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A coordinate deregulation of microRNAs expressed in mucosa adjacent to tumor predicts relapse after resection in localized colon cancer

Overview of attention for article published in Molecular Cancer, January 2018
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Title
A coordinate deregulation of microRNAs expressed in mucosa adjacent to tumor predicts relapse after resection in localized colon cancer
Published in
Molecular Cancer, January 2018
DOI 10.1186/s12943-018-0770-8
Pubmed ID
Authors

Angela Grassi, Lisa Perilli, Laura Albertoni, Sofia Tessarollo, Claudia Mescoli, Emanuele D. L. Urso, Matteo Fassan, Massimo Rugge, Paola Zanovello

Abstract

Up to 20% of colorectal cancer (CRC) node-negative patients develop loco-regional or distant recurrences within 5 years from surgery. No predictive biomarker able to identify the node-negative subjects at high risk of relapse after curative treatment is presently available.Forty-eight localized (i.e. stage I-II) colon cancer patients who underwent radical tumor resection were considered. The expression of five miRNAs, involved in CRC progression, was investigated by qRT-PCR in both tumor tissue and matched normal colon mucosa.Interestingly, we found that the coordinate deregulation of four miRNAs (i.e. miR-18a, miR-21, miR-182 and miR-183), evaluated in the normal mucosa adjacent to tumor, is predictive of relapse within 55 months from curative surgery.Our results, if confirmed in independent studies, may help to identify high-risk patients who could benefit most from adjuvant therapy. Moreover, this work highlights the importance of extending the search for tissue biomarkers also to the tumor-adjacent mucosa.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 18%
Student > Doctoral Student 2 12%
Researcher 2 12%
Student > Bachelor 1 6%
Librarian 1 6%
Other 2 12%
Unknown 6 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 18%
Medicine and Dentistry 3 18%
Nursing and Health Professions 1 6%
Chemistry 1 6%
Engineering 1 6%
Other 0 0%
Unknown 8 47%