School of Mathematics and Statistics - Research Publications

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Author: Li, Jason × Author: Speed, Terence × End date: 2015 × Start date: 2010 ×

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    Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data
    Loennstedt, IM ; Caramia, F ; Li, J ; Fumagalli, D ; Salgado, R ; Rowan, A ; Salm, M ; Kanu, N ; Savas, P ; Horswell, S ; Gade, S ; Loibl, S ; Neven, P ; Sotiriou, C ; Swanton, C ; Loi, S ; Speed, TP (BMC, 2014)
    Intra-tumor heterogeneity concerns the existence of genetically different subclones within the same tumor. Single sample quantification of heterogeneity relies on precise determination of chromosomal copy numbers throughout the genome, and an assessment of whether identified mutation variant allele fractions match clonal or subclonal copy numbers. We discuss these issues using data from SNP arrays, whole exome sequencing and pathologist purity estimates on several breast cancers characterized by ERBB2 amplification. We show that chromosomal copy numbers can only be estimated from SNP array signals or sequencing depths for subclonal tumor samples with simple subclonal architectures under certain assumptions.
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    Assessment of DNA methylation profiling and copy number variation as indications of clonal relationship in ipsilateral and contralateral breast cancers to distinguish recurrent breast cancer from a second primary tumour
    Huang, KT ; Mikeska, T ; Li, J ; Takano, EA ; Millar, EKA ; Graham, PH ; Boyle, SE ; Campbell, IG ; Speed, TP ; Dobrovic, A ; Fox, SB (BMC, 2015-10-09)
    BACKGROUND: Patients with breast cancer have an increased risk of developing subsequent breast cancers. It is important to distinguish whether these tumours are de novo or recurrences of the primary tumour in order to guide the appropriate therapy. Our aim was to investigate the use of DNA methylation profiling and array comparative genomic hybridization (aCGH) to determine whether the second tumour is clonally related to the first tumour. METHODS: Methylation-sensitive high-resolution melting was used to screen promoter methylation in a panel of 13 genes reported as methylated in breast cancer (RASSF1A, TWIST1, APC, WIF1, MGMT, MAL, CDH13, RARβ, BRCA1, CDH1, CDKN2A, TP73, and GSTP1) in 29 tumour pairs (16 ipsilateral and 13 contralateral). Using the methylation profile of these genes, we employed a Bayesian and an empirical statistical approach to estimate clonal relationship. Copy number alterations were analysed using aCGH on the same set of tumour pairs. RESULTS: There is a higher probability of the second tumour being recurrent in ipsilateral tumours compared with contralateral tumours (38 % versus 8 %; p <0.05) based on the methylation profile. Using previously reported recurrence rates as Bayesian prior probabilities, we classified 69 % of ipsilateral and 15 % of contralateral tumours as recurrent. The inferred clonal relationship results of the tumour pairs were generally concordant between methylation profiling and aCGH. CONCLUSION: Our results show that DNA methylation profiling as well as aCGH have potential as diagnostic tools in improving the clinical decisions to differentiate recurrences from a second de novo tumour.