TSitologiya i Genetika 2022, vol. 56, no. 4, 82-86
Cytology and Genetics 2022, vol. 56, no. 4, 379–390, doi: https://www.doi.org/10.3103/S0095452722040065


T.T.N. Nguyen, T.H.N. Nguyen, H.N. Phan, H.T. Nguyen

  1. Faculty of Biology and Biotechnology, University of Science, Ho Chi Minh City, Vietnam, 700000
  2. Vietnam National University, Ho Chi Minh City, Vietnam, 700000

Multiple common variations discovered via genome­wide association studies (GWASs) were shown to have a minimal association with breast cancer (BC) risk in Vietnamese women. This study analyzed the cumulative effect in predicting BC risk of ten single nucleotide polymorphisms (SNPs) identified by previous GWAS and were common in Vietnamese. In this case­control research, 240 BC patients and 271 healthy controls were recruited to assess candi­date SNPs’ association with BC risk. A polygenic risk score (PRS) was then created from SNPs strongly related to the risk of BC among the assessed population. The area under the receiver operating characteristic curve (AUC) was used to assess the effectiveness of the PRS model with BC risk. Logistic regression results showed seven individual SNPs (rs2155209, rs4784227, rs2605039, rs3817198, rs2981582, rs11614913, and rs12325489) were significantly associated with BC risk after multiple testing. These SNPs were then used to create the PRS model. Compared with women in the lowest quartile, women in the highest quartile of PRS had a considerably higher risk (odds ratio 2.65; 95 % confidence interval (95 % CI) 1.61–4.40) with AUC at 71 %. These findings suggest that the 7­SNP PRS would effectively distinguish between women with high and low risk of BC, indicating the genetic marker for BC risk prediction in a Vietnamese population.

Keywords: breast cancer risk; polygenic risk score; risk prediction model; single nucleotide polymorphism; Vietnam

TSitologiya i Genetika
2022, vol. 56, no. 4, 82-86

Current Issue
Cytology and Genetics
2022, vol. 56, no. 4, 379–390,
doi: 10.3103/S0095452722040065

Full text and supplemented materials


Allman, R., Dite, G.S., Hopper, J.L., et al., SNPs and breast cancer risk prediction for African American and Hispanic women, Breast Cancer Res. Treat., 2015, vol. 154, no. 3, pp. 583–589. https://doi.org/10.1007/s10549-015-3641-7

Bastami, M., Choupani, J., Saadatian, Z., et al., Evidences from a systematic review and meta-analysis unveil the role of miRNA polymorphisms in the predisposition to female neoplasms, Int. J. Mol. Sci., 2019, vol. 20, no. 20, art. ID 5088. https://doi.org/10.3390/ijms20205088

Black, M.H., Li, S., LaDuca, H., et al., Polygenic risk score for breast cancer in high-risk women, J. Clin. Oncol., 2018, vol. 36, pp. 1508-1508. https://doi.org/10.1200/JCO.2018.36.15_suppl.1508

Bradbury, A.R. and Olopade, O.I., Genetic susceptibility to breast cancer, Rev. Endocr. Metab. Disord., 2007, vol. 8, no. 3, pp. 255–267. https://doi.org/10.1007/s11154-007-9038-0

Cai, Q., Long, J., Lu, W., et al., Genome-wide association study identifies breast cancer risk variant at 10q21. 2: results from the Asia Breast Cancer Consortium, Hum. Mol. Genet., 2011, vol. 20, no. 24, pp. 4991–4999. https://doi.org/10.1093/hmg/ddr405

Cai, Q., Zhang, B., Sung, H., et al., Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1, Nature Genetics, 2014, vol. 46, no. 8, pp. 886–890. https://doi.org/10.1038/ng.3041

Campa, D., Kaaks, R., Le Marchand, L., et al., Interactions between genetic variants and breast cancer risk factors in the breast and prostate cancer cohort consortium, J. Natl. Cancer Inst., 2011, vol. 103, no. 16, pp. 1252–1263. https://doi.org/10.1093/jnci/djr265

