Next Article in Journal
The Complete Chloroplast Genome Sequence of Eupatorium fortunei: Genome Organization and Comparison with Related Species
Next Article in Special Issue
Whole Exome Sequencing Study Suggests an Impact of FANCA, CDH1 and VEGFA Genes on Diffuse Gastric Cancer Development
Previous Article in Journal
Exome Array Analysis of 9721 Ischemic Stroke Cases from the SiGN Consortium
Previous Article in Special Issue
Comprehensive Analysis of Potential Prognostic Values of ANGPTLs in Colorectal Cancer
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Association between INDELs in MicroRNAs and Susceptibility to Gastric Cancer in Amazonian Population

by
Antonio A. C. Modesto
1,
Milene R. de Moraes
2,
Cristina M. D. Valente
2,
Marta S. C. R. Costa
1,
Diana F. da V. B. Leal
1,
Esdras E. B. Pereira
1,
Marianne R. Fernandes
1,*,
Jhully A. dos S. Pinheiro
2,
Karla B. C. C. Pantoja
1,
Fabiano C. Moreira
1,
Rommel M. R. Burbano
3,
Paulo P. de Assumpção
1,
Ney P. C. dos Santos
1 and
Sidney E. B. dos Santos
1,2
1
Núcleo de Pesquisas em Oncologia, Universidade Federal do Pará, R. dos Mundurucus 4487, Guamá, Belém 66073-000, Brazil
2
Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66073-000, Brazil
3
Hospital Ophir Loyola, Belém 66063-240, Brazil
*
Author to whom correspondence should be addressed.
Genes 2023, 14(1), 60; https://doi.org/10.3390/genes14010060
Submission received: 26 September 2022 / Revised: 23 November 2022 / Accepted: 24 November 2022 / Published: 24 December 2022

Abstract

:
Gastric cancer (GC) is a multifactorial, complex, and aggressive disease with a prevalence of one million new cases and high global mortality. Factors such as genetic, epigenetic, and environmental changes contribute to the onset and progression of the disease. Identification of INDELs in miRNA and its target sites in current studies showed an important role in the development of cancer. In GC, miRNAs act as oncogenes or tumor suppressors, favoring important cancer pathways, such as cell proliferation and migration. This work aims to investigate INDELs in the coding region of miRNAs (hsa-miR-302c, hsa-miR-548AJ-2, hsa-miR-4274, hsa-miR-630, hsa-miR-516B-2, hsa-miR-4463, hsa-miR-3945, hsa-miR-548H_4, hsa-miR-920, has-mir-3171, and hsa-miR-3652) that may be associated with susceptibility and clinical variants of gastric cancer. For this study, 301 patients with GC and 145 individuals from the control group were selected from an admixed population in the Brazilian Amazon. The results showed the hsa-miR-4463, hsa-miR-3945, hsa-miR-548H_4, hsa-miR-920 and hsa-miR-3652 variants were associated with gastric cancer susceptibility. The hsa-miR-4463 was significantly associated with clinical features of GC such as diffuse gastric tumor histological type, “non-cardia” localization region, and early onset. Our findings indicated that INDELs could be potentially functional genetic variants for gastric cancer risk.

