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Clinical and biological relevance of genomic heterogeneity in chronic lymphocytic leukemia.

Friedman DR, Lucas JE, Weinberg JB - PLoS ONE (2013)

Bottom Line: We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups.We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes.Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Duke University, Durham, North Carolina, USA. daphne.friedman@duke.edu

ABSTRACT

Background: Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients' leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL.

Methods: To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups.

Results: Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes.

Conclusions: Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways.

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CLL gene expression data files from the fifteen individual datasets were evaluated by principal component analysis (PCA).A) PCA prior to Bayesian Factor Regression Modeling (BFRM) normalization was performed, and the first principal component (PC) is plotted against the second PC. Numbers represent dataset order found in Table 1. CLL samples from each dataset cluster together. B) PCA following BFRM normalization was performed, and the first PC is plotted against the second PC. Samples retain the same numbering as in Figure 1A. CLL samples now cluster together in one cloud.
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pone-0057356-g001: CLL gene expression data files from the fifteen individual datasets were evaluated by principal component analysis (PCA).A) PCA prior to Bayesian Factor Regression Modeling (BFRM) normalization was performed, and the first principal component (PC) is plotted against the second PC. Numbers represent dataset order found in Table 1. CLL samples from each dataset cluster together. B) PCA following BFRM normalization was performed, and the first PC is plotted against the second PC. Samples retain the same numbering as in Figure 1A. CLL samples now cluster together in one cloud.

Mentions: From a query of the GEO database for CLL-containing datasets, we identified fifteen datasets that contained 893 unique CLL sample data files (Table 1). The number of data files within each dataset ranged from eleven to 448. Associated CLL molecular prognostic markers (interphase cytogenetics, CD38 and ZAP70 expression, and IgVH mutation status) were available for many, but not all, data files.


Clinical and biological relevance of genomic heterogeneity in chronic lymphocytic leukemia.

Friedman DR, Lucas JE, Weinberg JB - PLoS ONE (2013)

CLL gene expression data files from the fifteen individual datasets were evaluated by principal component analysis (PCA).A) PCA prior to Bayesian Factor Regression Modeling (BFRM) normalization was performed, and the first principal component (PC) is plotted against the second PC. Numbers represent dataset order found in Table 1. CLL samples from each dataset cluster together. B) PCA following BFRM normalization was performed, and the first PC is plotted against the second PC. Samples retain the same numbering as in Figure 1A. CLL samples now cluster together in one cloud.
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585365&req=5

pone-0057356-g001: CLL gene expression data files from the fifteen individual datasets were evaluated by principal component analysis (PCA).A) PCA prior to Bayesian Factor Regression Modeling (BFRM) normalization was performed, and the first principal component (PC) is plotted against the second PC. Numbers represent dataset order found in Table 1. CLL samples from each dataset cluster together. B) PCA following BFRM normalization was performed, and the first PC is plotted against the second PC. Samples retain the same numbering as in Figure 1A. CLL samples now cluster together in one cloud.
Mentions: From a query of the GEO database for CLL-containing datasets, we identified fifteen datasets that contained 893 unique CLL sample data files (Table 1). The number of data files within each dataset ranged from eleven to 448. Associated CLL molecular prognostic markers (interphase cytogenetics, CD38 and ZAP70 expression, and IgVH mutation status) were available for many, but not all, data files.

Bottom Line: We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups.We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes.Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Duke University, Durham, North Carolina, USA. daphne.friedman@duke.edu

ABSTRACT

Background: Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients' leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL.

Methods: To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups.

Results: Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes.

Conclusions: Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways.

Show MeSH
Related in: MedlinePlus