AIMC Topic: Squamous Cell Carcinoma of Head and Neck

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Machine learning developed regulatory T cells-related signature for prognosis and immunotherapy benefit in oral squamous cell carcinoma.

American journal of otolaryngology
BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common malignancies with poor clinical outcome. Regulatory T cells (Tregs) have a dual role in maintaining immune homeostasis and suppressing anti-tumor immunity. The role of Tregs re...

Use of ChatGPT for patient education involving HPV-associated oropharyngeal cancer.

American journal of otolaryngology
OBJECTIVE: This study aims to investigate the ability of ChatGPT to generate reliably accurate responses to patient-based queries specifically regarding oropharyngeal squamous cell carcinoma (OPSCC) of the head and neck.

Histological tumor necrosis predicts decreased survival after neoadjuvant chemotherapy in head and neck squamous cell carcinoma.

Oral oncology
OBJECTIVE: Despite growing interest in neoadjuvant therapies, there are no methods to predict radio- (RT) or chemoradiotherapy (CRT) response in head and neck squamous cell carcinoma (HNSCC). The aim of this research was to study the effect of neoadj...

Pathogenomic fingerprinting to identify associations between tumor morphology and epigenetic states.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: Measuring the chromatin state of a tumor provides a powerful map of its epigenetic commitments; however, as these are generally bulk measurements, it has not yet been possible to connect changes in chromatin accessibility to the patholo...

Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Virtual staining is an artificial intelligence-based approach that transforms pathology images between stain types, such as hematoxylin and eosin (H&E) to immunohistochemistry (IHC), providing a tissue-preserving and efficient alternative...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

EBioMedicine
BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology an...

Optimizing fractionation schedules for de-escalation radiotherapy in head and neck cancers using deep reinforcement learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Patients with locally-advanced head and neck squamous cell carcinomas (HNSCCs), particularly those related to human papillomavirus (HPV), often achieve good locoregional control (LRC), yet they suffer significant toxicities from standard che...

Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomas.

Oral oncology
OBJECTIVES: Human papillomavirus (HPV) influences the pathobiology of Head and Neck Squamous Cell Carcinomas (HSNCCs). While deep learning shows promise in detecting HPV from hematoxylin and eosin (H&E) stained slides, the histologic features utilize...