ArticleOncotarget2019
PD-L1 checkpoint blockade delivered by retroviral replicating vector confers anti-tumor efficacy in murine tumor models.
Article in Oncotarget, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Anti-PD-1 single-chain variable fragments in cancer immunotherapy: from molecular engineering to clinical translation.Cancer chemotherapy and pharmacology · 2026Review
- Systemic Checkpoint Blockade by PD-L1 Single-Chain Antibody Confers Potent Antitumor Immunity and Long-term Survival.Molecular cancer therapeutics · 2022Article
- Formatting and gene-based delivery of a human PD-L1 single domain antibody for immune checkpoint blockade.Molecular therapy. Methods & clinical development · 2021Article
- Clinical development of retroviral replicating vector Toca 511 for gene therapy of cancer.Expert opinion on biological therapy · 2021Review
- Historic Overview of Genetic Engineering Technologies for Human Gene Therapy.Neurologia medico-chirurgica · 2020Review
- Introduction to immunotherapy for brain tumor patients: challenges and future perspectives.Neuro-oncology practice · 2020Review
- Review
- Novel Delivery Systems for Checkpoint Inhibitors.Medicines (Basel, Switzerland) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune checkpoint inhibitors (CPIs) are associated with a number of immune-related adverse events and low response rates. We provide preclinical evidence for use of a retroviral replicating vector (RRV) selective to cancer cells, to deliver CPI agents that may circumvent such issues and increase efficacy. An RRV, RRV-scFv-PDL1, encoding a secreted single chain variable fragment targeting PD-L1 can effectively compete with PD-1 for PD-L1 occupancy. Cell binding assays showed trans-binding activity on 100% of cells in culture when infection was limited to 5% RRV-scFv-PDL1 infected tumor cells. Further, the ability of scFv PD-L1 to rescue PD-1/PD-L1 mediated immune suppression was demonstrated in a co-culture system consisting of human-derived immune cells and further demonstrated in several syngeneic mouse models including an intracranial tumor model. These tumor models showed that tumors infected with RRV-scFv-PD-L1 conferred robust and durable immune-mediated anti-tumor activity comparable or superior to systemically administered anti-PD-1 or anti PD-L1 monoclonal antibodies. Importantly, the nominal level of scFv-PD-L1 detected in serum is ∼50-150 fold less than reported for systemically administered therapeutic antibodies targeting immune checkpoints. These results support the concept that RRV-scFv-PDL1 CPI strategy may provide an improved safety and efficacy profile compared to systemic monoclonal antibodies of currently approved therapies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.