Phosphorylated transducer and activator of transcription-3 (pSTAT3) immunohistochemical expression in paired primary and metastatic colorectal cancer
Bibliographic record
Abstract
BACKGROUND: Signal Transducer and Activator of Transcription-3 (STAT3) mediates cellular functions. We assessed the IHC expression of phosphorylated STAT3 (pSTAT3) in paired primary tumors and liver metastases in patients with advanced stage colorectal cancer (CRC). METHODS: We included patients with tissue blocks available from both the primary CRC and a surgically resected liver metastasis. The IHC pSTAT3 expression agreement was measured using Cohen's kappa statistic. RESULTS: The study included 103 patients, 55% male, median age was 64. 43% tumors originated in rectum, and 63% of the primary tumors were synchronous. Expression of pSTAT3 was 76% in liver metastases and 71% in primary tumors. A difference in pSTAT3 staining between the primary tumor and liver metastases was noted in 64%. There was lost expression of pSTAT3 in the liver metastases in 28% and gained expression in 36% of cases compared to the primary. The kappa statistic comparing agreement between staining patterns of the primary tumors and liver metastases was a "less-than-chance", at -0.02. Median survival was 4.9 years, with no difference in survival outcomes by pSTAT3 expression in the primary tumor or liver metastases. DISCUSSION: STAT3 is not a prognostic marker in the selective setting of metastatic CRC to liver, but it may remain a potential therapeutic target given most liver metastases expressed pSTAT3. Discordant pSTAT3 expression in between primary tumors and paired liver metastases suggests that use of this class of drug to treat liver predominant metastatic colorectal cancer in a biomarker-driven approach may require confirmatory liver tumor biopsy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".