TdIF1-LSD1 Axis Regulates Epithelial—Mesenchymal Transition and Metastasis via Histone Demethylation of E-Cadherin Promoter in Lung Cancer
Bibliographic record
Abstract
We have previously found that TdT-interacting factor 1 (TdIF1) is a potential oncogene expressed in non-small cell lung cancer (NSCLC) and is associated with poor prognosis. However, its exact mechanism is still unclear. The lysine-specific demethylase 1 (LSD1) is a crucial mediator of the epithelial-mesenchymal transition (EMT), an important process triggered during cancer metastasis. Here, we confirm that TdIF1 is highly expressed in NSCLC and related to lymph node metastasis through The Cancer Genome Atlas (TCGA) analysis of clinical samples. Silencing TdIF1 can regulate the expression of EMT-related factors and impair the migration and invasion ability of cancer cells in vitro. An analysis of tumor xenografts in nude mice confirmed that silencing TdIF1 inhibits tumor growth. Furthermore, we determined the interaction between TdIF1 and LSD1 using immunoprecipitation. Chromatin immunoprecipitation (ChIP) revealed that TdIF1 was enriched in the E-cadherin promoter region. The knockdown of TdIF1 repressed the enrichment of LSD1 at the E-cadherin promoter region, thereby regulating the level of promoter histone methylation and modulating E-cadherin transcription activity, ultimately leading to changes in EMT factors and cancer cell migration and invasion ability. The LSD1 inhibitor and TdIF1 knockdown combination showed a synergistic effect in inhibiting the growth, migration, and invasion of NSCLC cells. Taken together, this is the first demonstration that TdIF1 regulates E-cadherin transcription by recruiting LSD1 to the promoter region, thereby promoting EMT and tumor metastasis and highlighting the potential of TdIF1 as a therapeutic target for NSCLC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".