Prognostic immune scoring of colorectal cancer liver metastasis with MHC class-I expression combined to T cell quantification.
Bibliographic record
Abstract
3586 Background: Approximately 80% of patients recur after curative-intent resection of colorectal cancer liver metastasis (CRLM) and systemic chemotherapy. Immune profiling may help prognostication to individualize follow-up and lead to novel therapeutic strategies. We tested whether adding major histocompatibility class I (MHC-I) expression to T cell immune scoring in CRLMs could group patients with distinct prognosis. Methods: Tissue microarray analysis of 391 CRLMs resected in 214 patients (2011-2014) followed prospectively until 10/2017. Each CRLM arrayed with twelve 0.6 mm punch biopsies, 6 at the interface (IF) with normal liver and 6 intratumoral (IT). Automated quantification of CD3+ cells and MHC-I+ surface area stained by immunohistochemistry. We tested associations between immune, clinicopathological, and time to recurrence (TTR) and disease specific survival (DSS) outcome variables. Results: The mean patient age was 62.7 years, 78.5% received pre-operative chemotherapy (mean of 6 cycles), and a median of 2 CRLMs/patient were resected. The median TTR and DSS were 15.4 and 56.7 months, respectively. Pre-operative chemotherapy was associated with higher CD3 infiltration and lower MHC-I expression at IF and IT. Good pathological response to chemotherapy (Rubbia-Brandt TRG score 1-2-3) compared to lack of response (TRG 4-5) was associated with higher CD3 infiltration but no significant difference in MHC-I expression. CD3 immune scoring integrating the IF and IT areas had no prognostic value. MHC-I expression prognostically stratified patients with CD3low but not CD3high CRCLMs. Compared to the rest of the cohort, patients with at least one CD3lowMHC-Ihi CRLM (n = 35, 16.4 %) had significantly shorter median TTR (8.3 vs. 17.1 months, p < 0.001) and DSS (42.6 vs. 61.5 months, p < 0.001). CD3lowMHC-Ihi CRLMs were found in 41.2% of recurrent CRLMs in patients without this type of metastasis at first resection. CD3lowMHC-Ihi CRLM was an independent predictor of poor outcomes by multivariate analysis. Conclusions: CD3lowMHChi CRLMs may identify patients with poorly immunogenic tumors associated with worst outcome and suboptimal response to systemic chemotherapy.
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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 | 0.001 | 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".