MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patient Cohorts and Specimens
2.2. Isolation and Processing of Blood Cells
2.3. Assessment of Purity of Isolated RBCs, PBMCs, and Neutrophils
2.4. RNA Isolation
2.5. Real-Time PCR-Based Microarray Analysis of miRNAs
2.6. Droplet Digital PCR (ddPCR) Analysis of miRNAs
2.7. Statistical Analysis
3. Results
3.1. Isolation and Purification of Blood Cells and RNA Samples
3.2. Distinct miRNA Patterns Can Differentiate among Various Blood Cell Types
3.3. Distinct Cell-Specific miRNA Profiles Associated with Lung Cancer Patients
3.4. Distinct miRNA Profiles in Cell Types for Differentiating Lung Cancer from Controls
3.5. Integrated miRNAs from Distinct Blood Cell Types Exhibit Synergistic Effects on Lung Cancer Detection
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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An Exploratory Set | A Validation Set | ||||
---|---|---|---|---|---|
NSCLC cases (n = 26) | Controls (n = 26) | NSCLC cases (n = 42) | Controls (n = 39) | ||
Age | 66.73 (SD 11.25) | 65.782 (SD 10.39) | Age | 65.38 (SD 10.23) | 64.74 (SD 10.26) |
Sex | Sex | ||||
Female | 9 | 9 | Female | 12 | 11 |
Male | 17 | 17 | Male | 30 | 28 |
Race | Race | ||||
AAs | 11 | 11 | AAs | 26 | 25 |
WAs | 16 | 16 | WAs | 16 | 14 |
Smoking pack-years (median) | 32.7 | 30.9 | Smoking pack-years (median) | 33.8 | 31.2 |
Pulmonary nodule size (mm) | 21.26 (SD 10.25) | 6.72 (SD 3.58) | Pulmonary nodule size (mm) | 20.25 (SD 11.38) | 6.63 (SD 3.97) |
Stage | Stage | ||||
Stage I | 7 | Stage I | 10 | ||
Stage II | 5 | Stage II | 8 | ||
Stage III | 8 | Stage III | 9 | ||
Stage IV | 6 | Stage IV | 12 | ||
Unknown | 3 | ||||
Histological type | Histological type | ||||
Adenocarcinoma | 15 | AC | 26 | ||
SCC | 11 | SCC | 16 |
miRNAs | Mean Expression (Controls) | Mean Expression (Cancer Patients) | Mann–Whitney U Statistic | FDR-Adjusted p-Value |
---|---|---|---|---|
RBC miR-93-5p | 0.922 | 1.529 | 41 | <0.001 |
RBC miR-449b-5p | −0.585 | 0.370 | 116 | <0.001 |
RBC miR-29c-3p | −0.585 | −0.145 | 189 | 0.006 * |
RBC miR-15a-5p | 2.039 | −1.041 | 10 | <0.001 * |
RBC miR-449a | 2.431 | −1.299 | 0 | <0.001 * |
RBC miR-148a-3p | 2.728 | −1.701 | 0 | <0.001 * |
Neutrophil miR-423-3p | −0.464 | 1.550 | 75 | <0.001 |
Neutrophil miR-574-3p | −0.255 | 1.014 | 2 | <0.001 |
Neutrophil miR-26a-2-3p | 0.926 | −0.454 | 6 | <0.001 * |
PBMC miR-576-3p | −0.754 | 1.476 | 16 | <0.001 |
PBMC miR-19b-3p | −0.105 | 1.219 | 126 | <0.001 |
PBMC miR-29b-3p | 1.739 | −0.528 | 0 | <0.001 * |
miRNAs | Mean Expression (Controls) | Mean Expression (Cancer Patients) | Mann–Whitney U Statistic | FDR-Adjusted p-Value |
---|---|---|---|---|
RBC miR-93-5p | 38.443 | 52.000 | 474 | 0.009 |
RBC miR-449b-5p | 0.016 | 0.022 | 631 | 0.008 |
RBC miR-29c-3p | 3.930 | 3.030 | 561 | 0.014 * |
RBC miR-15a-5p | 151.015 | 112.129 | 506 | 0.003 * |
PBMC miR-576-3p | 0.045 | 0.056 | 576 | 0.021 |
PBMC miR-19b-3p | 24.834 | 27.016 | 515 | 0.004 |
PBMC miR-29b-3p | 8.220 | 6.855 | 438 | 0.001 * |
Neutrophil miR-574-3p | 0.605 | 0.790 | 532 | 0.010 |
Neutrophil miR-26a-2-3p | 0.031 | 0.019 * | 397 | 0.003 * |
AUC, % (95% CI) | Sensitivity, % (95% CI) | Specificity, % (95% CI) | |
---|---|---|---|
A panel of three RBC miRNA biomarkers for NSCLC | 0.76 (0.64 to 0.87) | 77.42% (58.90% to 90.41%) | 68.29% (51.91% to 81.92%) |
A panel of four RBC miRNA biomarkers for AC | 0.84 (0.72 to 0.96) | 87.50% (61.65% to 98.45%) | 80.49% (65.13% to 91.18%) |
A panel of four RBC miRNA biomarkers for SCC | 0.74 (0.57 to 0.90) | 71.43% (29.04% to 96.33%) | 80.49% (65.13% to 91.18%) |
A panel of three PBMC miRNA biomarkers for NSCLC | 0.75 (0.63 to 0.86) | 70.59% (52.52% to 84.90%) | 65.79% (48.65% to 80.37%) |
A PBMC miRNA biomarker for AC | 0.73 (0.59 to 0.86) | 57.14% (28.86% to 82.34%) | 67.44% (51.46% to 80.92%) |
A panel of three PBMC miRNA biomarkers for SCC | 0.85 (0.72to 0.97) | 72.73% (39.03% to 93.98%) | 86.49% (71.23% to 95.46%) |
A panel of two neutrophil miRNA biomarkers for NSCLC | 0.69 (0.57 to 0.82) | 64.10% (47.18% to 78.80%) | 63.64% (45.12% to 79.60%) |
A neutrophil miRNA biomarker for AC | 0.74 (0.61 to 0.87) | 53.33% (26.59% to 78.73%) | 66.67% (50.45% to 80.43%) |
Integrated panel of biomarkers for NSCLC | 0.87 (0.79to 0.96) | 8056%, (63.98% to 91.81%) | 83.33% (67.19% to 93.63% |
Integrated panel of biomarkers for AC | 0.90 (0.79 to 1.00) | 85.00% (62.11% to 96.79%) | 86.49% (71.23% to 95.46%) |
Integrated panel of biomarkers for SCC | 0.95 (0.89 to 1.00) | 81.82% (48.22% to 97.72%) | 89.19% (74.58% to 96.97%) |
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Geng, X.; Ma, J.; Dhilipkannah, P.; Jiang, F. MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis. Cancers 2023, 15, 5312. https://doi.org/10.3390/cancers15225312
Geng X, Ma J, Dhilipkannah P, Jiang F. MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis. Cancers. 2023; 15(22):5312. https://doi.org/10.3390/cancers15225312
Chicago/Turabian StyleGeng, Xinyan, Jie Ma, Pushpa Dhilipkannah, and Feng Jiang. 2023. "MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis" Cancers 15, no. 22: 5312. https://doi.org/10.3390/cancers15225312
APA StyleGeng, X., Ma, J., Dhilipkannah, P., & Jiang, F. (2023). MicroRNA Profiling of Red Blood Cells for Lung Cancer Diagnosis. Cancers, 15(22), 5312. https://doi.org/10.3390/cancers15225312