Background/Objectives: Cancer-associated cachexia in head and neck squamous cell carcinoma (HNSCC) is challenging to diagnose due to its complex pathophysiology. This study aimed to identify metabolic biomarkers linked to cachexia and survival in HNSCC patients using [¹⁸F]FDG-PET/CT imaging and machine learning (ML) techniques. Methods: We retrospectively analyzed 253 HNSCC patients from Vienna General Hospital and the MD Anderson Cancer Center. Automated organ segmentation was employed to quantify metabolic and volumetric data from [¹⁸F]FDG-PET/CT scans across 29 tissues and organs. Patients were categorized into low weight loss (LoWL; grades 0–2) and high weight loss (HiWL; grades 3–4) groups, according to the weight loss grading system (WLGS). Machine learning models, combined with Cox regression, were used to identify survival predictors. Shapley additive explanation (SHAP) analysis was conducted to determine the significance of individual features. Results: The HiWL group exhibited increased glucose metabolism in skeletal muscle and adipose tissue (p = 0.01), while the LoWL group showed higher lung metabolism. The one-year survival rate was 84.1% in the LoWL group compared to 69.2% in the HiWL group (p < 0.01). Pancreatic volume emerged as a key biomarker associated with cachexia, with the ML model achieving an AUC of 0.79 (95% CI: 0.77–0.80) and an accuracy of 0.82 (95% CI: 0.81–0.83). Multivariate Cox regression confirmed pancreatic volume as an independent prognostic factor (HR: 0.66, 95% CI: 0.46–0.95; p < 0.05). Conclusions: The integration of metabolic and volumetric data provided a strong predictive model, highlighting pancreatic volume as a key imaging biomarker in the metabolic assessment of cachexia in HNSCC. This finding enhances our understanding and may improve prognostic evaluations and therapeutic strategies.

Background: Multiple mechanisms might lead to cancer-related hypercoagulability. In brain tumors, podoplanin, via its ability to activate platelets, seems to play a crucial role in developing venous thromboembolism (VTE). Different stimuli (including activated platelets) can trigger the release of prothrombotic neutrophil extracellular traps (NETs) by neutrophils. It remains to be elucidated whether podoplanin-induced platelet aggregates might also impact NET formation and subsequent hypercoagulability and thrombosis. Methods: Patients with glioma were enrolled in this prospective observational cohort study. The primary endpoint was VTE. Immunohistochemical staining of NETs (via citrullinated histone H3 [H3Cit]) and neutrophils (via myeloperoxidase [MPO]) was conducted in glioma specimens and correlated with intravascular platelet clusters (via CD61) and podoplanin. Results: In total, 154 patients were included. H3Cit+ tumor vessels were found in 45/154 cases. H3Cit were significantly associated with increased intravascular platelet clusters (CD61− vs. CD61+ vs. CD61++ vs. CD61+++: 3.7% (1/27) vs. 18.6% (11/59) vs. 39.4% (13/33) vs. 57.1% (20/35), p < 0.001) and podoplanin expression (PDPN− vs. PDPN+: 14.3% (7/49) vs. 36.2% (38/105), p = 0.007) in the tumor tissue. Furthermore, H3Cit+ tumor vessels were significantly associated with tumor-infiltrating MPO+ neutrophils (H3Cit− vs. H3Cit+, median [Q1-Q3]: 6.0 [3.3–12.3] vs. 12.5 [5.9–22.0] cells/mm², p < 0.001) and with D-dimer levels (H3Cit− vs. H3Cit+: 0.53 [0.32–1.10] vs. 0.84 [0.46–2.75] µg/mL, p = 0.034). The VTE risk was not linked to H3Cit+ tumor vessels (p = 0.613, log-rank). Conclusions: H3Cit in tumor vessels was not associated with VTE. However, H3Cit was linked to a local procoagulant phenotype in glioma, thereby potentially contributing to a systemic hypercoagulable state and thrombus formation.

Stress impacts our health and triggers physiological adaptations, yet the metabolic programs engaged during stress remain incompletely understood. To fill this knowledge gap, we utilize total-body positron emission tomography (PET), multi-OMICS, and endocrine profiling to assess how various murine stress models affect systemic metabolic remodeling. We find that acute immobilization and surgery activate brown adipose tissue as part of the stress response, independently of hypothermia, thereby acting as a highly stress-sensitive metabolic hub. Additionally, we identify stress-specific hypo- and hypermetabolic signatures in different brain regions, and distinguish networks between brain and adipose tissue depots across the different stress groups. Our work presents a novel perspective on stress and its mobilization of metabolic resources and identifies PET imaging of brain and adipose tissue as a valuable, minimally invasive technique for tracking metabolic stress responses in mice, with relevance for animal welfare and disease models, and translational impact for mental health studies and preventive medicine.