Discovery of a novel monoclonal PD-L1 antibody H1A that promotes T-cell mediated tumor killing activity in renal cell carcinoma
Bibliographic record
Abstract
Abstract In the last decade, the therapeutic landscape of renal cell carcinoma has rapidly evolved with the addition of PD-1/PD-L1 immune checkpoint inhibitors in the armamentarium of oncologists. Despite clinical evidence of improved oncological outcomes, only a minority of patients experience long-lasting antitumor immune response and complete response. The intrinsic and acquired resistance to PD-1/PD-L1 immune checkpoint blockade is an important challenge for patients and clinicians as no reliable tool has been developed to predict individualized response to immunotherapy. In this study, we demonstrate the translational relevance of an ex-vivo functional assay that measure the tumor cell killing ability of patient-derived CD8 T cells isolated from peripheral blood. Cytotoxic activity of CD8 T cells was improved at 3-month post-radical nephrectomy compared to baseline and it was associated with higher circulating levels of tumor-reactive effector CD8 T cells (CD11a high CX3CR1 + GZMB + ). Pretreatment of peripheral immune cells with FDA-approved PD-1/PD-L1 inhibitors enhanced tumor cell killing activity of CD8 T cells but differential response was observed at the individual patient level. Finally, we found a newly developed monoclonal antibody (H1A), which induces PD-L1 degradation, demonstrated superior efficacy in promoting T-cell mediated tumor killing activity compared to FDA-approved PD-1/PD-L1 inhibitors. PBMC immunophenotyping by mass cytometry revealed enrichment of effector CD8 T cells in H1A-treated PBMC. To conclude, our study lays the ground for future investigation of the therapeutic value of H1A as a next-generation immune checkpoint inhibitor. Furthermore, further work is needed to evaluate the potential of measuring T-cell cytotoxicity activity as a tool to predict individual response to immune checkpoint inhibitors in patients with advanced renal cell carcinoma.
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".