Could miRNA Signatures be Useful for Predicting Uterine Sarcoma and Carcinosarcoma Prognosis and Treatment?
Abstract
:1. Introduction
2. Results
3. Discussion
4. Materials and Methods
4.1. Samples
4.2. MicroRNAs Expression Profile Analysis
4.3. Statistical Analysis
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Variables | Categories | n (%) |
---|---|---|
Age | >50 years | 59 (74) |
≤50 years | 21 (26) | |
N. A. | 0 (0) | |
Main complaint | Bleeding | 48 (60) |
Pelvic Pain | 18 (23) | |
N. A. | 14 (17) | |
Menopause | Yes | 54 (67) |
No | 11 (14) | |
N. A. | 15 (19) | |
Contraceptive | Yes | 3 (4) |
No | 42 (52) | |
N. A. | 35 (44) | |
Hormone replacement therapy (HRT) | Yes | 2 (3) |
No | 49 (61) | |
N. A. | 29 (36) | |
Smoking | Yes | 3 (4) |
No | 30 (37) | |
N. A. | 47 (59) | |
Surgical treatment | Yes | 78 (98) |
No | 2 (2) | |
Follow up | Average | 36 months |
Range | 1 to 183 months | |
Metastasis | Yes | 52 (65) |
No | 21 (26) | |
N. A. | 7 (9) | |
Death | Yes | 55 (69) |
Alive | 15 (19) | |
N. A. | 10 (12) |
Variables | Categories | LMS n (%) | CS n (%) | ESS n (%) | ADS n (%) |
---|---|---|---|---|---|
Clinical Stage | I | 10 (27) | 4 (17.4) | 7 (38.9) | 2 (100) |
II | 10 (27) | 2 (8.7) | 3 (16.7) | 0 (0) | |
III | 5 (13.5) | 11 (47.8) | 7 (38.9) | 0 (0) | |
IV | 12 (32.5) | 6 (26.1) | 1 (5.5) | 0 (0) | |
N. A. | 0 (0) | 0 (0) | 0 (0) | 0 (0) | |
Histological Grade | High | 27 (73) | 23 (100) | 13 (72.2) | 1 (50) |
Low | 10 (27) | 0 (0) | 5 (27.8) | 1 (50) | |
N. A. | 0 (0) | 0 (0) | 0 (0) | 0 (0) | |
Recurrence | No | 6 (17) | 8 (35) | 3 (17) | 1 (50) |
Persistence | 12 (32) | 6 (26) | 7 (39) | 0 (0) | |
Relapse | 15 (40) | 5 (22) | 7 (39) | 0 (0) | |
N. A. | 4 (11) | 4 (17) | 1 (5) | 1 (50) | |
Metastasis | Locoregional | 12 (5) | 2 (9) | 3 (17) | 0 (0) |
Distant | 15 (55) | 9 (39) | 11 (61) | 0 (0) | |
N. A. | 10 (40) | 12 (52) | 4 (22) | 2 (100) | |
Adjuvant Treatment | No | 10 (27) | 5 (21.7) | 5 (27.8) | 0 (0) |
RT | 11 (29.7) | 8 (34.8) | 6 (33.3) | 2 (100) | |
CT | 11 (29.7) | 3 (13.1) | 4 (22.2) | 0 (0) | |
CT+RT | 5 (13.6) | 7 (30.4) | 3 (16.7) | 0 (0) | |
N. A. | 0 (0) | 0 (0) | 0 (0) | 0 (0) | |
Status | Alive | 7 (18.9) | 3 (13) | 4 (22.2) | 1 (50) |
Death | 26 (70.3) | 16 (70) | 13 (72.2) | 0 (0) | |
Loss of follow-up | 4 (10.8) | 4 (17) | 1 (5.6) | 1 (50) | |
N. A. | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
Clinical Variable | LMS | CS | ESS | |||
---|---|---|---|---|---|---|
miRNA | p | miRNA | p | miRNA | p | |
Age (over 50 years old) | 220c-3p a 29a-3p b | 0.049 0.033 | - | - | - | - |
Main complaint—Bleeding | - | - | - | - | 142-5p a 148b-3p a 214-3p a | 0.031 0.016 0.016 |
Menopause | 148a-3p a 7-5p a 32-5p a | 0.022 0.023 0.030 | 30c-5p b,* 148a-3p b 100-5p b let-7i-5p b,* | 0.001 0.004 0.034 0.001 | 335-5p b | 0.025 |
Oral contraceptive | - | - | - | - | 132-3p b 34c-5p b | 0.005 0.006 |
