Separation of kallikrein 6 glycoprotein subpopulations in biological fluids by anion‐exchange chromatography coupled to ELISA and identification by mass spectrometry
Bibliographic record
Abstract
Kallikrein 6 (KLK6) has been shown to be aberrantly glycosylated in ovarian cancer. Here, we report a novel HPLC anion exchange method, coupled to a KLK6-specific ELISA, capable of differentiating KLK6 glycoform subgroups in biological fluids. Biological fluids were fractionated using anion exchange and resulting fractions were analyzed for KLK6 content by ELISA producing a four-peak elution profile. Using this assay, the KLK6 elution profile and distribution across peaks of a set (n = 7) of ovarian cancer patient matched serum and ascites fluid samples was found to be different than the profile of serum and cerebrospinal fluid (CSF) of normal individuals (n = 7). Glycosylation patterns of recombinant KLK6 (rKLK6) were characterized using tandem mass spectrometry (MS/MS), and found to consist of a highly heterogeneous KLK6 population. This protein was found to contain all of the four diagnostic KLK6 peaks present in the previously assayed biological fluids. The rKLK6 glycoform composition of each peak was assessed by lectin affinity and MS/MS based glycopeptide quantification by product ion monitoring. The combined results showed an increase in terminal alpha 2-6 linked sialic acid in the N-glycans found on KLK6 from ovarian cancer serum and ascites, as opposed to CSF and serum of normal individuals.
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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 | 0.001 |
| 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) | 0.000 | 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".