Chan, C.H.T., Munusamy, P., Loke, S.Y., et al., Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese, Oncotarget, 2018, vol. 9, no. 16, pp. 12796–12804. https://doi.org/10.18632/oncotarget.24374

Chen, Q.H., Wang, Q.B., and Zhang, B., Ethnicity modifies the association between functional microRNA polymorphisms and breast cancer risk: a HuGE meta-analysis, Tumor Biol., 2014, vol. 35, no. 1, pp. 529–543. https://doi.org/10.1007/s13277-013-1074-7

Chen, Y., Fu, F., Lin, Y., et al., The precision relationships between eight GWAS-identified genetic variants and breast cancer in a Chinese population, Oncotarget, 2016, vol. 7, no. 46, art. ID 75457. https://doi.org/10.18632/oncotarget.12255

Chen, Y., Shi, C., and Guo, Q., TNRC9 rs12443621 and FGFR2 rs2981582 polymorphisms and breast cancer risk, World J. Surg. Oncol., 2016, vol. 14, no. 1, art. ID 50. https://doi.org/10.1186/s12957-016-0795-7

Choupani, J., Nariman-Saleh-Fam, Z., Saadatian, Z., et al., Association of mir-196a-2 rs11614913 and mir-149 rs2292832 polymorphisms with risk of cancer: an updated meta-analysis, Front. Genet., 2019, vol. 10, art. ID 186. https://doi.org/10.3389/fgene.2019.00186

Couch, F.J., Kuchenbaecker, K.B., Michailidou, K., et al., Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer, Nat. Commun., 2016, vol. 7, no. 1, art. ID 11375. https://doi.org/10.1038/ncomms11375

Dai, Z.J., Shao, Y.P., Wang, X.J., et al., Five common functional polymorphisms in microRNAs (rs2910164, rs2292832, rs11614913, rs3746444, rs895819) and the susceptibility to breast cancer: evidence from 8361 cancer cases and 8504 controls, Curr. Pharm. Des., 2015, vol. 21, no. 11, pp. 1455–1463. https://doi.org/10.2174/1381612821666141208143533

Dai, Z.M., Kang, H.F., Zhang, W.G., et al., The Associations of Single Nucleotide Polymorphisms in miR196a2, miR-499, and miR-608 with breast cancer susceptibility: A STROBE-compliant observational study, Medicine (Baltimore), 2016, vol. 95, no. 7, art. ID e2826. https://doi.org/10.1097/MD.0000000000002826

Darabi, H., Czene, K., Zhao, W., et al., Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement, Breast Cancer Res., 2012, vol. 14, no. 1, art. ID R25. https://doi.org/10.1186/bcr3110

Dinger, M.E., Amaral, P.P., Mercer, T.R., et al., Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation, Genome Res., 2008, vol. 18, no. 9, pp. 1433–1445. https://doi.org/10.1101/gr.078378.108

Dite, G.S., MacInnis, R.J., Bickerstaffe, A., et al., Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: australian breast cancer family registry, Cancer Epidemiol. Biomarkers Prev., 2016, vol. 25, no. 2, pp. 359–365. https://doi.org/10.1158/1055-9965.Epi-15-0838

Dite, G.S., Mahmoodi, M., Bickerstaffe, A., et al., Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model, Breast Cancer Res. Treat., 2013, vol. 139, no. 3, pp. 887–896. https://doi.org/10.1007/s10549-013-2610-2

Easton, D.F., Pooley, K.A., Dunning, A.M., et al., Genome-wide association study identifies novel breast cancer susceptibility loci, Nature, 2007, vol. 447, no. 7148, pp. 1087–1093. https://doi.org/10.1038/nature05887

Evans, D.G., Brentnall, A., Byers, H., et al., The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case–control study, J. Med. Genet., 2017, vol. 54, no. 2, art. ID 111113. https://doi.org/10.1136/jmedgenet-2016-104125

Fernandes, G.C., Michelli, R.A., Scapulatempo-Neto, C., et al., Association of polymorphisms with a family history of cancer and the presence of germline mutations in the BRCA1/BRCA2 genes, Hered. Cancer Clin. Pract., 2016, vol. 14, no. 1, art.ID. 2. https://doi.org/10.1186/s13053-015-0042-1

