Skin Cancer

A predictive 14-gene signature and FLI1 inhibition overcome tumor-infiltrating lymphocyte dysfunction in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking effective targeted therapies. Although immune checkpoint inhibitors such as pembrolizumab have improved clinical outcomes in a subset of patients, limited response rates and durability highlight the need for alternative strategies. Tumor-infiltrating lymphocyte (TIL)-based adoptive cell therapy represents a promising approach; h...

Mechanism-Informed Machine Learning Enables Discovery of Oncolytic Peptides for Cancer Immunotherapy.

Oncolytic peptides (OPs) represent a promising class of cancer therapeutics capable of rapidly lysing tumor cells and activating antitumor immunity. However, accurate in silico identification of potent OPs remains challenging due to limited datasets and high false-positive rates. Here, we present MISPOP (Mechanism-Informed Screening Pipeline for Oncolytic Peptides), an integrated machine learning ...

Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.

BACKGROUND: Ovarian cancer (OC) is a highly aggressive malignancy with poor prognosis and limited response to immunotherapy. Ribosomal stress, a cellu...

Differential Attention Feature Aggregator (DAFE) for Advanced Melanoma Detection.

Melanoma is a highly aggressive form of skin cancer with a significant mortality rate. Over the past two decades, its incidence has been on the rise a...

Artificial intelligence model predicts malignant transformation of oral leukoplakia and optimizes interventions.

PURPOSE: Oral leukoplakia (OL), the most common oral potentially malignant disorder (OPMD), poses a significant risk for transformation to oral squamo...

RNA-based cancer immunotherapy: Harnessing the power of RNA nanoparticles for melanoma treatment.

RNA-based cancer immunotherapy has emerged as a next-generation strategy in oncology, harnessing the versatile properties of RNA molecules to activate...

Integrating multi-omics analysis and machine learning to refine molecular subtypes and prognostic assessment of lower-grade glioma.

Lower-grade glioma (LGG) is a highly heterogeneous disease, making accurate prognosis prediction and the development of precise, personalized treatmen...

Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the ter...

Identification of RPL4 as a biomarker associated with disulfidptosis and arachidonic acid metabolism in breast cancer.

OBJECTIVE: Disulfidptosis is a recently discovered mechanism of cell death caused by disulfide stress. Arachidonic acid metabolism (AAM) is one of the...

Machine learning-based prognostic signature integrating mitochondrial function and programmed cell death patterns in pancreatic adenocarcinoma.

The interplay between mitochondria and programmed cell deaths (PCD) is associated with tumor pathogenesis. However, the specific roles of genes relate...

Integrating single-cell multi-omics and machine learning to reveal triaptosis heterogeneity in clear cell renal cell carcinoma.

Triaptosis, an emerging form of cell death, remains poorly characterized in terms of its heterogeneity within clear cell renal cell carcinoma (ccRCC)....

Artificial intelligence in retinoblastoma and uveal melanoma: a narrative review.

INTRODUCTION: Artificial intelligence (AI) is reshaping diagnostic paradigms across oncology. In ophthalmic oncology encompassing conditions like reti...

Multidimensional immune ecological subtyping identifies RUNX1 as a prognostic factor in uveal melanoma.

Uveal melanoma (UVM) is an aggressive intraocular malignancy with a high risk of metastasis but few effective therapies. However, current molecular cl...

Non-invasive profiling of the tumour microenvironment with spatial ecotypes.

Multicellular programs in the tumour microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and p...

The density of tumour infiltrating lymphocytes in oesophago-gastric cancer varies with disease stage, geographical region and treatment: a post hoc analysis of nine phase III clinical trials.

BACKGROUND: Tumour infiltrating lymphocytes (TILs) are a key component of the tumour microenvironment. To establish a clinically relevant TILs cut-off...

Comprehensive evaluation of cross cancer generalization in histopathology segmentation models across 21 tumor types.

BACKGROUND: Artificial intelligence has significantly advanced computational pathology by enabling high-resolution, clinical-grade tumor segmentation ...

Engineered artificial antigen-presenting cells for tumor immunotherapy: Design strategies, clinical applications, and translational challenges.

Immunotherapy has long played a pivotal role in cancer treatment, and antigen-presenting cell (APC)-based immunotherapy represents a promising strateg...

Synthetic inducible bacteria normalize the microenvironment of refractory tumors, potentiating checkpoint inhibitor responses.

Immunotherapy has transformed cancer treatment but remains ineffective in many solid tumors, largely due to the immunosuppressive tumor microenvironme...

Overexpression of NMNAT3 suppresses melanoma progression by reprogramming NAD⁺ metabolism.

BACKGROUND: Melanoma represents a highly aggressive and metastatic form of malignant skin cancer. that remains challenging to treat clinically. Tumor ...

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite rec...