Skip to main content

Advertisement

SpringerLink
Log in

XPC as breast cancer susceptibility gene: evidence from genetic profiling, statistical inferences and protein structural analysis

  • Original Article
  • Published:
Breast Cancer Aims and scope Submit manuscript

Abstract

Background

Gene polymorphisms that affect nucleotide excision repair (NER) pathway may link with higher susceptibility of breast cancer (BC); however, the significance of these associations may vary conferring to the individual ethnicity. Xeroderma pigmentosum complementation gene (XPC) plays a substantial role in recognizing damaged DNA during NER process.

Objective and methods

To estimate the relationship among XPC polymorphisms and breast cancer (BC) risk, we carried out a case–control-association study with 493 BC cases and 387 controls using TETRA–ARMS-PCR. Distributional differences of clinical features, demographic factors and XPC polymorphisms among BC cases and controls were examined by conditional logistic regression model. Kaplan–Meier test was applied to predict survival distributions and protein structure was predicted using computational tools.

Results

Obesity, consanguinity, positive marital status and BC family history were associated (P ≤ 0.01) with higher BC risk. Genotyping revealed significant involvement (P ≤ 0.01) of two XPC polymorphisms rs2228001–A > C (OR = 3.8; CI 1.9–7.6) and rs2733532–C > T (OR = 2.6; CI 1.4–5.03) in BC development, asserting them potential risk factors for increased BC incidence. However, no association (P > 0.05) was detected for overall or progression free survival for both XPC polymorphisms possibly due to shorter follow-up time (45 months). As compared to normal XPC structure, pronounced conformational changes have been observed in the C-terminus of XPCQ939K, bearing rs2228001–A > C substitution. In XPCQ939K, two additional α-helices were observed at A292-E297 and Y252-R286, while L623-M630 and L649-L653 helices were converted into loop conformation.

Conclusion

In conclusion, both XPC polymorphisms confer significant association with increased BC risk. rs2228001 substitution may change the structural and functional preferences of XPC C-terminus, while rs2733532 may have regulatory role thereby leading to potential BC risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. He B-s, Xu T, Pan Y-q, Wang H-j, Cho WC, Lin K, Sun H-l, Gao T-y, Wang S-k. Nucleotide excision repair pathway gene polymorphisms are linked to breast cancer risk in a Chinese population. Oncotarget. 2016;7(51):84872.

    Article  Google Scholar 

  2. Grand RJA, Reynolds JJ. DNA repair and replication: mechanisms and clinical significance. Boca Raton: CRC Press; 2018.

    Book  Google Scholar 

  3. Pongsavee M, Wisuwan K. ERCC5 rs751402 polymorphism is the risk factor for sporadic breast cancer in Thailand. Int J Mol Epidemiol Genet. 2018;9(4):27.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Winczura A, Reynolds JJ. The repair of DNA single-strand breaks and DNA adducts: mechanisms and links to human disease. DNA repair and replication: mechanisms and clinical significance, 2018.

  5. Lehmann J. Functional relevance of spontaneous alternative splice variants of xeroderma pigmentosum genes: Prognostic marker for skin cancer risk and disease outcome?, Georg-August-Universität Göttingen, 2017.

  6. Schäfer A. Clinical, functional, and genetic analysis of NER defective patients and characterization of five novel XPG mutations. Niedersächsische Staats-und Universitätsbibliothek Göttingen, 2012.

  7. Latimer JJ, Johnson JM, Kelly CM, Miles TD, Beaudry-Rodgers KA, Lalanne NA, Vogel VG, Kanbour-Shakir A, Kelley JL, Johnson RR. Nucleotide excision repair deficiency is intrinsic in sporadic stage I breast cancer. Proc Natl Acad Sci. 2010;107(50):21725–30.

    Article  CAS  Google Scholar 

  8. Cui J, Tan H, Jiang L, Yuan W, Guan Q. Association between XPC rs2228000 (C/T) polymorphism and the susceptibility of breast cancer: a Meta-analysis. J Int Oncol. 2016;43(10):752–7.

    Google Scholar 

  9. Özgöz A, Öztürk KH, Yükseltürk A, Şamlı H, Başkan Z, İçduygu FM, Bacaksız M. Genetic variations of DNA repair genes in breast cancer. Pathol Oncol Res. 2019;25(1):107–14.

    Article  Google Scholar 

  10. Malik SS, Mubarik S, Masood N, Khadim MT. An insight into clinical outcome of XPG polymorphisms in breast cancer. Mol Biol Rep. 2018;45(6):2369–75.

