Trem2-expressing multinucleated giant macrophages are a biomarker of good prognosis in head and neck squamous cell carcinoma.
Grégoire GessainAhmed-Amine AnzaliMarvin LerousseauKevin MulderMathilde BiedAnne AuperinDaniel StockholmNicolas SignolleSassi FarahMaria Eugénia Marques da CostaAntonin MarchaisAlexandre SayadiDaniela WeidnerStefan UderhardtQuentin BlampeySumanth Reddy NakkireddySophie BroutinCharles-Antoine DutertrePierre BussonThomas WalterAlix MarhicAntoine Moya-PlanaJoanne GuerlainIngrid BreuskinOdile CasiraghiPhilippe GorpheMarion ClasseJean Yves ScoazecCamille BlériotFlorent GinhouxPublished in: Cancer discovery (2024)
Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk-management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC) - a type of macrophages - in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative-chemotherapy-treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the anti-tumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor associated macrophages, which co-localized in keratin tumor niches.
Keyphrases
- deep learning
- induced apoptosis
- cell cycle arrest
- clinical practice
- squamous cell
- newly diagnosed
- end stage renal disease
- patients undergoing
- convolutional neural network
- endoplasmic reticulum stress
- type diabetes
- prognostic factors
- signaling pathway
- machine learning
- cell death
- metabolic syndrome
- hiv infected
- artificial intelligence
- optical coherence tomography
- bone marrow
- locally advanced
- peritoneal dialysis
- patient reported outcomes
- insulin resistance
- rna seq
- drug induced
- skeletal muscle
- replacement therapy