Fernandez-Navarro, P., Pita, G., Santamarina, C., et al., Association analysis between breast cancer genetic variants and mammographic density in a large population-based study (Determinants of Density in Mammographies in Spain) identifies susceptibility loci in TOX3 gene, Eur. J. Cancer, 2013, vol. 49, no. 2, pp. 474–481. https://doi.org/10.1016/j.ejca.2012.08.026

Fletcher, O., Johnson, N., Orr, N., et al., Novel breast cancer susceptibility locus at 9q31.2: results of a genome-wide association study, J. Natl. Cancer Inst., 2011, vol. 103, no. 5, pp. 425–435. https://doi.org/10.1093/jnci/djq563

Fogarty, M.P., Emmenegger, B.A., Grasfeder, L.L., et al., Fibroblast growth factor blocks Sonic hedgehog signaling in neuronal precursors and tumor cells, Proc. Natl. Acad. Sci., 2007, vol. 104, no. 8, pp. 2973–2978. https://doi.org/10.1073/pnas.0605770104

Gapska, P., Scott, R.J., Serrano-Fernandez, P., et al., Vitamin D receptor variants and breast cancer risk in the Polish population, Breast Cancer Res. Treat., 2009, vol. 115, no. 3, pp. 629–633. https://doi.org/10.1007/s10549-008-0107-1

Ghosh, J.C., Dohi, T., Kang, B.H., et al., Hsp60 regulation of tumor cell apoptosis, J. Biol. Chem., 2008, vol. 283, no. 8, pp. 5188–5194. https://doi.org/10.1074/jbc.M705904200

Gibb, E.A., Brown, C.J., and Lam, W.L., The functional role of long non-coding RNA in human carcinomas, Mol. Cancer, 2011, vol. 10, no. 1, art. ID 38. https://doi.org/10.1186/1476-4598-10-38

Glubb, D.M., Maranian, M.J., Michailidou, K., et al., Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1, Am. J. Hum. Genet., 2015, vol. 96, no. 1, pp. 5–20. https://doi.org/10.1016/j.ajhg.2014.11.009

Gold, B., Kirchhoff, T., Stefanov, S., et al., Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33, Proc. Natl. Acad. Sci., 2008, vol. 105, no. 11, pp. 4340–4345. https://doi.org/10.1073/pnas.0800441105

Guttman, M., Amit, I., Garber, M., et al., Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals, Nature, 2009, vol. 458, no. 7235, pp. 223–227. https://doi.org/10.1038/nature07672

Haiman, C.A., Chen, G.K., Vachon, C.M., et al., A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer, Nat. Genet., 2011, vol. 43, no. 12, pp. 1210–1214. https://doi.org/10.1038/ng.985

Han, M.-R., Long, J., Choi, J.-Y., et al., Genome-wide association study in East Asians identifies two novel breast cancer susceptibility loci, 2016, Hum. Mol. Genet., vol. 25, no. 15, pp. 3361-3371. https://doi.org/10.1093/hmg/ddw164

Han, M.R., Deming-Halverson, S., Cai, Q., et al., Evaluating 17 breast cancer susceptibility loci in the Nashville breast health study, Breast Cancer, 2015, vol. 22, no. 5, pp. 544–551. https://doi.org/10.1007/s12282-014-0518-2

Harrison, R.E., Sikorski, B.A., and Jongstra, J., Leukocyte-specific protein 1 targets the ERK/MAP kinase scaffold protein KSR and MEK1 and ERK2 to the actin cytoskeleton, J. Cell Sci., 2004, vol. 117, no. 10, pp. 2151–2157.https://doi.org/10.1242/jcs.00955

Hein, A., Rack, B., Li, L., et al., Genetic breast cancer susceptibility variants and prognosis in the prospectively randomized SUCCESS a study, Geburtshilfe Frauenheilk., 2017, vol. 77, no. 6, pp. 651–659. https://doi.org/10.1055/s-0042-113189

Hill, K., The demography of menopause, Maturitas, 1996, vol. 23, no. 2, pp. 113–127. https://doi.org/10.1016/0378-5122(95)00968-x

