Recognition of Dimeric Lewis X by Anti-Dimeric Lex Antibody SH2
Bibliographic record
Abstract
The carbohydrate antigen dimeric Lewis X (DimLex), which accumulates in colonic and liver adenocarcinomas, is a valuable target to develop anti-cancer therapeutics. Using the native DimLex antigen as a vaccine would elicit an autoimmune response against the Lex antigen found on normal, healthy cells. Thus, we aim to study the immunogenic potential of DimLex and search internal epitopes displayed by DimLex that remain to be recognized by anti-DimLex monoclonal antibodies (mAbs) but no longer possess epitopes recognized by anti-Lex mAbs. In this context, we attempted to map the epitope recognized by anti-DimLex mAb SH2 by titrations and competitive inhibition experiments using oligosaccharide fragments of DimLex as well as Lex analogues. We compare our results with that reported for anti-Lex mAb SH1 and anti-polymeric Lex mAbs 1G5F6 and 291-2G3-A. While SH1 recognizes an epitope localized to the non-reducing end Lex trisaccharide, SH2, 1G5F6, and 291-2G3-A have greater affinity for DimLex conjugates than for Lex conjugates. We show, however, that the Lex trisaccharide is still an important recognition element for SH2, which (like 1G5F6 and 291-2G3-A) makes contacts with all three sugar units of Lex. In contrast to mAb SH1, anti-polymeric Lex mAbs make contact with the GlcNAc acetamido group, suggesting that epitopes extend further from the non-reducing end Lex. Results with SH2 show that this epitope is only recognized when DimLex is presented by glycoconjugates. We have reported that DimLex adopts two conformations around the β-d-GlcNAc-(1→3)-d-Gal bond connecting the Lex trisaccharides. We propose that only one of these conformations is recognized by SH2 and that this conformation is favored when the hexasaccharide is presented as part of a glycoconjugate such as DimLex-bovine serum albumin (DimLex-BSA). Proper presentation of the oligosaccharide candidate via conjugation to a protein or lipid is essential for the design of an anti-cancer vaccine or immunotherapeutic based on DimLex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".