Retrospective screening of microarray data to identify candidate IFN-inducible genes in a HTLV-1 transformed model
- Alaa Refaat
- Mohamed Owis
- Sherif Abdelhamed
- Ikuo Saiki
- Hiroaki Sakurai
Published online on: February 9, 2018
Copyright: © Refaat et al.
This is an open access article distributed under the terms of Creative Commons Attribution License.
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.