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Mesenchymal Stem Cells Engineered to Inhibit Complement-Mediated Damage

2012· article· en· W2567252082 on OpenAlexaff
Melisa Soland, Mariana G. Bego, Evan Colletti, Christopher D. Porada, Esmail D. Zanjani, Stephen St. Jeor, Graça Almeida‐Porada

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsMesenchymal stem cellCD59CD46Complement systemTransplantationBiologyStem cellCell biologyAnaphylatoxinImmune systemMolecular biologyChemistryImmunologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Abstract 1253 Mesenchymal stem cells (MSC) preferentially migrate to damaged tissues and, due to their immunomodulatory and trophic properties, contribute to tissue repair. Although MSC express low levels of molecules, such as CD59, which confer protection from complement-mediated lysis, MSC are recruited and activated by anaphylatoxins after transplantation, potentially causing MSC death and limiting therapeutic benefit. It has been demonstrated that transduction of MSC with a retrovirus encoding HCMV US proteins resulted in higher levels of MSC engraftment and diminished recognition by the immune system, due to a decrease in HLA-I expression. Here we investigate whether engineering MSC to express US2, US3, US6, or US11 HCMV proteins can alter complement recognition, and thereby protect MSC from complement attack and lysis. US HCMV proteins increased MSC CD59 expression to differing degrees, as determined by flow cytometric evaluation of the median fluorescence intensity ratio (MFI) (n=3). CD59 MFI on untransduced MSC was 128±33, and this value remained largely unchanged on MSC transduced with an empty retroviral vector (MSC-E) and on MSC transduced with US11 (MSC-11). In contrast, a significant increase in CD59 MFI was seen in MSC transduced with US2 (MSC-2), US3 (MSC-3), and US6 (MSC-6), with MFIs of 273±35 (p<0.05), 319±64 (p<0.05), and 265±16 (p<0.05), respectively. Although overexpression of HCMV proteins on MSC did not change the MFI for membrane cofactor protein (CD46) and complement decay accelerating factor (CD55), it significantly altered the percentage of MSC that expressed these two complement-protective proteins (n=3). Specifically, while no statistically significant difference was seen in the percentage of MSC-E, MSC-6, or MSC-11 expressing CD46 (17.9±1%, 19±0.1%, 21.3±1.4%, respectively), 27.7±0.7% of MSC-3 (p<0.05) and 27.7±1.6% of MSC-2 (p<0.05) expressed CD46. Similarly, while comparable percentages of MSC, MSC-E, and MSC-3 expressed CD55 (37.8±3%, 42.8±1%, and 45.2±1, respectively), the overexpression of HCMV US2, US6, and US11 each led to a significant increase in the percentage of MSC expressing CD55 (MSC-2: 49±1% (p<0.05); MSC-6: 56±0.6% (p<0.05); MSC-11: 60±1.3% (p<0.05)). Because the HCMV US2 protein was the most efficient at up-regulating all three complement regulatory proteins, we used two different complement-mediated cytotoxicity assays to investigate whether MSC-2 were protected from complement-mediated lysis. We demonstrated that over-expression of the US2 protein reduced complement lysis of MSC-2 by 59.10±12.89 % when compared to untransduced MSC. This is the first report, to our knowledge, describing a role of HCMV US proteins in complement evasion, and our results demonstrate that over-expression of HCMV US proteins on MSC could serve as a strategy to generate cells protected from complement lysis. Disclosures: No relevant conflicts of interest to declare.

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 score0.004

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 head0.043
GPT teacher head0.296
Teacher spread0.254 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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