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| Status |
Public on Apr 12, 2018 |
| Title |
Circulating microRNA of advanced colorectal cancer patients |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by RT-PCR
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| Summary |
Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex -omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed an innovative multi-objective optimisation method which effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. We have found 9 signatures of colorectal cancer prognosis comprising a total of 19 circulating microRNAs. The identified signatures predict the patients’ survival outcome and target pathways underlying colorectal cancer progression. The altered expression of the microRNAs within these signatures was confirmed in two independent public datasets of plasma and tumour samples of patients in early stage versus advanced colorectal cancer.
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| Overall design |
Total RNA was isolated from patient plasma samples. Global profiling of miRNA was carried out using the OpenArray platform. The entire RT reaction was used for pre-amplification and the resultant cDNA combined with OpenArray real-time PCR master mix and loaded onto OpenArray miRNA panel plates and run according to the default protocol for reaction conditions.
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| Contributor(s) |
Diakos C, Vafaee F, Kirschner MB, Reid G, Michael M, Horvath LG, Cheng ZJ, Kuncic Z, Clarke S |
| Citation(s) |
29872543 |
| |
| Submission date |
Apr 11, 2018 |
| Last update date |
Jul 14, 2018 |
| Contact name |
Fatemeh Vafaee |
| E-mail(s) |
f.vafaee@unsw.edu.au
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| Phone |
0061403012736
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| Organization name |
University of New South Wales
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| Department |
School of Biotechnology and Biomolecular Sciences
|
| Street address |
Gate 11 Botany Street, UNSW Sydney, School of BABS
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| City |
Sydney |
| State/province |
UNSW |
| ZIP/Postal code |
2052 |
| Country |
Australia |
| |
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| Platforms (1) |
| GPL17837 |
TaqMan OpenArray Human MicroRNA Panel (4461104) |
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| Samples (75)
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| Relations |
| BioProject |
PRJNA449608 |
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