TY - JOUR
T1 - Urinary CE-MS peptide marker pattern for detection of solid tumors
AU - Belczacka, Iwona
AU - Latosinska, Agnieszka
AU - Siwy, Justyna
AU - Metzger, Jochen
AU - Merseburger, Axel S.
AU - Mischak, Harald
AU - Vlahou, Antonia
AU - Frantzi, Maria
AU - Jankowski, Vera
N1 - Funding Information:
This work was supported by the Chromatin3D grant n°622934 (Chromatin3D-MSCA-ITN) project funded by the European Commission.
Publisher Copyright:
© 2018 The Author(s).
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.
AB - Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.
UR - http://www.scopus.com/inward/record.url?scp=85044606389&partnerID=8YFLogxK
U2 - 10.1038/s41598-018-23585-y
DO - 10.1038/s41598-018-23585-y
M3 - Journal articles
C2 - 29588543
AN - SCOPUS:85044606389
VL - 8
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
IS - 1
M1 - 5227
ER -
