Profile of MicroRNAs Associated with Death Due to Disease Progression in Metastatic Papillary Thyroid Carcinoma Patients
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Data Survey
2.2. Selection of Samples for Molecular Study
2.3. Sequencing for BRAF and TERT Mutations
2.4. MicroRNA Detection Technique
2.5. Statistical Analyses
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Leite, A.K.N.; Cavalheiro, B.G.; Kulcsar, M.A.; Hoff, A.O.; Brandao, L.G.; Cernea, C.R.; Matos, L.L. Deaths related to differentiated thyroid cancer: A rare but real event. Arch. Endocrinol. Metab. 2017, 61, 222–227. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Leite, A.K.N.; de Araujo Filho, V.J.F.; de Matos, L.L. Are All Small Papillary Thyroid Cancers Harmless? A Word of Caution. Endocr. Pract. 2019, 25, 1233–1234. [Google Scholar] [CrossRef]
- Nunes, K.S.; Matos, L.L.; Cavalheiro, B.G.; Magnabosco, F.F.; Tavares, M.R.; Kulcsar, M.A.; Hoff, A.O.; Kowalski, L.P.; Leite, A.K. Risk factors associated with disease-specific mortality in papillary thyroid cancer patients with distant metastases. Endocrine 2022, 75, 814–822. [Google Scholar] [CrossRef]
- Pacini, F.; Castagna, M.G. Approach to and treatment of differentiated thyroid carcinoma. Med. Clin. N. Am. 2012, 96, 369–383. [Google Scholar] [CrossRef] [PubMed]
- Bose, S.; Walts, A.E. Thyroid fine needle aspirate: A post-Bethesda update. Adv. Anat. Pathol. 2012, 19, 160–169. [Google Scholar] [CrossRef] [PubMed]
- Maciel, R.M.; Kimura, E.T.; Cerutti, J.M. Pathogenesis of differentiated thyroid cancer (papillary and follicular). Arq. Bras. Endocrinol. Metabol. 2005, 49, 691–700. [Google Scholar] [CrossRef] [Green Version]
- Jansson, M.D.; Lund, A.H. MicroRNA and cancer. Mol. Oncol. 2012, 6, 590–610. [Google Scholar] [CrossRef] [Green Version]
- Yuan, Z.M.; Yang, Z.L.; Zheng, Q. Deregulation of microRNA expression in thyroid tumors. J. Zhejiang Univ. Sci. B 2014, 15, 212–224. [Google Scholar] [CrossRef] [Green Version]
- Amin, M.B.; Edge, S.B.; Greene, F.L.; Byrd, D.R.; Brookland, R.K.; Washington, M.K.; Gershenwald, J.E.; Compton, C.C.; Hess, K.R.; Sullivan, D.C.; et al. AJCC Cancer Staging Manual, 8th ed.; Springer: Chicago, IL, USA, 2017. [Google Scholar]
- Leite, A.K.; Kulcsar, M.A.; de Godoi Cavalheiro, B.; de Mello, E.S.; Alves, V.A.; Cernea, C.R.; Matos, L.L. Death Related to Pulmonary Metastasis in Patients with Differentiated Thyroid Cancer. Endocr. Pract. 2017, 23, 72–78. [Google Scholar] [CrossRef]
- Haugen, B.R.; Alexander, E.K.; Bible, K.C.; Doherty, G.M.; Mandel, S.J.; Nikiforov, Y.E.; Pacini, F.; Randolph, G.W.; Sawka, A.M.; Schlumberger, M.; et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016, 26, 1–133. [Google Scholar] [CrossRef]
