4.8 Article

SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines

Journal

NUCLEIC ACIDS RESEARCH
Volume 36, Issue 7, Pages 2446-2456

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkn089

Keywords

-

Funding

  1. NCI NIH HHS [P50 CA097186, P50 CA090381, K08 CA122833, P50 CA69568, K08 CA122833-01A1, P50 CA069568, R01 CA109038, R01CA109038] Funding Source: Medline
  2. NIA NIH HHS [R01AG21404, R01 AG021404] Funding Source: Medline

Ask authors/readers for more resources

Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available