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A resource for discovering specific and universal biomarkers for distributed stem cells.

Noh M, Smith JL, Huh YH, Sherley JL - PLoS ONE (2011)

Bottom Line: This delineation has several significant implications.These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs.Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy, Ajou University, Suwon, South Korea.

ABSTRACT
Specific and universal biomarkers for distributed stem cells (DSCs) have been elusive. A major barrier to discovery of such ideal DSC biomarkers is difficulty in obtaining DSCs in sufficient quantity and purity. To solve this problem, we used cell lines genetically engineered for conditional asymmetric self-renewal, the defining DSC property. In gene microarray analyses, we identified 85 genes whose expression is tightly asymmetric self-renewal associated (ASRA). The ASRA gene signature prescribed DSCs to undergo asymmetric self-renewal to a greater extent than committed progenitor cells, embryonic stem cells, or induced pluripotent stem cells. This delineation has several significant implications. These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs. Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification.

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Related in: MedlinePlus

Statistical evaluation of the biological uniqueness of the ASRA gene signature.A. Shown is the histogram for p values determined by the Student's t-test for Between Group Analysis (BGA) separation of the ASYM versus the SYM/p53SYM training datasets described in Fig. 4. Each of the 10,000 determinations was performed with the expression values of a random sample of 85 genes. The vertical line indicates the p value of the 85 gene ASRA gene signature. B. Comparison of the observed frequencies (ordinate; blue) of randomly sampled 85 gene subsets, which had lower p values than the ASRA gene signature in A and contained the indicated number of ASRA genes (abscissa), to the frequencies predicted by chance (red). C. Analyses of the BGA separation distance between microarray data sets for mouse embryonic stem cells (ESC) versus cultured mouse neural stem cells (NSC) relative to the separation distance of respective SYM versus ASYM training datasets (see Fig. 4) using the randomly sampled 85 gene subsets that had lower p values than the ASRA gene signature in A. All gene subsets whose BGA analyses lacked altogether the respective correspondence between ESC∶NSC and SYM∶ASYM separation were grouped as “<0”. The vertical line indicates the relative ESC∶NSC separation using the 85 gene ASRA gene signature.
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pone-0022077-g005: Statistical evaluation of the biological uniqueness of the ASRA gene signature.A. Shown is the histogram for p values determined by the Student's t-test for Between Group Analysis (BGA) separation of the ASYM versus the SYM/p53SYM training datasets described in Fig. 4. Each of the 10,000 determinations was performed with the expression values of a random sample of 85 genes. The vertical line indicates the p value of the 85 gene ASRA gene signature. B. Comparison of the observed frequencies (ordinate; blue) of randomly sampled 85 gene subsets, which had lower p values than the ASRA gene signature in A and contained the indicated number of ASRA genes (abscissa), to the frequencies predicted by chance (red). C. Analyses of the BGA separation distance between microarray data sets for mouse embryonic stem cells (ESC) versus cultured mouse neural stem cells (NSC) relative to the separation distance of respective SYM versus ASYM training datasets (see Fig. 4) using the randomly sampled 85 gene subsets that had lower p values than the ASRA gene signature in A. All gene subsets whose BGA analyses lacked altogether the respective correspondence between ESC∶NSC and SYM∶ASYM separation were grouped as “<0”. The vertical line indicates the relative ESC∶NSC separation using the 85 gene ASRA gene signature.

Mentions: We developed a statistical method to evaluate how unique the ASRA gene signature was for its ability to discriminate known asymmetric self-renewal states from known symmetric self-renewal states based on its ASYM∶SYM∶p53SYM selection design. We used BGA to estimate the probability of finding, by random sampling within the founding microarray data, other 85 gene subsets of greater ability to discriminate self-renewal pattern compared to that of the ASRA gene signature. The Student's t-test was used to determine statistical confidence levels for the degree of ASYM versus SYM/p53SYM discrimination. The distribution for 10,000 randomly sampled 85 gene sets with respect to BGA p value is shown in Fig. 5A. Based on this analysis, the ASRA gene signature was in the 5th percentile for the statistical confidence of its ASYM versus SYM/p53SYM discrimination, indicating a high degree of biological specificity.


A resource for discovering specific and universal biomarkers for distributed stem cells.

