Combination of oncolytic Maraba virus with immune checkpoint blockade overcomes therapy resistance in an immunologically cold model of advanced melanoma with dysfunctional T cell receptor signalling
Bibliographic record
Abstract
Abstract Background Over the past decade, cancer immunotherapies have revolutionised the treatment of melanoma; however, responses vary across patient populations. Recently, baseline tumour size has been identified as an independent prognostic factor for overall survival in melanoma patients receiving immune checkpoint inhibitors (ICIs). MG1 is a novel oncolytic agent with broad tumour tropism that has recently entered early phase clinical trials. The aim of this study was to characterise T cell responses in human and mouse melanoma models following MG1 treatment and to establish if features of the tumour immune microenvironment (TIME) at two distinct tumour burdens would impact the efficacy of oncolytic virotherapy. Methods Human 3D in vitro priming assays were performed to measure anti-tumour and anti-viral T cell responses following MG1 infection. TCR sequencing, T2 killing assay, and peptide recall assays were used to assess the evolution of the TCR repertoire, and measure specific T cell responses, respectively. In vivo , subcutaneous 4434 melanomas were characterised using RNAseq, immunohistochemistry (IHC), and flow cytometry. The effectiveness of intra-tumoural MG1 was assessed in advancing 4434 tumours and the generation of anti-tumour and anti-viral T cells measured by splenocyte recall assays. Finally, combination MG1 and α-PD-1 therapy was investigated in advanced 4434 tumours. Results MG1 effectively primed functional cytotoxic T cells (CTLs) against tumour associated antigens (TAA) as well as virus-derived peptides, as assessed using peptide recall and T2 killing assays, respectively. TCR sequencing revealed that MG1-primed CTL comprised larger clusters of similar CDR3 amino acid sequences compared to controls. In vivo testing of MG1 demonstrated that MG1 monotherapy was highly effective at treating early disease, resulting in 90% cures; however, the efficacy of MG1 reduced as the disease burden (local tumour size) increased, and the addition of α-PD-1 was required to overcome resistance in more advanced disease. Differential gene expression profiles revealed that increased tumour burden was associated with an immunologically colder TIME. Furthermore, analysis of TCR signalling in advancing tumours demonstrated a different dynamic of TCR engagement compared to smaller tumours, in particular a shift in antigen recognition by CD4+ cells, from conventional to regulatory subset. Conclusion Combination of MG1 with αPD-1 overcomes therapy resistance in an immunologically ‘cold’ model of advanced melanoma.
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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 | 0.001 |
| 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".