MicroRNA Profiling as a Predictive Indicator for Time to First Treatment in Chronic Lymphocytic Leukemia: Insights from the O-CLL1 Prospective Study
Abstract
:1. Introduction
2. Results
2.1. TTFT Prediction by the Basic Model
2.2. TTFT Prediction by miRNAs
2.3. Correlation and Interaction Analysis between miRNAs and Genes Found to Be Related to TTFT by an AI Model
2.4. Pathways Regulation by the 16 miRNAs Linked to TTFT
3. Discussion
4. Materials and Methods
4.1. Patient Population and Study Design
4.2. Assessment of Biological Markers
4.3. miRNAs Analysis
4.4. miRNA–mRNA Correlation, Interaction, and Enrichment Analyses
4.5. Statistical Analyses
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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miRNA-ID | Units of Increase 1 | HR | 95%CI Lower Limit | 95% CI Upper Limit | p-Value |
---|---|---|---|---|---|
1-3p | 1 | 1.166 | 1.006 | 1.352 | 0.041 |
103a-3p | 1 | 0.998 | 0.996 | 1.000 | 0.05 |
106a-5p | 1 | 1.438 | 1.003 | 2.062 | 0.048 |
10b-3p | 1 | 1.239 | 1.055 | 1.456 | 0.009 |
1224-5p | 1 | 1.064 | 1.024 | 1.105 | 0.002 |
1225-5p | 100 | 1.062 | 1.001 | 1.126 | 0.046 |
124-3p | 1 | 1.458 | 1.178 | 1.805 | <0.001 |
125b-5p | 1 | 0.744 | 0.56 | 0.989 | 0.042 |
138-5p | 1 | 0.599 | 0.4 | 0.896 | 0.013 |
140-3p | 1 | 0.991 | 0.986 | 0.996 | 0.001 |
144-3p | 1 | 1.004 | 1.002 | 1.006 | 0.002 |
144-5p | 1 | 1.024 | 1.008 | 1.041 | 0.003 |
146b-5p | 1 | 0.991 | 0.983 | 0.998 | 0.019 |
148a-3p | 1 | 1.006 | 1.002 | 1.010 | 0.007 |
150-5p | 1000 | 0.925 | 0.858 | 0.997 | 0.041 |
150-3p | 1 | 1.035 | 1.009 | 1.062 | 0.008 |
151-3p | 1 | 0.971 | 0.946 | 0.996 | 0.026 |
151-5p | 1 | 0.996 | 0.993 | 0.998 | 0.001 |
155-5p | 100 | 1.058 | 1.014 | 1.104 | 0.009 |
15a-5p | 100 | 1.074 | 1.034 | 1.117 | <0.001 |
184 | 1 | 1.472 | 1.126 | 1.925 | 0.005 |
193a-3p | 1 | 1.132 | 1.026 | 1.250 | 0.014 |
20a-3p | 1 | 1.049 | 1.007 | 1.093 | 0.022 |
21-5p | 1000 | 1.152 | 1.056 | 1.257 | 0.001 |
222-3p | 1 | 0.946 | 0.907 | 0.988 | 0.012 |
223-5p | 1 | 0.819 | 0.712 | 0.943 | 0.006 |
24-1-5p | 1 | 1.312 | 1.013 | 1.698 | 0.04 |
26a-5p | 100 | 0.901 | 0.813 | 0.999 | 0.047 |
28-5p | 1 | 1.005 | 1.001 | 1.009 | 0.012 |
296-3p | 1 | 0.570 | 0.348 | 0.934 | 0.026 |
298 | 1 | 1.307 | 1.022 | 1.670 | 0.033 |
29c-3p | 100 | 0.951 | 0.923 | 0.980 | <0.001 |
29c-5p | 1 | 0.952 | 0.924 | 0.982 | 0.002 |
301a-3p | 1 | 1.038 | 1.005 | 1.073 | 0.024 |
30c-5p | 100 | 0.621 | 0.400 | 0.962 | 0.033 |
323-3p | 1 | 0.646 | 0.426 | 0.979 | 0.04 |
338-5p | 1 | 0.785 | 0.643 | 0.960 | 0.018 |
339-3p | 1 | 0.689 | 0.521 | 0.910 | 0.009 |
33a-3p | 1 | 0.375 | 0.220 | 0.639 | <0.001 |
361-3p | 1 | 0.989 | 0.978 | 0.999 | 0.034 |
370 | 1 | 1.058 | 1.028 | 1.088 | <0.001 |
371-5p | 1 | 1.082 | 1.016 | 1.152 | 0.014 |
373-5p | 1 | 1.071 | 1.006 | 1.14 | 0.031 |
376b-3p | 1 | 1.523 | 1.046 | 2.218 | 0.028 |
491-3p | 1 | 1.766 | 1.331 | 2.343 | <0.001 |
500-3p | 1 | 0.817 | 0.717 | 0.931 | 0.002 |
502-3p | 1 | 0.872 | 0.796 | 0.955 | 0.003 |
502-5p | 1 | 0.673 | 0.504 | 0.898 | 0.007 |
513a-5p | 1 | 1.007 | 1.002 | 1.012 | 0.008 |
518c-5p | 1 | 1.148 | 1.033 | 1.276 | 0.01 |
520b | 1 | 1.234 | 1.067 | 1.426 | 0.005 |
532-3p | 1 | 0.898 | 0.841 | 0.959 | 0.001 |
532-5p | 1 | 0.939 | 0.891 | 0.989 | 0.018 |
552 | 1 | 1.556 | 1.014 | 2.388 | 0.043 |
557 | 1 | 1.197 | 1.099 | 1.303 | <0.001 |
566 | 1 | 1.616 | 1.188 | 2.197 | 0.002 |
574-3p | 1 | 1.030 | 1.006 | 1.055 | 0.015 |
582-3p | 1 | 0.465 | 0.274 | 0.789 | 0.005 |
584-5p | 1 | 1.162 | 1.022 | 1.32 | 0.022 |
