Skin Cancer

Targeting cholesterol metabolism: a core regulator of tumor-associated macrophage plasticity and immunotherapy response.

Tumor-associated macrophages (TAMs) are one of the main immunosuppressive components in the tumor microenvironment (TME). Growing evidence indicates that their functional state is closely related to metabolic signaling, with cholesterol metabolism dysregulation receiving increasing attention. Abnormal cholesterol metabolism alters membrane lipid composition and signaling pathways, resulting in imp...

Machine learning-based programmed cell death gene signature for prognosis and drug sensitivity in breast cancer.

Breast cancer (BRCA) heterogeneity necessitates robust prognostic biomarkers. Programmed cell death (PCD) serves a key role in tumor progression and therapy response. However, the prognostic potential of PCD-related genes (CRGs) in BRCA remains to be fully elucidated. Therefore, the present study integrated transcriptomic data from The Cancer Genome Atlas, Molecular Taxonomy of Breast Cancer Inter...

Targeting immunosenescence in lung diseases: mechanistic insights and clinical interventions.

Immunosenescence, the age-related decline in immune function, plays a crucial role in the pathogenesis and progression of lung diseases, including chr...

Predicting Melanoma Impact on the Swedish Healthcare System from the Adult Population Using Machine Learning on Registry Data.

Melanoma incidence has increased in Western countries over the past 50 years, leading to significant healthcare costs. In Sweden, comprehensive health...

A Review of Automatic Hair Removal in Dermoscopy Images: From Image Processing to Deep Learning.

Early melanoma detection is made possible by dermoscopy, but automated analysis and clinical evaluation are often hampered by hair artifacts in images...

Smart medical system integrating clinical workflows for robust skin cancer detection across heterogeneous pathologies.

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion...

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential.

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its complex tumor microenvironment (TME) is a key barr...

Integrative multi-omics identifies a diagnostic T cell signature for cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) involves complex immune interactions. This study aimed to identify a T cell-related gene signature to charact...

Comparison of Indocyanine Green Versus Isosulfan Blue in Melanoma Sentinel Node Biopsy.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is the standard for staging melanoma. Traditional dual-mapping with technetium-99m radioisotope (RI) and...

mRNA-based melanoma vaccines targeting gp100 and TRP2 macromolecules.

Integrative Machine Learning and Network Pharmacology Approach to Uncover Phytochemical Therapeutics for Melanoma and Breast Cancer.

INTRODUCTION: Melanoma and Breast cancer are the leading cancers that cause thousands of deaths annually worldwide. Although several early identificat...

Clinical and immunological significance of FOXO1 as a biomarker of improved response to immune checkpoint plus tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma.

BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TKI) therapy in metastatic renal cell carcinoma (mRC...

Beyond black-box AI: Comparing ChatGPT-4 interpretability and accuracy to CNNs in melanocytic lesions diagnosis.

BACKGROUND: Artificial intelligence (AI) algorithms have advanced and recently shown high accuracy in diagnosing skin cancer from dermoscopic images. ...

Integrated spatial transcriptomics and pan-cancer XGBoost modeling uncover spatial drivers of immune exclusion and predict immunotherapy response.

Immunotherapy has revolutionized cancer treatment, yet characterizing the spatial complexity of the tumor immune microenvironment remains a challenge....

Small but mighty: Peptides as next-generation immunotargeting agents in gynecological cancers.

The most common cancers in women, ovarian, cervical and endometrial, are still a significant cause of cancer-related illness and death around the worl...

mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.

The unprecedented success of mRNA vaccines during the COVID-19 pandemic has accelerated the development of nucleic acid-based therapeutics, particular...

From prediction to precision: how immunopeptidomics advances neoantigen discovery.

T cell recognition of peptides presented by class I and II human leukocyte antigen (HLA) molecules is fundamental to cancer immunity and personalized ...

Integrating Bulk RNA-Seq and Spatial Transcriptomics Data to Reveal Distinct Immune Escape Mechanism and Immunotherapy Based on Post-Translational Modification in Head and Neck Squamous Cell Carcinoma.

Post-translational modification (PTM) plays a crucial role in head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic...

A high-speed attention network for MHC-bound peptide identification and 3D modeling.

We developed SwiftMHC, an ultra-fast and accurate structure-based framework for peptide-MHC (pMHC) modeling and binding affinity prediction. Using tas...

A Multitask Deep Learning Approach for Tumor Segmentation and Morphological Quantification in Acral Melanoma Whole-Slide Images.

This study presents an integrated multitask deep learning framework for the automated analysis of acral melanoma from whole-slide images (WSIs). We co...