Direct Profiling of Cancer Biomarkers in Tumor Tissue Using a Multiplexed Nanostructured Microelectrode Integrated Circuit
Bibliographic record
Abstract
The analysis of panels of nucleic acid biomarkers offers valuable diagnostic and prognostic information for cancer management. A cost-effective, highly sensitive electronic chip would offer an ideal platform for clinical biomarker readout and would have maximal utility if it was (i) multiplexed, enabling on-chip assays of multiple biomarkers, and (ii) able to perform direct (PCR-free) readout of disease-related genes. Here we report a chip onto which we integrate novel nanostructured microelectrodes and with which we directly detect cancer biomarkers in heterogeneous biological samples-both cell extracts and tumor tissues. Coarse photolithographic microfabrication defines a multiplexed sensing array; bottom-up fabrication of nanostructured microelectrodes then provides sensing elements. We analyzed a panel of mRNA samples for prostate cancer related gene fusions using the chip. We accurately identified gene fusions that correlate with aggressive prostate cancer and distinguished these from fusions associated with slower-progressing forms of the disease. The multiplexed nanostructured microelectrode integrated circuit reported herein provides direct, amplification-free, sample-to-answer in under 1 h using the 10 ng of mRNA readily available in biopsy samples.
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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".