Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population
Abstract
:1. Introduction
2. Material and Methods
2.1. Ethical Declaration
2.2. Sample Selection
2.3. DNA Extraction and Quantification
2.4. Selection Polymorphism—INDEL
2.5. Genotyping
2.6. Statistical Analysis
3. Results
3.1. Demographic Characteristics
3.2. Distribution of Genotypes Associated with Susceptibility to GC
3.3. Distribution of Genotypes Associated with Clinical Variants in GC
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
- Instituto Nacional de Câncer José de Alencar Gomes da Silva—INCA. Estimativa 2020—Síntese de Resultados Comentários. Available online: https://www.inca.gov.br/estimativa (accessed on 12 September 2022).
- Oliveira, K.S.M.; Ferreira, L.D.C.; Carvalho, F.P.B.; Soares, F.R.R. Stomach Cancer: Epidemiological Profile of Elderly Patients. Revista Uningé Review. 2016. Available online: http://revista.uninga.br/index.php/uningareviews/article/view/1845 (accessed on 7 September 2022).
- Magalhães, L.; Quintana, L.G.; Lopes, D.C.F.; Vidal, A.F.; Pereira, A.L.; D’Araujo Pinto, L.C.; de Jesus Viana Pinheiro, J.; Khayat, A.S.; Goulart, L.R.; Burbano, R.; et al. APC gene is modulated by hsa-miR-135b-5p in both diffuse and intestinal gastric cancer subtypes. BMC Cancer 2018, 18, 1055. Available online: https://pubmed.ncbi.nlm.nih.gov/30376837/ (accessed on 14 May 2021).
- Instituto Nacional de Câncer José de Alencar Gomes da Silva—INCA. Tipos de Câncer|INCA—Instituto Nacional de Câncer. Leucemia. 2020. Available online: https://www.gov.br/inca/pt-br/assuntos/cancer/tipos/ (accessed on 12 September 2022).
- Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global cancer statistics 2020: GLOBOCANstimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2021, 71, 209–249. Available online: https://acsjournals.onlinelibrary.wiley.com/doi/full/10.3322/caac.21660 (accessed on 15 May 2021).
- Jiang, Y.; Lu, J.; Wu, Y.E.; Zhao, X.; Li, L. Genetic variation in the HLA-G 3UTR 14–bp insertion/deletion and the associated cancer risk: Evidence from 25 case–control studies. Biosci. Rep. 2019, 39. Available online: https://pubmed.ncbi.nlm.nih.gov/30962267/ (accessed on 10 May 2021).
- Marques, D.; Ferreira-Costa, L.R.; Ferreira-Costa, L.L.; da Silva Correa, R.; Borges, A.M.P.; Ito, F.R.; de Oliveira Ramos, C.C.; Bortolin, R.H.; Luchessi, A.D.; Ribeiro-dos-Santos, Â.; et al. Association of insertion-deletions polymorphisms with colorectal cancer risk and clinical features. World J. Gastroenterol. 2017, 23, 6854–6867. Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5645618/ (accessed on 22 May 2021).
- Rodriguez-Murillo, L.; Salem, R.M. Insertion/Deletion Polymorphism. In Encyclopedia of Behavioral Medicine; Springer: New York, NY, USA, 2013; p. 1076. Available online: https://link.springer.com/referenceworkentry/10.1007/978-1-4419-1005-9_706 (accessed on 22 May 2021).
- Chen, J.; Guo, J. Comparative assessments of indel annotations in healthy and cancer genomes withext-generation sequencing data. BMC Med. Genomics 2020, 13, 170. Available online: https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00818-6 (accessed on 1 December 2021).
- Bhattacharya, A.; Ziebarth, J.D.; Cui, Y. Systematic Analysis of microRNA Targeting Impacted by Small Insertions and Deletions in Human Genome. PLoS ONE 2012, 7, e46176. Available online: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0046176 (accessed on 25 May 2021).
- Sambrook, J.; Fritsch, E.F.; Maniatis, T. Molecular Cloning: A Laboratory Manual. Mol Cloning a Lab Manual. 1989 (Ed. 2). Available online: https://www.cabdirect.org/cabdirect/abstract/19901616061 (accessed on 11 September 2022).
- 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 2015, 526, 68–74. Available online: https://www.nature.com/articles/nature15393 (accessed on 20 August 2022).
