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2021 | OriginalPaper | Chapter

Construction of a New Model to Investigate Breast Cancer Data

Authors : Umut Ağyüz, Vilda Purutçuoğlu, Eda Purutçuoğlu, Yüksel Ürün

Published in: Modeling, Dynamics, Optimization and Bioeconomics IV

Publisher: Springer International Publishing

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Abstract

Modelling is a way to describe the elements of the network/system, their states and their interactions with other elements in order to understand the current state of knowledge of a system. Thereby, the mathematical models may predict the experiments which are difficult or impossible to do in the lab and can be used to discover indirect relationships between model’s components. Hereby, the aim of this study is to develop a network structure for the breast cancer from the analyses of different datasets which include the data of the luminal type at the stage 1–3 breast cancer diagnosed in total 377 patients and related to the PI3KCD signalling pathway. Accordingly, in the analyses, the relations of the 65 oncogenes are revealed by a true network in a binary format. Then, we construct the quasi breast cancer networks by using different parametric and non-parametric models, namely, Gaussian graphical model, copula Gaussian graphical model and multivariate adaptive regression splines with/without interaction terms. In the computations, we evaluate the performance of all suggested mathematical models via F-measure and accuracy measure criteria. We consider that the outcomes can be useful for the selection of the best fitted model in the construction of the breast cancer gene-gene interaction networks.