    Article  CAS  Google Scholar 

  11. Romanowicz H, Strapagiel D, Słomka M, Sobalska-Kwapis M, Kępka E, Siewierska-Górska A, Zadrożny M, Bieńkiewicz J, Smolarz B. New single nucleotide polymorphisms (SNPs) in homologous recombination repair genes detected by microarray analysis in Polish breast cancer patients. Clin Exp Med. 2017;17(4):541–6.

    Article  CAS  Google Scholar 

  12. Aizat AAA, Nurfatimah MSS, Aminudin MM, Ankathil R. XPC Lys939Gln polymorphism, smoking and risk of sporadic colorectal cancer among Malaysians. World J Gastroenterol. 2013;19(23):3623.

    Article  Google Scholar 

  13. DeSantis CE, Bray F, Ferlay J, Lortet-Tieulent J, Anderson BO, Jemal A. International variation in female breast cancer incidence and mortality rates. Cancer Epidemiol Biomarkers Prev. 2015;24(10):1495–506. https://doi.org/10.1158/1055-9965.EPI-15-0535.

    Article  PubMed  Google Scholar 

  14. McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 2005;97(16):1180–4.

    Article  CAS  Google Scholar 

  15. Ye S, Dhillon S, Ke X, Collins AR, Day IN. An efficient procedure for genotyping single nucleotide polymorphisms. Nucleic Acids Res. 2001;29(17):e88.

    Article  CAS  Google Scholar 

  16. Bhagwat M. Searching NCBI’s dbSNP database. Curr Protoc Bioinform. 2010;32(1):1–19.

    Article  Google Scholar 

  17. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc. 2015;10(6):845.

    Article  CAS  Google Scholar 

  18. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. The I-TASSER Suite: protein structure and function prediction. Nat Methods. 2015;12(1):7.

    Article  CAS  Google Scholar 

  19. Abraham M, van der Spoel D, Lindahl E, Hess B. The GROMACS development team GROMACS User Manual version 5.1. SoftwareX. 2016;1:19.

    Google Scholar 

  20. Wang W, Xia M, Chen J, Deng F, Yuan R, Zhang X, Shen F. Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODs in Gossypium raimondii and G. arboreum. Data Brief. 2016;9:345–8.

    Article  Google Scholar 

  21. Wallner B, Elofsson A. Can correct protein models be identified? Protein Sci. 2003;12(5):1073–86.

    Article  CAS  Google Scholar 

  22. Emsley P, Lohkamp B, Scott WG, Cowtan K. Features and development of Coot. Acta Crystallogr D Biol Crystallogr. 2010;66(4):486–501.

    Article  CAS  Google Scholar 

  23. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605–12.

    Article  CAS  Google Scholar 

  24. Zhang ET, He Y, Grob P, Fong YW, Nogales E, Tjian R. Architecture of the human XPC DNA repair and stem cell coactivator complex. Proc Natl Acad Sci. 2015;112(48):14817–22.

    Article  CAS  Google Scholar 

  25. Siegel RL, Miller KD. Jemal A (2018) Cancer statistics. CA Cancer J Clin. 2018;68(1):7–30. https://doi.org/10.3322/caac.21442.

    Article  Google Scholar 

  26. Rojas K, Stuckey A. Breast cancer epidemiology and risk factors. Clin Obstet Gynecol. 2016;59(4):651–72.

    Article  Google Scholar 

  27. Mubarik S, Malik SS, Wang Z, Li C, Fawad M, Yu C. Recent insights into breast cancer incidence trends among four Asian countries using age-period-cohort model. Cancer Manag Res. 2019;11:8145.

    Article  Google Scholar 

  28. Anders CK, Johnson R, Litton J, Phillips M, Bleyer A. Breast cancer before age 40 years. Semin Oncol. 2009;36(3):237–49. https://doi.org/10.1053/j.seminoncol.2009.03.001.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Butt Z, Haider SF, Arif S, Khan MR, Ashfaq U, Shahbaz U, Bukhari MH. Breast cancer risk factors: a comparison between pre-menopausal and post-menopausal women. J Pak Med Assoc. 2012;62(2):120.

    PubMed  Google Scholar 

  30. Surakasula A, Nagarjunapu GC, Raghavaiah KV. A comparative study of pre- and post-menopausal breast cancer: risk factors, presentation, characteristics and management. J Res Pharm Pract. 2014;3(1):12–8. https://doi.org/10.4103/2279-042X.132704.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Aldabal BK, Koura MR. Risk factors of breast cancer among the primary health-care attendees in Eastern Saudi Arabia. Int J Med Sci Public Health. 2016;5(2):276–81.