- R Development Core Team. R: The R Project for Statistical Computing. 2021. Available online: https://www.r-project.org/ (accessed on 25 May 2021).
- Cavalcante, G.C.; de Moraes, M.R.; Valente, C.M.D.; Silva, C.S.; Modesto, A.A.C.; de Assumpção, P.B.; de Assumpção, P.P.; Santos, S.; Ribeiro-dos-Santos, Â. Investigation of INDEL variants in apoptosis: The relevance to gastric cancer. BMC Med. Genet. 2020, 21. Available online: https://pubmed.ncbi.nlm.nih.gov/33076854/ (accessed on 3 November 2020).
- Koh, H.M.; Song, D.H. Prognosticole of Rab27A and Rab27Bxpression in patients withon-small cell lung carcinoma. Thorac. Cancer 2019, 10, 143–149. Available online: https://pubmed.ncbi.nlm.nih.gov/30480360/ (accessed on 2 February 2021).
- Guo, L.; Gao, R.; Gan, J.; Zhu, Y.; Ma, J.; Lv, P.; Zhang, Y.; Li, S.; Tang, H. Downregulation of TNFRSF19 and RAB43 by a novel miRNA, miR-HCC3, promotes proliferation and epithelial–mesenchymal transition in hepatocellular carcinoma cells. Biochem. Biophys. Res. Commun. 2020, 525, 425–432. Available online: https://pubmed.ncbi.nlm.nih.gov/32102752/ (accessed on 2 February 2021).
- Liu, W.; Wang, X. Prediction of functional microRNA targets by integrative modeling of microRNA binding and target expression data. Genome Biol. 2019, 20, 18. [Google Scholar]
- Chen, J.; Yan, C.; Yu, H.; Zhen, S.; Yuan, Q. miR-548d-3p inhibits osteosarcoma by downregulating KRAS. Aging 2019, 11, 5058–5069. Available online: https://pdfs.semanticscholar.org/7606/bc0e517da9a463159f126a0ea9fdfe9efc73.pdf (accessed on 21 June 2021).
- NCBI. National Center for Biotechnology Information. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information. 1988. Available online: https://www.ncbi.nlm.nih.gov/ (accessed on 21 June 2021).
- Yoon, C.; Till, J.; Cho, S.; Chang, K.K.; Lin, J.; Huang, C.; Ryeom, S.; Yoon, S.S. KRAS activation in gastric adenocarcinoma stimulates epithelial-to-mesenchymal transition to cancer stem-like cells and promotes metastasis. Mol. Cancer Res. 2019, 17, 1945–1957. Available online: https://pubmed.ncbi.nlm.nih.gov/31217166/ (accessed on 21 June 2021).
- Singh, R.; Saini, N. Downregulation of BCL2 by miRNAs augments drug-induced apoptosis—A combined computational and experimental approach. J. Cell Sci. 2012, 125 Pt 6, 1568–1578. Available online: https://pubmed.ncbi.nlm.nih.gov/22328513/ (accessed on 30 July 2021).
- Chen, S.; He, Y.; Ding, J.; Jiang, Y.; Jia, S.; Xia, W.; Zhao, J.; Lu, M.; Gu, Z.; Gao, Y. An insertion/deletion polymorphism in the 3′ untranslated region of β-transducin repeat-containing protein (βTrCP) is associated with susceptibility for hepatocellular carcinoma in Chinese. Biochem. Biophys. Res. Commun. 2010, 391, 552–556. [Google Scholar]
- Vlachos, I.S.; Zagganas, K.; Paraskevopoulou, M.D.; Georgakilas, G.; Karagkouni, D.; Vergoulis, T.; Dalamagas, T.; Hatzigeorgiou, A.G. DIANA-miRPath v3.0: Deciphering microRNA function with experimental support. Nucleic Acids Res. 2015, 43, W460–W466. Available online: http://diana.imis.athena-innovation.gr/DianaTools/index.php (accessed on 26 September 2021).