Hsieh, Y.C., Tu, S.H., Su, C.T., et al., A polygenic risk score for breast cancer risk in a Taiwanese population, Breast Cancer Res. Treat., 2017, vol. 163, no. 1, pp. 131–138. https://doi.org/10.1007/s10549-017-4144-5

Huarte, M. and Rinn, J.L., Large non-coding RNAs: missing links in cancer?, Hum. Mol. Genet., 2010, vol. 19, no. R2, pp. R152–R161. https://doi.org/10.1093/hmg/ddq353

Hughes, E., Judkins, T., Wagner, S., et al., Development and validation of a residual risk score to predict breast cancer risk in unaffected women negative for mutations on a multi-gene hereditary cancer panel, J. Clin. Oncol., 2017, vol. 35, pp. 1579–1579. https://doi.org/10.1200/JCO.2017.35.15_suppl.1579

Hunter, D.J., Kraft, P., Jacobs, K.B., et al., A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer, Nat. Genet., 2007, vol. 39, no. 7, pp. 870–874. https://doi.org/10.1038/ng2075

Kim, H.-C., Lee, J.-Y., Sung, H., et al., A genome-wide association study identifies a breast cancer risk variant in ERBB4 at 2q34: results from the Seoul Breast Cancer Study, Breast Cancer Res., 2012, vol. 14, no. 2, art. ID R 56. https://doi.org/10.1186/bcr3158

Kuchenbaecker, K.B., McGuffog, L., Barrowdale, D., et al., Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers, J. Natl. Cancer Inst., 2017, vol. 109, no. 7. https://doi.org/10.1093/jnci/djw302

Lakeman, I.M.M., Hilbers, F.S., Rodríguez-Girondo, M., et al., Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1/2 breast cancer families, J. Med. Genet., 2019, vol. 56, no. 9, pp. 581–589. https://doi.org/10.1136/jmedgenet-2019-106072

Li, H., Feng, B., Miron, A., et al., Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab, Genet. Med., 2017, vol. 19, no. 1, pp. 30–35. https://doi.org/10.1038/gim.2016.43

Li, N., Zhou, P., Zheng, J., et al., A polymorphism rs12325489C>T in the LincRNA-ENST00000515084 exon was found to modulate breast cancer risk via GWAS-based association analyses, PLoS One, 2014, vol. 9, no. 5, art. ID e98251. https://doi.org/10.1371/journal.pone.0098251

Lin, Y., Fu, F., Chen, M., et al., Associations of two common genetic variants with breast cancer risk in a Chinese population: a stratified interaction analysis, PLoS One, 2014, vol. 9, no. 12, pp. 1–12. https://doi.org/10.1371/journal.pone.0115707

Lindström, S., Thompson, D.J., Paterson, A.D., et al., Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk, Nat. Commun., 2014, vol. 5, no. 1, art. ID 5303. https://doi.org/10.1038/ncomms6303

Lobrich, M. and Jeggo, P., The impact of a negligent G2/M checkpoint on genomic instability cancer induction, Nat. Rev. Cancer, 2007, vol. 7, no. 11, pp. 861–869. https://doi.org/10.1038/nrc2248

Long, J., Shu, X.O., Cai, Q., et al., Evaluation of breast cancer susceptibility loci in Chinese women, Cancer Epidemiol., Biomarkers Prev., 2010, vol. 19, no. 9, pp. 2357–2365. https://doi.org/10.1158/1055-9965.EPI-10-0054

Ma, L., Teruya-Feldstein, J., and Weinberg, R.A., Tumour invasion and metastasis initiated by microRNA-10b in breast cancer, Nature, 2007, vol. 449, no. 7163, pp. 682–688. https://doi.org/10.1038/nature06174

MacLachlan, T.K., Sang, N., and Giordano, A., Cyclins, cyclin-dependent kinases and Cdk inhibitors: implications in cell cycle control and cancer, Crit. Rev. Eukaryotic Gene Expression, 1995, vol. 5, no. 2, pp. 127–156. https://doi.org/10.1615/critreveukargeneexpr.v5.i2.20

