CD4+ T cells in classical Hodgkin lymphoma express exhaustion associated transcription factors TOX and TOX2
Bibliographic record
Abstract
In classical Hodgkin lymphoma (cHL), the highly abundant CD4+ T cells in the vicinity of tumor cells are considered essential for tumor cell survival, but are ill-defined. Although they are activated, they consistently lack expression of activation marker CD26. In this study, we compared sorted CD4+CD26- and CD4+CD26+ T cells from cHL lymph node cell suspensions by RNA sequencing and T cell receptor variable gene segment usage analysis. This revealed that although CD4+CD26- T cells are antigen experienced, they have not clonally expanded. This may well be explained by the expression of exhaustion associated transcription factors TOX and TOX2, immune checkpoints PDCD1 and CD200, and chemokine CXCL13, which were amongst the 100 significantly enriched genes in comparison with the CD4+CD26+ T cells. Findings were validated in single-cell RNA sequencing data from an independent cohort. Interestingly, immunohistochemistry revealed predominant and high frequency of staining for TOX and TOX2 in the T cells attached to the tumor cells. In conclusion, the dominant CD4+CD26- T cell population in cHL is antigen experienced, polyclonal, and exhausted. This population is likely a main contributor to the very high response rates to immune checkpoint inhibitors in cHL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".