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 37356 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.
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 37356 data points were generated for each sample. A training set of spectra from 56 cancerpatients 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 cancerpatients 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.
Authors: Alexandra Lucs; Benjamin Saltman; Christine H Chung; Bettie M Steinberg; David L Schwartz Journal: Head Neck Date: 2012-01-27 Impact factor: 3.147
Authors: Xiaolan Zhang; Ming Jin; Haifeng Wu; Tibor Nadasdy; Gyongyi Nadasdy; Nathan Harris; Kari Green-Church; Haikady Nagaraja; Daniel J Birmingham; Chack-Yung Yu; Lee A Hebert; Brad H Rovin Journal: Kidney Int Date: 2008-07-02 Impact factor: 10.612
Authors: John C Whitin; Taichang Jang; Milton Merchant; Tom T-S Yu; Kenneth Lau; Benjamin Recht; Harvey J Cohen; Lawrence Recht Journal: PLoS One Date: 2012-11-19 Impact factor: 3.240