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Updated: Oct 11, 2025
Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
Published on: June 27, 2020
Study of transcription factor druggabilty for prostate cancer using structure information, gene regulatory networks
Ashmita Dey1, Sagnik Sen1, Ujjwal Maulik1
1Computer Science and Engineering, Jadavpur University, Kolkata, India.
Abstract:
Prostate cancer is the second leading cause of cancer-related death in men. Metastasis shows poor survival even though the recovery rate is high. In spite of numerous studies regarding prostate carcinoma, multiple questions are still unanswered. In this regards, gene regulatory network can uncover the mechanisms behind cancer progression, and metastasis. Under a feed forward loop, transcription factors (TFs) can be a good druggable candidate. We have proposed a computational model to study the uncertainty of TFs and suggest the appropriate cellular conditions for drug targeting. We have selected feed-forward loops depending on the shared list of the functional annotations among TFs, genes and miRNAs. From the potential feed forward loop cores, six TFs were identified as druggable targets, which include AR, CEBPB, CREB1, ETS1, NFKB1 and RELA. However, TFs are known for their Protein Moonlighting properties, which provide unrelated multi-functionalities within the same or different subcellular localizations. Following that, we have identified such functions that are suitable for drug targeting. On the other hand, we have tried to identify membraneless organelles for providing more specificity to the proposed time and space theory. The study has provided certain possibilities on TF-based therapeutics. The controlled dynamic nature of the TF may have enhanced the chances where TFs can be considered as one of the prime drug targets. Finally, the combination of membranless phase separation and protein moonlighting has provided possible druggable period within the biological clock.
Insights
This study identifies transcription factors (TFs) as potential drug targets for prostate cancer by analyzing gene regulatory networks. It proposes targeting TFs within specific cellular conditions and utilizing their moonlighting functions for effective cancer therapeutics.
Area of Science:
- Computational biology
- Cancer research
- Systems biology
Background:
- Prostate cancer is a leading cause of male cancer deaths, with metastasis significantly impacting survival rates.
- Gene regulatory networks (GRNs) offer insights into cancer progression and metastasis mechanisms.
- Transcription factors (TFs) within feed-forward loops (FFLs) present potential druggable targets.
Purpose of the Study:
- To develop a computational model for identifying druggable transcription factors (TFs) in prostate cancer.
- To explore the role of TF protein moonlighting and membraneless organelles in drug targeting strategies.
- To propose novel therapeutic approaches for prostate cancer based on TF-targeted interventions.
Main Methods:
- Construction and analysis of gene regulatory networks focusing on feed-forward loops (FFLs).
- Identification of TFs based on shared functional annotations among TFs, genes, and miRNAs.
- Investigation of transcription factor (TF) protein moonlighting and membraneless organelles for drug targeting specificity.
Main Results:
- Six transcription factors (AR, CEBPB, CREB1, ETS1, NFKB1, RELA) were identified as potential druggable targets.
- Protein moonlighting properties of TFs were analyzed to identify suitable functions for drug targeting.
- Membraneless organelles were explored for enhancing the specificity of time and space drug delivery.
Conclusions:
- The study presents a computational framework for identifying TF-based therapeutic strategies in prostate cancer.
- Targeting TFs, considering their moonlighting functions and subcellular localization within membraneless organelles, offers promising avenues for cancer treatment.
- The dynamic nature of TFs and their integration with cellular organization provide a basis for developing effective, targeted therapies.
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