Dataset Information

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method.

ABSTRACT:

Purpose

The analysis of MET gene copy number (CN) has been considered to be a potential biomarker to predict the response to MET-targeted therapies in various cancers. However, the current standard methods to determine MET CN are SNP 6.0 in the genomic DNA of cancer cell lines and fluorescence in situ hybridization (FISH) in tumor models, respectively, which are costly and require advanced technical skills and result in relatively subjective judgments. Therefore, we employed a novel method, droplet digital PCR (ddPCR), to determine the MET gene copy number with high accuracy and precision.

Methods

The genomic DNA of cancer cell lines or tumor models were tested and compared with the MET gene CN and MET/CEN-7 ratio determined by SNP 6.0 and FISH, respectively.

Results

In cell lines, the linear association of the MET CN detected by ddPCR and SNP 6.0 is strong (Pearson correlation = 0.867). In tumor models, the MET CN detected by ddPCR was significantly different between the MET gene amplification and non-amplification groups according to FISH (mean: 15.4 vs 2.1; P = 0.044). Given that MET gene amplification is defined as MET CN >5.5 by ddPCR, the concordance rate between ddPCR and FISH was 98.0%, and Cohen's kappa coefficient was 0.760 (95% CI, 0.498-1.000; P <0.001).

Conclusions

The results demonstrated that the ddPCR method has the potential to quantify the MET gene copy number with high precision and accuracy as compared with the results from SNP 6.0 and FISH in cancer cell lines and tumor samples, respectively.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC4713204 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method.

Zhang Yanni Y Tang En-Tzu ET Du Zhiqiang Z

PloS one 20160114 1

<h4>Purpose</h4>The analysis of MET gene copy number (CN) has been considered to be a potential biomarker to predict the response to MET-targeted therapies in various cancers. However, the current standard methods to determine MET CN are SNP 6.0 in the genomic DNA of cancer cell lines and fluorescence in situ hybridization (FISH) in tumor models, respectively, which are costly and require advanced technical skills and result in relatively subjective judgments. Therefore, we employed a novel meth ...[more]

PMID: 26765781

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Project description:Bacteria can be considered as biological nanofactories that manufacture a cornucopia of bioproducts most notably recombinant proteins. As such, they must perfectly match with appropriate plasmid vectors to ensure successful overexpression of target genes. Among many parameters that correlate positively with protein productivity plasmid copy number plays pivotal role. Therefore, development of new and more accurate methods to assess this critical parameter will result in optimization of expression of plasmid-encoded genes. In this study, we present a simple and highly accurate method for quantifying plasmid copy number utilizing an EvaGreen single colour, droplet digital PCR. We demonstrate the effectiveness of this method by examining the copy number of the pBR322 vector within Escherichia coli DH5? cells. The obtained results were successfully validated by real-time PCR. However, we observed a strong dependency of the plasmid copy number on the method chosen for isolation of the total DNA. We found that application of silica-membrane-based columns for DNA purification or DNA isolation with use of bead-beating, a mechanical cell disruption lead to determination of an average of 20.5 or 7.3 plasmid copies per chromosome, respectively. We found that recovery of the chromosomal DNA from purification columns was less efficient than plasmid DNA (46.5 ± 1.9% and 87.4 ± 5.5%, respectively) which may lead to observed differences in plasmid copy number. Besides, the plasmid copy number variations dependent on DNA template isolation method, we found that droplet digital PCR is a very convenient method for measuring bacterial plasmid content. Careful determination of plasmid copy number is essential for better understanding and optimization of recombinant proteins production process. Droplet digital PCR is a very precise method that allows performing thousands of individual PCR reactions in a single tube. The ddPCR does not depend on running standard curves and is a straightforward and reliable method to quantify the plasmid copy number. Therefore we believe that the ddPCR designed in this study will be widely used for any plasmid copy number calculation in the future.

Project description:Plasmids are widely used for molecular cloning or production of proteins in laboratory and industrial settings. Constant modification has brought forth countless plasmid vectors whose characteristics in terms of average plasmid copy number (PCN) and stability are rarely known. The crucial factor determining the PCN is the replication system; most replication systems in use today belong to a small number of different classes and are available through repositories like the Standard European Vector Architecture (SEVA).In this study, the PCN was determined in a set of seven SEVA-based expression plasmids only differing in the replication system. The average PCN for all constructs was determined by Droplet Digital PCR and ranged between 2 and 40 per chromosome in the host organism Escherichia coli. Furthermore, a plasmid-encoded EGFP reporter protein served as a means to assess variability in reporter gene expression on the single cell level. Only cells with one type of plasmid (RSF1010 replication system) showed a high degree of heterogeneity with a clear bimodal distribution of EGFP intensity while the others showed a normal distribution. The heterogeneous RSF1010-carrying cell population and one normally distributed population (ColE1 replication system) were further analyzed by sorting cells of sub-populations selected according to EGFP intensity. For both plasmids, low and highly fluorescent sub-populations showed a remarkable difference in PCN, ranging from 9.2 to 123.4 for ColE1 and from 0.5 to 11.8 for RSF1010, respectively.The average PCN determined here for a set of standardized plasmids was generally at the lower end of previously reported ranges and not related to the degree of heterogeneity. Further characterization of a heterogeneous and a homogeneous population demonstrated considerable differences in the PCN of sub-populations. We therefore present direct molecular evidence that the average PCN does not represent the true number of plasmid molecules in individual cells.

Dataset Information

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method.

Purpose

Methods

Results

Conclusions

Publications

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method.

Similar Datasets

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