The Use of Plasma Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Proteomic Patterns for Detection of Head and Neck Squamous Cell Cancers

• Published in: Clinical cancer research 2004-07, Vol.10 (14), p.4806-4812
• Main Authors: SOLTYS, Scott G, LE, Quynh-Thu, SHI, Gongyi, TIBSHIRANI, Robert, GIACCIA, A. J, KOONG, Albert C
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Antineoplastic agents; Biological and medical sciences; Biomarkers, Tumor - blood; Female; Head and Neck Neoplasms - blood; Head and Neck Neoplasms - diagnosis; Head and Neck Neoplasms - metabolism; Humans; Male; Medical sciences; Middle Aged; Neoplasms, Squamous Cell - blood; Neoplasms, Squamous Cell - diagnosis; Neoplasms, Squamous Cell - metabolism; Pharmacology. Drug treatments; Proteome - analysis; Reproducibility of Results; Sensitivity and Specificity; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization - methods; Tumors
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1078-0432.CCR-03-0469

Purpose: Our study was undertaken to determine the utility of plasma proteomic profiling using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry for the detection of head and neck squamous cell carcinomas (HNSCCs). Experimental Design: Pretreatment plasma samples from HNSCC patients or controls without known neoplastic disease were analyzed on the Protein Biology System IIc SELDI-TOF mass spectrometer (Ciphergen Biosystems, Fremont, CA). Proteomic spectra of mass:charge ratio ( m / z ) were generated by the application of plasma to immobilized metal-affinity-capture (IMAC) ProteinChip arrays activated with copper. A total of 37,356 data points were generated for each sample. A training set of spectra from 56 cancer patients and 52 controls were applied to the “Lasso” technique to identify protein profiles that can distinguish cancer from noncancer, and cross-validation was used to determine test errors in this training set. The discovery pattern was then used to classify a separate masked test set of 57 cancer and 52 controls. In total, we analyzed the proteomic spectra of 113 cancer patients and 104 controls. Results: The Lasso approach identified 65 significant data points for the discrimination of normal from cancer profiles. The discriminatory pattern correctly identified 39 of 57 HNSCC patients and 40 of 52 noncancer controls in the masked test set. These results yielded a sensitivity of 68% and specificity of 73%. Subgroup analyses in the test set of four different demographic factors (age, gender, and cigarette and alcohol use) that can potentially confound the interpretation of the results suggest that this model tended to overpredict cancer in control smokers. Conclusions: Plasma proteomic profiling with SELDI-TOF mass spectrometry provides moderate sensitivity and specificity in discriminating HNSCC. Further improvement and validation of this approach is needed to determine its usefulness in screening for this disease.