Stem cell gene expression programs influence clinical outcome in human leukemia

By K. Eppert, K. Takenaka, E. Lechman, Levi Waldron, B. Nilsson, P. Galen, K. Metzeler, A. Poeppl, Vicki Ling, Joseph Beyene and 9 more. Nature Medicine, 2011

1,068 citations recorded by the source corpus.

Subfields: Cancer Research, Hematology, Oncology

View Paper: https://www.semanticscholar.org/paper/62025ea4e17173f24a036bf51010a26e21ebd6b4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. J. Dick
2. Antonija Krešo
3. Jane E. Visvader
4. G. Lindeman
5. J. Lathia
6. Jeremy N. Rich
7. Peter W. Laird
8. Antonio Colaprico

In Hematology

1. Jane E. Visvader
2. G. Lindeman
3. J. Dick
4. S. Morrison

In Oncology

1. Jane E. Visvader
2. G. Lindeman
3. J. Medema
4. Antonija Krešo
5. S. Morrison
6. J. Dick
7. Louis Vermeulen
8. F. D. S. E. Melo

Citations in the corpus

• Cancer stem cells: current status and evolving complexities. (2012, background): “The molecular analyses of functionally defined LSC populations from AML patients led to the generation of a LSC signature that largely reflects a self-renewal or stemness signature (Eppert et al., 2011).”
• BCL-2 inhibition targets oxidative phosphorylation and selectively eradicates quiescent human leukemia stem cells (2013, background): “Since a number of recent studies have highlighted that LSCs may display disparate phenotypic patterns besides CD34/CD38 /CD123 (Eppert et al., 2011; Sarry et al., 2011), in performing our initial analyses of ROS levels in primary AML samples, we did not rely on standard phenotypic profiles, but rath”
• Evolution of the cancer stem cell model. (2014, background): “We have recently reported initial identification of an L-IC-specific transcriptional signature through gene-expression analysis of 16 AML samples that were each separated into four fractions and the L-IC activity of each fraction tested in optimized xenograft assays (Eppert et al., 2011).”
• Cancer stem cells: impact, heterogeneity, and uncertainty. (2012, background): “…are therefore more likely to be detected in more highly immunocompromised 288 Cancer Cell 21, March 20, 2012 ª2012 Elsevier Inc. mice: NOD/SCID mice treated with anti-CD122 antibody to deplete NK cells or NOD/SCID IL2Rgnull mice (Eppert et al., 2011; McDermott et al., 2010; Quintana et al., 2008).”
• Cancer stem cells in glioblastoma (2015, background): “Leukemia stem cells are considered a definitive tumor population, yet no marker signature for these cells is definitive (Eppert et al. 2011).”
• Chemotherapy Resistant Human Acute Myeloid Leukemia Cells are Not Enriched for Leukemic Stem Cells but Require Oxidative Metabolism (2017, methodology): “Such cells were initially described as CD34+CD38−, although LSCs have also been identified in more mature CD34+CD38+ populations in vivo (11, 13, 14).”
• Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation (2018, background): “We examined breast invasive carcinoma (BRCA), acute myeloid leukemia (AML), and gliomas to study if the mRNAsi/mDNAsi predict stemness in poorly differentiated tumors.”
• Cancer heterogeneity—a multifaceted view (2013, positive): “The identification of patients with poor prognosis in breast cancers [91], colon cancers [35,92] and leukaemia [93], based on their association with CSC signatures, has indeed supported the relevance of CSCs in a clinical setting.”