Development and Validation of a Pathomics Model Using Machine Learning to Predict <i>CXCL8</i> Expression and Prognosis in Head and Neck Cancer

Author:

Wang WeihuaORCID,Ruan SuyuORCID,Xie YuhangORCID,Fang ShengjianORCID,Yang JunxianORCID,Li XueyanORCID,Zhang YuORCID

Abstract

Objectives. The necessity to develop a method for prognostication and to identify novel biomarkers for personalized medicine in patients with head and neck squamous cell carcinoma (HNSCC) cannot be overstated. Recently, pathomics, which relies on quantitative analysis of medical imaging, has come to the forefront. CXCL8, an essential inflammatory cytokine, has been shown to correlate with overall survival (OS). This study examined the relationship between <i>CXCL8</i> mRNA expression and pathomics features and aimed to explore the biological underpinnings of <i>CXCL8</i>.Methods. Clinical information and transcripts per million mRNA sequencing data were obtained from The Cancer Genome Atlas (TCGA)-HNSCC dataset. We identified correlations between <i>CXCL8</i> mRNA expression and patient survival rates using a Kaplan-Meier survival curve. A retrospective analysis of 313 samples diagnosed with HNSCC in the TCGA database was conducted. Pathomics features were extracted from hematoxylin and eosin–stained images, and then the minimum redundancy maximum relevance, with recursive feature elimination (mRMR-RFE) method was applied, followed by screening with the logistic regression algorithm.Results. Kaplan-Meier curves indicated that high expression of <i>CXCL8</i> was significantly associated with decreased OS. The logistic regression pathomics model incorporated 16 radiomics features identified by the mRMR-RFE method in the training set and demonstrated strong performance in the testing set. Calibration plots showed that the probability of high gene expression predicted by the pathomics model was in good agreement with actual observations, suggesting the model’s high clinical applicability.Conclusion. The pathomics model of <i>CXCL8</i> mRNA expression serves as an effective tool for predicting prognosis in patients with HNSCC and can aid in clinical decision-making. Elevated levels of <i>CXCL8</i> expression may lead to reduced DNA damage and are associated with a pro-inflammatory tumor microenvironment, offering a potential therapeutic target.

Publisher

Korean Society of Otorhinolaryngology-Head and Neck Surgery

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