Advertisement

Correlation of MLH1 polymorphisms, survival statistics, in silico assessment and gene downregulation with clinical outcomes among breast cancer cases

  • Saima Shakil MalikEmail author
  • Ayisha Zia
  • Sumaira Mubarik
  • Nosheen Masood
  • Sajid Rashid
  • Alice Sherrard
  • Muhammad Bilal Khan
  • Muhammad Tahir Khadim
Original Article
  • 39 Downloads

Abstract

This study aimed to investigate the role of MLH1 polymorphisms, respective protein structure prediction, survival analysis, related clinicopathological details and MLH1 expression in breast cancer (BC). Genotyping of selected SNPs in BC patients (493) and age matched controls (387) were performed by Tetra–ARMS PCR. Gene expression among breast tumors (127) and adjacent control tissues were analysed using reverse transcriptase PCR (RT-PCR) and immunohistochemistry. Statistical analysis was performed by SPSS and MedCalc. Conditional logistic regression analysis was applied to compute the odds ratio and confidence interval. Phyre2 and I-TASSER were used to generate MLH1 protein structures and verified by a variety of computational tools. Genotyping illustrated that MLH1 polymorphisms (rs63749795 and rs63749820) were significantly associated (P ≤ 0.05) with risk of developing BC. Down regulation of MLH1 gene expression/loss of the MLH1 protein (OR 12; CI 2.8–53.1) was observed in BC cases, illustrating its potential role in disease development. Moreover, loss of the MLH1 protein was found to be associated with higher grade cancer (P = 0.02) and lymph node positivity (P = 0.03), highlighting its essential role, as a component of the mismatch repair (MMR) machinery. Bioinformatics analysis confirmed that nonsense mutations produce a truncated MLH1 protein, causing a reduction in MMR efficiency. No association between MLH1 polymorphisms and overall and progression free survival statistics was observed among BC cases, possibly due to short follow–up study. Results at DNA, RNA and protein levels, along with in silico analysis, highlights the potential role of MLH1 in DNA repair mechanisms, within BC. Therefore, it was concluded that MLH1 may contribute towards BC development and progression.

Keywords

MLH1 ARMS PCR Breast cancer Polymorphisms Expression Survival analysis 

Notes

Acknowledgements

We would like to thank all the patients, their family members and colleagues at Armed Forces Institute of Pathology for their kind help and support.

Funding

No support or funding is available for this study.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

