Immunotherapy against colorectal cancer via delivery of anti-PD-L1 nanobody mRNA
Bibliographic record
Abstract
Background Monoclonal antibodies (mAbs) targeting immune checkpoint molecules such as programmed death ligand 1 (PD-L1), which is expressed in both immune and tumour cells, are conventional immunotherapy approaches. Although approved as monotherapy for the first-line treatment of several cancers, mAbs targeting PD-L1 have shown limited efficacy in colorectal cancer (CRC). Here, we investigated if nucleic acids translated into anti-PD-L1 nanobodies (PDL1Nbs) effectively suppress CRC tumourigenesis in mouse models. Methods Mice were transplanted with MC-38 mouse sporadic CRC (sCRC) cells or challenged with azoxymethane and dextran sodium sulfate, a combination treatment that induces colitis-associated CRC (CAC). The tumour-bearing mice were treated with a PDL1Nb-encoding plasmid DNA (pDNA) delivered via polymers, or treated with PDL1Nb-encoding nucleoside-modified messenger RNA (PDL1Nb mRNA) delivered via lipid nanoparticles (LNP). Moreover, bone marrow haematopoietic stem cells (BMHSCs) were differentiated and maturated by treating growth factors in the presence of PDL1Nb mRNA-LNP or control luciferase mRNA-LNP with/without lipopolysaccharide. We examined sCRC tumour proliferation and growth, CAC tumour incidences and numbers, tumour infiltration of immune cells and bone marrow-derived macrophages (BMDMs). Results Polymer delivery of PDL1Nb pDNA efficiently repressed sCRC progression in tumour-bearing mice. Intriguingly, LNP delivery of the quadruple PDL1Nb (qPDL1Nb) mRNA showed a greater efficacy than the delivery of the monomeric PDL1Nb (mPDL1Nb) mRNA in suppressing sCRC tumour progression. Moreover, qPDL1Nb mRNA-LNP treatment significantly reduced CAC incidence. Mechanistically, PD-L1 blockade by qPDL1Nb resulted in marked decreases in tumour-infiltrating myeloid-derived suppressor cells and tumour-associated macrophages, as well as expression of PD-L1, but increases in tumour-infiltrating CD3 + CD8 + cells during CAC tumourigenesis . Notably , in vitro LNP delivery of PDL1Nb mRNA into BMHSCs significantly inhibited their differentiation and maturation into BMDMs and strikingly reduced the expression of PD-L1, CD80, CD86 and CD206 in BMDMs. Conclusion These results suggest that the PDL1Nb therapy is effective for both CAC and sCRC and using qPDL1Nb mRNA-LNP is a promising alternative strategy for CRC immunotherapy.
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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".