1. Introduction

Cancer is a global health problem, with 18 million new cases and 9.6 million deaths per year. It represents about 12% of all causes of death and is the fourth leading cause of death of those aged 70 years or over in most countries [1,2]. Among all types of cancer, gastric cancer (GC) is the fifth most frequently diagnosed cancer and the third most deadly neoplasm worldwide. GC is a multifactorial, complex, and aggressive disease with a number of genetic, epigenetic, and environmental factors [3].
In 2020, over one million new cases of gastric cancer and 769,000 deaths were estimated worldwide. Infection with Helicobacter pylori is the primary identified cause of gastric cancer. Other risk factors for gastric cancer include a high intake of salty and smoked food, obesity, alcoholism, and smoking. However, a diet rich in fruits, vegetables, cereals, and seafood acts as a protective factor against GC [4,5]. Recent evidence shows that genetic variants are also an important factor for the tumorigenic process [6,7,8].
Somatic mutations such as INDELs may provide a selective advantage for cell growth and may initiate cancer development, including GC [9]. These genomic alterations in miRNA genes (pri-miRNAs, pre-miRNAs, mature region and SEED region) or target sites (RNAm) lead to post transcriptional regulation of mRNAs and the biogenesis of mature miRNAs and may be related to the risk of diseases. An experimental study of INDELs in miRNAs and their target sites showed the functional role of these polymorphisms in the development of diseases such as GC [10].
Investigating genetic mutation caused by INDELs in a DNA sequence is relevant because they can alter DNA sequences, which potentially results in a structurally and functionally modified protein [5,6,7]. The objective of this work was to investigate INDELs in the coding region of miRNAs that may be associated with susceptibility and clinical variants of gastric cancer.

2. Material and Methods

2.1. Ethical Declaration

The study protocol was approved by the ethics committee of Núcleo de Pesquisas em Oncologia da Universidade Federal do Pará (CAE: 30352920.0.0000.5634). Written informed consent was obtained from all study subjects.

2.2. Sample Selection

This is a case-control study which included 446 participants that were randomly selected from a public healthcare center in the Brazilian Amazon. In total, 301 patients who were diagnosed with gastric cancer in Hospital João Barros Barreto were included in the case group and 145 participants were admitted to the same hospital without any oncological disease and were included in control group. The analyses were performed from the collection of 5 mL of whole blood from each patient for the next step of DNA extraction.

2.3. DNA Extraction and Quantification

The DNA was extracted using the phenol–chloroform method and stored at −24 °C [11]. DNA quantity and quality were measured with a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA).

2.4. Selection Polymorphism—INDEL

Eleven INDELs in miRNA genes were selected for their function in several diseases. These miRNAs were found differently expressed in cancer in the literature [12]. INDELs were selected with medium and highest allele frequencies (MAF) ≥ 0.02 MAF based on the 1000 Genomes Project [12] (Table 1).

2.5. Genotyping

Multiplex PCR allowed the simultaneous analysis of 11 INDELs. Each primer was labeled (FAM, VIC, or HEX). Amplification of fluorescent PCR was performed in the ABI Verity thermocycler (Life Technologies, Foster City, CA, USA). A single multiplex reaction used the Master Mix QIAGEN Multiplex PCR Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions.
For fragment analysis, capillary electrophoresis was carried out, using the ABI 3500 Genetic Analyzer instrument (Thermofisher Scientific, Waltham, MA, USA). For capillary electrophoresis, 1.0 μL of the PCR product was added to 8.5 μL of HI-DI deionized formamide (Life Technologies, Carlsbad, CA, USA) and 0.5 μL of GeneScan 500 LIZ size standard (Life Technologies). The samples were analyzed using both GeneMapper® ID v.3.7 software (Thermofisher Scientific).

2.6. Statistical Analysis

The chi-square test was performed to determine whether genotype distributions were within Hardy–Weinberg equilibrium. Logistic regression analyses with Bonferroni correction factor were applied to improve the accuracy of genotypic models and the variables of clinical characteristics. Additional statistical analyses were made using the software RStudio [13]. A p-value of <0.05 was considered statistically significant.

3. Results

3.1. Demographic Characteristics

We analyzed 301 samples from individuals with GC and 145 samples from cancer-free individuals and we compared epidemiological characteristics of gender and age between groups, but no significant differences were found (chi-square test). Table 2 describes the clinical and epidemiological characteristics of the investigated patients. Statistical comparison between case-control characteristics related to gender and age were not significant. Regarding the location of the tumor, the most common type among the samples was the antrum and the least common was the pylorus, and when we classified samples according to Lauren, the diffuse type was the most found. In terms of staging, stage two was the most identified among the samples.

