Evidence map›Paper›PMID 33673145›Full record

ArticleCancers2021

Notch Signaling Pathway in Cancer-Review with Bioinformatic Analysis.

Dorota Anusewicz, Magdalena Orzechowska, Andrzej K Bednarek

Abstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
–field-weighted citation impact
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

43 citing papers in PubMed.

  1. Article
  2. Review
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  15. Article
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  17. Review
  18. Article
  19. Article
  20. Decoding the NRF2-NOTCH Crosstalk in Lung Cancer-An Update.Antioxidants (Basel, Switzerland) · 2025
    Review
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

3 authors.

Dorota AnusewiczDepartment of Molecular Carcinogenesis, Medical University of Lodz, 90-752 Lodz, Poland.
Magdalena OrzechowskaDepartment of Molecular Carcinogenesis, Medical University of Lodz, 90-752 Lodz, Poland.ORCID 0000-0002-8301-8059
Andrzej K BednarekDepartment of Molecular Carcinogenesis, Medical University of Lodz, 90-752 Lodz, Poland.

Funding

Narodowe Centrum Nauki 2016/23/N/NZ5/02575Narodowe Centrum Nauki 2016/23/NZ2/02372
6 · The paper itself

Abstract

Notch signaling is an evolutionarily conserved pathway regulating normal embryonic development and homeostasis in a wide variety of tissues. It is also critically involved in carcinogenesis, as well as cancer progression. Activation of the Notch pathway members can be either oncogenic or suppressive, depending on tissue context. The present study is a comprehensive overview, extended with a bioinformatics analysis of TCGA cohorts, including breast, bladder, cervical, colon, kidney, lung, ovary, prostate and rectum carcinomas. We performed global expression profiling of the Notch pathway core components and downstream targets. For this purpose, we implemented the Uniform Manifold Approximation and Projection algorithm to reduce the dimensions. Furthermore, we determined the optimal cutpoint using Evaluate Cutpoint software to established disease-free and overall survival with respect to particular Notch members. Our results demonstrated separation between tumors and their corresponding normal tissue, as well as between tumors in general. The differentiation of the Notch pathway, at its various stages, in terms of expression and survival resulted in distinct profiles of biological processes such as proliferation, adhesion, apoptosis and epithelial to mesenchymal transition. In conclusion, whether oncogenic or suppressive, Notch signaling is proven to be associated with various types of malignancies, and thus may be of interest as a potential therapeutic target.

Indexed as

carcinogenesisglobal signalingNotch signaling

Identifiers

PMID33673145
PMCPMC7918426

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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.