| Autor: |
Sivadasan P; Head and Neck Oncology, Mazumdar Shaw Medical Center, Narayana Health, Bangalore 560099, India ; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India., Kumar Gupta M; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India., Sathe GJ; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India., Balakrishnan L; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India., Palit P; Head and Neck Oncology, Mazumdar Shaw Medical Center, Narayana Health, Bangalore 560099, India., Gowda H; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India., Suresh A; Head and Neck Oncology, Mazumdar Shaw Medical Center, Narayana Health, Bangalore 560099, India ; Mazumdar Shaw Center for Translational Research, Mazumdar Shaw Medical Foundation, Narayana Health, Bangalore 560099, India., Abraham Kuriakose M; Head and Neck Oncology, Mazumdar Shaw Medical Center, Narayana Health, Bangalore 560099, India ; Mazumdar Shaw Center for Translational Research, Mazumdar Shaw Medical Foundation, Narayana Health, Bangalore 560099, India., Sirdeshmukh R; Institute of Bioinformatics, International Tech Park, Bangalore 560066, India ; Mazumdar Shaw Center for Translational Research, Mazumdar Shaw Medical Foundation, Narayana Health, Bangalore 560099, India. |
| Abstrakt: |
Salivary proteins are an important source for developing marker-based assays for oral cancers. To get an insight into the proteins present in human saliva, we applied multiple strategies involving affinity-based depletion of abundant proteins, fractionation of the resulting proteins or their tryptic peptides followed by LC-MS/MS analysis, using high resolution mass spectrometry. By integrating the protein identifications observed by us with those from similar workflows employed in earlier investigations, we compiled an updated salivary proteome. We have mapped the salivary proteome to the published data on differentially expressed proteins from oral cancer tissues and also for their secretory features using prediction tools, SignalP 4.1, TMHMM 2c and Exocarta. Proteotypic peptides for the subset of proteins implicated in oral cancer and mapped to any two of the prediction tools for secretory potential have been listed. The data here are related to the research article "Human saliva proteome - a resource of potential biomarkers for oral cancer" in the Journal of Proteomics [1]. |