3.2. Distribution of Genotypes Associated with Susceptibility to GC

Hardy–Weinberg equilibrium (HWE) analysis was performed on the samples studied to control the variables that could be influenced by genotyping errors. Four variants MIRNA302C, MIRNA630, MIRNA3171, and MIRNA548AJ_2 were in Hardy–Weinberg disequilibrium (p < 0.05) and were removed from the analysis.
The genotypic and allelic frequencies of the groups are described in Table 3. Significant differences were found in variants miRNA4463, miRNA920, and miRNA 3652 between cases and controls. The complete table can be found in the Supplementary Materials Table S1.
When analyzing the seven INDELs variants regarding the association for susceptibility to GC, three variants were found associated with increased risk for GC (the Del allele of miRNA4463, miRNA3945, and miRNA548H_4) and two variants associated with decreased risk for CG (the Del allele of miRNA3652 and miRNA920), as shown in Table 4. The complete table on susceptibility to gastric cancer can be found in the Supplementary Materials Table S2.

3.3. Distribution of Genotypes Associated with Clinical Variants in GC

In addition to susceptibility, the clinical variants of the investigated patients were also evaluated, and when evaluating the genetic impact of the seven INDELs variants on the clinical variants categorized into Lauren subtype (diffuse or intestinal), location (cardia and non-cardia), and age (less than 40 years and more than 40 years), a significant association was found only in the miRNA4463 variant, as shown in Table 5.
There was no correlation of the other variants with the clinical characteristics as no variant had a significant association with tumor staging. The complete table of associations with the clinical variants can be found in the Supplementary Materials Table S3.
Regarding the type of gastric adenocarcinoma, significant associations of the Del allele of the MIRNA4463 gene with an increased risk for the incidence of diffuse gastric adenocarcinoma were observed. By categorizing the tumors in relation to location (cardia and non-cardia), the analyses showed a significant association of the Del allele of the MIRNA4463 gene with an increased risk of developing the tumor in the “non-cardia” region. When evaluating the allelic distribution in relation to age (less or more than 40 years), it was observed that the Del allele of MIRNA4463 was associated with a higher incidence in younger patients.

