) ...

The Integration of Artificial Intelligence Into Precision Medicine for Neuro-Oncology: Ethical, Clinical, and Nursing Implications in Immunotherapy Care.

This paper explores how artificial intelligence (AI) is being woven into precision medicine for neuro-oncology, highlighting its ethical, clinical, an...

Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis.

OBJECTIVES: Decades of clinical and fundamental research advancements in oncology have led to significant breakthroughs such as early screening, targe...