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Lipid starvation and hypoxia synergistically activate ICAM1 and multiple genes in an Sp1-dependent manner to promote the growth of ovarian cancer

Overview of attention for article published in Molecular Cancer, April 2015
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Title
Lipid starvation and hypoxia synergistically activate ICAM1 and multiple genes in an Sp1-dependent manner to promote the growth of ovarian cancer
Published in
Molecular Cancer, April 2015
DOI 10.1186/s12943-015-0351-z
Pubmed ID
Authors

Shiro Koizume, Shin Ito, Yoshiyasu Nakamura, Mitsuyo Yoshihara, Mitsuko Furuya, Roppei Yamada, Etsuko Miyagi, Fumiki Hirahara, Yasuo Takano, Yohei Miyagi

Abstract

Elucidation of the molecular mechanisms by which cancer cells overcome hypoxia is potentially important for targeted therapy. Complexation of hypoxia-inducible factors (HIFs) with aryl hydrocarbon receptor nuclear translocators can enhance gene expression and initiate cellular responses to hypoxia. However, multiple molecular mechanisms may be required for cancer cells to adapt to diverse microenvironments. We previously demonstrated that a physical interaction between the ubiquitously expressed transcription factor Sp1 and HIF2 is a major cause of FVII gene activation in poor prognostic ovarian clear cell carcinoma (CCC) cells under hypoxia. Furthermore, it was found that FVII activation is synergistically enhanced when serum-starved cells are cultured under hypoxic conditions. In this study, we investigated whether HIFs and transcription factor Sp1 cooperate to activate multiple genes in CCC cells under conditions of serum starvation and hypoxia (SSH) and then contribute to malignant phenotypes. To identify genes activated under hypoxic conditions in an Sp1-dependent manner, we first performed cDNA microarray analyses. We further investigated the molecular mechanisms of synergistic gene activations including the associated serum factors by various experiments such as real-time RT-PCR, western blotting and chromatin immunoprecipitation. The study was further extended to animal experiments to investigate how it contributes to CCC progression in vivo. ICAM1 is one such gene dramatically induced by SSH and is highly induced by SSH and its synergistic activation involves both the mTOR and autonomously activated TNFα-NFκB axes. We identified long chain fatty acids (LCFA) as a major class of lipids that is associated with albumin, a serum factor responsible for synergistic gene activation under SSH. Furthermore, we found that ICAM1 can be induced in vivo to promote tumor growth. Sp1 and HIFs collaborate to activate genes required for the adaptation of CCC cells to severe microenvironments, such as LCFA starvation and hypoxia. This study highlights the importance of transcriptional regulation under lipid starvation and hypoxia in the promotion of CCC tumor growth.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 5 21%
Student > Bachelor 3 13%
Professor > Associate Professor 3 13%
Other 2 8%
Other 5 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 25%
Medicine and Dentistry 6 25%
Agricultural and Biological Sciences 4 17%
Nursing and Health Professions 1 4%
Mathematics 1 4%
Other 5 21%
Unknown 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 April 2015.
All research outputs
#3,540,536
of 5,005,286 outputs
Outputs from Molecular Cancer
#422
of 604 outputs
Outputs of similar age
#123,351
of 169,258 outputs
Outputs of similar age from Molecular Cancer
#38
of 43 outputs
Altmetric has tracked 5,005,286 research outputs across all sources so far. This one is in the 16th percentile – i.e., 16% of other outputs scored the same or lower than it.
So far Altmetric has tracked 604 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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