Skin Cancer

Immunotyping the Tumor Microenvironment Reveals Molecular Heterogeneity for Personalized Immunotherapy in Cancer.

The tumor microenvironment (TME) significantly influences cancer prognosis and therapeutic outcomes, yet its composition remains highly heterogeneous, and currently, no highly accessible, high-throughput method exists to define it. To address this complexity, the TMEclassifier, a machine-learning tool that classifies cancers into three distinct subtypes: immune Exclusive (IE), immune Suppressive (...

Gastrointestinal microbiota and inflammasomes interplay in health and disease: a gut feeling.

The intricate interplay between the gut microbiota and the GI tract has garnered significant attention, as growing evidence has identified the inflammasome as a crucial yet underexplored master regulator in microbiota-driven diseases. Triggered by a variety of dangers, inflammasomes are supramolecular complexes that regulate immune response. A large number of bacterial-derived inducers have been c...

Biophysical modeling for accurate T cell specificity prediction of viral and tumor antigens.

Accurate predictions of T cell receptor (TCR) specificity remain an important open problem in immunology, with broad implications for vaccine design, ...

[Progress of individualized precision therapy for peritoneal metastasis in gastric cancer].

Peritoneal metastasis represents the most aggressive form of gastric cancer metastasis and serves as a primary contributor to poor prognosis. Conventi...

[Current status and trends of perioperative immunotherapy for gastric cancer].

In recent years,immunotherapy,particularly immune checkpoint inhibitors,has been widely used in the treatment of both solid and non-solid tumors,and i...

Nomograms versus artificial intelligence platforms: which one can better predict sentinel node positivity in melanoma patients?

Nomograms are commonly used in oncology to assist clinicians in individualized decision-making processes, such as considering sentinel node biopsy (SN...

Baseline Radiomics as a Prognostic Tool for Clinical Benefit from Immune Checkpoint Inhibition in Inoperable NSCLC Without Activating Mutations.

Checkpoint inhibitors (ICIs) are key therapies for NSCLC, but current selection criteria, such as excluding mutation carriers and assessing PD-L1, la...

Multimodal integration of longitudinal noninvasive diagnostics for survival prediction in immunotherapy using deep learning.

OBJECTIVES: Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced 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 eff...

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...

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...