- Assumpção, P.P.; Barra, W.F.; Ishak, G.; Coelho, L.G.V.; Coimbra, F.J.F.; Freitas, H.C.; Dias-Neto, E.; Camargo, M.C.; Szklo, M. The diffuse-type gastric cancer epidemiology enigma. BMC Gastroenterol. 2020, 201, 223. Available online: https://bmcgastroenterol.biomedcentral.com/articles/10.1186/s12876-020-01354-4 (accessed on 24 September 2021). [CrossRef] [PubMed]
- Ding, C.; Tang, W.; Wu, H.; Fan, X.; Luo, J.; Feng, J.; Wen, K.; Wu, G. The PEAK1-PPP1R12B axis inhibits tumor growth and metastasis by regulating Grb2/PI3K/Akt signalling in colorectal cancer. Cancer Lett. 2019, 442, 383–395. Available online: https://pubmed.ncbi.nlm.nih.gov/30472186/ (accessed on 19 February 2021).
- Tan, J.; Lu, T.; Xu, J.; Hou, Y.; Chen, Z.; Zhou, K.; Ding, Y.; Jiang, B.; Zhu, Y. MicroRNA-4463 facilitateshe development of colon cancer by suppression of the expression of PPP1R12B. Clin. Transl. Oncol. 2022, 24, 1115–1123. Available online: https://pubmed.ncbi.nlm.nih.gov/35064454/ (accessed on 19 February 2021).
- Hu, T.; Li, J.; Zhang, C.; Li, S.; He, S.; Yan, H.; Tan, Y.; Lei, M.; Wen, M.; Zuo, J. The potential value of microRNA-4463 in the prognosis evaluation in hepatocellular carcinoma. Genes Dis. 2017, 4, 116–122. Available online: https://www.sciencedirect.com/science/article/pii/S2352304217300260 (accessed on 11 June 2021).
- Jima, D.D.; Zhang, J.; Jacobs, C.; Richards, K.L.; Dunphy, C.H.; Choi, W.W.; Yan Au, W.; Srivastava, G.; Czader, M.B.; Rizzieri, D.A.; et al. Deep sequencing of the small RNA transcriptome of normal and malignant human B cells identifies hundreds of novel microRNAs. Blood 2010, 116, e118–e127. Available online: https://pubmed.ncbi.nlm.nih.gov/20733160/ (accessed on 11 June 2021).
- Zhang, Y.; Li, M.; Ding, Y.; Fan, Z.; Zhang, J.; Zhang, H.; Jiang, B.; Zhu, Y. Serum MicroRNA profile in patients with colon adenomas or cancer. BMC Med. Genom. 2017, 10, 23. Available online: http://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-017-0260-7 (accessed on 11 June 2021).
Gene | ID | Region | Alleles | MAF | Primers | Amplicon |
---|---|---|---|---|---|---|
miRNA302C | rs199971565 | seed | CACTT/C | 0.08 | F5′GCTTCCAGTTCCATCCATGT3′ | 253–257 bp |
R5′CTCAGCGTGGTAGTGTTGGA3′ | ||||||
miRNA3945 | rs145931056 | mature | CCTATGCCCTCC/- | 0.28 | F5′AGGAGTATCCCCTCGTGGAC3′ | 145–157 bp |
R5′CAAGAGTCAGGCAAAAACAGG3′ | ||||||
miRNA548AJ-2 | rs145326096 | mature | AAGT/- | 0.39 | F5′CTCTTCAATGCTTCCTTGAGGT3′ | 207–211 bp |
R5′CTGCATGCCAGGAGCTAAGTAT3′ | ||||||
miRNA4274 | rs202195689 | mature | -/CCC/CCCCA | 0.26 | F5′TTTTTGTCCTCCAAGCTTCC3′ | 132–135 bp |
R5′GAACAAGAGAGAGGGCAGGA3′ | ||||||
miRNA630 | rs139334001 | pre-miRNA | -/TTG | 0.42 | F5′GGTGACCCCAGAATTGACCCT3′ | 96–99 bp |
