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Record W4224229447 · doi:10.26685/urncst.340

Efficacy of Different Immunological Approaches Targeting CD22 for the Treatment of Relapsed or Refractory Acute Lymphoblastic Leukemia: A Research Protocol

2022· article· en· W4224229447 on OpenAlexaff
Vitoria M Olyntho, Cheryl Xing, Erica Zeng

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsWestern UniversityMcMaster University
Fundersnot available
KeywordsCD22Monoclonal antibodyAntibodyImmunologyCancer researchRefractory (planetary science)MedicinePharmacologyBiology

Abstract

fetched live from OpenAlex

Introduction: Monoclonal antibodies (mAbs) have emerged as a promising immune-oncological approach to target cancer cells. mAbs have been seen to outperform traditional drug treatments in treating severe cancers despite their low relative cytotoxicity due to their high selectivity. CD22 is expressed in 60-90% of individuals with B-cell Acute Lymphoblastic Leukemia (B-ALL), and is rapidly internalized when bound to an antibody, making it an effective point of entry for cytotoxic agents. Epratuzumab is an anti-CD22 mAb, effective against B-ALL. Epratuzumab-SN-38 (Emab-SN-38) and Inotuzumab ozogamicin (InO) are promising anti-CD22 Antibody-Drug Conjugates (ADCs). Methods: Epratuzumab, Inotuzumab, and Emab-SN38 treatments will be evaluated in vitro and in vivo. B lymphocytes collected from a 30-35-year-old R/R ALL patient will be purified and expanded. A cell culture assay will evaluate the treatments. Cells will be engrafted into humanized mice. Mice will be assorted into four treatment groups: saline (control), Epratuzumab, Inotuzumab, and Emab-SN-38. Quantitative flow cytometric analysis will be used to assess treatment effectiveness. Complete Response will be determined as ≅ zero human leukemic cells, Partial Response as ≤5% cells, and Remission as >5% cells or with identifiable clinical signs. Mice will be followed for 6 months after the last dose of treatment to assess for relapse and survival rate. Results: It is expected that all three treatments will result in more significant results regarding tumour shrinkage and rate of cancer growth than saline. The ADCs are expected to perform better than unconjugated Epratuzumab. Relapse and Adverse Event rates are expected to be lowest in Epratuzumab-SN-38. Discussion: The comparison of the effectiveness of these treatments are expected to establish Emab-SN-38 as a potential treatment option and propel research into other cytotoxic agents which could be used in conjugation with Epratuzumab and other mAbs. Conclusion: ADCs combine the cytotoxicity of chemotherapy and the specificity of mAbs to treat R/R ALL. The ADCs are expected to outperform Epratuzumab in decreasing leukemic cell load given their potent targeted cytotoxicity. Emab-SN-38 is expected to be less toxic but as effective as Inotuzumab. These results could inform research on safer and more potent ADCs in treating R/R ALL via CD22.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.137
GPT teacher head0.442
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreProtocol

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
Published2022
Admission routes1
Has abstractyes

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