Literature DB >> 16388850

Aven overexpression: association with poor prognosis in childhood acute lymphoblastic leukemia.

Jaewon Choi1, Yu Kyeong Hwang, Ki Woong Sung, Dong Hyun Kim, Keon Hee Yoo, Hye Lim Jung, Hong Hoe Koo.   

Abstract

Aven expression has recently been identified as an anti-apoptotic protein. In this study, Aven expression in 91 children with acute lymphoblastic leukemia (ALL) was investigated for possible correlation with clinical features at diagnosis and treatment outcome. Aven expression was found to be higher in patients >or=10 years old or <1 year (P=0.003), and in patients with unfavorable cytogenetic abnormalities (P<0.001). Aven expression was also significantly higher in relapsed patients in the standard-risk group. Aven overexpression was an independent poor prognostic factor. These findings demonstrate that Aven expression can predict prognosis in childhood ALL.

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Year:  2006        PMID: 16388850     DOI: 10.1016/j.leukres.2005.11.001

Source DB:  PubMed          Journal:  Leuk Res        ISSN: 0145-2126            Impact factor:   3.156


  10 in total

1.  Aven-dependent activation of ATM following DNA damage.

Authors:  Jessie Yanxiang Guo; Ayumi Yamada; Taisuke Kajino; Judy Qiju Wu; Wanli Tang; Christopher D Freel; Junjie Feng; B Nelson Chau; Michael Zhuo Wang; Seth S Margolis; Hae Yong Yoo; Xiao-Fan Wang; William G Dunphy; Pablo M Irusta; J Marie Hardwick; Sally Kornbluth
Journal:  Curr Biol       Date:  2008-06-19       Impact factor: 10.834

2.  Genomic profiling in locally advanced and inflammatory breast cancer and its link to DCE-MRI and overall survival.

Authors:  Sharareh Siamakpour-Reihani; Kouros Owzar; Chen Jiang; Peter M Scarbrough; Oana I Craciunescu; Janet K Horton; Holly K Dressman; Kimberly L Blackwell; Mark W Dewhirst
Journal:  Int J Hyperthermia       Date:  2015-03-26       Impact factor: 3.914

3.  The Apaf-1-binding protein Aven is cleaved by Cathepsin D to unleash its anti-apoptotic potential.

Authors:  I M Melzer; S B M Fernández; S Bösser; K Lohrig; U Lewandrowski; D Wolters; S Kehrloesser; M-L Brezniceanu; A C Theos; P M Irusta; F Impens; K Gevaert; M Zörnig
Journal:  Cell Death Differ       Date:  2012-03-02       Impact factor: 15.828

4.  Identification of dAven, a Drosophila melanogaster ortholog of the cell cycle regulator Aven.

Authors:  Sige Zou; Joy Chang; Leesa LaFever; Wangli Tang; Erika L Johnson; Jack Hu; Ronit Wilk; Henry M Krause; Daniela Drummond-Barbosa; Pablo M Irusta
Journal:  Cell Cycle       Date:  2011-03-15       Impact factor: 4.534

5.  Tanshinone IIA reverses oxaliplatin resistance in colorectal cancer through microRNA-30b-5p/AVEN axis.

Authors:  Tingrui Ge; Yonggang Zhang
Journal:  Open Med (Wars)       Date:  2022-07-12

6.  Aven recognition of RNA G-quadruplexes regulates translation of the mixed lineage leukemia protooncogenes.

Authors:  Palaniraja Thandapani; Jingwen Song; Valentina Gandin; Yutian Cai; Samuel G Rouleau; Jean-Michel Garant; Francois-Michel Boisvert; Zhenbao Yu; Jean-Pierre Perreault; Ivan Topisirovic; Stéphane Richard
Journal:  Elife       Date:  2015-08-12       Impact factor: 8.140

Review 7.  RNA G-quadruplexes and their potential regulatory roles in translation.

Authors:  Jingwen Song; Jean-Pierre Perreault; Ivan Topisirovic; Stéphane Richard
Journal:  Translation (Austin)       Date:  2016-10-04

8.  Overexpression of X-linked inhibitor of apoptosis protein (XIAP) is an independent unfavorable prognostic factor in childhood de novo acute myeloid leukemia.

Authors:  Ki Woong Sung; Jaewon Choi; Yu Kyeong Hwang; Sang Jin Lee; Hee-Jin Kim; Ju Youn Kim; Eun Joo Cho; Keon Hee Yoo; Hong Hoe Koo
Journal:  J Korean Med Sci       Date:  2009-07-29       Impact factor: 2.153

9.  MicroRNA miR-30 family regulates non-attachment growth of breast cancer cells.

Authors:  Maria Ouzounova; Tri Vuong; Pierre-Benoit Ancey; Mylène Ferrand; Geoffroy Durand; Florence Le-Calvez Kelm; Carlo Croce; Chantal Matar; Zdenko Herceg; Hector Hernandez-Vargas
Journal:  BMC Genomics       Date:  2013-02-28       Impact factor: 3.969

10.  Identifying new targets in leukemogenesis using computational approaches.

Authors:  Archana Jayaraman; Kaiser Jamil; Haseeb A Khan
Journal:  Saudi J Biol Sci       Date:  2015-01-20       Impact factor: 4.219

  10 in total

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