Back

TNIK maintains a MYC-driven partial EMT state that supports proliferation and evasion of senescence in lung squamous cell carcinoma.

Torres-Ayuso, P.; Hamidi, M.; Omolo, K. O.; Hart, K. W.; Sitaram, S.; Zhou, Y.

2026-08-31 cancer biology
10.64898/2026.08.28.747625 bioRxiv
Show abstract

Lung squamous cell carcinoma (LUSC) is an aggressive malignancy characterized by high cellular plasticity and few targeted treatment options. TNIK overexpression is common in LUSC and promotes tumor growth, with TNIK inhibition sensitizing LUSC to radiotherapy, though the underlying mechanisms are not well defined. Through transcriptomic analyses and functional assays, we identified TNIK as a regulator of a MYC-dependent transcriptional network that coordinates epithelial-mesenchymal plasticity and cell proliferation in LUSC. Depletion of TNIK reprogrammed LUSC cells from a hybrid epithelial/mesenchymal state towards an epithelial, senescent-like state characterized by reduced cell migration, invasion, reduced DNA synthesis, and enhanced {beta}-galactosidase activity. Using a small-molecule screen approach, we found that TNIK inhibitors cooperated with agents suppressing the histone methyltransferase and MYC binding partner EZH2, which further suppressed partial epithelial-to-mesenchymal transition (pEMT). Mechanistically, we identified MYC as a key downstream TNIK effector in LUSC cells: MYC depletion phenocopied the effects of TNIK loss on pEMT and senescence, and restoring MYC expression bypassed the effects of TNIK depletion. Collectively, these results implicate TNIK in the mechanisms linking epithelial-mesenchymal plasticity with proliferation and evasion of senescence and provide insights into future strategies for the clinical deployment of TNIK inhibitors in LUSC and other TNIK-dependent malignancies.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.