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
BACKGROUND: Over the past decade, cancer immunotherapies have revolutionized the treatment of melanoma; however, responses vary across patient populations. Recently, baseline tumor size has been identified as an independent prognostic factor for overall survival in patients with melanoma receiving immune checkpoint inhibitors. MG1 is a novel oncolytic agent with broad tumor tropism that has recently entered early-phase clinical trials. The aim of this study was to characterize T-cell responses in human and mouse melanoma models following MG1 treatment and to establish if features of the tumor immune microenvironment (TIME) at two distinct tumor burdens would impact the efficacy of oncolytic virotherapy. METHODS: Human three-dimensional in vitro priming assays were performed to measure antitumor and antiviral T-cell responses following MG1 infection. T-cell receptor (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 characterized using RNA sequencing, immunohistochemistry, and flow cytometry. The effectiveness of intratumoral MG1 was assessed in advancing 4434 tumors and the generation of antitumor and antiviral T cells measured by splenocyte recall assays. Finally, combination MG1 and programmed cell death protein-1 antibody (αPD-1) therapy was investigated in advanced 4434 tumors. RESULTS: MG1 effectively supported priming of functional cytotoxic T cells (CTLs) against tumor-associated antigens 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 with 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 tumor size) increased, and the addition of αPD-1 was required to overcome resistance in more advanced disease. Differential gene expression profiles revealed that increased tumor burden was associated with an immunologically colder TIME. Furthermore, analysis of TCR signaling in advancing tumors demonstrated a different dynamic of TCR engagement compared with smaller tumors, in particular a shift in antigen recognition by CD4+ cells, from conventional to regulatory subsets. CONCLUSION: Addition of αPD-1 to MG1 is required to overcome viral therapy resistance in immunologically 'colder' more advanced melanoma, highlighting the importance of tumor burden to different types of immunotherapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".