Mavaddat, N., Pharoah, P.D., Michailidou, K., et al., Prediction of breast cancer risk based on profiling with common genetic variants, J. Natl. Cancer Inst., 2015, vol. 107, no. 5, art. ID djv036. https://doi.org/10.1093/jnci/djv036

Mealiffe, M.E., Stokowski, R.P., Rhees, B.K., et al., Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information, J. Natl. Cancer Inst., 2010, vol. 102, no. 21, pp. 1618–1627. https://doi.org/10.1093/jnci/djq388

Michailidou, K., Beesley, J., Lindstrom, S., et al., Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer, Nat. Genet., 2015, vol. 47, no. 4, pp. 373–380. https://doi.org/10.1038/ng.3242

Möller, S., Mucci, L.A., Harris, J.R., et al., The heritability of breast cancer among women in the nordic twin study of cancer, Cancer Epidemiol. Prev. Biomarkers, 2016, vol. 25, no. 1, pp. 145–150. https://doi.org/10.1158/1055-9965.EPI-15-0913

Mu, K., Wu, Z.Z., Yu, J.P., et al., Meta-analysis of the association between three microRNA polymorphisms and breast cancer susceptibility, Oncotarget, 2017, vol. 8, no. 40, pp. 68809–68824. https://doi.org/10.18632/oncotarget.18516

Muranen, T.A., Mavaddat, N., Khan, S., et al., Polygenic risk score is associated with increased disease risk in 52 Finnish breast cancer families, Breast Cancer Res. Treat., 2016, vol. 158, no. 3, pp. 463–469. https://doi.org/10.1007/s10549-016-3897-6

Na, Li., Ping, Zhou., Jian, Zheng., et al., A polymorphism rs12325489C>T in the LincRNA-ENST00000515084 exon was found to modulate breast cancer risk via GWAS-based association analyses, PLoS One, 2014, vol. 9, no. 5, pp. e98251–e98251. https://doi.org/10.1371/journal.pone.0098251

Orr, N., Dudbridge, F., Dryden, N., et al., Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2, Hum. Mol. Genet., 2015, vol. 24, no. 10, pp. 2966–2984. https://doi.org/10.1093/hmg/ddv035

Özgöz, A., İçduygu, F.M., Yükseltürk, A., et al., Low-penetrance susceptibility variants and postmenopausal oestrogen receptor positive breast cancer, J. Genet., 2020, vol. 99, no. 1, art. ID 15. https://doi.org/10.1007/s12041-019-1174-2

Pace, A., Barone, G., Lauria, A., et al., Hsp60, a novel target for antitumor therapy: structure-function features and prospective drugs design, Curr. Pharm. Des., 2013, vol. 19, no. 15, pp. 2757–2764. https://doi.org/10.2174/1381612811319150011

Peto, J., Collins, N., Barfoot, R., et al., Prevalence of BRCA1 and BRCA2 gene mutations in patients with early-onset breast cancer, J. Natl. Cancer Inst., 1999, vol. 91, no. 11, pp. 943–949. https://doi.org/10.1093/jnci/91.11.943

Pharoah, P.D., Dunning, A.M., Ponder, B.A., et al., Association studies for finding cancer-susceptibility genetic variants, Nat. Rev. Cancer, 2004, vol. 4, no. 11, pp. 850–860. https://doi.org/10.1038/nrc1476

Qi, P., Wang, L., Zhou, B., et al., Associations of miRNA polymorphisms and expression levels with breast cancer risk in the Chinese population, Genet. Mol. Res., 2015, vol. 14, no. 2, pp. 6289–6296. https://doi.org/10.4238/2015.June.11.2

Qian, B., Zheng, H., Yu, H., et al., Genotypes and phenotypes of IGF-I and IGFBP-3 in breast tumors among Chinese women, Breast Cancer Res. Treat., 2011, vol. 130, no. 1, pp. 217–226. https://doi.org/10.1007/s10549-011-1552-9

Ricol, D., Cappellen, D., El Marjou, A., et al., Tumour suppressive properties of fibroblast growth factor receptor 2-IIIb in human bladder cancer, Oncogene, 1999, vol. 18, no. 51, pp. 7234–7243. https://doi.org/10.1038/sj.onc.1203186

