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. 2019 Nov 8;20(1):555.
doi: 10.1186/s12859-019-3148-z.

An EM algorithm to improve the estimation of the probability of clonal relatedness of pairs of tumors in cancer patients

Audrey Mauguen  1 , Venkatraman E Seshan  2 , Irina Ostrovnaya  2 , Colin B Begg  2
Affiliations

An EM algorithm to improve the estimation of the probability of clonal relatedness of pairs of tumors in cancer patients

Audrey Mauguen et al. BMC Bioinformatics. .

Abstract

Background: We previously introduced a random-effects model to analyze a set of patients, each of which has two distinct tumors. The goal is to estimate the proportion of patients for which one of the tumors is a metastasis of the other, i.e. where the tumors are clonally related. Matches of mutations within a tumor pair provide the evidence for clonal relatedness. In this article, using simulations, we compare two estimation approaches that we considered for our model: use of a constrained quasi-Newton algorithm to maximize the likelihood conditional on the random effect, and an Expectation-Maximization algorithm where we further condition the random-effect distribution on the data.

Results: In some specific settings, especially with sparse information, the estimation of the parameter of interest is at the boundary a non-negligible number of times using the first approach, while the EM algorithm gives more satisfactory estimates. This is of considerable importance for our application, since an estimate of either 0 or 1 for the proportion of cases that are clonal leads to individual probabilities being 0 or 1 in settings where the evidence is clearly not sufficient for such definitive probability estimates.

Conclusions: The EM algorithm is a preferable approach for our clonality random-effect model. It is now the method implemented in our R package Clonality, making available an easy and fast way to estimate this model on a range of applications.

Keywords: Cancer; Clonality; EM algorithm; Parameter estimation; Random effect model; Tumor mutation.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Log-normal distributions of the clonality signal
See this image and copyright information in PMC

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References

    1. Teixeira MR, Ribeiro FR, Torres L, Pandis N, Andersen JA, Lothe RA, Heim S. Assessment of clonal relationships in ipsilateral and bilateral multiple breast carcinomas by comparative genomic hybridisation and hierarchical clustering analysis. Br J Cancer. 2004;91(4):775–82. doi: 10.1038/sj.bjc.6602021. - DOI - PMC - PubMed
    1. Schultheis Anne M., Ng Charlotte K. Y., De Filippo Maria R., Piscuoglio Salvatore, Macedo Gabriel S., Gatius Sonia, Perez Mies Belen, Soslow Robert A., Lim Raymond S., Viale Agnes, Huberman Kety H., Palacios Jose C., Reis-Filho Jorge S., Matias-Guiu Xavier, Weigelt Britta. Massively Parallel Sequencing-Based Clonality Analysis of Synchronous Endometrioid Endometrial and Ovarian Carcinomas. Journal of the National Cancer Institute. 2015;108(6):djv427. doi: 10.1093/jnci/djv427. - DOI - PMC - PubMed
    1. Perea J, García JL, Corchete L, Lumbreras E, Arriba M, Rueda D, Tapial S, Pérez J, Vieiro V, Rodríguez Y, Brandáriz L, García-Arranz M, García-Olmo D, Goel A, Urioste M, Sarmiento RG. Redefining synchronous colorectal cancers based on tumor clonality. Int J Cancer. 2019;144(7):1596–608. doi: 10.1002/ijc.31761. - DOI - PMC - PubMed
    1. Cereda M, Gambardella G, Benedetti L, Iannelli F, Patel D, Basso G, Guerra RF, Mourikis TP, Puccio I, Sinha S, Laghi L, Spencer J, Rodriguez-Justo M, Ciccarelli FD. Patients with genetically heterogeneous synchronous colorectal cancer carry rare damaging germline mutations in immune-related genes. Nat Commun. 2016;7:12072. doi: 10.1038/ncomms12072. - DOI - PMC - PubMed
    1. Bao L, Messer K, Schwab R, Harismendy O, Pu M, Crain B, Yost S, Frazer KA, Rana B, Hasteh F, Wallace A, Parker BA. Mutational Profiling Can Establish Clonal or Independent Origin in Synchronous Bilateral Breast and Other Tumors. PLoS ONE. 2015;10(11):e0142487. doi: 10.1371/journal.pone.0142487. - DOI - PMC - PubMed

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