Lack of stem-like exhausted T cells and increased inhibitory receptor expression distinguishes diffuse large B cell lymphomas from Hodgkin lymphoma
Bibliographic record
Abstract
Abstract Immune checkpoint (IC) blockade has revolutionized the treatment of chemo-refractory solid tumors and has demonstrated promising results for the treatment of resistant blood cancers, including lymphoma. However, clinical response to PD1 blockade depends on the subtype of lymphoma, with durable responses observed in 70 % of Hodgkin lymphoma (HL) versus only 10 to 40% of Diffuse Large B-Cell Lymphoma (DLBCL) and Follicular Lymphoma (FL). The biological aspects that hinder the efficacy of immunotherapy in DLBCL and FL are not well-known. Since DLBCL and FL are more refractory to IC therapy than HL, we hypothesized that TILs from DLBCL and FL present a more advanced state of exhaustion than TILs from HL. We performed an immunophenotyping of TILs from 57 HL, FL or DLBCL lymphoma samples collected at diagnosis and frozen as viable cell suspension. Our data revealed that CD8 TILs from DLBCL express higher levels of ICs (PD1, Tim3 and Lag3) compared to TILs from FL and HL. Boolean analysis demonstrated that DLBCL and FL had a higher frequency of CD8T cells that co-expressed 6–7 ICs, compared to HL, suggesting more advanced exhaustion. In contrast, we observed that HL and FL exhibited significantly more stem-like exhausted cells (PD1+/Tim3−/CD38−/TCF1+) compared to DLBCL. Stem-like exhausted CD8 T cells are driven by the transcription factor TCF-1 and extensively proliferate in response to PD1 blockade. Collectively, our data indicate that TILs from DLBCL and FL express a whole array of ICs. DLBCL further lack protective stem-like CD8 T-cell subsets which correlate with poor clinical outcome. These results strengthen our understanding of the cellular defects precluding potent anti-tumor T cell functions in DLBCL and FL.
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".