The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Quantitative and sensitive detection of rare mutations using droplet-based microfluidics
Abstract
Somatic mutations within tumoral DNA can be used as highly specific biomarkers to distinguish cancer cells from their normal counterparts. These DNA biomarkers are potentially useful for the diagnosis, prognosis, treatment and follow-up of patients. In order to have the required sensitivity and specificity to detect rare tumoral DNA in stool, blood, lymph and other patient samples, a simple, sensitive and quantitative procedure to measure the ratio of mutant to wild-type genes is required. However, techniques such as dual probe TaqMan(®) assays and pyrosequencing, while quantitative, cannot detect less than ∼1% mutant genes in a background of non-mutated DNA from normal cells. Here we describe a procedure allowing the highly sensitive detection of mutated DNA in a quantitative manner within complex mixtures of DNA. The method is based on using a droplet-based microfluidic system to perform digital PCR in millions of picolitre droplets. Genomic DNA (gDNA) is compartmentalized in droplets at a concentration of less than one genome equivalent per droplet together with two TaqMan(®) probes, one specific for the mutant and the other for the wild-type DNA, which generate green and red fluorescent signals, respectively. After thermocycling, the ratio of mutant to wild-type genes is determined by counting the ratio of green to red droplets. We demonstrate the accurate and sensitive quantification of mutated KRAS oncogene in gDNA. The technique enabled the determination of mutant allelic specific imbalance (MASI) in several cancer cell-lines and the precise quantification of a mutated KRAS gene in the presence of a 200,000-fold excess of unmutated KRAS genes. The sensitivity is only limited by the number of droplets analyzed. Furthermore, by one-to-one fusion of drops containing gDNA with any one of seven different types of droplets, each containing a TaqMan(®) probe specific for a different KRAS mutation, or wild-type KRAS, and an optical code, it was possible to screen the six common mutations in KRAS codon 12 in parallel in a single experiment.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Vogelstein, B., & Kinzler, K. W. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9236 · Cited by 1,770
Detection and quantification of mutations in the plasma of patients with colorectal tumors
Diehl, F., Li, M., Dressman, D., He, Y., Shen, D., Szabo, S., Diaz, L. A., Goodman, S. N., David, K. A., Juhl, H., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507904102 · Cited by 1,188
Microdroplet-based PCR enrichment for large-scale targeted sequencing
Tewhey, R., Warner, J. B., Nakano, M., Libby, B., Medkova, M., David, P. H., Kotsopoulos, S. K., Samuels, M. L., Hutchison, J. B., Larson, J. W., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1583 · Cited by 454
Self-citationSensitive digital quantification of DNA methylation in clinical samples
Li, M., Chen, W.-D., Papadopoulos, N., Goodman, S. N., Bjerregaard, N. C., Laurberg, S., Levin, B., Juhl, H., Arber, N., Moinova, H., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1559 · Cited by 341
Shen, F., Du, W., Kreutz, J. E., Fok, A., & Ismagilov, R. F. (2010) · Lab on a Chip · doi:10.1039/c004521g · Cited by 295
BEAMing up for detection and quantification of rare sequence variants
Li, M., Diehl, F., Dressman, D., Vogelstein, B., & Kinzler, K. W. (2006) · Nature Methods · doi:10.1038/nmeth850 · Cited by 261
Cited by
Huggett, J. F., Foy, C. A., Benes, V., Emslie, K., Garson, J. A., Haynes, R., Hellemans, J., Kubista, M., Mueller, R. D., Nolan, T., et al. (2013) · Clinical Chemistry · doi:10.1373/clinchem.2013.206375 · Cited by 859
Surfactants in droplet-based microfluidics
Baret, J.-C. (2012) · Lab Chip · doi:10.1039/c1lc20582j · Cited by 649
Self-citationGorgannezhad, L., Umer, M., Islam, M. N., Nguyen, N.-T., & Shiddiky, M. J. A. (2018) · Lab on a Chip · doi:10.1039/c8lc00100f · Cited by 312
Controlled droplet microfluidic systems for multistep chemical and biological assays
Kaminski, T. S., & Garstecki, P. (2017) · Chemical Society Reviews · doi:10.1039/c5cs00717h · Cited by 299
Micro Total Analysis Systems for Cell Biology and Biochemical Assays
Kovarik, M. L., Gach, P. C., Ornoff, D. M., Wang, Y., Balowski, J., Farrag, L., & Allbritton, N. L. (2012) · Analytical Chemistry · doi:10.1021/ac202611x · Cited by 270
Metadata
- Authors
- Pekin, D., Skhiri, Y., Baret, J.-C., Le Corre, D., Mazutis, L., Ben Salem, C., Millot, F., El Harrak, A., Hutchison, J. B., Larson, J. W., Link, D. R., Laurent-Puig, P., Griffiths, A. D., & Taly, V.
- Venue
- Lab on a Chip
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2011
- Volume
- 11
- Issue
- 13
- Pages
- 2156
- ISSN
- 1473-0189 (ISSN-L)
- 1473-0197
- OpenAlex
- W2026125236
- Cited by
- 540
- References
- 6
- FWCI
- 20.06
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quantitative and sensitive detection of rare mutations using droplet-based microfluidics. https://app.cochat.ai/papers/10.1039/c1lc20128j
- The paper
- Pekin, D., Skhiri, Y., Baret, J.-C., Le Corre, D., Mazutis, L., Ben Salem, C., Millot, F., El Harrak, A., Hutchison, J. B., Larson, J. W., Link, D. R., Laurent-Puig, P., Griffiths, A. D., & Taly, V. (2011). Quantitative and sensitive detection of rare mutations using droplet-based microfluidics. Lab on a Chip. https://doi.org/10.1039/c1lc20128j
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.