References

  1. 1.
    Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA: Cancer J Clin 68(1):7–30Google Scholar
  2. 2.
    Malik SS, Mubarik S, Masood N, Khadim MT (2018) An insight into clinical outcome of XPG polymorphisms in breast cancer. Mol Biol Rep 45(6):2369–2375CrossRefGoogle Scholar
  3. 3.
    DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A (2016) Breast cancer statistics, 2015: convergence of incidence rates between black and white women. CA: Cancer J Clin 66(1):31–42Google Scholar
  4. 4.
    Mavaddat N, Pharoah PD, Michailidou K, Tyrer J, Brook MN, Bolla MK, Wang Q, Dennis J, Dunning AM, Shah M (2015) Prediction of breast cancer risk based on profiling with common genetic variants. JNCI: J Natl Cancer Inst.  https://doi.org/10.1093/jnci/djv036 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Kappil M, Terry MB, Delgado-Cruzata L, Liao Y, Santella RM (2016) Mismatch repair polymorphisms as markers of breast cancer prevalence in the Breast Cancer Family Registry. Anticancer Res 36(9):4437–4441.  https://doi.org/10.21873/anticanres.10987 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Ma Y, Chen Y, Petersen I (2017) Expression and promoter DNA methylation of MLH1 in colorectal cancer and lung cancer. Pathol-Res Pract 213(4):333–338CrossRefGoogle Scholar
  7. 7.
    Buchanan DD, Tan YY, Walsh MD, Clendenning M, Metcalf AM, Ferguson K, Arnold ST, Thompson BA, Lose FA, Parsons MT (2014) Tumor mismatch repair immunohistochemistry and DNA MLH1 methylation testing of patients with endometrial cancer diagnosed at age younger than 60 years optimizes triage for population-level germline mismatch repair gene mutation testing. J Clin Oncol 32(2):90CrossRefGoogle Scholar
  8. 8.
    Dowty JG, Win AK, Buchanan DD, Lindor NM, Macrae FA, Clendenning M, Antill YC, Thibodeau SN, Casey G, Gallinger S (2013) Cancer risks for MLH 1 and MSH 2 mutation carriers. Hum Mutat 34(3):490–497CrossRefGoogle Scholar
  9. 9.
    Lagerstedt-Robinson K, Rohlin A, Aravidis C, Melin B, Nordling M, Stenmark-Askmalm M, Lindblom A, Nilbert M (2016) Mismatch repair gene mutation spectrum in the Swedish Lynch syndrome population. Oncol Rep 36(5):2823–2835CrossRefGoogle Scholar
  10. 10.
    Karahan B, Argon A, Yıldırım M, Vardar E (2015) Relationship between MLH-1, MSH-2, PMS-2, MSH-6 expression and clinicopathological features in colorectal cancer. Int J Clin Exp Pathol 8(4):4044–4053PubMedPubMedCentralGoogle Scholar
  11. 11.
    Ali W, Shafique S, Rashid S (2018) Structural characterization of β-catenin and RX-5902 binding to phospho-p68 RNA helicase by molecular dynamics simulation. Prog Biophys Mol Biol 140:79–89CrossRefGoogle Scholar
  12. 12.
    DeSantis CE, Bray F, Ferlay J, Lortet-Tieulent J, Anderson BO, Jemal A (2015) International variation in female breast cancer incidence and mortality rates. Cancer Epidemiol Biomark Prev 24(10):1495–1506.  https://doi.org/10.1158/1055-9965.EPI-15-0535 CrossRefGoogle Scholar
  13. 13.
    McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM (2005) Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst 97(16):1180–1184CrossRefGoogle Scholar
  14. 14.
    Ye S, Dhillon S, Ke X, Collins AR, Day IN (2001) An efficient procedure for genotyping single nucleotide polymorphisms. Nucleic Acids Res 29(17):e88–e88CrossRefGoogle Scholar
  15. 15.
    Masood N, Malik FA, Kayani MA (2011) Expression of xenobiotic metabolizing genes in head and neck cancer tissues. Asian Pac J Cancer Prev 12(2):377–382PubMedGoogle Scholar
  16. 16.
    Masood N, Kayani MA (2013) Expression patterns of carcinogen detoxifying genes (CYP1A1, GSTP1 & GSTT1) in HNC patients. Pathol Oncol Res 19(1):89–94CrossRefGoogle Scholar
  17. 17.
    Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242CrossRefGoogle Scholar
  18. 18.
    Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25(13):1605–1612CrossRefGoogle Scholar
  19. 19.
    Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ (2015) The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc 10(6):845CrossRefGoogle Scholar
  20. 20.
    Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER Suite: protein structure and function prediction. Nat Methods 12(1):7CrossRefGoogle Scholar
  21. 21.
    Chen VB, Arendall WB, Headd JJ, Keedy DA, Immormino RM, Kapral GJ, Murray LW, Richardson JS, Richardson DC (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D 66(1):12–21CrossRefGoogle Scholar
  22. 22.
    Wang W, Xia M, Chen J, Deng F, Yuan R, Zhang X, Shen F (2016) Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODs in Gossypium raimondii and G. arboreum. Data Brief 9:345–348CrossRefGoogle Scholar
  23. 23.
    Colovos C, Yeates T (1993) ERRAT: an empirical atom-based method for validating protein structures. Protein Sci 2:1511–1519CrossRefGoogle Scholar
  24. 24.
    Eisenberg D, Lüthy R, Bowie JU (1997) [20] VERIFY3D: assessment of protein models with three-dimensional profiles. Methods in enzymology, vol 277. Elsevier, Amsterdam, pp 396–404Google Scholar
  25. 25.
    Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35(suppl_2):W407–W410CrossRefGoogle Scholar
  26. 26.
    Emsley P, Lohkamp B, Scott WG, Cowtan K (2010) Features and development of Coot. Acta Crystallogr D 66(4):486–501CrossRefGoogle Scholar
  27. 27.
    Fu T, Liu Y, Li K, Wan W, Pappou EP, Iacobuzio-Donahue CA, Kerner Z, Baylin SB, Wolfgang CL, Ahuja N (2016) Tumors with unmethylated MLH1 and the CpG island methylator phenotype are associated with a poor prognosis in stage II colorectal cancer patients. Oncotarget 7(52):86480CrossRefGoogle Scholar
  28. 28.
    Haber G, Ahmed NU, Pekovic V (2012) Family history of cancer and its association with breast cancer risk perception and repeat mammography. Am J Public Health 102(12):2322–2329.  https://doi.org/10.2105/AJPH.2012.300786 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Chollet-Hinton L, Anders CK, Tse C-K, Bell MB, Yang YC, Carey LA, Olshan AF, Troester MA (2016) Breast cancer biologic and etiologic heterogeneity by young age and menopausal status in the Carolina Breast Cancer Study: a case-control study. Breast Cancer Res 18(1):79.  https://doi.org/10.1186/s13058-016-0736-y CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Bener A, Çatan F, El Ayoubi HR, Acar A, Ibrahim WH (2017) Assessing breast cancer risk estimates based on the Gail model and its predictors in Qatari women. J Prim Care Community Health 8(3):180–187CrossRefGoogle Scholar
  31. 31.
    Baudhuin LM, Ferber MJ, Winters JL, Steenblock KJ, Swanson RL, French AJ, Butz ML, Thibodeau SN (2005) Characterization of hMLH1 and hMSH2 gene dosage alterations in Lynch syndrome patients. Gastroenterology 129(3):846–854CrossRefGoogle Scholar
  32. 32.
    Poulogiannis G, Frayling IM, Arends MJ (2010) DNA mismatch repair deficiency in sporadic colorectal cancer and Lynch syndrome. Histopathology 56(2):167–179CrossRefGoogle Scholar
  33. 33.
    Wang T, Stadler ZK, Zhang L, Weiser MR, Basturk O, Hechtman JF, Vakiani E, Saltz LB, Klimstra DS, Shia J (2018) Immunohistochemical null-phenotype for mismatch repair proteins in colonic carcinoma associated with concurrent MLH1 hypermethylation and MSH2 somatic mutations. Fam Cancer 17(2):225–228CrossRefGoogle Scholar
  34. 34.
    Kanumuri P, Hayse B, Killelea BK, Chagpar AB, Horowitz NR, Lannin DR (2015) Characteristics of multifocal and multicentric breast cancers. Ann Surg Oncol 22(8):2475–2482CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Fatima Jinnah Women UniversityRawalpindiPakistan
  2. 2.National Centre for Bioinformatics, Quaid-i-Azam UniversityIslamabadPakistan
  3. 3.Department of Epidemiology and Biostatistics, School of Health SciencesWuhan UniversityWuhanChina
  4. 4.Department of Cellular and Molecular Medicine, School of Life SciencesBristol UniversityBristolUK
  5. 5.Armed Forces Institute of PathologyRawalpindiPakistan

Personalised recommendations