Expression of osteopontin coregulators in primary colorectal cancer and associated liver metastases
Bibliographic record
Abstract
BACKGROUND: A transcription regulatory complex (TRC) that includes Ets1, Ets2, PEA3 and β-catenin/T-cell factors regulates osteopontin (OPN) that is implicated in colorectal cancer (CRC) dissemination. The consistency of OPN transcriptional control between primary CRC and metastases is unclear. This study investigates expression and prognostic significance of the OPN-TRC in primary human CRC and associated colorectal liver metastases (CRLM). METHODS: Osteopontin-TRC factors were assayed by digital microscopy in 38 primary CRCs and matched CRLM specimens and assessed against clinical prognosis. RESULTS: In primary CRC, OPN expression intensity correlated with that of its co-activators, PEA3 (r=0.600; P<0.01), Ets1 (r=0.552; P<0.01), Ets2 (r=0.521; P<0.01) and had prognostic significance. Osteopontin intensity in primary CRC inversely correlated with the interval between diagnosis and resection of CRLM. Overall OPN intensity was lower in CRLM than primary CRC and correlations with co-activators were weaker, for example, Ets1 (P=0.047), PEA3 (P=0.022) or nonsignificant (Ets2). The ratio of OPN expression in CRLM vs primary CRC had prognostic significance. CONCLUSION: This study supports transcriptional control of OPN by known coregulators in both primary and secondary CRC. Weaker associations in CRLM suggest involvement of other unknown factors possibly from the liver microenvironment or resulting from additional genetic or epigenetic changes that drive tumour metastatic capability in OPN transcriptional control.
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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".