TRIM14 is a Putative Tumor Suppressor and Regulator of Innate Immune Response in Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Non-small-cell lung carcinoma (NSCLC) accounts for 85% of malignant lung tumors and is the leading cause of cancer deaths. Our group previously identified Tripartite Motif 14 (TRIM14) as a component of a prognostic multigene expression signature for NSCLC. Little is known about the function of TRIM14 protein in normal or disease states. We investigated the functional and prognostic role of TRIM14 in NSCLC using in vitro and in vivo perturbation model systems. Firstly, a pooled RNAi screen identified TRIM14 to effect cell proliferation/survival in NSCLC cells. Secondly, silencing of TRIM14 expression significantly enhanced tumor growth in NSCLC xenograft mouse models, while exogenous TRIM14 expression attenuated tumorigenesis. In addition, differences in apoptotic activity between TRIM14-deficient and control tumors suggests that TRIM14 tumor suppressor activity may depend on cell death signaling pathways. TRIM14-deficient cell lines showed both resistance to hypoxia-induced cell death and attenuation of interferon response via STAT1 signaling. Consistent with these phenotypes, multivariate analyses on published mRNA expression datasets of over 600 primary NSCLCs demonstrated that low TRIM14 mRNA levels are significantly associated with poorer prognosis in early stage NSCLC patients. Our functional data therefore establish a novel tumor suppressive role for TRIM14 in NSCLC progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
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".