ArticleInternational journal of molecular sciences2019
Gene-Specific Intron Retention Serves as Molecular Signature that Distinguishes Melanoma from Non-Melanoma Cancer Cells in Greek Patients.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed, 16 citations in OpenAlex.
- PRELP-associated transcriptomic remodeling links alternative splicing and immune checkpoint blockade outcome in melanoma.Frontiers in immunology · 2026Article
- Intron Retention and Alzheimer's Disease (AD): A Review of Regulation Genes Implicated in AD.Genes · 2025Review
- Synthesis, Stability, and Biological Evaluation of Novel Aminoderivatives Incorporating the Aza-Acridine Scaffold.Molecules (Basel, Switzerland) · 2025Article
- Article
- Towards resolution of the intron retention paradox in breast cancer.Breast cancer research : BCR · 2022Article
- miRNAs in the Diagnosis and Prognosis of Skin Cancer.Frontiers in cell and developmental biology · 2020Review
- Challenges in detecting and quantifying intron retention from next generation sequencing data.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
22 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundSkin cancer represents the most common human malignancy, and it includes BCC, SCC, and melanoma. Since melanoma is one of the most aggressive types of cancer, we have herein attempted to develop a gene-specific intron retention signature that can distinguish BCC and SCC from melanoma biopsy tumors.
methodsIntron retention events were examined through RT-sqPCR protocols, using total RNA preparations derived from BCC, SCC, and melanoma Greek biopsy specimens. Intron-hosted miRNA species and their target transcripts were predicted via the miRbase and miRDB bioinformatics platforms, respectively. Ιntronic ORFs were recognized through the ORF Finder application. Generation and visualization of protein interactomes were achieved by the IntAct and Cytoscape softwares, while tertiary protein structures were produced by using the I-TASSER online server.
results
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Registered trials
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