Noh M, Smith JL, Huh YH, Sherley JL - PLoS ONE (2011)

Statistical evaluation of the biological uniqueness of the ASRA gene signature.A. Shown is the histogram for p values determined by the Student's t-test for Between Group Analysis (BGA) separation of the ASYM versus the SYM/p53SYM training datasets described in Fig. 4. Each of the 10,000 determinations was performed with the expression values of a random sample of 85 genes. The vertical line indicates the p value of the 85 gene ASRA gene signature. B. Comparison of the observed frequencies (ordinate; blue) of randomly sampled 85 gene subsets, which had lower p values than the ASRA gene signature in A and contained the indicated number of ASRA genes (abscissa), to the frequencies predicted by chance (red). C. Analyses of the BGA separation distance between microarray data sets for mouse embryonic stem cells (ESC) versus cultured mouse neural stem cells (NSC) relative to the separation distance of respective SYM versus ASYM training datasets (see Fig. 4) using the randomly sampled 85 gene subsets that had lower p values than the ASRA gene signature in A. All gene subsets whose BGA analyses lacked altogether the respective correspondence between ESC∶NSC and SYM∶ASYM separation were grouped as “<0”. The vertical line indicates the relative ESC∶NSC separation using the 85 gene ASRA gene signature.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3139609&req=5

pone-0022077-g005: Statistical evaluation of the biological uniqueness of the ASRA gene signature.A. Shown is the histogram for p values determined by the Student's t-test for Between Group Analysis (BGA) separation of the ASYM versus the SYM/p53SYM training datasets described in Fig. 4. Each of the 10,000 determinations was performed with the expression values of a random sample of 85 genes. The vertical line indicates the p value of the 85 gene ASRA gene signature. B. Comparison of the observed frequencies (ordinate; blue) of randomly sampled 85 gene subsets, which had lower p values than the ASRA gene signature in A and contained the indicated number of ASRA genes (abscissa), to the frequencies predicted by chance (red). C. Analyses of the BGA separation distance between microarray data sets for mouse embryonic stem cells (ESC) versus cultured mouse neural stem cells (NSC) relative to the separation distance of respective SYM versus ASYM training datasets (see Fig. 4) using the randomly sampled 85 gene subsets that had lower p values than the ASRA gene signature in A. All gene subsets whose BGA analyses lacked altogether the respective correspondence between ESC∶NSC and SYM∶ASYM separation were grouped as “<0”. The vertical line indicates the relative ESC∶NSC separation using the 85 gene ASRA gene signature.
Mentions: We developed a statistical method to evaluate how unique the ASRA gene signature was for its ability to discriminate known asymmetric self-renewal states from known symmetric self-renewal states based on its ASYM∶SYM∶p53SYM selection design. We used BGA to estimate the probability of finding, by random sampling within the founding microarray data, other 85 gene subsets of greater ability to discriminate self-renewal pattern compared to that of the ASRA gene signature. The Student's t-test was used to determine statistical confidence levels for the degree of ASYM versus SYM/p53SYM discrimination. The distribution for 10,000 randomly sampled 85 gene sets with respect to BGA p value is shown in Fig. 5A. Based on this analysis, the ASRA gene signature was in the 5th percentile for the statistical confidence of its ASYM versus SYM/p53SYM discrimination, indicating a high degree of biological specificity.

Bottom Line: This delineation has several significant implications.These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs.Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification.

View Article: PubMed Central - PubMed

Affiliation: School of Pharmacy, Ajou University, Suwon, South Korea.

ABSTRACT
Specific and universal biomarkers for distributed stem cells (DSCs) have been elusive. A major barrier to discovery of such ideal DSC biomarkers is difficulty in obtaining DSCs in sufficient quantity and purity. To solve this problem, we used cell lines genetically engineered for conditional asymmetric self-renewal, the defining DSC property. In gene microarray analyses, we identified 85 genes whose expression is tightly asymmetric self-renewal associated (ASRA). The ASRA gene signature prescribed DSCs to undergo asymmetric self-renewal to a greater extent than committed progenitor cells, embryonic stem cells, or induced pluripotent stem cells. This delineation has several significant implications. These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs. Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification.

Show MeSH
Related in: MedlinePlus