Skin Cancer

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks.

Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequences to enhance immunotherapy predictability and efficacy. The most variable and crucial part of the TCR receptor is the CDR3 sequence region. Current methods for generating CDR3 sequences, including motif-based and Markov models, struggle to generate reliable, diverse, and novel TCR sequences. In thi...

The development of predictive biomarkers and immunologic markers for breast cancer: current status and future perspectives.

Breast cancer is the leading cause of cancer-related mortality among women worldwide. The development of predictive biomarkers and immunologic markers has revolutionized breast cancer diagnosis and treatment, enabling personalized medicine approaches. This study aims to review the current status, challenges, and future directions of predictive and immunologic biomarkers in breast cancer. Predictiv...

Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.

Skin cancer is one of the most prevalent malignant tumors, and early detection is crucial for patient prognosis, leading to the development of mobile ...

Learnable prototype-guided multiple instance learning for detecting tertiary lymphoid structures in multi-cancer whole-slide pathological images.

Tertiary lymphoid structures (TLS) are ectopic lymphoid aggregates that form under specific pathological conditions, such as chronic inflammation and ...

Construction and Multi-dimensional Validation of a Lactylation-Related Signature for Glioblastoma Multiforme Prognostic and Therapeutic Purposes.

Glioblastoma multiforme, one of the most malignant types of brain tumor, heavily relies on glycolytic pathways and is significantly influenced by immu...

Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Despit...

Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.

Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appe...

Immune-related gene risk model establishment and role of key gene FUCA1 in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare type of tumor closely associated with asbestos exposure. Increasing evidence shows that hig...

Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer.

INTRODUCTION: Colorectal cancer (CRC), the third most common cancer worldwide, often shows limited responsiveness to immunotherapy due to its predomin...

Immunopeptidomics-guided discovery and characterization of neoantigens for personalized cancer immunotherapy.

Neoantigens have emerged as ideal targets for personalized cancer immunotherapy. We depict the pan-cancer peptide atlas by comprehensively collecting ...

Arginine methylation patterns in LUAD: defining prognostic subtypes and relevance to immunotherapy.

BACKGROUND: Lung cancer remains the leading cause of cancer-related death worldwide, with lung adenocarcinoma (LUAD) being the most common subtype. Ar...

ImmunoStruct: a multimodal neural network framework for immunogenicity prediction from peptide-MHC sequence, structure, and biochemical properties.

Epitope-based vaccines are promising therapeutic modalities for infectious diseases and cancer, but identifying immunogenic epitopes is challenging. T...

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-depe...

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 comprehendin...

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...