Roles of antigen receptors and CA215 in the innate immunity of cancer cells
Bibliographic record
Abstract
Antigen receptors, including immunoglobulins and T-cell receptors, are known to be widely expressed by cancer cells through unconfirmed mechanisms and for unknown purposes. Recently, a monoclonal antibody, designated as RP215, was generated against the ovarian cancer cell line, OC-3-VGH, and was shown to react with CA215, which consisted mainly of these cancer cell-expressed antigen receptors. Experimental evidence has clearly indicated that cancerous immunoglobulins play significant roles in the growth and proliferation of cancer cells in vitro and in vivo. RP215 and anti-antigen receptor antibodies were equally effective in inducing apoptosis and complement-dependent cytotoxicity reactions to cultured cancer cells. Through gene regulation studies, both RP215 and antibodies against antigen-receptors were shown to affect more than a dozen of genes involved in cell proliferation (such as NFκB-1, IgG, P21, cyclin D1, ribosomal P1, and c-fos). Furthermore, selected toll-like receptor genes (TLR- 2, -3, -4, and -9) were also found to be highly regulated by both RP215 and anti-antigen receptor antibodies. For example, RP215 and anti-antigen receptor antibodies were found to both up-regulate TLR-2 and/or TLR-3 and down- regulate TLR-4 and TLR-9 intwo types of cancer cells. Based on these studies, it is reasonable to postulate that cancerous immunoglobulins play important roles in the modulation of the innate immune system to allow the growth and survival of cancer cells within the human body. Consequently, RP215 inits humanized forms may be utilized to target cancer cells for potential therapeutic purposes.
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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 | 0.001 | 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".