Skin Cancer

Integrated genomic profiling identifies predictive biomarkers for neoadjuvant therapy response in Chinese breast cancer patients.

Neoadjuvant therapy (NAT) has emerged as a standard treatment strategy for locally advanced breast cancer (BC), yet robust biomarkers for response prediction remain elusive. Here, we established a real-world NAT cohort of 1161 Chinese BC patients, including 1145 cases with matched clinicopathological data and targeted sequencing, to systematically evaluate genomic features associated with NAT outc...

Personalized neoantigen cancer vaccines: Why clinical benefit remains inconsistent.

Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen identification, and vaccine delivery platforms. Early-phase clinical trials have consistently demonstrated feasibility, safety, and induction of neoantigen-specific immune responses, with clinical benefit observed in a subset of patients. Despite these...

High-throughput strategy for targeting MDM2 in uveal melanoma to reverse radiation therapy resistance.

Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy comb...

Regulatory B cells and SIVA1-LAG3 immune suppression predict poor prognosis in prostate cancer.

Prostate cancer (PCa) is among the most prevalent malignancies affecting men globally. The immunosuppressive characteristics of the tumor microenviron...

Challenges and Controversies in the Diagnosis and Management of Thymic Epithelial Tumors from the Thymic Tumor Subcommittee of the International Association for the Study of Lung Cancer Rare Tumors Committee.

Thymic epithelial tumors (TETs), comprising thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms, are rare prevascular (anterior) mediasti...

Post-translational modification signature shapes the tumor immune microenvironment and predicts clinical outcomes in melanoma.

Deep learning-based pathomics signature predicts prognosis and treatment response in gastric cancer: a multicenter retrospective study.

The existing TNM staging system provides insufficient prognostic information in gastric cancer (GC) patients. This study aims to establish a pathomics...

Efferocytosis-related biomarkers and immune infiltration in pancreatic ductal adenocarcinoma based on single-cell sequencing and machine learning: a comprehensive bioinformatics analysis and experimental validation.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and lethal malignancy, with its complex tumor microenvironment (TME) severely...

Improved tumor-only variant calling and mutation burden estimation with VarNet-T.

Somatic variant calling algorithms typically detect mutations in cancer genomes by comparing sequence data from a tumor sample against a matched norma...

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 t...

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 t...

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...