HRT | - | - | - | - | 125a-5p b 222-3p b 205-5p b | 0.039 0.039 0.019 |
Smoking | - | - | 125a-5p a 30c-5p a 135b-5p a let-7i-5p a 27b-3p a 29a-3p a let-7f-5p a 34a-5p a 25-3p a 125b-5p a 23b-3p a 335-5p a 21-5p a | 0.018 0.018 0.011 0.006 0.011 0.044 0.018 0.011 0.007 0.028 0.028 0.044 0.029 | 27b-3p a 143-3p a | 0.006 0.038 |
Patients who died | 96-5p b 132-3p b 183-5p b,* 124-3p b | 0.023 0.026 0.001 0.024 | 122-5p a | 0.025 | 29b-3p b 206 b | 0.027 0.026 |
Presence of relapse | 148a-3p a 29b-3p a 301a-3p b 29a-3p a 144-3p b | 0.021 0.008 0.027 0.040 0.020 | 335-5p b 96-5p b 378a-3p b 130a-3p b 183-5p b 134-5p b 7-5p b 128-3p b 18a-5p b 203a-3p b 32-5p b | 0.050 0.008 0.028 0.046 0.010 0.016 0.040 0.026 0.033 0.020 0.008 | 301a-3p b | 0.041 |
127-5p b | 0.045 | |||||
Presence of metastasis | 140-5p a 193b-3p a let-7i-5p a 27b-3p a 143-3p a 125b-5p a | 0.002 0.002 0.034 0.029 0.004 0.025 | - | - | 193b-3p b 210-3p b | 0.015 0.044 |
Stage I | - | - | - | - | - | - |
Stage II | - | - | 335-5p a,* 218-5p a | 0.001 0.014 | 23b-3p a | 0.017 |
Stage IV | - | - | - | - | 7-5p b | 0.014 |
High histological grade | let-7a-5p a 125a-5p b 222-3p b 148b-3p b 92a-3p b let-7b-5p a 205-5p b 20a-5p b 30c-5p b let-7g-5p a let-7c-5p a let-7e-5p a let-7f-5p b 218-5p b,* 100-5p b 155-5p b 1-3p b 191-5p b let-7d-5p b 15b-5p b 98-5p b 25-3p b 128-3p b 143-3p b 19a-3p b 23b-3p b 16-5p b 17-5p b 18a-5p b 27b-3p b | 0.008 0.047 0.040 0.050 0.029 0.009 0.010 0.008 0.031 0.005 0.029 0.014 0.045 0.001 0.044 0.012 0.011 0.024 0.010 0.002 0.002 0.010 0.041 0.047 0.031 0.017 0.033 0.034 0.049 0.020 | 184 a,* | 0.001 | - | - |
miRNA | r * | p |
---|---|---|
miR-146b-5p | 0.358 | 0.032 |
miR-218-5p | 0.331 | 0.048 |
miR-138-5p | 0.534 | <0.001 |
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Gonzalez dos Anjos, L.; De Almeida, B.C.; Gomes de Almeida, T.; Mourão Lavorato Rocha, A.; De Nardo Maffazioli, G.; Soares, F.A.; Werneck da Cunha, I.; Baracat, E.C.; Carvalho, K.C. Could miRNA Signatures be Useful for Predicting Uterine Sarcoma and Carcinosarcoma Prognosis and Treatment? Cancers 2018, 10, 315. https://doi.org/10.3390/cancers10090315
Gonzalez dos Anjos L, De Almeida BC, Gomes de Almeida T, Mourão Lavorato Rocha A, De Nardo Maffazioli G, Soares FA, Werneck da Cunha I, Baracat EC, Carvalho KC. Could miRNA Signatures be Useful for Predicting Uterine Sarcoma and Carcinosarcoma Prognosis and Treatment? Cancers. 2018; 10(9):315. https://doi.org/10.3390/cancers10090315
Chicago/Turabian StyleGonzalez dos Anjos, Laura, Bruna Cristine De Almeida, Thais Gomes de Almeida, André Mourão Lavorato Rocha, Giovana De Nardo Maffazioli, Fernando Augusto Soares, Isabela Werneck da Cunha, Edmund Chada Baracat, and Katia Candido Carvalho. 2018. "Could miRNA Signatures be Useful for Predicting Uterine Sarcoma and Carcinosarcoma Prognosis and Treatment?" Cancers 10, no. 9: 315. https://doi.org/10.3390/cancers10090315