Pathomics models based on H&E slides to predict the survival prognosis of patients with head and neck squamous cell carcinoma

Abstract

Abstract Head and neck squamous cell carcinoma is the most common tumor of the head and neck region and has a low survival rate. This study innovatively proposes the use of pathomics to determine the correlation between clinicopathological and genomic data and patient prognosis, while exploring the underlying molecular mechanisms behind histology subtypes. In this study, hematoxylin and eosin slides were subjected to image segmentation and feature extraction, followed by unsupervised clustering analysis, to establish a predictive model for survival. Differential gene expression and pathways were explored based on the pathological subtypes, and transcriptome data from our hospital were used for validation. A total of 485 samples with complete pathological images and clinical information were included in this study, with 271 from the TCGA dataset and 214 from patients from our hospital with a 5-year follow-up. Thirteen pathomechanical features were selected based on different survival rates. In the training and validation set, there were significant differences in the pathological grade among the different pathological histology subtypes. In addition, different pathological classification also differed in early-stage tumor (Histologic grade G1/G2). A total of 76 differentially expressed genes were identified among the different pathological subtypes that were enriched in energy metabolism-related pathways. Visualization of mutation profiles for different pathomic subtypes revealed high mutation rates in PI3K-AKT, MAPK, and apoptosis pathways. Finally, using TCGA and our hospital's transcriptome data, we identified the differential expression of MTOR, COL9A1, and CD44 among pathological subtypes. The pathological histological subtype model had excellent predictive performance for survival. MTOR, COL9A1, and CD44 may regulate tumor differentiation and the immune microenvironment to ultimately drive pathological changes.