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Record W3149633952 · doi:10.1038/s41419-021-03611-0

Development of a bispecific immune engager using a recombinant malaria protein

2021· article· en· W3149633952 on OpenAlexaff
Mie A. Nordmaj, Morgan E. Roberts, Emilie S. Sachse, Robert Dagil, Anne Poder Andersen, Nanna Skeltved, Kaare V. Grunddal, Sayit Mahmut Erdoğan, Swati Choudhary, Tobias Gustsavsson, Maj Sofie Ørum-Madsen, Igor Moskalev, Weihua Tian, Zhang Yang, Thomas Mandel Clausen, Thor G. Theander, Mads Daugaard, Morten A. Nielsen, Ali Salanti

Bibliographic record

VenueCell Death and Disease · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsUniversity of British Columbia
FundersGangstedfondenKirsten og Freddy Johansens FondAase og Ejnar Danielsens FondDanmarks GrundforskningsfondNational Research FoundationSvend Andersen FondenKræftens Bekæmpelse
KeywordsRecombinant DNAMalariaImmune systemVirologyBiologyImmunologyCancer researchBiochemistryGene

Abstract

fetched live from OpenAlex

As an immune evasion and survival strategy, the Plasmodium falciparum malaria parasite has evolved a protein named VAR2CSA. This protein mediates sequestration of infected red blood cells in the placenta through the interaction with a unique carbohydrate abundantly and exclusively present in the placenta. Cancer cells were found to share the same expression of this distinct carbohydrate, termed oncofetal chondroitin sulfate on their surface. In this study we have used a protein conjugation system to produce a bispecific immune engager, V-aCD3, based on recombinant VAR2CSA as the cancer targeting moiety and an anti-CD3 single-chain variable fragment linked to a single-chain Fc as the immune engager. Conjugation of these two proteins resulted in a single functional moiety that induced immune mediated killing of a broad range of cancer cells in vitro and facilitated tumor arrest in an orthotopic bladder cancer xenograft model.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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 teacher head, 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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

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