4. Discussion

The study of variants in miRNAs is of great importance to understand the pathways that affect cancer since several genomic alterations occur in specific regions of the gene that can modify the functionality and biogenesis of a molecule to be encoded as a microRNA. Additionally, evaluating variants in genes of patients with GC in the northern region of Brazil, a region that presented a high incidence of new cases compared to the general rates elsewhere, is very relevant and may provide valuable data for the elucidation of gastric carcinogenesis [1,9,10,14].
In this case-control study, we analyzed a panel of 11 INDELs in 446 samples, including 301 patients with GC and 145 individuals in the control group, all of them from an admixed population of the Brazilian Amazon. A limiting factor in the study for the control group was the absence of negative upper digestive endoscopy exams in the patients. It is important to highlight that no previous studies associating these 11 INDELs variants with GC were found. Our data demonstrated a significant association regarding the susceptibility between five variants (hsa-miR-3945_rs145931056, hsa-miR-548H_4_rs150141473, hsa-miR-920_rs66686007, hsa-miR-3652_rs62747560, and hsa-miR-4463_rs5877455) and a significant association regarding the clinicopathological data (and hsa-miR-4463_rs5877455).
MIRNA3945, located on chromosome 4, presented an INDEL of 12 base pairs in the mature region of the gene. As for the susceptibility analysis, we found a significant association of the altered Del allele of hsa-miR-3945 with an increased risk for the development of GC. Although this miRNA is not described in the literature associated with GC, the miRDB database (database for functional targets of miRNA) points to hsa-miR-3945 as a target of proteins of the Rab family, which is considered a potential indicator of metastasis and prognosis for lung carcinoma [15]; in addition, hsa-miR-3945 is also a target of the TNF receptor protein family that acts in the process of cell proliferation and tumorigenesis [16,17].
The miR548h-4 variant, located on chromosome 8, showed an INDEL of 5 base pairs in the pre-miRNA region. Regarding susceptibility, we found a significant association of the altered Del allele with an increased risk of GC development (Table 4). This INDEL has been mentioned in several important studies, such as the study with osteosarcoma, in which the analysis negatively correlated the expression of miRNA548 with the expression of KRAS, a gene active in the process of tumorigenesis and metastasis of several types of cancer, including gastric adenocarcinoma [18,19,20].
The INDEL miRNA548H_4 enables changes that influence the functioning of miRNA548, as its underexpression acts by reversing the effects of KRAS silencing, stimulating metastatic growth and migration [18]. Therefore, this study reinforces the hypothesis that the altered Del allele may act on the loss of miRNA548 function in patients with GC and consequently reverse the effects of KRAS silencing, which stimulates cell growth and the metastatic process of cancer.
Regarding MIRNA3652, our data also demonstrate a significant association of the altered Del allele of miRNA3652 with decreased risk for the development of GC (Table 4). Changes in this gene act on MIRNA3652, which plays an important role in regulating the expression of some members of the BCL2 family. Bcl-2 is an anti-apoptotic protein capable of regulating mitochondrial physiology and cell death. When dysregulated, Bcl2 also impairs sensitivity to apoptosis-inducing anticancer drugs [21]. Therefore, a possible interpretation of the data from this INDEL is that the altered Del allele in MIRNA3652 is downregulating genes such as BCL2, thus contributing to a reduced risk of GC, which corroborates our data.
With an INDEL of 5 base pairs in the pre-miRNA region, MIRNA920, located on chromosome 12, showed a significant difference in the susceptibility of cases and controls, in which the altered Del allele of this miRNA showed a decreased risk for GC (Table 4). Research involving this miRNA is associated with hepatocellular carcinoma [22], in which the study associated levels of hsa-miR-920 to the β protein TrCP, that regulates the NFKβ signaling pathway, both involved in the progression of hepatocarcinoma. Moreover, miR920 acts on several cancer pathways, involving genes of great potential in oncology, such as CEBPB, MYC and TGFBR2, which are related to the proliferation, anti-apoptosis, invasion, and metastasis pathways in pathologies such as colorectal cancer, leukemia, lymphoma, sarcoma, prostate cancer, and neuroblastoma [23]. Therefore, we suggest that the altered Del allele is preventing the expression of miRNA920 and thus favoring the reduced risk to the GC. Despite the importance that the marker presented in several cancer-associated pathways, further studies of this marker associated with gastric cancer are necessary.
In addition to these variants, our study showed a significant association of the MIRNA4463 gene with susceptibility to developing GC (Table 4). Regarding the clinical characteristics, our data also showed that the Del allele of MIRNA4463 had an increased risk for the development of early gastric cancer, and when we categorized the tumors by region of the stomach, we observed that the Del allele of this miRNA presented an increased risk of developing tumors in the non-cardia region. Moreover, when analyzed according to the classification from Lauren, the Del allele of the MIRNA4463 gene showed a significant difference and was associated with a greater chance of developing diffuse gastric tumors (Table 5).
According to Assumpção (2020), diffuse GC has a high frequency in younger patients and a stronger relevance in the association with genetic than environmental factors, and thus finding a significant association of the Del allele of MIRNA4463 to diffuse type tumors and associating it with a significant chance of developing GC earlier reinforces the potential of the miRNA4463 marker since tumors of this type are those that are not associated with precancerous lesions, occur in younger patients, and have a worse prognosis and an invasive growth pattern [24].
The miRNA4463 is associated with proliferation, migration and inhibition of apoptosis in colorectal cancer (CRC), as it is overexpressed in these types of tissues, with an even greater expression in metastatic RCC tissues. miRNA4463 targets the tumor suppressor PPP1R12B, which acts by impairing tumorigenesis and metastatic process in CCR [25,26]. In this case, our data suggest that the deletion of this marker is silencing of PPP1R12B tumor suppressor gene, so that would favor oncogenic pathways and, with that, the progression of GC. Therefore, it is understood that this variant may be an excellent candidate as a risk marker for early gastric cancer and with a worse prognosis. In addition, the literature also points out that miRNA4463 influences some types of cancer since its overexpression was associated with shorter overall survival in patients with hepatocellular carcinoma [27] and with clinically relevant subgroups of lymphoma [28]; it is, in addition, a possible diagnostic biomarker for colon cancer, as high levels of expression of this miRNA have been identified in colon tumors [29].

