Location of CD39<sup>+</sup> T cell subpopulations within tumors predict differential outcomes in non-small cell lung cancer
Bibliographic record
Abstract
Purpose An improved mechanistic understanding of immunosuppressive pathways in non-small cell lung cancer (NSCLC) is important to develop novel diagnostic and therapeutic approaches. Here, we investigate the prognostic significance of the ectonucleotidases CD39 and CD73 in NSCLC. Experimental design The expression and localization of CD39, CD73 and CD103 was digitally quantified in a cohort of 162 early treatment naïve NSCLC patients using multiplex-immunofluorescence and related to patient outcome. Expression among different cell-populations was assessed via flow cytometry. Targeted RNA-Seq was performed on CD4+ and CD8+ T cells from digested NSCLC tumor tissue and single-cell RNA-Seq data was analyzed to investigate the functional significance of CD39+ T cell populations. Results We demonstrate that flow cytometry of early untreated NSCLC patients shows an upregulation of CD39 expression in the tumor tissue among natural killer (NK) cells, fibroblasts and T cells. CD73 expression is mainly found among fibroblasts and Epcam+cells in the tumor tissue. Multiplex Immunofluorescence in a cohort of 162 early untreated NSCLC patients demonstrates that CD39 expression is mainly localized in the tumor stroma while CD73 expression is equally distributed between tumor nest and stroma, and high expression of CD39 and CD73 in the tumor stroma is associated with poor recurrence-free survival (RFS) at 5 years. Additionally, we find that CD8+T cells located in the tumor nest express CD103 and the density of CD39+CD103+CD8+ T cells in the tumor nest predicts improved RFS at 5 years. Targeted RNA-Seq shows that the tumor microenvironment of NSCLC upregulates regulatory pathways in CD4+ T cells and exhaustion in CD8+ T cells, and analysis of a single cell RNA sequencing dataset shows that CD39+CD4+ cells are enriched in Treg signature gene-sets, and CD39+CD103+ cytotoxic T lymphocyte show gene signatures indicative of an exhausted cytotoxic phenotype with upregulated expression of CXCL13. Conclusions Knowledge of patterns of distribution and location are required to understand the prognostic impact of CD39+ T cell populations in NSCLC. This study provides an improved understanding of spatial and functional characteristics of CD39+ T cells and their significance to patient outcome.
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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".