Study for metastasis prediction of head and neck squamous cell carcinomas using RNA-sequencing data and PET image feature

Abstract

The aim of this study is to predict the head and neck squamous cell carcinomas (HNSCs) patient metastasis using PET radiomics with RNA-sequencing data. We performed Gene set enrichment analysis (GSEA) and identified 72 genes have important roles as Epithelial mesenchymal transition (EMT) functional modules by the mount of gene expression pattern during the cancer metastasis. The 47 features were extracted form PET images by local image features extraction. GLZLM_LZHGE and CXCL6, SHAPE_Volume and CLCL6, GLCM_Energy and COL11A1 identified as a high relation by P-value. The test and training value PETr and FEG were 0.45 and 0.50 in LR and 0.75 and 0.83 in GB, respectively.