10.1021/pr500591e.s002
Francisca
O. Gbormittah
Francisca
O.
Gbormittah
Ling Y. Lee
Ling Y.
Lee
KyOnese Taylor
KyOnese
Taylor
William S. Hancock
William S.
Hancock
Othon Iliopoulos
Othon
Iliopoulos
Comparative Studies of the
Proteome, Glycoproteome, and N‑Glycome of Clear Cell Renal
Cell Carcinoma Plasma before and after Curative Nephrectomy
American Chemical Society
2015
cell carcinoma cancer plasma
kidney cancer cases
cell carcinoma plasma
Protein abundance analysis
Curative NephrectomyClear cell
protein glycosylation alterations
ECM
13 candidate glycoproteins
Clear Cell Renal Cell Carcinoma Plasma
SYNE
disease samples
HSPG
LC
VCAM 1. Importantly
cell carcinoma candidate biomarkers
2015-12-17 05:39:30
Dataset
https://acs.figshare.com/articles/dataset/Comparative_Studies_of_the_Proteome_Glycoproteome_and_N_Glycome_of_Clear_Cell_Renal_Cell_Carcinoma_Plasma_before_and_after_Curative_Nephrectomy/2043372
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 (<i>n</i> =
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.