Positive identification of CA215 pan cancer biomarker from serum specimens of cancer patients
Bibliographic record
Abstract
BACKGROUND: To evaluate the clinical utility of CA215 as a pan cancer biomarker, serum levels of CA215 were determined with clinically defined serum specimens from over 500 cancer patients and compared with results obtained by other nine established cancer markers. The molecular nature of this cancer-associated antigen from selected patients' sera was determined. METHODS: By using improved immunoassays, serum levels of CA215 and other known biomarkers were determined for respective positive detection rates. The molecular size of CA215 from cancer patients was determined by Western blot assay. RESULTS: By using 0.1 AU/ml as the normal cut-off value, the positive rates of CA215 for different cancers were shown to be 52% (lung), 74% (liver), 44% (colon), 61% (esophagus), 60% (stomach), 59% (ovary), 40% (prostate), 71% (breast), 38% (kidney), 41% (pancreas), 51% (cervix), and 83% (lymphoma), respectively. Other cancer markers including AFP, CEA, CA125, CA19-9, CA15-3, Cyfra21-1, Ferritin, beta(2) microglobulin and PSA were also parallelly compared. A combination of CA215 with other tissue-associated cancer markers generally resulted in much higher cancer detection rates. CA215 detected from cancer patients was confirmed to be human immunoglobulins that contain common RP215-specific carbohydrate-associated epitope. CONCLUSION: Through clinical evaluations of serum specimens of various cancer patients, CA215 was confirmed to be human cancer cell-derived immunoglobulins. CA215 is apparently comparable to or better than other known biomarkers for the positive detection and monitoring of many types of human cancers.
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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 | 0.000 | 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) | 0.000 | 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".