Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia

	Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia
	Yang, XH; Li, MY; Wang, B; Zhu, WQ; Desgardin, A; Onel, KN; de Jong, J; Chen, JJ; Chen, LN; Cunningham, JM
刊名	BMC BIOINFORMATICS
	2015
卷号	16 期号:1 页码:97-97
关键词	Functional gene-set Dynamic network biomarker Relative effect analysis Leukemic stem cell AML outcome
通讯作者	Yang, XH (reprint author), Univ Chicago, Dept Pediat, 900 East 57th St,KCBD Room 5121, Chicago, IL 60637 USA.,xyang2@uchicago.edu
英文摘要	Background: Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational "gene-to-function, snapshot-to-dynamics, and biology-to-clinic" framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform. Results: We introduced an adjustable "soft threshold" to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08). Conclusion: The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about AML and other complex diseases.
学科主题	Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Mathematical & Computational Biology
类目[WOS]	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
关键词[WOS]	ACUTE-MYELOGENOUS-LEUKEMIA ; DYNAMICAL NETWORK BIOMARKERS ; EARLY-WARNING SIGNALS ; RNA-SEQ DATA ; EXPRESSION SIGNATURE ; COMPLEX DISEASES ; PATHWAY ; KINASE ; CANCER ; AML
收录类别	SCI
语种	英语
WOS记录号	WOS:000351819100001
内容类型	期刊论文
版本	出版稿
源URL	[http://202.127.25.143/handle/331003/108]
专题	上海生化细胞研究所_上海生科院生化细胞研究所
推荐引用方式 GB/T 7714	Yang, XH,Li, MY,Wang, B,et al. Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia[J]. BMC BIOINFORMATICS,2015,16(1):97-97.
APA	Yang, XH.,Li, MY.,Wang, B.,Zhu, WQ.,Desgardin, A.,...&Cunningham, JM.(2015).Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia.BMC BIOINFORMATICS,16(1),97-97.
MLA	Yang, XH,et al."Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia".BMC BIOINFORMATICS 16.1(2015):97-97.