Liquid biopsy‐based targeted gene screening highlights tumor cell subtypes in patients with advanced prostate cancer
Bibliographic record
Abstract
Prostate cancer (PCa) clinical heterogeneity underscores tumor heterogeneity, which may be best defined by cell subtypes. To test if cell subtypes contributing to progression can be assessed noninvasively, we investigated whether 14 genes representing luminal, neuroendocrine, and stem cells are detectable in whole blood RNA of patients with advanced PCa. For each gene, reverse transcription quantitative polymerase chain reaction assays were first validated using RNA from PCa cell lines, and their traceability in blood was assessed in cell spiking experiments. These were next tested in blood RNA of 40 advanced PCa cases and 40 healthy controls. Expression in controls, which was low or negative, was used to define stringent thresholds for gene overexpression in patients to account for normal variation in white blood cells. Thirty-five of 40 patients overexpressed at least one gene. Patients with more genes overexpressed had a higher risk of death (hazard ratio 1.42, range 1.12-1.77). Progression on androgen receptor inhibitors was associated with overexpression of stem (odds ratio [OR] 7.74, range 1.68-35.61) and neuroendocrine (OR 13.10, range 1.24-142.34) genes, while luminal genes were associated with taxanes (OR 2.7, range 1.07-6.82). Analyses in PCa transcriptomic datasets revealed that this gene panel was most prominent in metastases of advanced disease, with diversity among patients. Collectively, these findings support the contribution of the prostate cell subtypes to disease progression. Cell-subtype specific genes are traceable in blood RNA of patients with advanced PCa and are associated with clinically relevant end points. This opens the door to minimally invasive liquid biopsies for better management of this deadly disease.
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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 | 0.001 |
| 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".