5‐fluorouracil‐related gene expression levels in primary colorectal cancer and corresponding liver metastasis
Bibliographic record
Abstract
Gene expression levels of thymidylate synthase (TS), dihydropyrimidine dehydrogenase (DPD), thymidine phosphorylase (TP) and orotate phosphoribosyl transferase (OPRT) have been shown to be associated with response to 5-fluorouracil-based therapies. Analyzing these gene expression levels in liver metastases is important to obtain the best prediction of therapy. Our aim was to determine how TS, DPD, TP and OPRT gene expression levels in primary colorectal cancer (CRC) were related to those in liver metastases. Formalin-fixed, paraffin-embedded tumor specimens from 31 pairs of primary CRC and corresponding liver metastases were dissected by using laser-captured microdissection. RNA was extracted and cDNA was prepared by reverse-transcription. Quantitation of target gene and internal reference gene was performed using real-time PCR. No significant difference was seen between median mRNA expression levels of TS, DPD, TP and OPRT in primary cancer and those in corresponding liver metastases (median value: TS 1.48 vs. 1.43; p=0.92, DPD 0.19 vs.0.12; p=0.10, TP 1.20 vs. 0.98; p=0.39, OPRT 1.17 vs. 0.95; p=0.10). When matched tissue sets were compared on an individual basis, there was a significant correlation for TS mRNA expression between primary cancer and corresponding liver metastases (rs=0.52, p=0.0026). However, no correlation was seen between matched sets for DPD, TP or OPRT. Significant correlation was seen between DPD and TP expression levels in both primary CRC (rs=0.38, p=0.03) and liver metastases (rs=0.72, p<0.0001). A good prediction of TS mRNA levels in liver metastases can be obtained by measuring those of primary CRC, although no correlation was seen for DPD, TP and OPRT.
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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 | 0.001 |
| 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".