Bioinformatics modeling for KLF2-Binding downstream promoter motifs of cytotoxic T-cell regulation

Abstract

To support the study of Krüppel-like factor 2 (KLF2) regulatory mechanisms on cytotoxic T lymphocytes (CTLs), we studied a possibility with a web-based bioinformatics module that enables researchers to identify putative KLF2-binding promoter regions in genomic DNA sequences. After a KLF2 protein structure with C₂H₂ zinc finger domain and binding-site analysis, we successfully set up a tool to integrate Python-based sequence parsing and motif identification routines to locate CACCC motifs near potential start codons (e.g., ATG) across reading frames associated with key CTL genes such as TNF-α and IFN-γ. The tool supports visualization and sequence upload functionality through a static website interface, making it accessible for researchers and clinicians investigating KLF2-mediated transcriptional control in tumor-infiltrating lymphocytes (TILs). This work supplements our primary study on spatial-temporal regulatory networks involved in TIL reactivation by KLF2 down-regulation.

Keywords

KLF2 / C2H2 zinc finger domain / Omics analysis / T-cells / Tumor-infiltrating lymphocytes (TILs) / cytotoxic T lymphocytes (CTLs) / quantitative pathway and network / spatial-timely quantitative network (spatial-temporal quantitative network) / personalized therapy

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