Evidence map›Paper›PMID 20013022›Full record

ArticleCellular and molecular life sciences : CMLS2010

Functional interplay between E2F1 and chemotherapeutic drugs defines immediate E2F1 target genes crucial for cancer cell death.

David Engelmann, Susanne Knoll, Daniel Ewerth, Marc Steder, Anja Stoll, Brigitte M Pützer

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In one paragraph

Article in Cellular and molecular life sciences : CMLS, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 21 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

David EngelmannDepartment of Vectorology and Experimental Gene Therapy, Biomedical Research Center, University of Rostock, Germany.
Susanne Knoll
Daniel Ewerth
Marc Steder
Anja Stoll
Brigitte M Pützer
University of Rostock · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The E2F1 transcription factor enhances apoptosis by DNA damage in tumors lacking p53. To elucidate the mechanism of a potential cooperation between E2F1 and chemotherapy, whole-genome microarrays of chemoresistant tumor cell lines were performed focusing on the identification of cooperation response genes (CRG). This gene class is defined by a synergistic expression response upon endogenous E2F1 activation and drug treatment. Cluster analysis revealed an expression pattern of CRGs similar to E2F1 mono-therapy, suggesting that chemotherapeutics enhance E2F1-dependent gene expression at the transcriptional level. Using this approach as a tool to explore E2F1-driven gene expression in response to anticancer drugs, we identified novel apoptosis genes such as the tumor suppressor TIEG1/KLF10 as direct E2F1 targets. We show that TIEG1/KLF10 is transcriptionally activated by E2F1 and crucial for E2F1-mediated chemosensitization of cancer cells. Our results provide a broader picture of E2F1-regulated genes in conjunction with cytotoxic treatment that allows the design of more rational therapeutics.

Indexed as

Antineoplastic AgentsCell DeathCluster AnalysisE2F1 Transcription FactorEarly Growth Response Transcription FactorsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKruppel-Like Transcription FactorsNeoplasmsOligonucleotide Array Sequence AnalysisReverse Transcriptase Polymerase Chain ReactionTumor Cells, CulturedAntineoplastic AgentsE2F1 protein, humanE2F1 Transcription FactorEarly Growth Response Transcription FactorsKLF10 protein, humanKruppel-Like Transcription Factors

Identifiers

PMID20013022
PMCPMC11115677
OpenAlexW2031406944

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.