Dataset Information

BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor.

ABSTRACT: Most published copy number datasets on solid tumors were obtained from specimens comprised of mixed cell populations, for which the varying tumor-stroma proportions are unknown or unreported. The inability to correct for signal mixing represents a major limitation on the use of these datasets for subsequent analyses, such as discerning deletion types or detecting driver aberrations. We describe the BACOM2.0 method with enhanced accuracy and functionality to normalize copy number signals, detect deletion types, estimate tumor purity, quantify true copy numbers, and calculate average-ploidy value. While BACOM has been validated and used with promising results, subsequent BACOM analysis of the TCGA ovarian cancer dataset found that the estimated average tumor purity was lower than expected. In this report, we first show that this lowered estimate of tumor purity is the combined result of imprecise signal normalization and parameter estimation. Then, we describe effective allele-specific absolute normalization and quantification methods that can enhance BACOM applications in many biological contexts while in the presence of various confounders. Finally, we discuss the advantages of BACOM in relation to alternative approaches. Here we detail this revised computational approach, BACOM2.0, and validate its performance in real and simulated datasets.

SUBMITTER: Fu Y

PROVIDER: S-EPMC4563570 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor.

Fu Yi Y Yu Guoqiang G Levine Douglas A DA Wang Niya N Shih Ie-Ming IeM Zhang Zhen Z Clarke Robert R Wang Yue Y

Scientific reports 20150909

Most published copy number datasets on solid tumors were obtained from specimens comprised of mixed cell populations, for which the varying tumor-stroma proportions are unknown or unreported. The inability to correct for signal mixing represents a major limitation on the use of these datasets for subsequent analyses, such as discerning deletion types or detecting driver aberrations. We describe the BACOM2.0 method with enhanced accuracy and functionality to normalize copy number signals, detect ...[more]

PMID: 26350498

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Project description:BackgroundQuantification of transcripts, proteins, or metabolites is straightforward when the factor used to normalize these values remains constant between samples. However, normalization factors often vary among samples and thus must be developed for each new analytical method.ResultsWe demonstrate quantification of transcript and protein levels in Arabidopsis based on genomic DNA copy number. We extracted total nucleic acid from 3-week-old rosette leaves of wild-type Arabidopsis and the pale-green/dwarf mutant, abc4, and quantified the number of transcripts by quantitative reverse-transcription PCR using genomic DNA copy number and ploidy (as determined by cytometry) for normalization. Our data indicated that normalization using genes commonly employed as references resulted in inaccuracies in transcript levels of the genes RBC-L and RBC-S (encoding the large and small subunits, respectively, of ribulose 1,5-bisphosphate carboxylase/oxygenase) in wild type and mutant. Normalization using genomic DNA copy number and ploidy, however, appropriately showed that the RBC-L and RBC-S transcript levels per cell in the mutant were significantly lower than that in wild type. Furthermore, quantification revealed that a cell of a 3-week-old wild-type Arabidopsis rosette leaf had an average of 7.5 × 103 transcripts of RBC-L, 9.9 × 103 transcripts of RBC-S, and 1.4 × 106 18S rRNA. We similarly analyzed the accumulation of RBC-L and LHCP (light-harvesting chlorophyll a/b protein) in wild type and mutant based on ploidy and genomic DNA copy number that was determined by direct quantitative PCR analysis of extracts using a DNA polymerase tolerant to a wide range of common PCR inhibitors. Furthermore, we estimated the number of RBC-L molecules (2.63 × 108) and chlorophyll molecules (1.85 × 109) in each cell in 3-week-old wild-type rosette leaves; these values had relatively low coefficients of variation, underscoring the reliability of our method.ConclusionGenomic DNA copy number and ploidy are useful as general normalization factors, providing an easy method for determining the number of transcripts, proteins, and metabolites in a cell.

Project description:Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. We conducted longitudinal whole-genome sequencing of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. Subclonal copy-number alterations were identified in all patients except one. In 5 patients, subclones from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clones in 6 of 7 patients with multiple clones. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy-number clones. A chromosomal duplication timing analysis revealed that complex genomic rearrangements typically occurred prior to diagnosis, supporting a macroevolutionary model of evolution, where a large number of genomic aberrations are acquired over a short period of time followed by clonal selection, as opposed to ongoing evolution. A mutational signature analysis of recurrent tumors revealed that homologous repair deficiency (HRD)-related SBS3 increases at each time point in patients with recurrent disease, suggesting that HRD continues to be an active mutagenic process after diagnosis. Overall, by examining the clonal relationships between temporally and spatially separated samples from patients with relapsed/refractory osteosarcoma, this study sheds light on the intratumor heterogeneity and potential drivers of treatment resistance in this disease.SignificanceThe chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.

Project description:Intratumour heterogeneity fuels carcinogenesis and allows circumventing specific targeted therapies. HER2 gene amplification is associated with poor outcome in invasive breast cancer. Heterogeneous HER2 amplification has been described in 5-41% of breast cancers. Here, we investigated the genetic differences between HER2-positive and HER2-negative admixed breast cancer components. We performed an in-depth analysis to explore the potential heterogeneity in the somatic mutational landscape of each individual tumour component. Formalin-fixed, paraffin-embedded breast cancer tissue of ten patients with at least one HER2-negative and at least one HER2-positive component was microdissected. Targeted next-generation sequencing was performed using a customized 53-gene panel. Somatic mutations and copy number variations were analysed. Overall, the tumours showed a heterogeneous distribution of 12 deletions, 9 insertions, 32 missense variants and 7 nonsense variants in 26 different genes, which are (likely) pathogenic. Three splice site alterations were identified. One patient had an EGFR copy number gain restricted to a HER2-negative in situ component, resulting in EGFR protein overexpression. Two patients had FGFR1 copy number gains in at least one tumour component. Two patients had an 8q24 gain in at least one tumour component, resulting in a copy number increase in MYC and PVT1. One patient had a CCND1 copy number gain restricted to a HER2-negative tumour component. No common alternative drivers were identified in the HER2-negative tumour components. This series of 10 breast cancers with heterogeneous HER2 gene amplification illustrates that HER2 positivity is not an unconditional prerequisite for the maintenance of tumour growth. Many other molecular aberrations are likely to act as alternative or collaborative drivers. This study demonstrates that breast carcinogenesis is a dynamically evolving process characterized by a versatile somatic mutational profile, of which some genetic aberrations will be crucial for cancer progression, and others will be mere 'passenger' molecular anomalies.

Dataset Information

BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor.

Publications

BACOM2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor.

Similar Datasets

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