Cancer Diagnostics via Ultrasensitive Multiplexed Detection of Parathyroid Hormone-Related Peptides with a Microfluidic Immunoarray
Bibliographic record
Abstract
Parathyroid hormone-related peptide (PTHrP) is recognized as the major causative agent of humoral hypercalcemia of malignancy (HHM). The paraneoplastic PTHrP has also been implicated in tumor progression and metastasis of many human cancers. Conventional PTHrP detection methods like immunoradiometric assay (IRMA) lack the sensitivity required to measure target peptide levels prior to the development of hypercalcemia. In general, sensitive, multiplexed peptide measurement by immunoassay represents challenges that we address in this paper. We describe here the first ultrasensitive multiplexed peptide assay to measure intact PTHrP 1-173 as well as circulating N-terminal and C-terminal peptide fragments. This versatile approach should apply to almost any collection of peptides that are long enough to present binding sites for two antibodies. To target PTHrP, we employed a microfluidic immunoarray featuring a chamber for online capture of the peptides from serum onto magnetic beads decorated with massive numbers of peptide-specific antibodies and enzyme labels. Magnetic bead-peptide conjugates were then washed and sent to a detection chamber housing an antibody-modified 8-electrode array fabricated by inkjet printing of gold nanoparticles. Limits of detection (LODs) of 150 aM (∼1000-fold lower than IRMA) in 5 μL of serum were achieved for simultaneous detection of PTHrP isoforms and peptide fragments in 30 min. Good correlation for patient samples was found with IRMA (n = 57); r(2) = 0.99 assaying PTHrP 1-86 equiv fragments. Analysis by a receiver operating characteristic (ROC) plot gave an area under the curve of 0.96, 80-83% clinical sensitivity, and 96-100% clinical specificity. Results suggest that PTHrP1-173 isoform and its short C-terminal fragments are the predominant circulating forms of PTHrP. This new ultrasensitive, multiplexed assay for PTHrP and fragments is promising for clinical diagnosis, prognosis, and therapeutic monitoring from early to advanced stage cancer patients and to examine underlying mechanisms of PTHrP overproduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".