Profiling the proteoforms of urinary prostate-specific antigen by capillary electrophoresis – mass spectrometry
Bibliographic record
Abstract
Early detection of prostate cancer may lead to the overdiagnosis and overtreatment of patients as well as missing significant cancers. The current diagnostic approach uses elevated serum concentrations of prostate-specific antigen (PSA) as an indicator of risk. However, this test has been widely criticized as it shows poor specificity and sensitivity. In order to improve early detection and diagnosis, several studies have investigated whether different PSA proteoforms are correlated to prostate cancer. Until now, studies and methodologies for the comprehensive characterization of PSA proteoforms from biofluids are scarce. For this purpose, we developed an intact protein assay to analyze PSA by capillary electrophoresis-electrospray ionization-mass spectrometry after affinity purification from patients' urine. Here, we determined six proteolytic cleavage variants. In regard to glycosylation, tri-, di-, mono- and non-sialylated complex-type N-glycans were found on non-cleaved PSA, as well as the non-glycosylated variant. The performance of the intact protein assay was assessed using a pooled sample, obtaining an inter-day variability of 15%. Furthermore, urinary patient samples were analyzed by intact protein analysis and a bottom-up approach (glycopeptide analysis). This combined approach revealed complimentary information on both levels, demonstrating the benefit of using two orthogonal techniques to provide a thorough profile of urinary PSA. SIGNIFICANCE: The detection of clinically relevant prostate cancer requires a more specific and sensitive biomarker and, in this case, several PSA proteoforms may be able to aid or improve the current PSA test. However, a comprehensive analysis of the intact PSA proteoform profile is still lacking. This study investigated the PSA proteoforms present in urine and, in particular, determined the relative contribution of cleaved PSA and non-cleaved PSA forms to the total glycosylation profile. Importantly, intact protein analysis did not require further sample treatment before being measured by CE-ESI-MS. Furthermore, its glycosylation was also assessed in a bottom-up approach to provide complementary information. Overall, these results represent an important basis for future characterization and biomarker studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".