Skin Cancer

A multi-faceted discovery strategy identifies functional antibodies binding to cysteine-rich domain 1 of hDKK1 for cancer immunotherapy via Wnt non-canonical pathway.

Wnt signaling is important in embryonic development and tumorigenesis. These biological effects can be exerted by the activation of the β-catenin-dependent canonical pathway or the β-catenin-independent non-canonical pathway. DKK1 is a potent inhibitor of Wnt signaling by competing with Wnt binding to LRP5/6 co-receptors. DKK1 is tumorigenic in multiple cancer types and immunosuppressive in NK cel...

Assessing the generalization capabilities of TCR binding predictors via peptide distance analysis.

Understanding the interaction between T Cell Receptors (TCRs) and peptide-bound Major Histocompatibility Complexes (pMHCs) is crucial for comprehending immune responses and developing targeted immunotherapies. While recent machine learning (ML) models show remarkable success in predicting TCR-pMHC binding within training data, these models often fail to generalize to peptides outside their trainin...

Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.

INTRODUCTION: Prostate adenocarcinoma (PRAD) is an extremely widespread site of urological malignancy and is the second most common male cancer in the...

Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.

This comprehensive review examines artificial intelligence (AI) applications in dermatology, approved by the United States (U.S.) Food and Drug Admini...

Prognostic prediction model for Chinese uveal melanoma patients based on matrix metalloproteinase-2 and -28 expression levels in the tumor.

AIM: To explore the relationship between matrix metalloproteinases (MMPs) expression levels in the tumor and the prognosis of uveal melanoma (UM) and ...

The Role of Artificial Intelligence With Deep Convolutional Neural Network in Screening Melanoma: A Systematic Review and Meta-Analyses of Quasi-Experimental Diagnostic Studies.

INTRODUCTION: Detecting melanoma as one of the most common skin cancer with using artificial intelligence (AI), such as deep convolutional neural netw...

Predicting Immunotherapy Response in Unresectable Hepatocellular Carcinoma: A Comparative Study of Large Language Models and Human Experts.

Hepatocellular carcinoma (HCC) is an aggressive cancer with limited biomarkers for predicting immunotherapy response. Recent advancements in large lan...

Deciphering Shared Gene Signatures and Immune Infiltration Characteristics Between Gestational Diabetes Mellitus and Preeclampsia by Integrated Bioinformatics Analysis and Machine Learning.

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common and serious disorders of pregnancy that threaten maternal safety and perinatal ou...

A novel model for predicting immunotherapy response and prognosis in NSCLC patients.

BACKGROUND: How to screen beneficiary populations has always been a clinical challenge in the treatment of non-small-cell lung cancer (NSCLC) with imm...

Deciphering the Immunomodulatory Function of GSN Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis.

The heterogeneity of cancer-associated fibroblasts (CAFs) could affect the response to immune checkpoint inhibitor (ICI) therapy. However, limited stu...

Updated Techniques for Melanoma Diagnosis.

Melanoma, an aggressive skin cancer, requires timely diagnostics for improved patient outcomes. The ABCDE criteria-assessing asymmetry, borders, color...

From Multi-Omics to Visualization and Beyond: Bridging Micro and Macro Insights in CAR-T Cell Therapy.

Chimeric antigen receptor T (CAR-T) cell therapies, a cornerstone of immunotherapy, have demonstrated remarkable efficacy in treating hematological ma...

Isolation and characterization of a bioactive compound from Sphingomonas sanguinis DM with cytotoxic and molecular docking analysis.

Datura metel, a common plant in the Solanaceae family, is known for its valuable medicinal properties. The metabolites created by its rhizosphere bact...

Precise Electromagnetic Modulation of the Cell Cycle and Its Applications in Cancer Therapy.

Precise modulation of the cell cycle via electromagnetic (EM) control presents a groundbreaking approach for cancer therapy, especially in the develop...

Breakthroughs and challenges of organoid models for assessing cancer immunotherapy: a cutting-edge tool for advancing personalised treatments.

Organoid models are powerful tools for evaluating cancer immunotherapy that provide a more accurate representation of the tumour microenvironment (TME...

Application of multivalent aptamers in tumor diagnosis, analysis and therapy (Review).

Cancer remains one of the leading causes of mortality worldwide, making early diagnosis and precise treatment crucial for enhancing patient survival r...

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep lear...

Global burden of non-melanoma skin cancers among older adults: a comprehensive analysis using machine learning approaches.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), have shown significant global increases in ...

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT i...

Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis.

BACKGROUND AND AIM: Artificial intelligence (AI) networks offer significant potential for predicting immunotherapy outcomes in gastrointestinal cancer...