Extent of N-glycosylation of the metalloproteinase inhibitor and cytokine TIMP-1 determines pancreatic cancer cell proliferation and survival via CD63
Bibliographic record
Abstract
Glycosylation emerges as a critical determinant of protein function in cancer, yet its impact on multifunctional secreted factors remains understudied. Here, we identified tissue inhibitor of metalloproteinases-1 (TIMP-1), a glycoprotein with glycosylation sites at N30 and N78 harboring both a canonical anti-proteolytic and non-canonical cytokine-like activity, as one of the most-upregulated secreted glycoproteins circulating in the blood of pancreatic cancer (PC) patients. Whereas plasma from healthy donors contained similar amounts of double- (TIMP-1 glyc1/1 ), single-(N78 and not N30) (TIMP-1 glyc0/1 ), and non-glycosylated (TIMP-1 glyc0/0 ) TIMP-1, TIMP-1 glyc1/1 predominated in plasma from PC patients. scRNAseq and in vitro validation linked this shift to tumor progression-associated upregulation of the oligosaccharyltransferase (OST)-complex in epithelial cells. In human PC cell lines, OST complex activity was critical for synthesis of TIMP-1 glyc1/1 . Importantly, tumor cell-survival and proliferation-promoting activity via CD63 were dependent on TIMP-1 glycosylation, which required N30-glycosylation. In contrast, glycosylation was not necessary for the anti-proteolytic activity of TIMP-1 towards different matrix metalloproteinases (MMPs) (collagenases MMP-1, MMP-8; gelatinases MMP-2, MMP-9; stromelysin MMP-3; Matrilysin MMP-7) but modulated the respective inhibitory efficacy. Analysis of a published glycoproteome data set, allowing assessment of individual glycosylation site occupancy in TIMP-1, revealed that N30 site occupation correlated with poor survival, while N78 site occupation showed no prognostic value, corroborating the impact of double-glycosylation of TIMP-1, as observed in patients, on tumor-promotion. The glycosylation-dependent modulation of the multifunctionality of tumor-secreted TIMP-1 thus provide a molecular basis for its long-debated cancer-promoting role. Finally, it exemplifies the impact of glycosylation macroheterogeneity on disease-relevant modulation of protein function.
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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) | 0.001 | 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".