Literature DB >> 29305708

Identification of specific feed-forward apoptosis mechanisms and associated higher survival rates for low grade glioma and lung squamous cell carcinoma.

Dhiraj Sikaria1, Yaping N Tu1, Diana A Fisler1, James A Mauro1, George Blanck2,3,4.   

Abstract

The mechanisms of cell proliferation due to the overexpression of certain transcription factors (TFs) have been well documented in the cancer setting. However, many of these same TFs have pro-apoptotic effects, particularly when expressed or activated at high levels, a process referred to as feed-forward apoptosis (FFA). To determine whether cancers could be stratified on the basis of specific FFA signatures, RNASeq data representing samples from the cancer genome atlas were analyzed, revealing that high expression of the pro-proliferative TFs, MYC and YY1, is associated with a favorable outcome in low-grade glioma (LGG) and lung squamous cell carcinoma (LUSC), respectively. Analysis of the RNASeq data also led to the identification of specific apoptosis-effector genes whose expression levels correlate with increased survival rates, for both LGG and LUSC. Although FFA has been demonstrated as a general effect in cancer, in this report, for the first time, results identify specific TFs and their responsive effector genes that distinguish subsets of cancer samples undergoing more or less of a FFA process in a way that is associated with distinct patient survival rates.

Entities:  

Keywords:  Apoptosis-effector genes; Feed-forward apoptosis; Glioma; Lung cancer; Pro-proliferative transcription factors; The cancer genome atlas

Mesh:

Substances:

Year:  2018        PMID: 29305708     DOI: 10.1007/s00432-017-2569-1

Source DB:  PubMed          Journal:  J Cancer Res Clin Oncol        ISSN: 0171-5216            Impact factor:   4.553


  35 in total

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Journal:  Cell       Date:  1996-05-17       Impact factor: 41.582

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Journal:  Mol Cell Biol       Date:  1996-05       Impact factor: 4.272

Review 4.  Exploiting replicative stress to treat cancer.

Authors:  Matthias Dobbelstein; Claus Storgaard Sørensen
Journal:  Nat Rev Drug Discov       Date:  2015-05-08       Impact factor: 84.694

5.  Caspase 8 is deleted or silenced preferentially in childhood neuroblastomas with amplification of MYCN.

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Authors:  Huarui Lu; Timothy C Hallstrom
Journal:  J Biol Chem       Date:  2013-07-05       Impact factor: 5.157

7.  Stratifying melanoma and breast cancer TCGA datasets on the basis of the CNV of transcription factor binding sites common to proliferation- and apoptosis-effector genes.

Authors:  James A Mauro; John M Yavorski; George Blanck
Journal:  Gene       Date:  2017-02-28       Impact factor: 3.688

8.  Replication Stress Leading to Apoptosis within the S-phase Contributes to Synergism between Vorinostat and AZD1775 in HNSCC Harboring High-Risk TP53 Mutation.

Authors:  Noriaki Tanaka; Ameeta A Patel; Lin Tang; Natalie L Silver; Antje Lindemann; Hideaki Takahashi; Roman Jaksik; Xiayu Rao; Nene N Kalu; Tseng-Cheng Chen; Jiping Wang; Mitchell J Frederick; Faye Johnson; Frederico O Gleber-Netto; Siqing Fu; Marek Kimmel; Jing Wang; Walter N Hittelman; Curtis R Pickering; Jeffrey N Myers; Abdullah A Osman
Journal:  Clin Cancer Res       Date:  2017-08-08       Impact factor: 12.531

9.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

Authors:  Bo Li; Colin N Dewey
Journal:  BMC Bioinformatics       Date:  2011-08-04       Impact factor: 3.307

10.  N-myc downstream-regulated gene 1 promotes apoptosis in colorectal cancer via up-regulating death receptor 4.

Authors:  Xian Zhang; Bo Feng; Fan Zhu; Chaoran Yu; Jiaoyang Lu; Meng Pan; Zirui He; Xiongzhi Wangpu; Jing Sun; Xiao Yang
Journal:  Oncotarget       Date:  2017-07-28
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  3 in total

1.  Elucidating feed-forward apoptosis signatures in breast cancer datasets: Higher FOS expression associated with a better outcome.

Authors:  Diana A Fisler; Dhiraj Sikaria; John M Yavorski; Yaping N Tu; George Blanck
Journal:  Oncol Lett       Date:  2018-06-12       Impact factor: 2.967

2.  An age-based, RNA expression paradigm for survival biomarker identification for pediatric neuroblastoma and acute lymphoblastic leukemia.

Authors:  Andrea Diviney; Boris I Chobrutskiy; Saif Zaman; George Blanck
Journal:  Cancer Cell Int       Date:  2019-03-27       Impact factor: 5.722

3.  High levels of CCL2 or CCL4 in the tumor microenvironment predict unfavorable survival in lung adenocarcinoma.

Authors:  Lei Li; Yong-Dong Liu; Yu-Ting Zhan; Ying-Hui Zhu; Yan Li; Dan Xie; Xin-Yuan Guan
Journal:  Thorac Cancer       Date:  2018-05-02       Impact factor: 3.500

  3 in total

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