↓ Skip to main content

PLOS

Circulating MACC1 Transcripts in Colorectal Cancer Patient Plasma Predict Metastasis and Prognosis

Overview of attention for article published in PLOS ONE, November 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
66 Mendeley
Title
Circulating MACC1 Transcripts in Colorectal Cancer Patient Plasma Predict Metastasis and Prognosis
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049249
Pubmed ID
Authors

Ulrike Stein, Susen Burock, Pia Herrmann, Ina Wendler, Markus Niederstrasser, Klaus-Dieter Wernecke, Peter M. Schlag

Abstract

Metastasis is the most frequent cause of treatment failure and death in colorectal cancer. Early detection of tumors and metastases is crucial for improving treatment strategies and patient outcome. Development of reliable biomarkers and simple tests routinely applicable in the clinic for detection, prognostication, and therapy monitoring is of special interest. We recently identified the novel gene Metastasis-Associated in Colon Cancer 1 (MACC1), a key regulator of the HGF/Met-pathway. MACC1 is a strong prognostic biomarker for colon cancer metastasis and allows identification of high-risk subjects in early stages, when determined in patients' primary tumors. To overcome the limitation of a restricted number of molecular analyses in tumor tissue, the establishment of a non-invasive blood test for early identification of high-risk cancer patients, for monitoring disease course and therapy response is strongly needed.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Austria 1 2%
South Africa 1 2%
Japan 1 2%
United States 1 2%
Unknown 61 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 27%
Researcher 16 24%
Student > Master 8 12%
Other 4 6%
Student > Bachelor 3 5%
Other 11 17%
Unknown 6 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 26%
Medicine and Dentistry 16 24%
Biochemistry, Genetics and Molecular Biology 11 17%
Engineering 3 5%
Nursing and Health Professions 3 5%
Other 9 14%
Unknown 7 11%