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Cancer Cell International

, 16:2

First Online: 09 February 2016Received: 11 June 2015Accepted: 03 February 2016


BackgroundMutation rates are consistently varied in cancer genome and play an important role in tumorigenesis, however, little has been known about their function potential and impact on the distribution of functional mutations. In this study, we investigated genomic features which affect mutation pattern and the function importance of mutation pattern in cancer.

MethodsSomatic mutations of clear-cell renal cell carcinoma, liver cancer, lung cancer and melanoma and single nucleotide polymorphisms SNPs were intersected with 54 distinct genomic features. Somatic mutation and SNP densities were then computed for each feature type. We constructed 2856 1-Mb windows, in which each row 1-Mb window contains somatic mutation, SNP densities and 54 feature vectors. Correlation analyses were conducted between somatic mutation, SNP densities and each feature vector. We also built two random forest models, namely somatic mutation model CSM and SNP model to predict somatic mutation and SNP densities on a 1-Kb scale. The relation of CSM and SNP scores was further analyzed with the distributions of deleterious coding variants predicted by SIFT and Mutation Assessor, non-coding functional variants evaluated with FunSeq 2 and GWAVA and disease-causing variants from HGMD and ClinVar databases.

ResultsWe observed a wide range of genomic features which affect local mutation rates, such as replication time, transcription levels, histone marks and regulatory elements. Repressive histone marks, replication time and promoter contributed most to the CSM models, while, recombination rate and chromatin organizations were most important for the SNP model. We showed low mutated regions preferentially have higher densities of deleterious coding mutations, higher average scores of non-coding variants, higher fraction of functional regions and higher enrichment of disease-causing variants as compared to high mutated regions.

ConclusionsSomatic mutation densities vary largely across cancer genome, mutation frequency is a major indication of function and influence on the distribution of functional mutations in cancer.

KeywordsClear-cell renal cell carcinoma Liver cancer Lung cancer Melanoma Mutation pattern Random forest Functional variants Chuance Du and Xiaoyuan Wu contributed equally to this work

Electronic supplementary materialThe online version of this article doi:10.1186-s12935-016-0278-5 contains supplementary material, which is available to authorized users.

The authors are retracting this article 1 because they do not have ownership of the data they report. A formal investigation by the Institut de Biologie Intégrative de la Cellule I2BC, Gif-Sur-Yvette, France, has found that the methods and analyses presented in Figures 1, 3 and 5 and all computer analyses were performed at the Institut de Biologie Intégrative de la Cellule I2BC and the data have been previously reported in 2. All authors agree with this retraction.

1. Du C, Wu X, Li J. Mutation pattern is an influential factor on functional mutation rates in cancer. Cancer Cell Int 2016 16:2

2. Li J, Poursat M-A, Drubay D, Motz A, Saci Z, Morillon A, Michiels S, Gautheret D. A dual model for prioritizing cancer mutations in the non-coding genome based on germline and somatic events. PLoS Comput. Biol. 2015 1111: e1004583

An erratum to this article is available at

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Autor: Chuance Du - Xiaoyuan Wu - Jia Li


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