Safari, S., Baratloo, A., Elfil, M., et al., Evidence based emergency medicine; part 5 receiver operating curve and area under the curve, Emergency (Tehran, Iran), 2016, vol. 4, no. 2, pp. 111–113. https://doi.org/10.22037/aaem.v4i2.232

Sawyer, S., Mitchell, G., McKinley, J., et al., A role for common genomic variants in the assessment of familial breast cancer, J. Clin. Oncol., 2012, vol. 30, no. 35, pp. 4330–4336. https://doi.org/10.1200/JCO.2012.41.7469

Schwartz, M.D., Isaacs, C., Graves, K.D., et al., Long-term outcomes of BRCA1/BRCA2 testing: risk reduction and surveillance, Cancer, 2012, vol. 118, no. 2, pp. 510–517. https://doi.org/10.1002/cncr.26294

Shan, J., Dsouza, S.P., Bakhru, S., et al., TNRC9 downregulates BRCA1 expression and promotes breast cancer aggressiveness, Cancer Res., 2013, vol. 73, no. 9, pp. 2840–2849. https://doi.org/10.1158/0008-5472.CAN-12-4313

Shan, J., Mahfoudh, W., Dsouza, S.P., et al., Genome-Wide Association Studies (GWAS) breast cancer susceptibility loci in Arabs: susceptibility and prognostic implications in Tunisians, Breast Cancer Res. Treat., 2012, vol. 135, no. 3, pp. 715–724. https://doi.org/10.1007/s10549-012-2202-6

Shi, J., Zhang, Y., Zheng, W., et al., Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer, Int. J. Cancer, 2016, vol. 139, no. 6, pp. 1303–1317. https://doi.org/10.1002/ijc.30150

Shieh, Y., Hu, D., Ma, L., et al., Breast cancer risk prediction using a clinical risk model and polygenic risk score, Breast Cancer Res. Treat., 2016, vol. 159, no. 3, pp. 513–525. https://doi.org/10.1007/s10549-016-3953-2

Shieh, Y., Hu, D., Ma, L., et al., Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones, Breast Cancer Res. Treat., 2017, vol. 166, no. 2, pp. 603–612. https://doi.org/10.1007/s10549-017-4430-2

Stacey, S.N., Manolescu, A., Sulem, P., et al., Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer, Nat. Genet., 2007, vol. 39, no. 7, pp. 865–869. https://doi.org/10.1038/ng2064

Stacey, S.N., Manolescu, A., Sulem, P., et al., Common variants on chromosome 5p12 confer susceptibility to estrogen receptor–positive breast cancer, Nat. Genet., 2008, vol. 40, no. 6, pp. 703–706. https://doi.org/10.1038/ng.131

Starlard-Davenport, A., Allman, R., Dite, G.S., et al., Validation of a genetic risk score for Arkansas women of color, PLoS One, 2018, vol. 13, no. 10, art. ID e0204834. https://doi.org/10.1371/journal.pone.0204834

Tajbakhsh, A., Farjami, Z., Darroudi, S., et al., Association of rs4784227-CASC16 (LOC643714 locus) and rs4782447-ACSF3 polymorphisms and their association with breast cancer risk among Iranian population, EXCLI J., 2019, vol. 18, pp. 429–438. https://doi.org/10.17179/excli2019-1374

Tan, T., Zhang, K., Chen, W., Genetic variants of ESR1 and SGSM3 are associated with the susceptibility of breast cancer in the Chinese population, Breast Cancer, 2017, vol. 24, no. 3, pp. 369–374. https://doi.org/10.1007/s12282-016-0712-5

Turnbull, C., Ahmed, S., Morrison, J., et al., Genome-wide association study identifies five new breast cancer susceptibility loci, Nat. Genet., 2010, vol. 42, no. 6, pp. 504–507. https://doi.org/10.1038/ng.586

Vachon, C.M., Pankratz, V.S., Scott, C.G., et al., The contributions of breast density and common genetic variation to breast cancer risk, J. Natl. Cancer Inst., 2015, vol. 107, no. 5, art. ID dju397. https://doi.org/10.1093/jnci/dju397