- Kizys, M.M.; Cardoso, M.G.; Lindsey, S.C.; Harada, M.Y.; Soares, F.A.; Melo, M.C.; Montoya, M.Z.; Kasamatsu, T.S.; Kunii, I.S.; Giannocco, G.; et al. Optimizing nucleic acid extraction from thyroid fine-needle aspiration cells in stained slides, formalin-fixed/paraffin-embedded tissues, and long-term stored blood samples. Arq. Bras. Endocrinol. Metab. 2012, 56, 618–626. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ye, J.; Coulouris, G.; Zaretskaya, I.; Cutcutache, I.; Rozen, S.; Madden, T.L. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinform. 2012, 13, 134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kent, W.J.; Sugnet, C.W.; Furey, T.S.; Roskin, K.M.; Pringle, T.H.; Zahler, A.M.; Haussler, D. The human genome browser at UCSC. Genome Res. 2002, 12, 996–1006. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Matos, L.L.; Menderico Junior, G.M.; Theodoro, T.R.; Pasini, F.S.; Ishikawa, M.M.; Ribeiro, A.A.B.; de Mello, E.S.; Pinhal, M.; Moyses, R.A.; Kulcsar, M.A.V.; et al. Cancer-associated fibroblast regulation by microRNAs promotes invasion of oral squamous cell carcinoma. Oral. Oncol. 2020, 110, 104909. [Google Scholar] [CrossRef] [PubMed]
- Ulitsky, I.; Maron-Katz, A.; Shavit, S.; Sagir, D.; Linhart, C.; Elkon, R.; Tanay, A.; Sharan, R.; Shiloh, Y.; Shamir, R. Expander: From expression microarrays to networks and functions. Nat. Protoc. 2010, 5, 303–322. [Google Scholar] [CrossRef] [PubMed]
- Liu, X.; He, M.; Hou, Y.; Liang, B.; Zhao, L.; Ma, S.; Yu, Y.; Liu, X. Expression profiles of microRNAs and their target genes in papillary thyroid carcinoma. Oncol. Rep. 2013, 29, 1415–1420. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rosignolo, F.; Sponziello, M.; Giacomelli, L.; Russo, D.; Pecce, V.; Biffoni, M.; Bellantone, R.; Lombardi, C.P.; Lamartina, L.; Grani, G.; et al. Identification of Thyroid-Associated Serum microRNA Profiles and Their Potential Use in Thyroid Cancer Follow-Up. J. Endocr. Soc. 2017, 1, 3–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, J.; Wu, L.; Jin, Y.; Li, S.; Liu, X. Identification of key miRNAs in papillary thyroid carcinoma based on data mining and bioinformatics methods. Biomed. Rep. 2020, 12, 11–16. [Google Scholar] [CrossRef] [Green Version]
- Liu, X.; Liu, G.; Lu, Y.; Shi, Y. Long non-coding RNA HOTAIR promotes cell viability, migration and invasion in thyroid cancer cells by sponging miR-17-5p. Neoplasma 2020, 67, 229–237. [Google Scholar] [CrossRef]
- Geng, X.; Sun, Y.; Fu, J.; Cao, L.; Li, Y. MicroRNA-17-5p inhibits thyroid cancer progression by suppressing Early growth response 2 (EGR2). Bioengineered 2021, 12, 2713–2722. [Google Scholar] [CrossRef]
- Shi, Y.P.; Liu, G.L.; Li, S.; Liu, X.L. miR-17-5p knockdown inhibits proliferation, autophagy and promotes apoptosis in thyroid cancer via targeting PTEN. Neoplasma 2020, 67, 249–258. [Google Scholar] [CrossRef] [PubMed]
- Das, P.K.; Asha, S.Y.; Abe, I.; Islam, F.; Lam, A.K. Roles of Non-Coding RNAs on Anaplastic Thyroid Carcinomas. Cancers 2020, 12, 3159. [Google Scholar] [CrossRef] [PubMed]
- Fuziwara, C.S.; Saito, K.C.; Kimura, E.T. Thyroid Follicular Cell Loss of Differentiation Induced by MicroRNA miR-17-92 Cluster Is Attenuated by CRISPR/Cas9n Gene Silencing in Anaplastic Thyroid Cancer. Thyroid 2020, 30, 81–94. [Google Scholar] [CrossRef] [Green Version]
