Two-marker protein profile predicts poor prognosis in patients with early rectal cancer
Bibliographic record
Abstract
The aim of this study was to establish an immunohistochemical protein profile to complement preoperative staging and identify rectal cancer patients at high-risk of adverse outcome. Immunohistochemistry was performed on a tissue microarray including 482 rectal cancers for APAF-1, EphB2, MST1, Ki67, p53, RHAMM, RKIP and CD8(+) tumour infiltrating lymphocytes (TILs). After resampling of the data and multivariable analysis, the most reproducible markers were combined and prognosis evaluated as stratified by pT and pN status. In multivariable analysis, only positive RHAMM (P<0.001; HR=1.94 (1.44-2.61)) and loss of CD8(+) TILs (P=0.006; HR=0.63 (0.45-0.88)) were independent prognostic factors. The 5-year cancer-specific survival rate for RHAMM+/TIL- patients was 30% (95% CI 21-40%) compared to 76% (95% CI: 66-84%) for RHAMM-/TIL+ patients (P<0.001). The 5-year cancer-specific survival of T1/T2/RHAMM+/TIL- patients was 48% (20-72%) and significantly worse compared to T3/T4/RHAMM-/TIL+ patients (71% 95% CI 56-82%); P=0.039). Stratifying by nodal status, only N+/RHAMM+/TIL- patients demonstrated a significantly worse prognosis than N0/RHAMM+/TIL- patients (P=0.005). Loss of CD8(+) TILs was predictive of local recurrence in RHAMM+ tumours (P=0.009) only. RHAMM and CD8(+) TILs may assist in identifying early stage rectal cancer patients facing a particularly poor prognosis and who may derive a benefit from preoperative therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".