In silico characterization of transcription factors implicated in lung cancer

¹ Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India
² Department of Computer Science Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India
³ Centre of Healthcare Technologies and Informatics (CEHTI), Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India

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Abstract

Lung cancer is a leading cause of cancer-related deaths worldwide, primarily due to late-stage diagnosis and molecular heterogeneity. Transcription factors have a crucial role in tumor formation and progression. TFs that have not been adequately studied in lung cancer are numerous. The paper provides an in-silico analysis to identify unexplored TFs that may be implicated in the pathogenesis of lung cancer. A systematic curation of 13 TFs identified in databases and their analysis showed that TFs form complex regulatory interactions. The target gene network analysis revealed that the projected targets are enriched in cell death, differentiation, and proliferation. Motif analysis revealed a high level of conservation of cis-regulatory elements, suggesting high specificity of DNA-binding TFs such as ZNF266 and TSH2. The analysis of the PPI network revealed an enriched interaction network (23 nodes, 57 edges; PPI enrichment p-value < 1.0e-16), with the core cluster of proteins involved in mitotic regulation and cell-cycle control. PCGF2 is a sparsely connected group that mediates Polycomb-mediated epigenetic control and has significant interconnections with cell cycle control, p53 pathways, and cancer-related pathways. Profiling of genomic alterations in lung adenocarcinoma and squamous cell carcinoma pathways identified a common alteration in PCGF2, occurring through mutations and copy number increases, suggesting that the protein may be involved in transcriptional and epigenetic dysregulation in lung cancer. This research paper identifies new TFs linked to lung cancer and proposes a systematic bioinformatics analysis of key regulatory drivers, with the aim of developing TF-based biomarkers and therapeutic targets.