CTPS1 suppresses proliferation and migration in colorectal cancer cells
Bibliographic record
Abstract
Colorectal cancer (CRC) is now the third most prevalent tumor and one of the deadliest cancers worldwide, with an increasing prevalence every year. Therefore, we urgently need to understand the mechanisms regulating the progression of colorectal cancer and find potential diagnostic biomarkers. In this study, we performed an analysis using the TCGA and GEO databases to find a molecular biomarker for the diagnosis of CRC, namely CTPS1. The results of this analysis revealed that CTPS1 could promote tumor proliferation and metastasis. Furthermore, bioinformatics analysis revealed that CTPS1 promoted CRC progression through cell cycle and p53 pathways. Further investigation demonstrated that CTPS1 might be involved in the regulation of CCNB1, RRM2, GTSE1, CDK2 and CHEK2 genes. Moreover, PCR confirmed that CTPS1 regulated GTSE1 and CDK2 molecules. Then, western blot was used to verify that CTPS1 promoted the expression of GTSE1 and CDK2 by inhibiting the expression of p53. In summary, we identified an important diagnostic biomarker for CRC, namely CTPS1, and its importance was validated at the cellular level. These results suggest that CTPS1 could serve as a candidate biomarker for CRC and CTPS1 inhibitors may be a potential treatment for CRC.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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".