MétaCan
Menu
Back to cohort
Record W4399304973 · doi:10.1186/s12967-024-05340-2

Local delivery of accutox® synergises with immune-checkpoint inhibitors at disrupting tumor growth

2024· article· en· W4399304973 on OpenAlexafffund
Jean Pierre Bikorimana, Nehmé El-Hachem, Jamilah Abusarah, Marina Pereira Gonçalves, Roudy Farah, Gabrielle A. Mandl, Sébastien Talbot, Simon Beaudoin, Daniela Stanga, Sebastien Plouffe, Moutih Rafei

Bibliographic record

VenueJournal of Translational Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsQueen's UniversityDefence Research and Development CanadaCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à MontréalUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsCancer researchProgrammed cell deathCancer cellFlow cytometryApoptosisImmune systemCancerCell cycle checkpointCell cycleBiologyTranscriptomeEndosomeCell cultureCellChemistryMolecular biologyImmunologyBiochemistryGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

Abstract Background The Accum ® platform was initially designed to accumulate biomedicines in target cells by inducing endosomal-to-cytosol escape. Interestingly however, the use of unconjugated Accum ® was observed to trigger cell death in a variety of cancer cell lines; a property further exploited in the development of Accum ® -based anti-cancer therapies. Despite the impressive pro-killing abilities of the parent molecule, some cancer cell lines exhibited resistance. This prompted us to test additional Accum ® variants, which led to the identification of the AccuTOX ® molecule. Methods A series of flow-cytometry and cell-based assays were used to assess the pro-killing properties of AccuTOX ® along with its ability to trigger the production of reactive oxygen species (ROS), endosomal breaks and antigen presentation. RNA-seq was also conducted to pinpoint the most prominent processes modulated by AccuTOX ® treatment in EL4 T-cell lymphoma. Finally, the therapeutic potency of intratumorally-injected AccuTOX ® was evaluated in three different murine solid tumor models (EL4, E0771 and B16) both as a monotherapy or in combination with three immune-checkpoint inhibitors (ICI). Results In total, 7 Accum ® variants were screened for their ability to induce complete cell death in 3 murine (EL4, B16 and E0771) and 3 human (MBA-MD-468, A549, and H460) cancer cell lines of different origins. The selected compound (hereafter refereed to as AccuTOX ® ) displayed an improved killing efficiency (~ 5.5 fold compared to the parental Accum ® ), while retaining its ability to trigger immunogenic cell death, ROS production, and endosomal breaks. Moreover, transcriptomic analysis revealed that low dose AccuTOX ® enhances H2-K b cell surface expression as well as antigen presentation in cancer cells. The net outcome culminates in impaired T-cell lymphoma, breast cancer and melanoma growth in vivo especially when combined with anti-CD47, anti-CTLA-4 or anti-PD-1 depending on the animal model. Conclusions AccuTOX ® exhibits enhanced cancer killing properties, retains all the innate characteristics displayed by the parental Accum ® molecule, and synergizes with various ICI in controlling tumor growth. These observations will certainly pave the path to continue the clinical development of this lead compound against multiple solid tumor indications. Graphical Abstract

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.310
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Translational MedicineSame topicCAR-T cell therapy researchFrench-language works237,207