5. Conclusions

This study contributed to an increased knowledge on INDELs in microRNA genes in regard to GC development. Further studies in the same population with a greater sample number and in different populations for comparison are needed as well as functional studies focused on other INDELs to better understand the involvement of microRNA gene in gastric cancer. Our findings demonstrate that three INDELs variants in genes encoding microRNAs (hsa-miR-4463, hsa-miR-3945, and hsa-miR-548H_4) are associated with an increased risk of developing GC, whereas the hsa-miR-920 and hsa-miR-3652 variants are associated with a decreased risk of developing GC. These results corroborate the importance of searching for new biomarkers in the genetic and clinical analysis of patients with gastric cancer in the Amazon region.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14010060/s1, Table S1: Genotypic and allelic frequency of the 11 INDELs regarding susceptibility to GC; Table S2: Allelic variants in miRNAs associations for GC predisposition. Logistic regression analysis with Bonferroni correction; and Table S3: Significant associations of insertions and deletions in the analysis of the 11 INDELs regarding clinical variants in the GC.

Author Contributions

A.A.C.M., M.R.d.M. and C.M.D.V. designed the study, processed the data, and wrote the article; J.A.d.S.P., K.B.C.C.P., E.E.B.P., M.S.C.R.C. and F.C.M. contributed to data analysis; R.M.R.B., P.P.d.A. and N.P.C.d.S. supervised; M.R.F., D.F.d.V.B.L., N.P.C.d.S. and S.E.B.d.S. reviewed and edited; S.E.B.d.S. and P.P.d.A. were involved in funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), FAPESPA (Fundação Amazônica de Amparo a Estudos e Pesquisas), CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), UFPA (Universidade Federal do Pará) and Prefeitura Municipal de Ananindeua-PA (SEMED–Secretaria Municipal de Educação de Ananindeua-PA). These funding agencies played no role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript.

Institutional Review Board Statement

The study was approved by the Ethics Committee of Research Center of Oncology/Federal University of Pará (CAE: 30352920.0.0000.5634).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Acknowledgments

We acknowledge the Prefeitura Municipal de Ananindeua-PA; Universidade Federal do Pará (UFPA); Oncology Research Center (NPO/UFPA); Human and Medical Genetics Laboratory (LGHM/UFPA); João de Barros Barreto University Hospital (HUJBB/UFPA); and Hospital Offir Loyola (HOL-PA).

Conflicts of Interest

The authors declare that they have no competing interest.