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Literature
1.
go back to reference Ağraz, M., Purutçuoğlu, V.: Extended lasso-type MARS (\(\text{ LMARS }\)) model in the description of biological network. J. Stat. Comput. Simul. 89(1), 1–14 (2019)MathSciNetCrossRef Ağraz, M., Purutçuoğlu, V.: Extended lasso-type MARS (\(\text{ LMARS }\)) model in the description of biological network. J. Stat. Comput. Simul. 89(1), 1–14 (2019)MathSciNetCrossRef
2.
go back to reference Ayyildiz, E., Ağraz, M., Purutçuoğlu, V.: MARS as an alternative approach of Gaussian graphical model for biochemical networks. J. Appl. Stat. 44c(16), 2858–2876 (2017) Ayyildiz, E., Ağraz, M., Purutçuoğlu, V.: MARS as an alternative approach of Gaussian graphical model for biochemical networks. J. Appl. Stat. 44c(16), 2858–2876 (2017)
3.
go back to reference Ayyıldız, E., Purutçuoğlu, V.: Generating various types of graphical models via MARS. In: Arslan, O. (ed.) Chapter in: Information Complexity and Statistical Modeling in High Dimensions with Applications. Springer (In print) (2019) Ayyıldız, E., Purutçuoğlu, V.: Generating various types of graphical models via MARS. In: Arslan, O. (ed.) Chapter in: Information Complexity and Statistical Modeling in High Dimensions with Applications. Springer (In print) (2019)
4.
go back to reference Bahçivancı, B., Purutçuooğlu, V., Purutçuoğlu, E., Ürün, Y.: Estimation of gynecological cancer networks via target proteins. J. Multidiscip. Eng. Sci. 5(12), 9296–9302 (2018) Bahçivancı, B., Purutçuooğlu, V., Purutçuoğlu, E., Ürün, Y.: Estimation of gynecological cancer networks via target proteins. J. Multidiscip. Eng. Sci. 5(12), 9296–9302 (2018)
5.
go back to reference Barabási, A.L., Oltvai, Z.N.: Network biology: understanding the cells functional organization. Nat. Rev. Genet. 5, 101–113 (2004)CrossRef Barabási, A.L., Oltvai, Z.N.: Network biology: understanding the cells functional organization. Nat. Rev. Genet. 5, 101–113 (2004)CrossRef
6.
go back to reference Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., et al.: Minimum information about a microarray experiment (\(\text{ MIAME }\))-toward standards for microarray data. Nat. Genet. 29(4), 365–371 (2001)CrossRef Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., et al.: Minimum information about a microarray experiment (\(\text{ MIAME }\))-toward standards for microarray data. Nat. Genet. 29(4), 365–371 (2001)CrossRef
7.
go back to reference Bower, J.M., Bolouri, H.: Computational Modeling of Genetic and Biochemical Networks. MIT Press, Cambridge (2001) Bower, J.M., Bolouri, H.: Computational Modeling of Genetic and Biochemical Networks. MIT Press, Cambridge (2001)
8.
go back to reference Cancer Genome Atlas: Comprehensive molecular portraits of human breast tumours. Nature 490(7418), 61–70 (2012)CrossRef Cancer Genome Atlas: Comprehensive molecular portraits of human breast tumours. Nature 490(7418), 61–70 (2012)CrossRef
9.
go back to reference Dobra, A., Lenkoski, A.: Copula Gaussian graphical models and their application to modeling functional disability data. Ann. Appl. Stat. 5(2A), 969–993 (2010)MathSciNetMATH Dobra, A., Lenkoski, A.: Copula Gaussian graphical models and their application to modeling functional disability data. Ann. Appl. Stat. 5(2A), 969–993 (2010)MathSciNetMATH
10.
go back to reference Dokuzoğlu, D., Purutçuoğlu, V.: Comprehensive analyses of Gaussian graphical model under different biological networks. Acta Phys. Pol. Ser. A 132, 1106–1111 (2017)CrossRef Dokuzoğlu, D., Purutçuoğlu, V.: Comprehensive analyses of Gaussian graphical model under different biological networks. Acta Phys. Pol. Ser. A 132, 1106–1111 (2017)CrossRef
11.
go back to reference Edwards, D.: Introduction to Graphical Modelling, 2nd edn. Springer Texts in Statistics (2000) Edwards, D.: Introduction to Graphical Modelling, 2nd edn. Springer Texts in Statistics (2000)
12.
go back to reference Farnoudkia, H., Purutçuoğlu, V.: Copula Gaussian Graphical Modelling of Biological Networks and Bayesian Inference of Model Parameters. Scientia Iranica (in press) (2019) Farnoudkia, H., Purutçuoğlu, V.: Copula Gaussian Graphical Modelling of Biological Networks and Bayesian Inference of Model Parameters. Scientia Iranica (in press) (2019)
14.
15.
go back to reference Friedman, J., Hastie, T., Tibshirani, R.: Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9, 432–441 (2008)CrossRef Friedman, J., Hastie, T., Tibshirani, R.: Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9, 432–441 (2008)CrossRef
16.
go back to reference Hastie, T., Tibshirani, R., Friedman, J.H.: The Element of Statistical Learning. Springer, New York (2001)CrossRef Hastie, T., Tibshirani, R., Friedman, J.H.: The Element of Statistical Learning. Springer, New York (2001)CrossRef
17.
go back to reference Hatzis, C., Sun, H., Yao, H., Hubbard, R.E., Meric-Bernstam, F., Babiera, G.V., Wu, Y., Pusztai, L., Symmans, W.F.: Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers. J. Natl. Cancer Inst. 103(24), 1871–1883 (2011)CrossRef Hatzis, C., Sun, H., Yao, H., Hubbard, R.E., Meric-Bernstam, F., Babiera, G.V., Wu, Y., Pusztai, L., Symmans, W.F.: Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers. J. Natl. Cancer Inst. 103(24), 1871–1883 (2011)CrossRef
18.
go back to reference Irizarry, R.A., Hobbs, B., Collin, F., Beazer-Barclay, Y.D., Antonellis, K.J., Scherf, U., et al.: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003)CrossRef Irizarry, R.A., Hobbs, B., Collin, F., Beazer-Barclay, Y.D., Antonellis, K.J., Scherf, U., et al.: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003)CrossRef
