Evidence map›Paper›PMID 38173810›Full record

ArticleSynthetic and systems biotechnology2024

EMT transcription factors activated circuits: A novel tool to study EMT dynamics and its therapeutic implications.

Tianying Chen, Wangyue Jia, Bo Zhang, Hanqi Xie, Qiong Wu

Open access · goldAbstract read
In one paragraph

Article in Synthetic and systems biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
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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

5 authors at 1 institution in 1 country.

Tianying ChenMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Wangyue JiaMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Bo ZhangMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Hanqi XieMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Qiong WuMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Tsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The epithelial mesenchymal transition (EMT) plays significant roles in the progression of cancer and fibrotic disease. Moreover, this process is reversible, resulting in mesenchymal epithelial transition (MET), which plays an important role in cancer metastasis. There is a lack of methods to trace and target EMT cells using synthetic biology circuits, which makes it difficult to study the cell fate or develop targeted treatments. In this study, we introduced responsive EMT sensing circuits, which sense the EMT using specific promoters that respond to transcription factors typical of EMT activation (EMT-TFs). The transcriptional strength of EMT-sensing promoters decreased more than 13-fold in response to the overexpression of the EMT-TF. Then, the NOT gate circuits were built by placing the tetR transcription repressor under the control of EMT sensing promoters and expressed an output signal using the constitutive CMV promoter modified with tetO sites This circuit is named EMT sensing and responding circuits .When the EMT transcription factors was present, we observed a 5.8-fold signal increase in the system. Then, we successfully distinguished mesenchymal breast cancer cells from epithelial cancer cells and repressed the proliferation of EMT tumor cells using our circuits. The EMT sensing and responding circuits are promising tools for the identification of EMT cells, which is crucial for EMT-related disease therapy and investigating the mechanisms underlying the reversible EMT process.

Indexed as

Epithelial mesenchymal transitionSynthetic biologyTumor killing

Identifiers

PMID38173810
PMCPMC10758624
OpenAlexW4389286076

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.