Back to Search
Start Over
MicroRNA Expression Profiling Predicts Nodal Status and Disease Recurrence in Patients Treated with Curative Intent for Colorectal Cancer.
- Source :
-
Cancers [Cancers (Basel)] 2022 Apr 23; Vol. 14 (9). Date of Electronic Publication: 2022 Apr 23. - Publication Year :
- 2022
-
Abstract
- Background: Approximately one-third of colorectal cancer (CRC) patients will suffer recurrence. MiRNAs are small non-coding RNAs that play important roles in gene expression. We aimed to correlate miRNA expression with aggressive clinicopathological characteristics and survival outcomes in CRC. Methods: Tumour samples were extracted from 74 CRC patients. MiRNAs were quantified using real-time reverse transcriptase polymerase chain reaction. Descriptive statistics and Cox regression analyses were performed to correlate miRNA targets with clinicopathological and outcome data. Results: Aberrant miR-21 and miR-135b expression correlate with increased nodal stage (p = 0.039, p = 0.022). Using univariable Cox regression analyses, reduced miR-135b (β-coefficient −1.126, hazard ratio 0.324, standard error (SE) 0.4698, p = 0.017) and increased miR-195 (β-coefficient 1.442, hazard ratio 4.229, SE 0.446, p = 0.001) predicted time to disease recurrence. Survival regression trees analysis illustrated a relative cut-off of ≤0.488 for miR-195 and a relative cut-off of >−0.218 for miR-135b; both were associated with improved disease recurrence (p < 0.001, p = 0.015). Using multivariable analysis with all targets as predictors, miR-195 (β-coefficient 3.187, SE 1.419, p = 0.025) was the sole significant independent predictor of recurrence. Conclusion: MiR-195 has strong value in predicting time to recurrence in CRC patients. Additionally, miR-21 and miR-135b predict the degree nodal burden. Future studies may include these findings to personalize therapeutic and surgical decision making.
Details
- Language :
- English
- ISSN :
- 2072-6694
- Volume :
- 14
- Issue :
- 9
- Database :
- MEDLINE
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 35565239
- Full Text :
- https://doi.org/10.3390/cancers14092109