- Takakura, S.; Mitsutake, N.; Nakashima, M.; Namba, H.; Saenko, V.A.; Rogounovitch, T.I.; Nakazawa, Y.; Hayashi, T.; Ohtsuru, A.; Yamashita, S. Oncogenic role of miR-17-92 cluster in anaplastic thyroid cancer cells. Cancer Sci. 2008, 99, 1147–1154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sweat, Y.; Ries, R.J.; Sweat, M.; Su, D.; Shao, F.; Eliason, S.; Amendt, B.A. miR-17 acts as a tumor suppressor by negatively regulating the miR-17-92 cluster. Mol. Ther. Nucleic Acids 2021, 26, 1148–1158. [Google Scholar] [CrossRef]
- Liu, L.; Yang, J.; Zhu, X.; Li, D.; Lv, Z.; Zhang, X. Long noncoding RNA H19 competitively binds miR-17-5p to regulate YES1 expression in thyroid cancer. FEBS J. 2016, 283, 2326–2339. [Google Scholar] [CrossRef] [Green Version]
- Zhang, A.; Wang, C.; Lu, H.; Chen, X.; Ba, Y.; Zhang, C.; Zhang, C.Y. Altered Serum MicroRNA Profile May Serve as an Auxiliary Tool for Discriminating Aggressive Thyroid Carcinoma from Nonaggressive Thyroid Cancer and Benign Thyroid Nodules. Dis. Mrk. 2019, 2019, 3717683. [Google Scholar] [CrossRef] [Green Version]
- Wang, C.; Lu, S.; Jiang, J.; Jia, X.; Dong, X.; Bu, P. Hsa-microRNA-101 suppresses migration and invasion by targeting Rac1 in thyroid cancer cells. Oncol. Lett. 2014, 8, 1815–1821. [Google Scholar] [CrossRef] [Green Version]
- Lin, X.; Guan, H.; Li, H.; Liu, L.; Liu, J.; Wei, G.; Huang, Z.; Liao, Z.; Li, Y. miR-101 inhibits cell proliferation by targeting Rac1 in papillary thyroid carcinoma. Biomed. Rep. 2014, 2, 122–126. [Google Scholar] [CrossRef] [Green Version]
- Lima, C.R.; Gomes, C.C.; Santos, M.F. Role of microRNAs in endocrine cancer metastasis. Mol. Cell Endocrinol. 2017, 456, 62–75. [Google Scholar] [CrossRef]
- Zhu, J.; Li, Z. Overexpression of miR-101 promotes TRAIL-induced mitochondrial apoptosis in papillary thyroid carcinoma by targeting c-met and MCL-1. Oncotarget 2017, 8, 108665–108675. [Google Scholar] [CrossRef] [Green Version]
- Du, Y.L.; Liang, Y.; Cao, Y.; Liu, L.; Li, J.; Shi, G.Q. LncRNA XIST Promotes Migration and Invasion of Papillary Thyroid Cancer Cell by Modulating MiR-101-3p/CLDN1 Axis. Biochem. Genet. 2021, 59, 437–452. [Google Scholar] [CrossRef] [PubMed]
- Chen, F.; Yang, D.; Ru, Y.; Cao, S.; Gao, A. MicroRNA-101 Targets CXCL12-Mediated Akt and Snail Signaling Pathways to Inhibit Cellular Proliferation and Invasion in Papillary Thyroid Carcinoma. Oncol. Res. 2019, 27, 691–701. [Google Scholar] [CrossRef] [PubMed]
- Zhao, H.; Tang, H.; Huang, Q.; Qiu, B.; Liu, X.; Fan, D.; Gong, L.; Guo, H.; Chen, C.; Lei, S.; et al. MiR-101 targets USP22 to inhibit the tumorigenesis of papillary thyroid carcinoma. Am. J. Cancer Res. 2016, 6, 2575–2586. [Google Scholar] [PubMed]
- Guo, L.; Dou, Y.; Yang, Y.; Zhang, S.; Kang, Y.; Shen, L.; Tang, L.; Zhang, Y.; Li, C.; Wang, J.; et al. Protein profiling reveals potential isomiR-associated cross-talks among RNAs in cholangiocarcinoma. Comput. Struct. Biotechnol. J. 2021, 19, 5722–5734. [Google Scholar] [CrossRef]
- Liu, X.Y.; Liu, Z.J.; He, H.; Zhang, C.; Wang, Y.L. MicroRNA-101-3p suppresses cell proliferation, invasion and enhances chemotherapeutic sensitivity in salivary gland adenoid cystic carcinoma by targeting Pim-1. Am. J. Cancer Res. 2015, 5, 3015–3029. [Google Scholar]
