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Harnessing transcription factor activity for programmable therapeutic gene regulation
Preprint
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Harnessing transcription factor activity for programmable therapeutic gene regulation

Yingbo Jia, Chu-Yen Chen, Bo Zhu +14 more
January 2026
 ·
bioRxiv
 ·
DOI 
10.64898/2025.12.08.693012
94
%
Reproducible
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This paper passed independent validation.
QED's automated review checked the evidence supporting each claim, the statistical methods, and whether the results are reproducible from the data provided.

It ranks in the top 1% of preprints assessed in Synthetic Biology this quarter.
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Why this is interesting

By decoding endogenous transcription factor activity into programmable synthetic enhancers, this work transforms undruggable TFs from therapeutic dead-ends into precision logic gates—enabling tumor-selective gene circuits that drive robust antitumor immunity in vivo.

QED claims analysis

Summary

Endogenous transcription factor activity can be systematically decoded through high-throughput functional screening of synthetic enhancers and computationally integrated via protein interaction-based AND-gate circuits to achieve tumor-restricted therapeutic gene expression that drives robust antitumor immune responses in vivo, establishing a generalizable framework for harnessing undruggable TF activity as programmable regulatory signals for precision gene control across cancer and immune cell contexts.

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Main Claim 1 –

Synthetic enhancers directly decode endogenous TF activity for context specificity

Supporting evidence

  • TREND enhancers report cognate TFs with dose-dependent activation
  • TREND finds T-cell activation enhancers outperforming NFAT-based designs
Main Claim 2 –

Protein interaction AND-gates integrate TF activities to boost specificity

Main Claim 3 –

TF-guided AND-gates drive tumor-restricted immunotherapy and antitumor responses

Abstract

Transcription factors (TFs) regulate gene expression programs that define cellular identity, functional state, and disease progression. Despite their central role in biology and disease, only a small fraction of TFs are directly druggable, leaving most disease-associated TFs beyond pharmacological reach and limiting the development of TF-centric therapeutic strategies. Here we propose a generalizable regulatory framework that repurposes endogenous TF activity not as a therapeutic target, but as an intrinsic trigger for programmable gene control. Using high-throughput functional screening of synthetic enhancers, we decode TF activity with minimal regulatory elements that selectively respond to context-specific transcriptional programs. Applied to ovarian cancer, this framework enables the identification of cancer-selective synthetic enhancers that exploit aberrant TF activity to distinguish malignant cells from normal epithelial cells. By integrating these enhancers with protein interaction-based AND-gate circuits, multiple TF inputs are evaluated through Boolean logic, enabling enhanced tumor specificity and amplified transcriptional output. In murine ovarian cancer models, these circuits selectively drive combinatorial immune effector expression and trigger robust antitumor responses. Extending this framework beyond cancer, we identify activation-responsive synthetic enhancers in primary human T cells that leverage endogenous activation-induced TF programs. These enhancers achieve stronger inducibility with lower basal activity than conventional NFAT-based designs. Together, these results establish TF activity as a programmable regulatory signal that can be decoded, integrated, and deployed to enable precise and context-dependent therapeutic gene regulation.

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