Estimation of ALU Repetitive Elements in Plasma as a Cost-Effective Liquid Biopsy Tool for Disease Prognosis in Breast Cancer
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patient Recruitment
2.2. Plasma Preparation and DNA Extraction
2.3. Quantitative PCR of ALU Repeats
2.4. Next-Gen Sequencing-Primer Synthesis, Library Preparation, and Analysis
2.5. Statistical Analysis
3. Results
3.1. Patient Characteristics
3.2. Evaluation of ctDNA and the DI Index; ALU 247 Levels Decrease Post-Surgical Intervention and Are Higher in Metastatic Patients
3.3. Implication of Baseline ALU 115, ALU 247, and DI Levels on Prognosis and Association with Tumor Clinico-Pathological Characteristics
3.4. Detection of Mutations from ctDNA by NGS
3.5. Utility of Estimating Post-Surgical ALU 247 Levels for Predicting Prognosis
3.6. Nomogram and Decision Curve Analysis for Prediction of Prognosis
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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Sl No. | Parameter (n) | Category | Rel. Frequency/Category (%) | qPCR ALU115 Mean | p Value (Mann–Whitney) | qPCR ALU247 Mean | p Value (Mann–Whitney) | qPCR DNA Integrity Ratio Mean | p Value (Mann–Whitney) |
---|---|---|---|---|---|---|---|---|---|
1 | Age (129) | <50 | 29 | 0.227 | 0.837 | 0.611 | 0.360 | 1.485 | 0.464 |
>50 | 71 | 0.233 | 0.364 | 0.966 | |||||
2 | Age at Menarche (118) | Early | 14 | 0.197 | 0.259 | 0.402 | 0.453 | 1.029 | 0.462 |
Late | 86 | 0.252 | 0.490 | 1.175 | |||||
3 | Menopausal status (129) | Pre- | 26 | 0.225 | 0.912 | 0.554 | 0.520 | 1.242 | 0.864 |
Post- | 74 | 0.233 | 0.398 | 1.071 | |||||
4 | Breast side (129) | Left | 55 | 0.227 | 0.846 | 0.488 | 0.679 | 1.304 | 0.436 |
Right | 43 | 0.234 | 0.350 | 0.861 | |||||
5 | Diabetic (109) | Yes | 33 | 0.240 | 0.585 | 0.295 | 0.087 | 0.733 | 0.053 |
No | 67 | 0.253 | 0.597 | 1.477 | |||||
7 | Hypertension (114) | Yes | 48 | 0.250 | 0.986 | 0.433 | 0.313 | 1.097 | 0.372 |
No | 52 | 0.241 | 0.518 | 1.376 | |||||
8 | Tumor grade (128) | 1 | 19 | 0.228 | 1 v/s 2–0.641 | 0.155 | 1 v/s 2–0.704 | 0.464 | 1 v/s 2–0.494 |
2 | 55 | 0.244 | 1 v/s 3–0.788 | 0.561 | 1 v/s 3–0.952 | 1.396 | 1 v/s 3–0.886 | ||
3 | 21 | 0.195 | 2 v/s 3–0.353 | 0.300 | 2 v/s 3–0.623 | 0.873 | 2 v/s 3–0.577 | ||
9 | Tumor size (127) | <3cm | 40 | 0.185 | 0.048 | 0.437 | 0.409 | 1.094 | 0.639 |
>3cm | 60 | 0.250 | 0.414 | 1.102 | |||||
10 | Lymph node status (125) | Positive | 42 | 0.249 | 0.407 | 0.394 | 0.749 | 0.964 | 0.348 |
Negative | 58 | 0.221 | 0.471 | 1.202 | |||||
11 | Lymphovascular invasion (108) | Present | 40 | 0.244 | 0.597 | 0.376 | 0.844 | 0.953 | 0.526 |
Absent | 60 | 0.230 | 0.489 | 1.273 | |||||
12 | Tumor stage (117) | 1 v/s 0–0.953 | 1 v/s 0–0.953 | 1 v/s 0–0.961 | |||||
0 | 3 | 0.170 | 2 v/s 0–0.344 | 0.048 | 2 v/s 0–0.210 | 0.287 | 2 v/s 0–0.513 | ||
1 | 15 | 0.161 | 3 v/s 0–0.166 | 0.435 | 3 v/s 0–0.439 | 1.126 | 3 v/s 0–0.903 | ||
2 | 50 | 0.238 | 2 v/s 1–0.121 | 0.515 | 2 v/s 1–0.141 | 1.340 | 2 v/s 1–0.304 | ||
3 | 32 | 0.291 | 3 v/s 1–0.025 | 0.433 | 3 v/s 1–0.328 | 1.038 | 3 v/s 1–0.644 | ||
3 v/s 2–0.209 | 3 v/s 2–0.828 | 3 v/s 2–0.387 | |||||||
13 | Ki-67 index (91) | <15 | 40 | 0.279 | 0.044 | 0.531 | 0.218 | 1.290 | 0.890 |
>15 | 60 | 0.188 | 0.408 | 1.153 | |||||
14 | Immune infiltrate (120) | Mild | 43 | 0.252 | 0.309 | 0.572 | 0.263 | 1.456 | 0.098 |
High | 43 | 0.218 | 0.374 | 0.980 |
All; n = 36 | ||||
---|---|---|---|---|
Univariate | Multivariate | |||
HR (95% CI) | p-Value | HR (95% CI) | p-Value | |
Age | 1.006 (0.965–1.05) | 0.76 | 1.013 (0.972–1.056) | 0.537 |
T-size | 1.416 (0.911–2.203) | 0.12 | 1.604 (0.990–2.601) | 0.05 |
Lymph Node status | ||||
Negative | Reference | |||
Positive | 9.441 (2.026–44.003) | 0.004 | 8.073 (1.611–40.449) | 0.01 |
Grade | ||||
I and II | Reference | |||
III | 0.808 (0.175–3.735) | 0.78 | 1.347 (0.248–7.300) | 0.73 |
Post-Operative ALU 247 | 1.302 (1.074–1.578) | 0.007 | 1.3 (1.047–1.613) | 0.017 |
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Nair, M.G.; Ramesh, R.S.; Naidu, C.M.; Mavatkar, A.D.; V. P., S.; Ramamurthy, V.; Somashekaraiah, V.M.; C. E., A.; Raghunathan, K.; Panigrahi, A.; et al. Estimation of ALU Repetitive Elements in Plasma as a Cost-Effective Liquid Biopsy Tool for Disease Prognosis in Breast Cancer. Cancers 2023, 15, 1054. https://doi.org/10.3390/cancers15041054
Nair MG, Ramesh RS, Naidu CM, Mavatkar AD, V. P. S, Ramamurthy V, Somashekaraiah VM, C. E. A, Raghunathan K, Panigrahi A, et al. Estimation of ALU Repetitive Elements in Plasma as a Cost-Effective Liquid Biopsy Tool for Disease Prognosis in Breast Cancer. Cancers. 2023; 15(4):1054. https://doi.org/10.3390/cancers15041054
Chicago/Turabian StyleNair, Madhumathy G., Rakesh S. Ramesh, Chandrakala M. Naidu, Apoorva D. Mavatkar, Snijesh V. P., Vishakha Ramamurthy, Vidya M. Somashekaraiah, Anupama C. E., Kiruthiga Raghunathan, Anuradha Panigrahi, and et al. 2023. "Estimation of ALU Repetitive Elements in Plasma as a Cost-Effective Liquid Biopsy Tool for Disease Prognosis in Breast Cancer" Cancers 15, no. 4: 1054. https://doi.org/10.3390/cancers15041054