Cancer cell expressions of immunoglobulin heavy chains with unique carbohydrate-associated biomarker
Bibliographic record
Abstract
OC-3-VGH ovarian cancer cell line and numerous others from different human tissue origins were studied for their respective expressions of immunoglobulins as well as carbohydrate-associated epitope(s) recognized by RP215 monoclonal antibody. With no exceptions, all the cancer cell lines studied so far express human immunoglobulin G (IgG) heavy chains when determined by Western blot or nested RT-PCR with appropriate primers in the constant region. By Western blot assay, it was also shown that greater than 90% of cancer cell lines expressed RP215-specific epitope(s) on the detected heavy chain molecules. Further studies with OC-3-VGH cancer cells revealed the expressions of all immunoglobulin classes, subclasses, heavy as well as light chains. The primary structure of the IgG heavy chains expressed by single cloned cells of this cancer cell line was elucidated. It was shown to be homologous to that of normal human IgG1 heavy chain derived from B cells, except with high content of serine/threonine residues in the variable region. Expressions of other immunoglobulin-related genes were also detected. Widespread expressions of immunoglobulin heavy chains among cancer cells as well as the frequent presence of unique carbohydrate-associated epitope(s) recognized by RP215 monoclonal antibody might have important biological implications during carcinogenesis and applications in immunodiagnostics and antibody-based anti-cancer drug developments.
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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 | 0.001 |
| 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".