- Mondello, P.; Cuzzocrea, S.; Mian, M. Pim kinases in hematological malignancies: Where are we now and where are we going? J. Hematol. Oncol. 2014, 7, 95. [Google Scholar] [CrossRef] [Green Version]
- Eerola, S.K.; Kohvakka, A.; Tammela, T.L.J.; Koskinen, P.J.; Latonen, L.; Visakorpi, T. Expression and ERG regulation of PIM kinases in prostate cancer. Cancer Med. 2021, 10, 3427–3436. [Google Scholar] [CrossRef]
- Wen, Q.L.; Yi, H.Q.; Yang, K.; Yin, C.T.; Yin, W.J.; Xiang, F.Y.; Bao, M.; Shuai, J.; Song, Y.W.; Ge, M.H.; et al. Role of oncogene PIM-1 in the development and progression of papillary thyroid carcinoma: Involvement of oxidative stress. Mol. Cell Endocrinol. 2021, 523, 111144. [Google Scholar] [CrossRef]
- Warfel, N.A.; Kraft, A.S. PIM kinase (and Akt) biology and signaling in tumors. Pharmacol. Ther. 2015, 151, 41–49. [Google Scholar] [CrossRef] [Green Version]
- Losman, J.A.; Chen, X.P.; Vuong, B.Q.; Fay, S.; Rothman, P.B. Protein phosphatase 2A regulates the stability of Pim protein kinases. J. Biol. Chem. 2003, 278, 4800–4805. [Google Scholar] [CrossRef] [PubMed]
- Park, Y.K.; Obiang-Obounou, B.W.; Lee, K.B.; Choi, J.S.; Jang, B.C. AZD1208, a pan-Pim kinase inhibitor, inhibits adipogenesis and induces lipolysis in 3T3-L1 adipocytes. J. Cell Mol. Med. 2018, 22, 2488–2497. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Szydłowski, M.; Prochorec-Sobieszek, M.; Szumera-Ciećkiewicz, A.; Derezińska, E.; Hoser, G.; Wasilewska, D.; Szymańska-Giemza, O.; Jabłońska, E.; Białopiotrowicz, E.; Sewastianik, T.; et al. Expression of PIM kinases in Reed-Sternberg cells fosters immune privilege and tumor cell survival in Hodgkin lymphoma. Blood 2017, 130, 1418–1429. [Google Scholar] [CrossRef] [Green Version]
- Mohammad Khanlou, Z.; Pouladi, N.; Hosseinpour Feizi, M.; Pedram, N. Lack of Associations of the MDM4 rs4245739 Polymorphism with Risk of Thyroid Cancer among Iranian-Azeri Patients: A Case-Control Study. Asian Pac. J. Cancer Prev. 2017, 18, 1133–1138. [Google Scholar] [CrossRef] [PubMed]
- McEvoy, J.; Ulyanov, A.; Brennan, R.; Wu, G.; Pounds, S.; Zhang, J.; Dyer, M.A. Analysis of MDM2 and MDM4 single nucleotide polymorphisms, mRNA splicing and protein expression in retinoblastoma. PLoS ONE 2012, 7, e42739. [Google Scholar] [CrossRef]
- Wynendaele, J.; Bohnke, A.; Leucci, E.; Nielsen, S.J.; Lambertz, I.; Hammer, S.; Sbrzesny, N.; Kubitza, D.; Wolf, A.; Gradhand, E.; et al. An illegitimate microRNA target site within the 3’ UTR of MDM4 affects ovarian cancer progression and chemosensitivity. Cancer Res. 2010, 70, 9641–9649. [Google Scholar] [CrossRef] [Green Version]
- Colamaio, M.; Borbone, E.; Russo, L.; Bianco, M.; Federico, A.; Califano, D.; Chiappetta, G.; Pallante, P.; Troncone, G.; Battista, S.; et al. miR-191 down-regulation plays a role in thyroid follicular tumors through CDK6 targeting. J. Clin. Endocrinol. Metab. 2011, 96, E1915–E1924. [Google Scholar] [CrossRef] [PubMed]