Wacholder, S., Hartge, P., Prentice, R., et al., Performance of common genetic variants in breast-cancer risk models, N. Engl. J. Med., 2010, vol. 362, no. 11, pp. 986–993. https://doi.org/10.1056/NEJMoa0907727

Wang, J., Wang, Q., Liu, H., et al., The association of miR-146a rs2910164 and miR-196a2 rs11614913 polymorphisms with cancer risk: a meta-analysis of 32 studies, Mutagenesis, 2012, vol. 27, no. 6, pp. 779–788. https://doi.org/10.1093/mutage/ges052

Wang, P.Y., Gao, Z.H., Jiang, Z.H., et al., The associations of single nucleotide polymorphisms in miR-146a, miR-196a and miR-499 with breast cancer susceptibility, PLoS One, 2013, vol. 8, no. 9, art. ID e70656. https://doi.org/10.1371/journal.pone.0070656

Wen, W., Shu, X.O., Guo, X., et al., Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry, Breast Cancer Res., 2016, vol. 18, no. 1, art. ID 124. https://doi.org/10.1186/s13058-016-0786-1

Wu, Z., Wang, P., Song, C., et al., Evaluation of miRNA-binding-site SNPs of MRE11A, NBS1, RAD51 and RAD52 involved in HRR pathway genes and risk of breast cancer in China, Mol. Genet. Genomics, 2015, vol. 290, no. 3, pp. 1141–1153. https://doi.org/10.1007/s00438-014-0983-5

Xu, M., Xu, Y., Chen, M., et al., Association study confirms two susceptibility loci for breast cancer in Chinese Han women, Breast Cancer Res. Treat., 2016, vol. 159, no. 3, pp. 433–442. https://doi.org/10.1007/s10549-016-3952-3

Xu, W., Xu, J., Liu, S., et al., Effects of common polymorphisms rs11614913 in miR-196a2 and rs2910164 in miR-146a on cancer susceptibility: a meta-analysis, PLoS One, 2011, vol. 6, no. 5, art. ID e20471. https://doi.org/10.1371/journal.pone.0020471

Yu, K., Xu, J., Liu, Z., et al., Conditional inactivation of FGF receptor 2 reveals an essential role for FGF signaling in the regulation of osteoblast function and bone growth, Development, 2003, vol. 130, no. 13, pp. 3063–3074. https://doi.org/10.1242/dev.00491

Zhang, H., Zhang, Y., Yan, W., et al., Association between three functional microRNA polymorphisms (miR-499 rs3746444, miR-196a rs11614913 and miR-146a rs2910164) and breast cancer risk: a meta-analysis, Oncotarget, 2017, vol. 8, no. 1, pp. 393–407. https://doi.org/10.18632/oncotarget.13426

Zhang, Y., Zeng, X., Liu, P., et al., Association between FGFR2 (rs2981582, rs2420946 and rs2981578) polymorphism and breast cancer susceptibility: a meta-analysis, Oncotarget, 2017, vol. 8, no. 2, pp. 3454–3470. https://doi.org/10.18632/oncotarget.13839

Zheng, W., Wen, W., Gao, Y.-T., et al., Genetic and clinical predictors for breast cancer risk assessment and stratification among Chinese women, J. Natl. Cancer Inst., 2010, vol. 102, no. 13, pp. 972–981. https://doi.org/10.1093/jnci/djq170

Zheng, Y., Ogundiran, T.O., Falusi, A.G., et al., Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers, Carcinogenesis, 2013, vol. 34, no. 7, pp. 1520–1528. https://doi.org/10.1093/carcin/bgt090

Zhu, R.M., Lin, W., Zhang, W., et al., Modification effects of genetic polymorphisms in FTO, IL-6, and HSPD1 on the associations of diabetes with breast cancer risk and survival, PLoS One, 2017, vol. 12, no. 6, art. ID e0178850. https://doi.org/10.1371/journal.pone.0178850

Zuo, X., Wang, H., Mi, Y., et al., The association of CASC16 variants with breast Cancer risk in a northwest Chinese female population, Mol. Med., 2020, vol. 26, no. 1, pp. 1–10. https://doi.org/10.1186/s10020-020-0137-7