Human double negative T cells target lung cancer via ligand-dependent mechanisms that can be enhanced by IL-15
Bibliographic record
Abstract
<h3>Background</h3> The advents of novel immunotherapies have revolutionized the treatment of cancer. Adoptive cellular therapies using chimeric antigen receptor T (CAR-T) cells have achieved remarkable clinical responses in B cell leukemia and lymphoma but the effect on solid tumors including lung cancer is limited. Here we present data on the therapeutic potential of allogeneic CD3<sup>+</sup>CD4<sup>−</sup>CD8<sup>−</sup> double negative T (DNT) cells as a new cellular therapy for the treatment of lung cancer and underlying mechanisms. <h3>Methods</h3> DNTs were enriched and expanded ex vivo from healthy donors and phenotyped by flow cytometry. Functionally, their cytotoxicity was determined against primary and established non-small-cell lung cancer (NSCLC) cell lines in vitro or through in vivo adoptive transfer into xenograft models. Mechanistic analysis was performed using blocking antibodies against various cell surface and soluble markers. Furthermore, the role of IL-15 on DNT function was determined. <h3>Results</h3> We demonstrated that ex vivo expanded DNTs can effectively lyse various human NSCLC cells in vitro and inhibit tumor growth in xenograft models. Expanded DNTs have a cytotoxic phenotype, as they express NKp30, NKG2D, DNAM-1, membrane TRAIL (mTRAIL), perforin and granzyme B, and secrete IFNγ and soluble TRAIL (sTRAIL). DNT-mediated cytotoxicity was dependent on a combination of tumor-expressed ligands for NKG2D, DNAM-1, NKp30 and/or receptors for TRAIL, which differ among different NSCLC cell lines. Furthermore, stimulation of DNTs with IL-15 increased expression of effector molecules on DNTs, their TRAIL production and cytotoxicity against NSCLC in vitro and in vivo. <h3>Conclusion</h3> Healthy donor-derived DNTs can target NSCLC in vitro and in vivo<i>.</i> DNTs recognize tumors via innate receptors which can be up-regulated by IL-15. DNTs have the potential to be used as a novel adoptive cell therapy for lung cancer either alone or in combination with IL-15.
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) | 0.001 | 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".