Carbohydrate Sulfation As a Mechanism for Fine-Tuning Siglec Ligands
Why this work is in the frame
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Bibliographic record
Abstract
The immunomodulatory family of Siglecs recognizes sialic acid-containing glycans as “self”, which is exploited in cancer for immune evasion. The biochemical nature of Siglec ligands remains incompletely understood, with emerging evidence suggesting the importance of carbohydrate sulfation. Here, we investigate how specific sulfate modifications affect Siglec ligands by overexpressing eight carbohydrate sulfotransferases (CHSTs) in five cell lines. Overexpression of three CHSTs─CHST1, CHST2, or CHST4─significantly enhance the binding of numerous Siglecs. Unexpectedly, two other CHSTs (Gal3ST2 and Gal3ST3) diminish Siglec binding, suggesting a new mode to modulate Siglec ligands via sulfation. Results are cell type dependent, indicating that the context in which sulfated glycans are presented is important. Moreover, a pharmacological blockade of N- and O-glycan maturation reveals a cell-type-specific pattern of importance for either class of glycan. Production of a highly homogeneous Siglec-3 (CD33) fragment enabled a mass-spectrometry-based binding assay to determine ≥8-fold and ≥2-fold enhanced affinity for Neu5Acα2–3(6-O-sulfo)Galβ1–4GlcNAc and Neu5Acα2–3Galβ1–4(6-O-sulfo)GlcNAc, respectively, over Neu5Acα2–3Galβ1–4GlcNAc. CD33 shows significant additivity in affinity (≥28-fold) for the disulfated ligand, Neu5Acα2–3(6-O-sulfo)Galβ1–4(6-O-sulfo)GlcNAc. Moreover, joint overexpression of CHST1 with CHST2 in cells greatly enhanced the binding of CD33 and several other Siglecs. Finally, we reveal that CHST1 is upregulated in numerous cancers, correlating with poorer survival rates and sodium chlorate sensitivity for the binding of Siglecs to cancer cell lines. These results provide new insights into carbohydrate sulfation as a general mechanism for tuning Siglec ligands on cells, including in cancer.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 it