Related Experiment Video
Updated: Aug 7, 2026
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Detection of hypopharyngeal squamous cell carcinoma using serum proteomics
Liang Zhou1, Lei Cheng, Lei Tao
1Department of Otolaryngology-Head and Neck Surgery, Fudan University Affiliated Eye, Ear, Nose and Throat Hospital, Shanghai, China. zhlwc@online.sh.cn
Conclusions:
The combination of surface-enhanced laser desorption/ionization (SELDI) with bioinformatics tools could help find serum proteome biomarkers and establish a predictive model for early detection of hypopharyngeal squamous cell carcinoma (HSCC).
Objectives:
Proteomic profiling of serum using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is an emerging technique to identify new biomarkers in biological fluids and to establish clinically useful diagnostic computational models. We used it to find new potential biomarkers and to establish a predictive model for early detection of HSCC.
Materials And Methods:
One hundred serum samples including 48 from HSCC patients and 52 from normal controls which were divided into a training set and a blind testing set were treated on WCX2 and IMAC3 protein chip, and serum protein or peptide patterns were detected by SELDI-TOF-MS. The data of spectra were analyzed by Biomarker Wizard software to screen serum proteome biomarkers of HSCC. A decision tree classification algorithm and blind validation were determined by Biomarker Pattern Software (BPS).
Results:
Ranging from 2 to 30 kDa, 45 potential biomarkers could differentiate HSCC patients from normal controls (p < 0.05). Among them four candidate protein peaks with m/z values of 7796, 4216, 5927, and 5361Da were selected to establish a predictive model by BPS with sensitivity of 94% and specificity of 89%. A sensitivity of 92% and specificity of 82% were validated in the blind testing set.
