Quantification of Human Kallikrein-Related Peptidases in Biological Fluids by Multiplatform Targeted Mass Spectrometry Assays
Bibliographic record
Abstract
Human kallikrein-related peptidases (KLKs) are a group of 15 secreted serine proteases encoded by the largest contiguous cluster of protease genes in the human genome. KLKs are involved in coordination of numerous physiological functions including regulation of blood pressure, neuronal plasticity, skin desquamation, and semen liquefaction, and thus represent promising diagnostic and therapeutic targets. Until now, quantification of KLKs in biological and clinical samples was accomplished by enzyme-linked immunosorbent assays (ELISA). Here, we developed multiplex targeted mass spectrometry assays for the simultaneous quantification of all 15 KLKs. Proteotypic peptides for each KLK were carefully selected based on experimental data and multiplexed in single assays. Performance of assays was evaluated using three different mass spectrometry platforms including triple quadrupole, quadrupole-ion trap, and quadrupole-orbitrap instruments. Heavy isotope-labeled synthetic peptides with a quantifying tag were used for absolute quantification of KLKs in sweat, cervico-vaginal fluid, seminal plasma, and blood serum, with limits of detection ranging from 5 to 500 ng/ml. Analytical performance of assays was evaluated by measuring endogenous KLKs in relevant biological fluids, and results were compared with selected ELISAs. The multiplex targeted proteomic assays were demonstrated to be accurate, reproducible, sensitive, and specific alternatives to antibody-based assays. Finally, KLK4, a highly prostate-specific protein and a speculated biomarker of prostate cancer, was unambiguously detected and quantified by immunoenrichment-SRM assay in seminal plasma and blood serum samples from individuals with confirmed prostate cancer and negative biopsy. Mass spectrometry revealed exclusively the presence of a secreted isoform and thus unequivocally resolved earlier disputes about KLK4 identity in seminal plasma. Measurements of KLK4 in either 41 seminal plasma or 58 blood serum samples revealed no statistically significant differences between patients with confirmed prostate cancer and negative biopsy. The presented multiplex targeted proteomic assays are an alternative analytical tool to study the biological and pathological roles of human KLKs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".