Glycyl-tRNA Synthetase (GARS) Expression Is Associated with Prostate Cancer Progression and Its Inhibition Decreases Migration, and Invasion In Vitro
Bibliographic record
Abstract
Glycyl-tRNA synthetase (GARS) is a potential oncogene associated with poor overall survival in various cancers. However, its role in prostate cancer (PCa) has not been investigated. Protein expression of GARS was investigated in benign, incidental, advanced, and castrate-resistant PCa (CRPC) patient samples. We also investigated the role of GARS in vitro and validated GARS clinical outcomes and its underlying mechanism, utilizing The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA PRAD) database. Our data revealed a significant association between GARS protein expression and Gleason groups. Knockdown of GARS in PC3 cell lines attenuated cell migration and invasion and resulted in early apoptosis signs and cellular arrest in S phase. Bioinformatically, higher GARS expression was observed in TCGA PRAD cohort, and there was significant association with higher Gleason groups, pathological stage, and lymph nodes metastasis. High GARS expression was also significantly correlated with high-risk genomic aberrations such as PTEN, TP53, FXA1, IDH1, SPOP mutations, and ERG, ETV1, and ETV4 gene fusions. Gene Set Enrichment Analysis (GSEA) of GARS through the TCGA PRAD database provided evidence for upregulation of biological processes such as cellular proliferation. Our findings support the oncogenic role of GARS involved in cellular proliferation and poor clinical outcome and provide further evidence for its use as a potential biomarker in PCa.
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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 | 0.001 |
| 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".