Multi-Institutional Validation of Deep Learning for Pretreatment Identification of Extranodal Extension in Head and Neck Squamous Cell Carcinoma.

Purpose: Extranodal extension (ENE) is a well-established poor prognosticator and an indication for adjuvant treatment escalation in patients with head and neck squamous cell carcinoma (HNSCC). Identification of ENE on pretreatment imaging represents a diagnostic challenge that limits its clinical utility. We previously developed a deep learning algorithm that identifies ENE on pretreatment computed tomography (CT) imaging in patients with HNSCC.

Impact of obesity on outcomes for patients with head and neck cancer.

Objectives: The prognostic role of obesity in head and neck squamous cell carcinoma (HNSCC) is not well defined. This study aims to determine its effect on disease-specific outcomes such as recurrence-free survival (RFS), locoregional recurrence-free survival (LRRFS), and distant metastasis-free survival (DMFS) in addition to overall survival (OS).

Methods: For patients with newly diagnosed HNSCC undergoing radiation therapy (RT) at a single institution, body mass index (BMI) at diagnosis was categorized as normal (18.

Transcriptome-based repurposing of apigenin as a potential anti-fibrotic agent targeting hepatic stellate cells.

We have used a computational approach to identify anti-fibrotic therapies by querying a transcriptome. A transcriptome signature of activated hepatic stellate cells (HSCs), the primary collagen-secreting cell in liver, and queried against a transcriptomic database that quantifies changes in gene expression in response to 1,309 FDA-approved drugs and bioactives (CMap). The flavonoid apigenin was among 9 top-ranked compounds predicted to have anti-fibrotic activity; indeed, apigenin dose-dependently reduced collagen I in the human HSC line, TWNT-4.

Resolving cancer-stroma interfacial signalling and interventions with micropatterned tumour-stromal assays.

Tumour-stromal interactions are a determining factor in cancer progression. In vivo, the interaction interface is associated with spatially resolved distributions of cancer and stromal phenotypes. Here, we establish a micropatterned tumour-stromal assay (μTSA) with laser capture microdissection to control the location of co-cultured cells and analyse bulk and interfacial tumour-stromal signalling in driving cancer progression.