Targeting Noncanonical TEAD Axis to Overcome DNA Repair-Driven Chemoresistance
Kim, D.-H.; Kim, J.; Kang, S.; Kim, H.-R.; Cho, S. C.; Kim, Y.; Roe, J.-S.; Shin, D.; No, K. T.; Park, H. W.
Show abstract
How transcription factors contribute to DNA damage repair (DDR) independent of canonical gene regulation remains poorly understood. Here, we show that DNA double-strand break (DSB) triggers a functional state transition in TEAD, disengaging it from YAP-dependent transcription and translocating it to DNA lesions as a chromatin-associated DDR factor. Upon genotoxic stress, TEAD is rapidly recruited to damaged chromatin through a biphasic mechanism involving early poly(ADP-ribose)-dependent recruitment followed by ATM-driven {gamma}H2AX-mediated retention. At DNA lesions, TEAD constrains chromatin over-relaxation, suppresses excessive end resection, and promotes non-homologous end joining (NHEJ) independent of its canonical function. Conserved residues within the TEA domain mediate this noncanonical chromatin engagement of TEAD and define a druggable N-terminal interface. Pharmacological targeting of this interface impaired TEAD-dependent DSB repair and sensitized tumors to chemotherapy. Together, these findings establish noncanonical TEAD as a critical DNA repair factor and a clinically actionable driver of chemoresistance, while providing a conceptual framework for understanding how broader families of transcription factors may be repurposed as targetable DNA damage regulators in cancer.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Increased RNA and protein degradation is required for counteracting transcriptional burden and proteotoxic stress in human aneuploid cells 97%
- A molecular switch between mammalian MLL complexes dictates response to Menin-MLL inhibition 96%
- Electrical activity between skin cells regulates melanoma initiation 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.