Variable | Death Due to Cancer Progression n = 17 (%) | Alive Metastatic Patients n = 7 (%) |
---|---|---|
Sex | ||
Female | 12 (70.6) | 4 (57.1) |
Male | 5 (29.4) | 3 (42.9) |
Age | ||
Mean ± SD (years-old) | 54.8 ± 13.2 | 56 ± 13.4 |
Histopathological data | ||
Extrathyroidal extension | 9 (52.9) | 3 (50.0) |
Vascular invasion | 11 (73.3) | 4 (66.7) |
Multifocality | 9 (52.9) | 4 (57.1) |
Size (mean ± SD; cm) | 4.7 ± 3.6 | 4.1 ± 2.6 |
Initial pT classification | ||
pT1 | 4 (23.5) | 1 (16.7) |
pT2 | 2 (11.8) | 1 (16.7) |
pT3 | 5 (29.4) | 2 (33.3) |
pT4a | 2 (11.8) | 2 (33.3) |
pT4b | 4 (23.5) | 0 |
Initial pN classification | ||
pN0 | 8 (50) | 2 (28.6) |
pN1a | 3 (18.8) | 1 (14.3) |
pN1b | 5 (31.3) | 4 (57.1) |
Treatment | ||
Total thyroidectomy | 16 (94.1) | 7 (100) |
Central compartment neck dissection | 8 (50) | 5 (71.4) |
Level II-V neck dissection | 5 (31.3) | 4 (57.1) |
R0 surgery | 13 (86.7) | 6 (85.7) |
Radioiodine therapy (RIT) | 12 (70.6) | 7 (100) |
Number of RIT | ||
One | 6 (50) | 4 (57.1) |
>2 | 6 (50) | 3 (42.9) |
Distant metastases | 17 (100) | 7 (100) |
Lung | 16 (94.1) | 7 (100) |
Liver | 4 (23.5) | 0 |
Bones | 12 (70.6) | 1 (14.3) |
Multiple sites | 14 (82.4) | 1 (14.3) |
Diagnosis with the primary tumor | 12 (70.6) | 4 (57.1) |
Dedifferentiation | 8 (47.1) | 0 |
Follow-up | ||
Radioiodine refractory disease | 9 (75) | 3 (42.9) |
Regional failure | 7 (50) | 1 (14.3) |
Follow-up time (mean ± SD; months) | 51.9 ± 37.9 | 158.6 ± 32.9 |
miR | Death Due to Tumor Progression | Alive with Metastatic Disease | p-Value (Mann–Whitney) | ||
---|---|---|---|---|---|
MEAN | SE | MEAN | SE | ||
let-7b-5p | 0.082 | 0.036 | 0.076 | 0.038 | 0.413 |
let-7c-5p | 5.185 | 3.002 | 5.841 | 1.105 | 0.020 |
let-7d-5p | 0.445 | 0.052 | 0.470 | 0.064 | 0.619 |
let-7e-5p | 2.981 | 1.243 | 5.490 | 1.670 | 0.020 |
let-7f-5p | 3.855 | 0.748 | 4.950 | 1.164 | 0.494 |
let-7i-5p | 20.463 | 3.414 | 11.609 | 1.268 | 0.089 |
miR-1-3p | 17.129 | 7.263 | 14.596 | 6.562 | 0.891 |
miR-101-3p | 3.863 | 0.517 | 0.776 | 0.154 | 0.005 |
miR-10b-5p | 0.471 | 0.124 | 0.774 | 0.303 | 0.590 |
miR-125a-5p | 7.230 | 1.550 | 7.422 | 1.633 | 0.664 |
miR-138-5p | 3.919 | 0.906 | 1.811 | 0.618 | 0.081 |
miR-141-3p | 17.303 | 3.336 | 9.412 | 2.434 | 0.172 |
miR-146b-5p | 2.686 | 0.913 | 4.957 | 1.419 | 0.179 |
miR-16-5p | 5.610 | 1.402 | 0.926 | 0.144 | 0.019 |
miR-17-5p | 1.811 | 0.417 | 0.351 | 0.117 | 0.005 |
miR-181b-5p | 0.262 | 0.048 | 0.474 | 0.053 | 0.014 |
miR-18a-5p | 0.058 | 0.025 | 0.096 | 0.094 | 0.364 |
miR-191-5p | 1.057 | 0.181 | 0.236 | 0.044 | <0.001 |
miR-199a-3p | 1.328 | 0.512 | 0.752 | 0.230 | 0.757 |
miR-19a-3p | 0.566 | 0.212 | 0.053 | 0.019 | 0.003 |
miR-19b-3p | 2.220 | 1.134 | 0.125 | 0.035 | <0.001 |
miR-200a-3p | 3.842 | 0.642 | 2.183 | 0.386 | 0.209 |
miR-200b-3p | 38.351 | 11.600 | 51.367 | 9.258 | 0.065 |
miR-200c-3p | 16.783 | 4.204 | 33.108 | 4.673 | 0.011 |
miR-203a-3p | 0.101 | 0.044 | 0.056 | 0.032 | 0.773 |
miR-205-5p | 2.791 | 1.154 | 1.203 | 0.691 | 0.602 |
miR-20a-5p | 0.526 | 0.111 | 0.124 | 0.033 | <0.001 |
miR-21-5p | 55.030 | 19.916 | 19.751 | 5.168 | 0.383 |
