Liquid biopsy: ready to guide therapy in advanced prostate cancer?
Bibliographic record
Abstract
The identification of molecular markers associated with response to specific therapy is a key step for the implementation of personalised treatment strategies in patients with metastatic prostate cancer. Only in a low proportion of patients biopsies of metastatic tissue are performed. Circulating tumour cells (CTC), cell-free DNA (cfDNA) and RNA offer the potential for non-invasive characterisation of disease and molecular stratification of patients. Furthermore, a 'liquid biopsy' approach permits longitudinal assessments, allowing sequential monitoring of response and progression and the potential to alter therapy based on observed molecular changes. In prostate cancer, CTC enumeration using the CellSearch© platform correlates with survival. Recent studies on the presence of androgen receptor (AR) variants in CTC have shown that such molecular characterisation of CTC provides a potential for identifying patients with resistance to agents that inhibit the androgen signalling axis, such as abiraterone and enzalutamide. New developments in CTC isolation, as well as in vitro and in vivo analysis of CTC will further promote the use of CTC as a tool for retrieving molecular information from advanced tumours in order to identify mechanisms of therapy resistance. In addition to CTC, nucleic acids such as RNA and cfDNA released by tumour cells into the peripheral blood contain important information on transcriptomic and genomic alterations in the tumours. Initial studies have shown that genomic alterations of the AR and other genes detected in CTC or cfDNA of patients with castration-resistant prostate cancer correlate with treatment outcomes to enzalutamide and abiraterone. Due to recent developments in high-throughput analysis techniques, it is likely that CTC, cfDNA and RNA will be an important component of personalised treatment strategies in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".