R5′GCCCTCAGGACGCACCTCTG3′ | ||||||
miRNA516B-2 | rs10670323 | pre-miRNA | -/AAAGA | 0.32 | F5′CATGCACAGCTATCCAGGAG3′ | 162–167 bp |
R5′TTGTTCCTGTCCGATAGATGC3′ | ||||||
miRNA 4463 | rs5877455 | pre-miRNA | -/AG | 0.47 | F5′TGCCCCTACTTAGCAGTCTCA3′ | 191–193 bp |
R5′GAGAGGTGGAGAACTGGGATT3′ | ||||||
miRNA 920 | rs66686007 | pre-miRNA | GTTGT/A | 0.12 | F5′GCATCAGGACGCTGAACATA3′ | 215–220 bp |
R5′AATGCAACTTGCTCCAGAGG3′ | ||||||
miRNA 3171 | rs35170395 | pre-miRNA | -/TA | 0.21 | F5′CTGTGTGTCTGAGGGGTGAA3′ | 331–333 bp |
R5′ATCCTGCCACTTTCTGATGG3′ | ||||||
miRNA 548H-4 | rs150141473 | pre-miRNA | TAAAG/- | 0.28 | F5′GGAATGGAAAATAGACAAGAAGTGA3′ | 197–202 bp |
R5′TGGCAAGTGTACCACAGAAAAC3′ | ||||||
miRNA 3652 | rs62747560 | pre-miRNA | GGGGTGG/- | 0.36 | F5′ATTGGTGGGTTCATGTTTCC3′ | 236–246 bp |
R5′CAGAATCACTCACCGAAGGTC3′ |
Characteristic | Cases n = 301 | Controls n = 145 | p-Value |
---|---|---|---|
Age (yr) Median | 49 (18–88) | 41.5 (18–65) | 0.198 |
≤40 | 146 (48.6) | 80 (55.1) | |
>40 | 155 (51.4) | 65 (44.82) | |
Gender | 0.606 | ||
Male | 175 (58.4) | 81 (55.8) | |
Female | 126 (41.55) | 64 (44.1) | |
Tumor Location | |||
Body | 60 (20.7) | NA | |
Cardia | 88 (29.7) | NA | |
Antrum | 91 (30.7) | NA | |
Fundus | 31 (10.4) | NA | |
Pylorus | 6 (2) | NA | |
Missing | 25 (6.5) | NA | |
Lauren | |||
Intestinal | 111 (37.5) | NA | |
Diffuse | 160 (54) | NA | |
Missing | 30 (8.44) | NA | |
Tumor Staging | |||
Stage 1 | 32 (10.8) | NA | |
Stage 2 | 65 (21.9) | NA | |
Stage 3 | 56 (18.9) | NA | |
Stage 4 | 62 (20.9) | NA | |
Missing | 86 (27.5) | NA |
Gene | Cases n (%) | Controls n (%) | p-Value | OR (95% CI) |
---|---|---|---|---|
miRNA516B_2 (rs10670323) | ||||
Ins/Ins | 3 (1.0%) | 3 (2.1%) | ||
Ins/Del | 57 (19%) | 28 (19.4%) | 0.66 | 0.47 (0.09–2.37) |
Del/Del | 240 (80%) | 113 (78.5%) | ||
Ins | 0.10 | 0.11 | ||
Del | 0.89 | 0.88 | ||
miRNA4463 (rs5877455) | ||||
Ins/Ins | 85 (28.6%) | 57 (41.6%) | ||
Ins/Del | 148 (49.8%) | 59 (43.1%) | 0.02 | 2.04 (1.13–3.71) |
Del/Del | 64 (21.5%) | 21 (15.3%) | ||
Ins | 0.53 | 0.63 | ||
Del | 0.46 | 0.36 | ||
miRNA3945 (rs145931056) | ||||
Ins/Ins | 236 (80.3%) | 127 (88.8%) | ||
Ins/Del | 54 (18.4%) | 14 (9.8%) | 0.05 | 1.08 (0.19–5.96) |
Del/Del | 4 (1.4%) | 2 (1.4%) | ||
Ins | 0.89 | 0.93 | ||
Del | 0.10 | 0.06 | ||
miRNA548H_4 (rs150141473) | ||||
Ins/Ins | 220 (74.8%) | 120 (83.9%) | ||
Ins/Del | 71 (24.1%) | 22 (15.4%) | 0.09 | 1.64 (0.17–15.90) |
Del/Del | 3 (1.0%) | 1 (0.7%) | ||
Ins | 0.86 | 0.91 | ||
Del | 0.13 | 0.08 | ||
miRNA4274 (rs202195689) | ||||
Ins/Ins | 269 (90.9%) | 121 (85.2%) | ||
Ins/Del | 25 (8.4%) | 21 (14.8%) | 0.09 | 0.54 (0.29–0.99) |
Del/Del | 2 (0.7%) | 0 (0%) | ||
Ins | 0.95 | 0.92 | ||
Del | 0.04 | 0.07 | ||
