iScience (Dec 2023)
Spatial subsetting enables integrative modeling of oral squamous cell carcinoma multiplex imaging data
- Jakob Einhaus,
- Dyani K. Gaudilliere,
- Julien Hedou,
- Dorien Feyaerts,
- Michael G. Ozawa,
- Masaki Sato,
- Edward A. Ganio,
- Amy S. Tsai,
- Ina A. Stelzer,
- Karl C. Bruckman,
- Jonas N. Amar,
- Maximilian Sabayev,
- Thomas A. Bonham,
- Joshua Gillard,
- Maïgane Diop,
- Amelie Cambriel,
- Zala N. Mihalic,
- Tulio Valdez,
- Stanley Y. Liu,
- Leticia Feirrera,
- David K. Lam,
- John B. Sunwoo,
- Christian M. Schürch,
- Brice Gaudilliere,
- Xiaoyuan Han
Affiliations
- Jakob Einhaus
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA; Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany
- Dyani K. Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Julien Hedou
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Dorien Feyaerts
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Michael G. Ozawa
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Masaki Sato
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Edward A. Ganio
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Amy S. Tsai
- Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Ina A. Stelzer
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Karl C. Bruckman
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Jonas N. Amar
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Maximilian Sabayev
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Thomas A. Bonham
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Joshua Gillard
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Maïgane Diop
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Amelie Cambriel
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Zala N. Mihalic
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Tulio Valdez
- Division of Pediatrics, Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA, USA
- Stanley Y. Liu
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA; Division of Sleep Surgery, Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA, USA
- Leticia Feirrera
- Department of Oral and Maxillofacial Surgery, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA, USA
- David K. Lam
- Department of Oral and Maxillofacial Surgery, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA, USA
- John B. Sunwoo
- Division of Head and Neck Surgery, Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA, USA
- Christian M. Schürch
- Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- Brice Gaudilliere
- Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA; Corresponding author
- Xiaoyuan Han
- Department of Biomedical Sciences, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA, USA
- Journal volume & issue
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Vol. 26,
no. 12
p. 108486
Abstract
Summary: Oral squamous cell carcinoma (OSCC), a prevalent and aggressive neoplasm, poses a significant challenge due to poor prognosis and limited prognostic biomarkers. Leveraging highly multiplexed imaging mass cytometry, we investigated the tumor immune microenvironment (TIME) in OSCC biopsies, characterizing immune cell distribution and signaling activity at the tumor-invasive front. Our spatial subsetting approach standardized cellular populations by tissue zone, improving feature reproducibility and revealing TIME patterns accompanying loss-of-differentiation. Employing a machine-learning pipeline combining reliable feature selection with multivariable modeling, we achieved accurate histological grade classification (AUC = 0.88). Three model features correlated with clinical outcomes in an independent cohort: granulocyte MAPKAPK2 signaling at the tumor front, stromal CD4+ memory T cell size, and the distance of fibroblasts from the tumor border. This study establishes a robust modeling framework for distilling complex imaging data, uncovering sentinel characteristics of the OSCC TIME to facilitate prognostic biomarkers discovery for recurrence risk stratification and immunomodulatory therapy development.
