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Regulatory network reconstruction reveals genes with prognostic value for chronic lymphocytic leukemia.
- Source :
-
BMC genomics [BMC Genomics] 2015 Nov 25; Vol. 16, pp. 1002. Date of Electronic Publication: 2015 Nov 25. - Publication Year :
- 2015
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Abstract
- Background: The clinical course of chronic lymphocytic leukemia (CLL) is highly variable; some patients follow an indolent course, but others progress to a more advanced stage. The mutational status of rearranged immunoglobulin heavy chain variable (IGVH) genes in CLL is a feature that is widely recognized for dividing patients into groups that are related to their prognoses. However, the regulatory programs associated with the IGVH statuses are poorly understood, and markers that can precisely predict survival outcomes have yet to be identified.<br />Methods: In this study, (i) we reconstructed gene regulatory networks in CLL by applying an information-theoretic approach to the expression profiles of 5 cohorts. (ii) We applied master regulator analysis (MRA) to these networks to identify transcription factors (TFs) that regulate an IGVH mutational status signature. The IGVH mutational status signature was developed by searching for differentially expressed genes between the IGVH mutational statuses in numerous CLL cohorts. (iii) To evaluate the biological implication of the inferred regulators, prognostic values were determined using time to treatment (TTT) and overall survival (OS) in two different cohorts.<br />Results: A robust IGVH expression signature was obtained, and various TFs emerged as regulators of the signature in most of the reconstructed networks. The TF targets expression profiles exhibited significant differences with respect to survival, which allowed the definition of a reduced profile with a high value for OS. TCF7 and its targets stood out for their roles in progression.<br />Conclusion: TFs and their targets, which were obtained merely from inferred regulatory associations, have prognostic implications and reflect a regulatory context for prognosis.
- Subjects :
- Computational Biology methods
Databases, Nucleic Acid
Female
Gene Expression Profiling
Humans
Immunoglobulin Heavy Chains genetics
Immunoglobulin Variable Region genetics
Leukemia, Lymphocytic, Chronic, B-Cell metabolism
Male
Meta-Analysis as Topic
Mutation
Prognosis
Transcription Factors genetics
Transcription Factors metabolism
Biomarkers, Tumor
Gene Expression Regulation, Leukemic
Gene Regulatory Networks
Leukemia, Lymphocytic, Chronic, B-Cell genetics
Leukemia, Lymphocytic, Chronic, B-Cell mortality
Subjects
Details
- Language :
- English
- ISSN :
- 1471-2164
- Volume :
- 16
- Database :
- MEDLINE
- Journal :
- BMC genomics
- Publication Type :
- Academic Journal
- Accession number :
- 26606983
- Full Text :
- https://doi.org/10.1186/s12864-015-2189-6