miRNA920 (rs66686007) | ||||
Ins/Ins | 269 (91.5%) | 119 (82.1%) | ||
Ins/Del | 24 (8.2%) | 24 (16.6%) | 0.01 | 1.00 (0.39–1.47) |
Del/Del | 1 (0.3%) | 2 (1.4%) | ||
Ins | 0.95 | 0.90 | ||
Del | 0.04 | 0.09 | ||
miRNA3652 (rs62747560) | ||||
Ins/Ins | 183 (62.2%) | 89 (62.7%) | ||
Ins/Del | 103 (35%) | 39 (27.5%) | 0.00 | 1.28 (0.82–2.01) |
Del/Del | 8 (2.7%) | 14 (9.9%) | ||
Ins | 0.79 | 0.73 | ||
Del | 0.20 | 0.23 |
Gene | Model | OR (95% CI) | p-Value |
---|---|---|---|
miRNA4463_rs5877455_ | Ins/Ins vs. Del/Ins + Del/Del | 1.78 (1.16–2.71) | 0.007 |
miRNA3945_rs145931056 | Ins/Ins vs. Del/Ins + Del/Del | 1.95 (1.08–3.53) | 0.021 |
miRNA548H_4_rs150141473 | Ins/Ins vs. Del/Ins + Del/Del | 1.75 (1.05–2.95) | 0.028 |
miRNA920_rs66686007 | Ins/Ins vs. Del/Ins + Del/Del | 0,43 (0.24–0.77) | 0.004 |
miRNA3652_rs62747560 | Ins/Ins + Ins/Del vs. Del/Del | 0.26 (0.10–0.62) | 0.002 |
Gene | Model | Categorization | OR (95% CI) | p-Value |
---|---|---|---|---|
miRNA4463_rs5877455_ | Ins/Ins vs. Del/Ins + Del/Del | Diffuse or Intestinal type | 2.30 (1.27–4.18) | 0.004 |
miRNA4463_rs5877455_ | Ins/Ins vs. Del/Ins + Del/Del | Location (cardia and non-cardia) | 2.20 (1.26–3.84) | 0.005 |
miRNA4463_rs5877455_ | Ins/Ins vs. Del/Ins + Del/Del | Age (less or more than 40 years) | 2.80 (1.64–4.80) | 0.000 |
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Modesto, A.A.C.; Moraes, M.R.d.; Valente, C.M.D.; Costa, M.S.C.R.; Leal, D.F.d.V.B.; Pereira, E.E.B.; Fernandes, M.R.; Pinheiro, J.A.d.S.; Pantoja, K.B.C.C.; Moreira, F.C.; et al. Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population. Genes 2023, 14, 60. https://doi.org/10.3390/genes14010060
Modesto AAC, Moraes MRd, Valente CMD, Costa MSCR, Leal DFdVB, Pereira EEB, Fernandes MR, Pinheiro JAdS, Pantoja KBCC, Moreira FC, et al. Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population. Genes. 2023; 14(1):60. https://doi.org/10.3390/genes14010060
Chicago/Turabian StyleModesto, Antonio A. C., Milene R. de Moraes, Cristina M. D. Valente, Marta S. C. R. Costa, Diana F. da V. B. Leal, Esdras E. B. Pereira, Marianne R. Fernandes, Jhully A. dos S. Pinheiro, Karla B. C. C. Pantoja, Fabiano C. Moreira, and et al. 2023. "Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population" Genes 14, no. 1: 60. https://doi.org/10.3390/genes14010060
APA StyleModesto, A. A. C., Moraes, M. R. d., Valente, C. M. D., Costa, M. S. C. R., Leal, D. F. d. V. B., Pereira, E. E. B., Fernandes, M. R., Pinheiro, J. A. d. S., Pantoja, K. B. C. C., Moreira, F. C., Burbano, R. M. R., Assumpção, P. P. d., Santos, N. P. C. d., & Santos, S. E. B. d. (2023). Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population. Genes, 14(1), 60. https://doi.org/10.3390/genes14010060