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1.
J Proteome Res ; 13(11): 4889-900, 2014 Nov 07.
Article in English | MEDLINE | ID: mdl-25184692

ABSTRACT

Clear cell renal cell carcinoma is the most prevalent of all reported kidney cancer cases, and currently there are no markers for early diagnosis. This has stimulated great research interest recently because early detection of the disease can significantly improve the low survival rate. Combining the proteome, glycoproteome, and N-glycome data from clear cell renal cell carcinoma plasma has the potential of identifying candidate markers for early diagnosis and prognosis and/or to monitor disease recurrence. Here, we report on the utilization of a multi-dimensional fractionation approach (12P-M-LAC) and LC-MS/MS to comprehensively investigate clear cell renal cell carcinoma plasma collected before (disease) and after (non-disease) curative nephrectomy (n = 40). Proteins detected in the subproteomes were investigated via label-free quantification. Protein abundance analysis revealed a number of low-level proteins with significant differential expression levels in disease samples, including HSPG2, CD146, ECM1, SELL, SYNE1, and VCAM1. Importantly, we observed a strong correlation between differentially expressed proteins and clinical status of the patient. Investigation of the glycoproteome returned 13 candidate glycoproteins with significant differential M-LAC column binding. Qualitative analysis indicated that 62% of selected candidate glycoproteins showed higher levels (upregulation) in M-LAC bound fraction of disease samples. This observation was further confirmed by released N-glycans data in which 53% of identified N-glycans were present at different levels in plasma in the disease vs non-disease samples. This striking result demonstrates the potential for significant protein glycosylation alterations in clear cell renal cell carcinoma cancer plasma. With future validation in a larger cohort, information derived from this study may lead to the development of clear cell renal cell carcinoma candidate biomarkers.


Subject(s)
Biomarkers, Tumor/blood , Carcinoma, Renal Cell/blood , Carcinoma, Renal Cell/diagnosis , Glycoproteins/metabolism , Polysaccharides/metabolism , Proteome/metabolism , Proteomics/methods , Carcinoma, Renal Cell/surgery , Cell Fractionation , Chromatography, Liquid , Humans , Nephrectomy , Postoperative Period , Tandem Mass Spectrometry
2.
J Proteome Res ; 13(6): 2749-60, 2014 Jun 06.
Article in English | MEDLINE | ID: mdl-24669763

ABSTRACT

As part of the chromosome-centric human proteome project (C-HPP) initiative, we report our progress on the annotation of chromosome 22. Chromosome 22, spanning 51 million base pairs, was the first chromosome to be sequenced. Gene dosage alterations on this chromosome have been shown to be associated with a number of congenital anomalies. In addition, several rare but aggressive tumors have been associated with this chromosome. A number of important gene families including immunoglobulin lambda locus, Crystallin beta family, and APOBEC gene family are located on this chromosome. On the basis of proteomic profiling of 30 histologically normal tissues and cells using high-resolution mass spectrometry, we show protein evidence of 367 genes on chromosome 22. Importantly, this includes 47 proteins, which are currently annotated as "missing" proteins. We also confirmed the translation start sites of 120 chromosome 22-encoded proteins. Employing a comprehensive proteogenomics analysis pipeline, we provide evidence of novel coding regions on this chromosome which include upstream ORFs and novel exons in addition to correcting existing gene structures. We describe tissue-wise expression of the proteins and the distribution of gene families on this chromosome. These data have been deposited to ProteomeXchange with the identifier PXD000561.


Subject(s)
Chromosomes, Human, Pair 22/genetics , Proteome/genetics , Amino Acid Sequence , Genes, Neoplasm , Humans , Molecular Sequence Annotation , Molecular Sequence Data , Open Reading Frames , Peptide Mapping , Proteome/chemistry , Proteome/metabolism , Proteomics
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