Quantitative multiplex immunofluorescence (qmIF) and genomic evaluation of tumor microenvironment (TME) to identify candidate biomarkers in stage II/III melanoma.
Bibliographic record
Abstract
9580 Background: Biomarkers are needed to risk stratify for adjuvant trials in early stage melanoma. Features of the immune infiltrate within the TME are hypothesized to be prognostic, but quantification methods are not standardized for clinical practice. Expression profiling of stage II/III melanoma shows that Th1 genes have prognostic value. Combination of genomic and qmIF analyses of the TME may identify prognostic immune biomarkers. Methods: We performed qmIF analysis on 104 primary melanoma tumors (stage II-III) diagnosed at Columbia University Medical Center from 2000-2012. Tissue was stained for DAPI (nuclei), CD3 (T cell), CD8 (cytotoxic T cell (CTL)), CD68 (Mj), SOX10 (tumor), HLA-DR (activation) and Ki67 (proliferation). Phenotyping was performed with inForm software. High/low density cut-offs were defined by Classification and Regression Tree Analysis (CART) and Receiver Operating Characteristic (ROC) curves. For 64 patients (pts), with known of cause of death, KM curves were calculated. mRNA expression analysis for 63 immune genes (NanoString) was performed on 44 of 64 pts for whom sufficient tissue was available. Results: On qmIF, we find that high CTL and low Mj infiltration, particularly when located in the stroma, correlates with disease specific survival (DSS) (p = 0.004 and p < 0.001, respectively). Of greatest significance, when combined, low stromal CTL/Mj ratio correlates with death from melanoma using ROC (AUC = 0.724, p = 0.026). By AUC cutoff, low CTL/Mj ratio predicts poor DSS (p = 0.003) and overall survival (OS) (p = 0.008). On multivariable cox analysis, low CTL/Mj was independently associated with DSS (p = 0.002) and OS (p = 0.020). Genomic analysis identified increased expression of CXCL9, CXCR3, CCL5 and CD37 in non-recurrent pts (p < 0.050 after bonferoni correction) which did not correlate with CTL/Mj ratio. Conclusions: Multiparameter phenotyping of stage II/III melanoma pts shows that stromal CTL/Mj ratio strongly correlates with survival. mRNA analysis shows that high Th1 gene expression correlates with non-recurrence. Combination of qmIF and mRNA analysis may be useful in stratifying pts to receive immunotherapy.
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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 | 0.001 |
| 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) | 0.001 | 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".