Skin Cancer

Spatial proteomics of tertiary lymphoid structures reveals correlation with immunotherapy response in Merkel cell carcinoma.

BACKGROUND: Tertiary lymphoid structures (TLS) are ectopic lymphoid formations within or around tumours. They are emerging as important predictors of prognosis and response to immune checkpoint inhibitors (ICIs) in various cancers. However, in Merkel cell carcinoma (MCC), the correlation between TLS and ICI response has not yet been evaluated. Furthermore, the criteria for assessing TLS maturity v...

DANCE: Deep Learning-Assisted Analysis of ProteiN Sequences Using Chaos Enhanced Kaleidoscopic Images.

Cancer is a complex disease characterized by uncontrolled cell growth and requires an accurate classification for effective treatment. T cell receptors (TCRs), crucial proteins in the immune system, play a pivotal role in antigen recognition. Advancements in sequencing technologies have facilitated the comprehensive profiling of TCR repertoires, uncovering TCRs with potent anticancer activity and ...

From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chron...

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

Recent Advances in Analytical Techniques for Cancer Diagnostics and Therapeutics: Combining State-of-the-Art Technologies for Precision Oncology.

Cancer remains a leading global health challenge, necessitating continuous advancements in diagnostics and therapeutics to enhance patient outcomes. A...

Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often exhibits limited responsiveness to immune checkpoint inhibitors (ICIs), largely due to an immunosuppressive tumor...

Decoding immunotherapy response through computational modeling.

Immunotherapy has seen success in treating patients with cancer, but variable responses underscore the need for effective patient stratification and t...

AI-Generated Clinical Images of Head-and-Neck Lesions in Plastic Surgery Education: An Expert Evaluation.

BACKGROUND: Clinical images are essential in plastic and reconstructive surgery education, particularly for understanding pathology, planning reconstr...

STC2-mediated calcium homeostasis dysregulation in the osteosarcoma microenvironment: Insights from single-cell sequencing and machine learning.

BACKGROUND: Osteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. Dysregulated calcium homeostasis may contribute to OS progressio...

Cross-task interpretability through unified modeling reveals a universal shortcut bias in neoantigen prediction.

Accurate neoantigen prediction is central to the design of personalized cancer immunotherapy. The immune recognition of neoantigens is a multi-step pr...

Sharing a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations: an ENHANCE.PET initiative.

We present a large whole-body and total-body curated dataset of dual-modality 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-Positron Emission Tomography/Compu...

Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors.

Generative design and machine learning are increasingly prevalent in medicinal chemistry. To pilot the comprehensive use of automated molecular design...

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 id...

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...