Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Clinical relevance of circulating MACC1 and S100A4 transcripts for ovarian cancer

[img]
Preview
PDF (Original Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
789kB
[img]
Preview
PDF (Supporting Information) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
145kB

Item Type:Article
Title:Clinical relevance of circulating MACC1 and S100A4 transcripts for ovarian cancer
Creators Name:Link, T. and Kuhlmann, J.D. and Kobelt, D. and Herrmann, P. and Vassileva, Y. and Kramer, M. and Frank, K. and Göckenjan, M. and Wimberger, P. and Stein, U.
Abstract:Metastasis-associated in colon cancer 1 (MACC1) and S100 calcium binding protein A4 (S100A4) are prominent inducers of tumor progression and metastasis. For the first time, we systematically tracked circulating serum levels of MACC1 and S100A4 transcripts in the course of surgery and chemotherapy and analyzed their clinical relevance for ovarian cancer. MACC1 and S100A4 transcripts were quantified in a total of 318 serum samples from 79 ovarian cancer patients by RT-qPCR and digital droplet PCR, respectively. MACC1 and S100A4 transcripts were significantly elevated in serum of ovarian cancer patients, compared to healthy controls (P=0.024; P<0.001). At primary diagnosis, high levels of MACC1 or S100A4 correlated with advanced FIGO-stage (P=0.042; P=0.008), predicted suboptimal debulking surgery and indicated shorter progression-free survival (PFS; P=0.003; P=0.001) and overall survival (OS; P<0.001; P=0.002). This is the first study in ovarian cancer to propose circulating MACC1 and S100A4 transcripts as potential liquid biopsy markers.
Keywords:Ovarian Cancer, MACC1, S100A4, Blood-Based Biomarker, Prognosis, Survival
Source:Molecular Oncology
ISSN:1574-7891
Publisher:Wiley
Volume:13
Number:5
Page Range:1268-1279
Date:May 2019
Official Publication:https://doi.org/10.1002/1878-0261.12484
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library