Skin Cancer

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 (mRCC) remains challenging. Forkhead box protein O1 (FOXO1) is a key transcription factor regulating tumor suppression and T cell immunity, but its clinical and immunological significance in RCC is unclear. METHODS: FOXO1 expression was analyzed in TCGA-...

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. This study compared the diagnostic performance of the large language model ChatGPT-4 with that of specialized convolutional neural network (CNN)-based models in analyzing melanocytic lesions. PATIENTS AND METHODS: A cross-sectional comparative study ...

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...

Animal Models of Allergen Immunotherapy for Allergic Airway Inflammation.

Allergen immunotherapy (AIT) is currently the only disease-modifying therapy for allergic airway inflammation. However, its underlying mechanisms rema...

Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.

Neoantigens have emerged as central targets in the development of individualized cancer vaccines, as they are recognized by the immune system as forei...

Nanoparticle-based immunotherapeutic strategies to overcome cancer drug resistance: From biological barriers to artificial intelligence-driven design.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance...

KM-DBSCAN: an enhanced density and centroid based border detection framework for data reduction towards green AI.

Green AI aims to design and train machine learning models while taking into consideration sustainable resource usage without sacrificing model efficie...

Potential of SERS and proteomics for biomarker detection in cancer cells.

This study investigates the use of quantitative LC-MS/MS-based proteomics and surface-enhanced Raman spectroscopy (SERS) for biomarker detection in cl...

AI-driven body composition atlas reveals its association with NSCLC immunotherapy outcome and molecular background: a multicenter study.

Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations...

A novel cuproptosis-related prognostic gene signature is identified by machine learning and integrative analyses in gliomas.

Recent studies have highlighted the impact of copper-induced cell death (cuproptosis) on cancer progression, prognosis, and treatment, but it remains ...

IGH::FENDRR and specific KRAS mutations define a novel B-ALL molecular subtype with poor chemotherapy response.

Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic an...

Identification of MHC ligands through allele-guided isolation combined with machine learning for improved MHC assignment using ARDisplay-I.

The isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immuno...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Quality, Empathy, and Readability of AI Chatbot Responses to the Survivorship Needs of Adolescents and Young Adults With Melanoma: Evaluation Study.

BACKGROUND: Melanoma, a highly aggressive form of skin cancer, is the second most common type of cancer for adolescent and young adult (AYA, ages 15-3...