ArticleOncology letters2018
Retrospective screening of microarray data to identify candidate IFN-inducible genes in a HTLV-1 transformed model.
Article in Oncology letters, 2018. 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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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
7 citing papers in PubMed, 5 citations in OpenAlex.
- Interferon dynamics in deltaretroviruses: why HTLV-1 evades, but BLV responds.Molecular biology reports · 2026Review
- Research progress on TMEM proteins in cancer progression and chemoresistance (Review).International journal of molecular medicine · 2025Review
- Identification of potential bladder cancer drug targets through Mendelian randomization and molecular docking.Discover oncology · 2025Article
- Hsa_circRNA_0040462: a sensor of cells' response to CAP treatment with double-edged roles on breast cancer malignancy.International journal of medical sciences · 2022Article
- Differential DNA Methylation Landscape in Skin Fibroblasts from African Americans with Systemic Sclerosis.Genes · 2021Article
- Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis.Carcinogenesis · 2020Article
- IL-27 signaling activates skin cells to induce innate antiviral proteins and protects against Zika virus infection.Science advances · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
HuT-102 cells are considered one of the most representable human T-lymphotropic virus 1 (HTLV-1)-infected cell lines for studying adult T-cell lymphoma (ATL). In our previous studies, genome-wide screening was performed using the GeneChip system with Human Genome Array U133 Plus 2.0 for transforming growth factor-β-activated kinase 1 (TAK1)-, interferon regulatory factor 3 (IRF3)- and IRF4-regulated genes to demonstrate the effects of interferon-inducible genes in HuT-102 cells. Our previous findings demonstrated that TAK1 induced interferon inducible genes via an IRF3-dependent pathway and that IRF4 has a counteracting effect. As our previous data was performed by manual selection of common interferon-related genes mentioned in the literature, there has been some obscure genes that have not been considered. In an attempt to maximize the outcome of those microarrays, the present study reanalyzed the data collected in previous studies through a set of computational rules implemented using 'R' software, to identify important candidate genes that have been missed in the previous two studies. The final list obtained consisted of ten genes that are highly recommend as potential candidate for therapies targeting the HTLV-1 infected cancer cells. Those genes are ATM, CFTR, MUC4, PARP14, QK1, UBR2, CLEC7A (Dectin-1), L3MBTL, SEC24D and TMEM140. Notably, PARP14 has gained increased attention as a promising target in cancer cells.
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Registered trials
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