596 | 1 | 0.597 | 0.391 | 0.913 | 0.017 |
601 | 1 | 1.069 | 1.01 | 1.131 | 0.022 |
603 | 1 | 1.552 | 1.023 | 2.356 | 0.039 |
625-5p | 1 | 0.960 | 0.940 | 0.981 | <0.001 |
628-3p | 1 | 0.630 | 0.417 | 0.952 | 0.028 |
631 | 1 | 1.180 | 1.006 | 1.385 | 0.042 |
645 | 1 | 1.604 | 1.091 | 2.358 | 0.016 |
659-3p | 1 | 1.114 | 1.01 | 1.228 | 0.03 |
661 | 1 | 0.579 | 0.342 | 0.981 | 0.042 |
665 | 1 | 1.145 | 1.008 | 1.300 | 0.037 |
671-5p | 1 | 1.046 | 1.014 | 1.079 | 0.004 |
877-5p | 1 | 1.245 | 1.031 | 1.503 | 0.023 |
9-3p | 1 | 1.086 | 1.015 | 1.163 | 0.017 |
99a-5p | 1 | 0.615 | 0.421 | 0.898 | 0.012 |
miRNA-ID | Units of Increase 1 | HR | 95% CI Lower Limit | 95% CI Upper Limit | p-Value |
---|---|---|---|---|---|
582-3p | 1 | 0.278 | 0.145 | 0.535 | <0.001 |
33a-3p | 1 | 0.334 | 0.16 | 0.697 | 0.003 |
516a-5p | 1 | 0.490 | 0.297 | 0.810 | 0.005 |
99a-5p | 1 | 0.512 | 0.341 | 0.769 | 0.001 |
296-3p | 1 | 0.539 | 0.301 | 0.967 | 0.038 |
502-5p | 1 | 0.623 | 0.43 | 0.905 | 0.013 |
625-5p | 1 | 0.958 | 0.937 | 0.98 | <0.001 |
29c-3p | 100 | 0.936 | 0.903 | 0.970 | <0.001 |
150-5p | 1000 | 1.112 | 1.005 | 1.231 | 0.039 |
148a-3p | 1 | 1.009 | 1.004 | 1.014 | <0.001 |
28-5p | 1 | 1.01 | 1.005 | 1.014 | <0.001 |
144-5p | 1 | 1.049 | 1.026 | 1.072 | <0.001 |
671-5p | 1 | 1.075 | 1.027 | 1.125 | 0.002 |
1-3p | 1 | 1.261 | 1.047 | 1.517 | 0.014 |
193a-3p | 1 | 1.343 | 1.186 | 1.52 | <0.001 |
124-3p | 1 | 1.536 | 1.233 | 1.913 | <0.001 |
Basic Model | Expanded Model | |
---|---|---|
Harrell’s C-index | 75.0% | 81.1% |
Explained variation in TTFT | 45.4% | 63.3% |
IDI 1 | - | 14.9%, p < 0.001 |
NRI 2 | - | 44.2%, p < 0.001 |
Enrichment | ID | Term Specification | Associated miRNA Genes | Adjusted p-Value | q-Value |
---|---|---|---|---|---|
KEGG ORA summary | hsa05206 | MicroRNAs in cancer | MIR1-2, MIR28, MIR29C, MIR99A, MIR124-3, MIR150, MIR625 | 1.41 × 10−10 | 7.41 × 10−10 |
WikiPathways ORA summary | WP299 | Nuclear receptors in lipid metabolism and toxicity | MIR33A | 0.03 | 0.009 |
WP430 | Statin inhibition of cholesterol production | MIR33A | 0.03 | 0.009 | |
WP1545 | miRNAs involved in DNA damage response | MIR29C | 0.04 | 0.01 | |
WP1601 | Fluoropyrimidine activity | MIR29C | 0.03 | 0.009 | |
WP2023 | Cell differentiation expanded index | MIR150 | 0.04 | 0.01 | |
WP2249 | Metastatic brain tumor | MIR29C | 0.03 | 0.009 |
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Nano, E.; Reggiani, F.; Amaro, A.A.; Monti, P.; Colombo, M.; Bertola, N.; Ferrero, F.; Fais, F.; Bruzzese, A.; Martino, E.A.; et al. MicroRNA Profiling as a Predictive Indicator for Time to First Treatment in Chronic Lymphocytic Leukemia: Insights from the O-CLL1 Prospective Study. Non-Coding RNA 2024, 10, 46. https://doi.org/10.3390/ncrna10050046
Nano E, Reggiani F, Amaro AA, Monti P, Colombo M, Bertola N, Ferrero F, Fais F, Bruzzese A, Martino EA, et al. MicroRNA Profiling as a Predictive Indicator for Time to First Treatment in Chronic Lymphocytic Leukemia: Insights from the O-CLL1 Prospective Study. Non-Coding RNA. 2024; 10(5):46. https://doi.org/10.3390/ncrna10050046
Chicago/Turabian StyleNano, Ennio, Francesco Reggiani, Adriana Agnese Amaro, Paola Monti, Monica Colombo, Nadia Bertola, Fabiana Ferrero, Franco Fais, Antonella Bruzzese, Enrica Antonia Martino, and et al. 2024. "MicroRNA Profiling as a Predictive Indicator for Time to First Treatment in Chronic Lymphocytic Leukemia: Insights from the O-CLL1 Prospective Study" Non-Coding RNA 10, no. 5: 46. https://doi.org/10.3390/ncrna10050046