ArticleJournal of theoretical biology2016
Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.
Article in Journal of theoretical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- Epigenetic Factors and ncRNAs in Testicular Cancer.International journal of molecular sciences · 2023Review
- piR-36249 and DHX36 together inhibit testicular cancer cells progression by upregulating OAS2.Non-coding RNA research · 2023Article
- Review
- The role of mRNA in the development, diagnosis, treatment and prognosis of neural tumors.Molecular cancer · 2021Review
- CircRhoC promotes tumorigenicity and progression in ovarian cancer by functioning as a miR-302e sponge to positively regulate VEGFA.Journal of cellular and molecular medicine · 2019Article
- Combining Supervised and Unsupervised Learning for Improved miRNA Target Prediction.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies.
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Registered trials
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