Protein Paucimannosylation Is an Enriched <i>N</i> ‐Glycosylation Signature of Human Cancers
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Bibliographic record
Abstract
Abstract While aberrant protein glycosylation is a recognized characteristic of human cancers, advances in glycoanalytics continue to discover new associations between glycoproteins and tumorigenesis. This glycomics‐centric study investigates a possible link between protein paucimannosylation, an under‐studied class of human N ‐glycosylation [Man 1‐3 GlcNAc 2 Fuc 0‐1 ], and cancer. The paucimannosidic glycans (PMGs) of 34 cancer cell lines and 133 tissue samples spanning 11 cancer types and matching non‐cancerous specimens are profiled from 467 published and unpublished PGC‐LC‐MS/MS N ‐glycome datasets collected over a decade. PMGs, particularly Man 2‐3 GlcNAc 2 Fuc 1 , are prominent features of 29 cancer cell lines, but the PMG level varies dramatically across and within the cancer types (1.0–50.2%). Analyses of paired (tumor/non‐tumor) and stage‐stratified tissues demonstrate that PMGs are significantly enriched in tumor tissues from several cancer types including liver cancer ( p = 0.0033) and colorectal cancer ( p = 0.0017) and is elevated as a result of prostate cancer and chronic lymphocytic leukaemia progression ( p < 0.05). Surface expression of paucimannosidic epitopes is demonstrated on human glioblastoma cells using immunofluorescence while biosynthetic involvement of N ‐acetyl‐β‐hexosaminidase is indicated by quantitative proteomics. This intriguing association between protein paucimannosylation and human cancers warrants further exploration to detail the biosynthesis, cellular location(s), protein carriers, and functions of paucimannosylation in tumorigenesis and metastasis.
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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 | 0.000 |
| 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) | 0.000 | 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