N-Glycomic Changes in Human Breast Carcinoma MCF-7 and T-Lymphoblastoid Cells After Treatment with Herceptin and Herceptin/Lipoplex
Bibliographic record
Abstract
The humanized monoclonal antibody IgG1 in combination with chemotherapy has been demonstrated to enhance survival benefit in cancer treatment. Despite positive outcomes, some cancer cells develop multidrug resistance. Numerous mechanisms in cancers can be involved in the process of treatment therapy and most of them are not still well understood. To address how the carbohydrate moieties of cells are affected during treatment, the glycan profiles from the two most common cancer cell lines - human breast MCF-7 carcinoma and T-lymphoblastoid CEM cells - were studied here and compared with profiles after treatment with Herceptin alone or in combination with Lipofectamine mixed with plasmid DNA to form Lipoplex. N-Glycans were released from total cells by digestion with PNGaseF and analyzed by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). In summary, both original cell lines showed a dominant occurrence of high-mannose glycans. After treatment, these structures were suppressed and biantennary core-fucosylated glycans originating from IgG1 were the major carbohydrate products identified in cells. The high incidence of additional fucosylated or nonfucosylated galactosylated oligosaccharides, which were not detected in original cells or Herceptin, varied with conditions and time of exposure of cells to the antibody. The results presented in this study provide strong evidence for a role of glycosylation during antibody treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".