Abstract
Purpose: We have investigated the use of human urine as a non-invasive medium to screen for molecular biomarkers of carcinomas of the upper gastrointestinal (uGI) tract using SELDI-TOF-MS.
Experimental design: A total of 120 urine specimens from 60 control and 60 uGI cancer patients were analysed to establish a potential biomarker fingerprint for the weak cation exchanger CM10 chip surface, which was validated by blind testing using a further 59 samples from 33 control and 26 uGI cancer patients.
Results: Using Biomarker Pattern software, we established a model with a sensitivity of 98% and specificity of 95% for the learning sample set, and a sensitivity of 96% and specificity of 72% for the validation data set. Model variable importance included six peptides with m/z of 10,230, 10,436, 10,574, 10,311, 10,467, and 10,118 of which the 10, 230 molecular species was the main decider (sensitivity 86% and specificity 80%). Initial protein database searching identified 10,230 as S100-A6, 10,436 as S100-P, 10,467 as S100-A9, and 10,574 as S100-A12 of which S100-A6 and S100-A9 were confirmed by Western blotting.
Conclusions and clinical relevance: We have demonstrated that SELDI-TOF-MS as a screening tool is a rapid and valid methodology in the search for urinary cancer biomarkers, and is potentially useful in defining and consolidating biomarker patterns for uGI cancer screening.
Experimental design: A total of 120 urine specimens from 60 control and 60 uGI cancer patients were analysed to establish a potential biomarker fingerprint for the weak cation exchanger CM10 chip surface, which was validated by blind testing using a further 59 samples from 33 control and 26 uGI cancer patients.
Results: Using Biomarker Pattern software, we established a model with a sensitivity of 98% and specificity of 95% for the learning sample set, and a sensitivity of 96% and specificity of 72% for the validation data set. Model variable importance included six peptides with m/z of 10,230, 10,436, 10,574, 10,311, 10,467, and 10,118 of which the 10, 230 molecular species was the main decider (sensitivity 86% and specificity 80%). Initial protein database searching identified 10,230 as S100-A6, 10,436 as S100-P, 10,467 as S100-A9, and 10,574 as S100-A12 of which S100-A6 and S100-A9 were confirmed by Western blotting.
Conclusions and clinical relevance: We have demonstrated that SELDI-TOF-MS as a screening tool is a rapid and valid methodology in the search for urinary cancer biomarkers, and is potentially useful in defining and consolidating biomarker patterns for uGI cancer screening.
| Original language | English |
|---|---|
| Pages (from-to) | 289-299 |
| Number of pages | 11 |
| Journal | Proteomics. Clinical applications |
| Volume | 5 |
| Issue number | 5-6 |
| DOIs | |
| Publication status | Published - 2011 |