References

  1. 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).
  2. 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).
  3. 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).
  4. 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).
  5. 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).
  6. 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).
  7. 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).
  8. 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).
  9. 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).
  10. 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).
  11. 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).
  12. 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).
  13. R Development Core Team. R: The R Project for Statistical Computing. 2021. Available online: https://www.r-project.org/ (accessed on 25 May 2021).
  14. 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).
  15. 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).
  16. 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).
  17. 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]
  18. 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).
  19. 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).
  20. 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).
  21. 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).
  22. 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]
  23. 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).
  24. 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]
  25. 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).
  26. 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).
  27. 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).
  28. 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).
  29. 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).
Table 1. Technical characteristics of the markers selected in this study.
Table 1. Technical characteristics of the markers selected in this study.
GeneIDRegionAllelesMAFPrimersAmplicon
miRNA302Crs199971565seedCACTT/C0.08F5′GCTTCCAGTTCCATCCATGT3′253–257 bp
R5′CTCAGCGTGGTAGTGTTGGA3′
miRNA3945rs145931056matureCCTATGCCCTCC/-0.28F5′AGGAGTATCCCCTCGTGGAC3′145–157 bp
R5′CAAGAGTCAGGCAAAAACAGG3′
miRNA548AJ-2rs145326096matureAAGT/-0.39F5′CTCTTCAATGCTTCCTTGAGGT3′207–211 bp
R5′CTGCATGCCAGGAGCTAAGTAT3′
miRNA4274rs202195689mature-/CCC/CCCCA0.26F5′TTTTTGTCCTCCAAGCTTCC3′132–135 bp
R5′GAACAAGAGAGAGGGCAGGA3′
miRNA630rs139334001pre-miRNA-/TTG0.42F5′GGTGACCCCAGAATTGACCCT3′96–99 bp
R5′GCCCTCAGGACGCACCTCTG3′
miRNA516B-2rs10670323pre-miRNA-/AAAGA0.32F5′CATGCACAGCTATCCAGGAG3′162–167 bp
R5′TTGTTCCTGTCCGATAGATGC3′
miRNA 4463rs5877455pre-miRNA-/AG0.47F5′TGCCCCTACTTAGCAGTCTCA3′191–193 bp
R5′GAGAGGTGGAGAACTGGGATT3′
miRNA 920rs66686007pre-miRNAGTTGT/A0.12F5′GCATCAGGACGCTGAACATA3′215–220 bp
R5′AATGCAACTTGCTCCAGAGG3′
miRNA 3171rs35170395pre-miRNA-/TA0.21F5′CTGTGTGTCTGAGGGGTGAA3′331–333 bp
R5′ATCCTGCCACTTTCTGATGG3′
miRNA 548H-4rs150141473pre-miRNATAAAG/-0.28F5′GGAATGGAAAATAGACAAGAAGTGA3′197–202 bp
R5′TGGCAAGTGTACCACAGAAAAC3′
miRNA 3652rs62747560pre-miRNAGGGGTGG/-0.36F5′ATTGGTGGGTTCATGTTTCC3′236–246 bp
R5′CAGAATCACTCACCGAAGGTC3′
Table 2. Demographic data of gastric cancer cases and control.
Table 2. Demographic data of gastric cancer cases and control.
CharacteristicCases
n = 301
Controls
n = 145
p-Value
Age (yr) Median49 (18–88)41.5 (18–65)0.198
