Tumor‐associated antigen 90K/Mac‐2‐binding protein: Possible role in colon cancer
Bibliographic record
Abstract
The tumor-associated antigen 90K (TAA90K)/Mac-2-binding protein implicated in cancer progression and metastasis is modified by beta1-6 branched N-linked oligosaccharides in colon cancer cells, glycans shown to contribute to cancer metastasis. To elucidate the role of TAA90K in colon cancer, we examined its expression and function in human colon tumors and colon carcinoma cell lines. Immunohistochemical analyses of colon tumors revealed elevated expression of TAA90K in all samples analyzed compared to normal colon. To examine the function of TAA90K in colon cancer, we carried out protein and cell binding assays using TAA90K-His purified from HT-29 cells colon carcinoma cells infected with recombinant vaccinia virus expressing TAA90K containing a C-terminal poly-histidine tag. TAA90K-His bound to fibronectin, collagen IV, laminins-1, -5, and -10 and galectin-3 (Mac-2) but poorly to collagen I and galectin-1. As expected, binding of TAA90K to galectin-3 was dependent on carbohydrate since it was inhibitable by lactose and asiolofetuin, and a TAA90K-His glycoform purified from HT-29 cells treated with the glycosylation inhibitor 1-deoxymannojirimycin bound poorly to galectin-3. Unlike TAA90K isolated from other cell types, TAA90K-His isolated from colon cancer cells failed to mediate adhesion of colon cancer and normal cell lines, possibly due to cell-type specific glycosylation of TAA90K-His and/or its putative cellular receptor. However, at low concentrations, TAA90K-His enhanced galectin-3-mediated HT-29 cell adhesion while at high concentrations, it inhibited cell adhesion. Thus, a possible mechanism by which TAA90K may contribute to colon cancer progression is by modulating tumor cell adhesion to extracellular proteins, including galectin-3.
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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".