miR-214-3p | 0.965 | 0.503 | 0.094 | 0.062 | 0.100 |
miR-221-3p | 23.834 | 5.939 | 18.518 | 5.118 | 1.000 |
miR-222-3p | 1.667 | 0.406 | 1.721 | 0.312 | 0.452 |
miR-29a-3p | 6.587 | 1.112 | 3.260 | 0.399 | 0.006 |
miR-30a-5p | 5.969 | 1.762 | 2.299 | 0.433 | 0.072 |
miR-30b-5p | 15.418 | 3.490 | 4.958 | 0.964 | 0.018 |
miR-30c-5p | 26.561 | 5.902 | 3.662 | 0.694 | 0.005 |
miR-30d-5p | 1.930 | 0.383 | 0.663 | 0.171 | 0.021 |
miR-30e-3p | 0.691 | 0.154 | 0.550 | 0.201 | 0.559 |
miR-31-5p | 2.252 | 1.922 | 1.403 | 0.371 | 0.017 |
miR-34a-5p | 3.751 | 1.037 | 5.668 | 0.950 | 0.032 |
miR-423-5p | 0.454 | 0.093 | 0.896 | 0.267 | 0.091 |
miR-429 | 0.366 | 0.097 | 0.147 | 0.053 | 0.178 |
miR-483-3p | 1.298 | 0.752 | 0.289 | 0.103 | 0.831 |
miR-92a-3p | 15.574 | 7.610 | 4.612 | 0.887 | 0.671 |
Model | Unstandardized Coefficients | Standardized Coefficients | p-Value | 95% CI (for Beta) | |||
---|---|---|---|---|---|---|---|
B | IF | Beta | Lower | Upper | |||
1 | Constant | −0.021 | 0.113 | 0.860 | −0.310 | 0.268 | |
miR-17-5p | 0.555 | 0.073 | 0.959 | 0.001 | 0.367 | 0.743 | |
2 | Constant | −0.122 | 0.079 | 0.199 | −0.343 | 0.098 | |
miR-17-5p | 0.451 | 0.059 | 0.779 | 0.002 | 0.288 | 0.614 | |
miR-101-3p | 0.066 | 0.023 | 0.294 | 0.044 | 0.003 | 0.129 | |
3 | Constant | −0.183 | 0.036 | 0.015 | −0.298 | −0.068 | |
miR-17-5p | 0.341 | 0.035 | 0.589 | 0.002 | 0.230 | 0.452 | |
miR-101-3p | 0.071 | 0.010 | 0.318 | 0.005 | 0.041 | 0.102 | |
miR-191-5p | 0.265 | 0.060 | 0.231 | 0.021 | 0.075 | 0.456 |
Micro-RNA | Sensitivity | Specificity | AUC | 95% CI (AUC) | |
---|---|---|---|---|---|
Lower | Upper | ||||
Model 1 miR-17-5p ≥ 0.861 | 0.923 | 1.000 | 0.962 | 0.872 | 1.051 |
Model 2 miR-17-5p ≥ 0.861 AND miR-101-3p ≥ 2.155 | 0.786 | 1.000 | 0.893 | 0.750 | 1.036 |
Model 3 miR-17-5p ≥ 0.861 AND miR-101-3p ≥ 2.155 AND miR-191-5p ≥ 0.455 | 0.714 | 1.000 | 0.857 | 0.694 | 1.021 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Leite, A.K.; Saito, K.C.; Theodoro, T.R.; Pasini, F.S.; Camilo, L.P.; Rossetti, C.A.; Cavalheiro, B.G.; Alves, V.A.F.; Kowalski, L.P.; Pinhal, M.A.S.; et al. Profile of MicroRNAs Associated with Death Due to Disease Progression in Metastatic Papillary Thyroid Carcinoma Patients. Cancers 2023, 15, 869. https://doi.org/10.3390/cancers15030869
Leite AK, Saito KC, Theodoro TR, Pasini FS, Camilo LP, Rossetti CA, Cavalheiro BG, Alves VAF, Kowalski LP, Pinhal MAS, et al. Profile of MicroRNAs Associated with Death Due to Disease Progression in Metastatic Papillary Thyroid Carcinoma Patients. Cancers. 2023; 15(3):869. https://doi.org/10.3390/cancers15030869
Chicago/Turabian StyleLeite, Ana Kober, Kelly Cristina Saito, Thérèse Rachell Theodoro, Fátima Solange Pasini, Luana Perrone Camilo, Carlos Augusto Rossetti, Beatriz Godoi Cavalheiro, Venâncio Avancini Ferreira Alves, Luiz Paulo Kowalski, Maria Aparecida Silva Pinhal, and et al. 2023. "Profile of MicroRNAs Associated with Death Due to Disease Progression in Metastatic Papillary Thyroid Carcinoma Patients" Cancers 15, no. 3: 869. https://doi.org/10.3390/cancers15030869