19.
go back to reference Imkampe, A., Bendall, S., Bates, T.: The significance of the site of recurrence to subsequent breast cancer survival. Eur. J. Surg. Oncol. 33, 420–423 (2007)CrossRef Imkampe, A., Bendall, S., Bates, T.: The significance of the site of recurrence to subsequent breast cancer survival. Eur. J. Surg. Oncol. 33, 420–423 (2007)CrossRef
20.
go back to reference Kimbung, S., Kovács, A., Bendahl, P.O., Malmström, P., Fernö, M., Hatschek, T., Hedenfalk, I.: Claudin2 is an independent negative prognostic factor in breast cancer and specifically predicts early liver recurrences. Mol. Oncol. 8(1), 119–128 (2014) Kimbung, S., Kovács, A., Bendahl, P.O., Malmström, P., Fernö, M., Hatschek, T., Hedenfalk, I.: Claudin2 is an independent negative prognostic factor in breast cancer and specifically predicts early liver recurrences. Mol. Oncol. 8(1), 119–128 (2014)
22.
go back to reference Kreike, B., Halfwerk, H., Kristel, P., Glas, A., Peterse, H., Bartelink, H., Van de Vijver, M.J.: Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy. Clin. Cancer Res. 12(19), 5705–5712 (2006)CrossRef Kreike, B., Halfwerk, H., Kristel, P., Glas, A., Peterse, H., Bartelink, H., Van de Vijver, M.J.: Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy. Clin. Cancer Res. 12(19), 5705–5712 (2006)CrossRef
23.
go back to reference LaBreche, H.G., Nevins, J.R., Huang, E.: Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors. BMC Med. Genomics. 4(61) (2011) LaBreche, H.G., Nevins, J.R., Huang, E.: Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors. BMC Med. Genomics. 4(61) (2011)
24.
go back to reference Largillier, R., Ferrero, J.M., Doyen, J., Barriere, J., Namer, M., Mari, V., Courdi, A., Hannoun-Levi, J.M., Ettore, F., Birtwisle-Peyrottes, I., Balu-Maestro, C., Marcy, P.Y., Raoust, I., Lallement, M., Chamorey, E.: Prognostic factors in 1,038 women with metastatic breast cancer. Ann. Oncol. 19, 2012–2019 (2008)CrossRef Largillier, R., Ferrero, J.M., Doyen, J., Barriere, J., Namer, M., Mari, V., Courdi, A., Hannoun-Levi, J.M., Ettore, F., Birtwisle-Peyrottes, I., Balu-Maestro, C., Marcy, P.Y., Raoust, I., Lallement, M., Chamorey, E.: Prognostic factors in 1,038 women with metastatic breast cancer. Ann. Oncol. 19, 2012–2019 (2008)CrossRef
25.
go back to reference Mohammadi, A., Wit, E.C.: \(\text{ BDgraph }\): Bayesian structure learning of graphs in \(\text{ R }\). Bayesian Anal. 10, 109–138 (2015)MathSciNetCrossRef Mohammadi, A., Wit, E.C.: \(\text{ BDgraph }\): Bayesian structure learning of graphs in \(\text{ R }\). Bayesian Anal. 10, 109–138 (2015)MathSciNetCrossRef
26.
go back to reference Meinshausen, N., Bühlmann, P.: High dimensional graphs and variable selection with the lasso. Ann. Stat. 34, 1436–1462 (2006)MathSciNetMATH Meinshausen, N., Bühlmann, P.: High dimensional graphs and variable selection with the lasso. Ann. Stat. 34, 1436–1462 (2006)MathSciNetMATH
27.
go back to reference Purutçuoğlu, V., Farnoudkia, H.: Gibbs sampling in inference of copula Gaussian graphical model adapted to biological networks. Acta Phys. Pol. Ser A 132, 1112–1117 (2017)CrossRef Purutçuoğlu, V., Farnoudkia, H.: Gibbs sampling in inference of copula Gaussian graphical model adapted to biological networks. Acta Phys. Pol. Ser A 132, 1112–1117 (2017)CrossRef
28.
go back to reference Trivedi, P.K., Zimmer, D.M.: Copula modeling: an introduction for practitioners. Found. Trends R Econom. 1, 1–111 (2005)MATH Trivedi, P.K., Zimmer, D.M.: Copula modeling: an introduction for practitioners. Found. Trends R Econom. 1, 1–111 (2005)MATH
29.
go back to reference Turashvili, G., Bouchal, J., Baumforth, K., Wei, W, Dziechciarkova, M., Ehrmann, J., Klein, J., Fridman, E., Skarda, J., Srovnal, J. et al.: Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis. BMC Cancer. 7, 55–75 (2007) Turashvili, G., Bouchal, J., Baumforth, K., Wei, W, Dziechciarkova, M., Ehrmann, J., Klein, J., Fridman, E., Skarda, J., Srovnal, J. et al.: Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis. BMC Cancer. 7, 55–75 (2007)
30.
go back to reference Vanhaesebroeck, B., Leevers, S.J., Ahmadi, K., Timms, J., Katso, R., et al.: Synthesis and function of 3-phosphorylated inositol lipids. Ann. Rev. Biochem. 70, 535–602 (2001)CrossRef Vanhaesebroeck, B., Leevers, S.J., Ahmadi, K., Timms, J., Katso, R., et al.: Synthesis and function of 3-phosphorylated inositol lipids. Ann. Rev. Biochem. 70, 535–602 (2001)CrossRef
31.
go back to reference Wilkinson, D.J.: Stochastic Modelling for Systems Biology. Taylor and Francis, Boca Raton, FL (2006)CrossRef Wilkinson, D.J.: Stochastic Modelling for Systems Biology. Taylor and Francis, Boca Raton, FL (2006)CrossRef
32.
go back to reference Whittaker, J.: Graphical Models in Applied Multivariate Statistics. Wiley, New York (1990)MATH Whittaker, J.: Graphical Models in Applied Multivariate Statistics. Wiley, New York (1990)MATH
33.
go back to reference Wolpert, R.L., Schmidler, S.C.: \(\alpha \)-Stable limit laws for harmonic mean estimators of marginal likelihoods. Stat. Sinica 22, 1233–1251 (2012)MathSciNetCrossRef Wolpert, R.L., Schmidler, S.C.: \(\alpha \)-Stable limit laws for harmonic mean estimators of marginal likelihoods. Stat. Sinica 22, 1233–1251 (2012)MathSciNetCrossRef
Metadata
Title
Construction of a New Model to Investigate Breast Cancer Data
Authors
Umut Ağyüz
Vilda Purutçuoğlu
Eda Purutçuoğlu
Yüksel Ürün
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-78163-7_2

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