CopyDetective: Detection threshold-aware copy number variant calling in whole-exome sequencing data

Sequencing-based analysis of clonal evolution of 25 mantle cell lymphoma patients at diagnosis and after failure of standard immunochemotherapy

Our knowledge of genetic aberrations, that is, variants and copy number variations (CNVs), associated with mantle cell lymphoma (MCL) relapse remains limited. A cohort of 25 patients with MCL at diagnosis and the first relapse after the failure of standard immunochemotherapy was analyzed using whole-exome sequencing. The most frequent variants at diagnosis and at relapse comprised six genes: TP53, ATM, KMT2D, CCND1, SP140, and LRP1B. The most frequent CNVs at diagnosis and at relapse included TP53 and CDKN2A/B deletions, and PIK3CA amplifications. The mean count of mutations per patient significantly increased at relapse (n = 34) compared to diagnosis (n = 27). The most frequent newly detected variants at relapse, LRP1B gene mutations, correlated with a higher mutational burden. Variant allele frequencies of TP53 variants increased from 0.35 to 0.76 at relapse. The frequency and length of predicted CNVs significantly increased at relapse with CDKN2A/B deletions being the most frequent. Our data suggest, that the resistant MCL clones detected at relapse were already present at diagnosis and were selected by therapy. We observed enrichment of genetic aberrations of DNA damage response pathway (TP53 and CDKN2A/B), and a significant increase in MCL heterogeneity. We identified LRP1B inactivation as a new potential driver of MCL relapse.

Changes of Mutations and Copy-Number and Enhanced Cell Migration during Breast Tumorigenesis

Although cancer stem cells (CSCs) play a major role in tumorigenesis and metastasis, the role of genetic alterations in invasiveness of CSCs is still unclear. Tumor microenvironment signals, such as extracellular matrix (ECM) composition, significantly influence cell behaviors. Unfortunately, these signals are often lost in in vitro cell culture. This study determines putative CSC populations, examines genetic changes during tumorigenesis of human breast epithelial stem cells, and investigates single-cell migration properties on ECM-mimetic platforms. Whole exome sequencing data indicate that tumorigenic cells have a higher somatic mutation burden than non-tumorigenic cells, and that mutations exclusive to tumorigenic cells exhibit higher predictive deleterious scores. Tumorigenic cells exhibit distinct somatic copy number variations (CNVs) including gain of duplications in chromosomes 5 and 8. ECM-mimetic topography selectively enhances migration speed of tumorigenic cells, but not of non-tumorigenic cells, and results in a wide distribution of tumorigenic single-cell migration speeds, suggesting heterogeneity in cellular sensing of contact guidance cues. This study identifies mutations and CNVs acquired during breast tumorigenesis, which can be associated with enhanced migration of breast tumorigenic cells, and demonstrates that a nanotopographically-defined platform can be applied to recapitulate an ECM structure for investigating cellular migration in the simulated tumor microenvironment.

Exploring Current Challenges and Perspectives for Automatic Reconstruction of Clonal Evolution

BACKGROUND/AIM

In the field of cancer research, reconstructing clonal evolution is of major interest. The technique provides new insights for analysis and prediction of tumor development. However, reconstruction based on mutational data is characterized by several challenges.

MATERIALS AND METHODS

By performing extensive literature research, we identified 51 currently available tools for reconstructing clonal evolution. By analyzing two cancer data sets (n=21), we investigated the applicability and performance of each tool.

RESULTS

Seventeen out of 51 tools could be applied to our data. Correct clustering of variants can be observed for 4 patients in the presence of ≤3 clusters and ≥5 time points. Correct phylogenetic trees are determined for 10 patients. Accurate visualization is possible, by applying adjustments to the original algorithms.

CONCLUSION

Despite bearing considerable potential, automatic reconstruction of clonal evolution remains challenging. To replace tedious manual reconstruction, further research including systematic error analyses using simulation tools needs to be conducted.

CopyDetective: Detection threshold-aware copy number variant calling in whole-exome sequencing data

BACKGROUND

Copy number variants (CNVs) are known to play an important role in the development and progression of several diseases. However, detection of CNVs with whole-exome sequencing (WES) experiments is challenging. Usually, additional experiments have to be performed.

FINDINGS

We developed a novel algorithm for somatic CNV calling in matched WES data called "CopyDetective". Different from other approaches, CNV calling with CopyDetective consists of a 2-step procedure: first, quality analysis is performed, determining individual detection thresholds for every sample. Second, actual CNV calling on the basis of the previously determined thresholds is performed. Our algorithm evaluates the change in variant allele frequency of polymorphisms and reports the fraction of affected cells for every CNV. Analyzing 4 WES data sets (n = 100) we observed superior performance of CopyDetective compared with ExomeCNV, VarScan2, ControlFREEC, ExomeDepth, and CNV-seq.

CONCLUSIONS

Individual detection thresholds reveal that not every WES data set is equally apt for CNV calling. Initial quality analyses, determining individual detection thresholds-as realized by CopyDetective-can and should be performed prior to actual variant calling.