    Article  Google Scholar 

  32. Zahmatkesh BH, Keramat A, Alavi N, Khosravi A, Chaman R. Role of menopause and early menarche in breast cancer: a meta-analysis of Iranian studies. Nurs Midwifery Stud. 2017;6(1):e37712.

    Google Scholar 

  33. Pervaiz R, Tosun Ö, Besim H, Serakinci N. Risk factor assessment for breast cancer in North Cyprus: a comprehensive case–control study of Turkish Cypriot women. Turkish J Med Sci. 2018;48(2):293–304.

    CAS  Google Scholar 

  34. Malik SS, Baig M, Khan MB, Masood N (2019) Survival analysis of breast cancer patients with different treatments: a multi-centric clinicopathological study. JPMA.

  35. Hinyard L, Wirth LS, Clancy JM, Schwartz T. The effect of marital status on breast cancer-related outcomes in women under 65: a SEER database analysis. Breast. 2017;32:13–7.

    Article  Google Scholar 

  36. Cadet J, Douki T. Formation of UV-induced DNA damage contributing to skin cancer development. Photochem Photobiol Sci. 2018;17(12):1816–41.

    Article  CAS  Google Scholar 

  37. Knijnenburg TA, Wang L, Zimmermann MT, Chambwe N, Gao GF, Cherniack AD, Fan H, Shen H, Way GP, Greene CS. Genomic and molecular landscape of DNA damage repair deficiency across The Cancer Genome Atlas. Cell Rep. 2018;23(1):239–54.

    Article  CAS  Google Scholar 

  38. Zheng W, Cong X-F, Cai W-H, Yang S, Mao C, Zou H-W. Current evidences on XPC polymorphisms and breast cancer susceptibility: a meta-analysis. Breast Cancer Res Treat. 2011;128(3):811–5.

    Article  Google Scholar 

  39. Hernandez-Villafuerte K, Fischer A, Latimer N. Challenges and methodologies in using progression free survival as a surrogate for overall survival in oncology. Int J Technol Assess Health Care. 2018;34(3):300–16.

    Article  Google Scholar 

  40. Yang S, Jin T, Su H-X, Zhu J-H, Wang D-W, Zhu S-J, Li S, He J, Chen Y-H. The association between NQO1 Pro187Ser polymorphism and bladder cancer susceptibility: a meta-analysis of 15 studies. PLoS ONE. 2015;10(1):e0116500.

    Article  Google Scholar 

  41. Long X-D, Huang H-D, Huang X-Y, Yao J-G, Xia Q. XPC codon 939 polymorphism is associated with susceptibility to DNA damage induced by aflatoxin B1 exposure. Int J Clin Exp Med. 2015;8(1):1197.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Gangwar R, Mandhani A, Mittal RD. XPC gene variants: a risk factor for recurrence of urothelial bladder carcinoma in patients on BCG immunotherapy. J Cancer Res Clin Oncol. 2010;136(5):779–86.

    Article  Google Scholar 

  43. Krzeszinski JY, Choe V, Shao J, Bao X, Cheng H, Luo S, Huo K, Rao H. XPC promotes MDM2-mediated degradation of the p53 tumor suppressor. Mol Biol Cell. 2014;25(2):213–21.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank all the patients, their family members and colleagues for their kind help and support.

Author information

Author notes

  1. Ayisha Zia, Sajid Rashid and Sumaira Mubarik contributed equally to this work.

Authors and Affiliations

  1. Fatima Jinnah Women University, The Mall Rawalpindi, Rawalpindi, Pakistan

    Saima Shakil Malik, Nosheen Masood & Azra Yasmin

  2. National Centre for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan

    Ayisha Zia & Sajid Rashid

  3. Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan, China

    Sumaira Mubarik

  4. Department of Zoology, University of Gujrat, Gujrat, Pakistan

    Saima Shakil Malik & Mubashar Hussain

  5. Breast Clinic, Combined Military Hospital, Rawalpindi, Pakistan

    Razia Bano

Authors
  1. Saima Shakil Malik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ayisha Zia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sajid Rashid
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sumaira Mubarik
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nosheen Masood
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mubashar Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Azra Yasmin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Razia Bano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Saima Shakil Malik.

Ethics declarations

Consent for publication

The experiments were undertaken with the understanding and written consent of each subject, and that the study conforms with The Code of Ethics of the World Medical Association (Declaration of Helsinki).

Conflict of interest

All authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malik, S.S., Zia, A., Rashid, S. et al. XPC as breast cancer susceptibility gene: evidence from genetic profiling, statistical inferences and protein structural analysis. Breast Cancer 27, 1168–1176 (2020). https://doi.org/10.1007/s12282-020-01121-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12282-020-01121-z

Keywords

Search

Navigation