≤40146 (48.6)80 (55.1)
>40155 (51.4)65 (44.82)
Gender 0.606
Male175 (58.4)81 (55.8)
Female126 (41.55)64 (44.1)
Tumor Location
Body60 (20.7)NA
Cardia88 (29.7)NA
Antrum91 (30.7)NA
Fundus31 (10.4)NA
Pylorus6 (2)NA
Missing25 (6.5)NA
Lauren
Intestinal111 (37.5)NA
Diffuse160 (54)NA
Missing30 (8.44)NA
Tumor Staging
Stage 132 (10.8)NA
Stage 265 (21.9)NA
Stage 356 (18.9)NA
Stage 462 (20.9)NA
Missing86 (27.5)NA
Table 3. Genotypic and allelic frequency of selected INDELs from NCBI database.
Table 3. Genotypic and allelic frequency of selected INDELs from NCBI database.
GeneCases n (%)Controls n (%)p-ValueOR (95% CI)
miRNA516B_2 (rs10670323)
Ins/Ins3 (1.0%)3 (2.1%)
Ins/Del57 (19%)28 (19.4%)0.660.47 (0.09–2.37)
Del/Del240 (80%)113 (78.5%)
Ins0.100.11
Del0.890.88
miRNA4463 (rs5877455)
Ins/Ins85 (28.6%)57 (41.6%)
Ins/Del148 (49.8%)59 (43.1%)0.022.04 (1.13–3.71)
Del/Del64 (21.5%)21 (15.3%)
Ins0.530.63
Del0.460.36
miRNA3945 (rs145931056)
Ins/Ins236 (80.3%)127 (88.8%)
Ins/Del54 (18.4%)14 (9.8%)0.051.08 (0.19–5.96)
Del/Del4 (1.4%)2 (1.4%)
Ins0.890.93
Del0.100.06
miRNA548H_4 (rs150141473)
Ins/Ins220 (74.8%)120 (83.9%)
Ins/Del71 (24.1%)22 (15.4%)0.091.64 (0.17–15.90)
Del/Del3 (1.0%)1 (0.7%)
Ins0.860.91
Del0.130.08
miRNA4274 (rs202195689)
Ins/Ins269 (90.9%)121 (85.2%)
Ins/Del25 (8.4%)21 (14.8%)0.090.54 (0.29–0.99)
Del/Del2 (0.7%)0 (0%)
Ins0.950.92
Del0.040.07
miRNA920 (rs66686007)
Ins/Ins269 (91.5%)119 (82.1%)
Ins/Del24 (8.2%)24 (16.6%)0.011.00 (0.39–1.47)
Del/Del1 (0.3%)2 (1.4%)
Ins0.950.90
Del0.040.09
miRNA3652 (rs62747560)
Ins/Ins183 (62.2%)89 (62.7%)
Ins/Del103 (35%)39 (27.5%)0.001.28 (0.82–2.01)
Del/Del8 (2.7%)14 (9.9%)
Ins0.790.73
Del0.200.23
Table 4. Allelic variants in MIRNAs with significant associations for GC predisposition. Logistic regression analysis with Bonferroni correction.
Table 4. Allelic variants in MIRNAs with significant associations for GC predisposition. Logistic regression analysis with Bonferroni correction.
GeneModelOR (95% CI)p-Value
miRNA4463_rs5877455_Ins/Ins vs. Del/Ins + Del/Del1.78 (1.16–2.71)0.007
miRNA3945_rs145931056Ins/Ins vs. Del/Ins + Del/Del1.95 (1.08–3.53)0.021
miRNA548H_4_rs150141473Ins/Ins vs. Del/Ins + Del/Del1.75 (1.05–2.95)0.028
miRNA920_rs66686007Ins/Ins vs. Del/Ins + Del/Del0,43 (0.24–0.77)0.004
miRNA3652_rs62747560Ins/Ins + Ins/Del vs. Del/Del0.26 (0.10–0.62)0.002
Genotypes Del/Del = homozygous deletion, Del/Ins = heterozygous, and Ins/Ins = homozygous insertion.
Table 5. Significant associations between INDEL miRNA4463 and clinical variants in GC.
Table 5. Significant associations between INDEL miRNA4463 and clinical variants in GC.
GeneModelCategorizationOR (95% CI)p-Value
miRNA4463_rs5877455_Ins/Ins vs. Del/Ins + Del/DelDiffuse or Intestinal type2.30 (1.27–4.18)0.004
miRNA4463_rs5877455_Ins/Ins vs. Del/Ins + Del/DelLocation (cardia and non-cardia)2.20 (1.26–3.84)0.005
miRNA4463_rs5877455_Ins/Ins vs. Del/Ins + Del/DelAge (less or more than 40 years)2.80 (1.64–4.80)0.000
Genotypes Del/Del = homozygous deletion, Del/Ins = heterozygous, and Ins/Ins = homozygous insertion.
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.

Share and Cite

MDPI and ACS Style

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

AMA Style

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 Style

Modesto, 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

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop