Prognostic Value of MicroRNAs in Preoperative Treated Rectal Cancer

• Main Authors: Azadeh Azizian, Ingo Epping, Frank Kramer, Peter Jo, Markus Bernhardt, Julia Kitz, Gabriela Salinas, Hendrik A. Wolff, Marian Grade, Tim Beißbarth, B. Michael Ghadimi, Jochen Gaedcke
• Format: Article
• Language: English
• Published: MDPI AG 2016-04-01
• Series: International Journal of Molecular Sciences
• Subjects: rectal cancer; prognosis; tumor regression grade; biomarkers; miRNA; chemoradiotherapy
• Online Access: http://www.mdpi.com/1422-0067/17/4/568

Background: Patients with locally advanced rectal cancer are treated with preoperative chemoradiotherapy followed by surgical resection. Despite similar clinical parameters (uT2-3, uN+) and standard therapy, patients’ prognoses differ widely. A possible prediction of prognosis through microRNAs as biomarkers out of treatment-naïve biopsies would allow individualized therapy options. Methods: Microarray analysis of 45 microdissected preoperative biopsies from patients with rectal cancer was performed to identify potential microRNAs to predict overall survival, disease-free survival, cancer-specific survival, distant-metastasis-free survival, tumor regression grade, or nodal stage. Quantitative real-time polymerase chain reaction (qPCR) was performed on an independent set of 147 rectal cancer patients to validate relevant miRNAs. Results: In the microarray screen, 14 microRNAs were significantly correlated to overall survival. Five microRNAs were included from previous work. Finally, 19 miRNAs were evaluated by qPCR. miR-515-5p, miR-573, miR-579 and miR-802 demonstrated significant correlation with overall survival and cancer-specific survival (p < 0.05). miR-573 was also significantly correlated with the tumor regression grade after preoperative chemoradiotherapy. miR-133b showed a significant correlation with distant-metastasis-free survival. miR-146b expression levels showed a significant correlation with nodal stage. Conclusion: Specific microRNAs can be used as biomarkers to predict prognosis of patients with rectal cancer and possibly stratify patients’ therapy if validated in a prospective study.