Dataset Information

Aneuvis: web-based exploration of numerical chromosomal variation in single cells.

ABSTRACT:

Background

Numerical chromosomal variation is a hallmark of populations of malignant cells. Identifying the factors that promote numerical chromosomal variation is important for understanding mechanisms of carcinogenesis. However, the ability to quantify and visualize differences in chromosome number between experimentally-defined groups (e.g. control vs treated) obtained from single-cell experiments is currently limited by the lack of user-friendly software.

Results

Aneuvis is a web application that allows users to determine whether numerical chromosomal variation exists between experimental treatment groups. The web interface allows users to upload molecular cytogenetic or processed single cell whole-genome sequencing data in a cell-by-chromosome matrix format and automatically generates visualizations and summary statistics that reflect the degree of numeric chromosomal variability.

Conclusions

Aneuvis is the first user-friendly web application to help researchers identify the genetic and environmental perturbations that promote numerical chromosomal variation. Aneuvis is freely available as a web application at https://dpique.shinyapps.io/aneuvis/ and the source code for the application is available at https://github.com/dpique/aneuvis .

SUBMITTER: Pique DG

PROVIDER: S-EPMC6580570 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Aneuvis: web-based exploration of numerical chromosomal variation in single cells.

Piqué Daniel G DG Andriani Grasiella A GA Maggi Elaine E Zimmerman Samuel E SE Greally John M JM Montagna Cristina C Mar Jessica C JC

BMC bioinformatics 20190617 1

<h4>Background</h4>Numerical chromosomal variation is a hallmark of populations of malignant cells. Identifying the factors that promote numerical chromosomal variation is important for understanding mechanisms of carcinogenesis. However, the ability to quantify and visualize differences in chromosome number between experimentally-defined groups (e.g. control vs treated) obtained from single-cell experiments is currently limited by the lack of user-friendly software.<h4>Results</h4>Aneuvis is a ...[more]

PMID: 31208319

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Project description:Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.

Dataset Information

Aneuvis: web-based exploration of numerical chromosomal variation in single cells.

Background

Results

Conclusions

Publications

Aneuvis: web-based exploration of numerical chromosomal variation in single cells.

Similar Datasets

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