The Mutational Landscape of Metastatic Castration-sensitive Prostate Cancer: The Spectrum Theory Revisited
Bibliographic record
Abstract
BACKGROUND: Emerging data suggest that metastasis is a spectrum of disease burden rather than a binary state, and local therapies, such as radiation, might improve outcomes in oligometastasis. However, current definitions of oligometastasis are solely numerical. OBJECTIVE: To characterize the somatic mutational landscape across the disease spectrum of metastatic castration-sensitive prostate cancer (mCSPC) to elucidate a biological definition of oligometastatic CSPC. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective study of men with mCSPC who underwent clinical-grade sequencing of their tumors (269 primary tumor, 25 metastatic sites). Patients were classified as having biochemically recurrent (ie, micrometastatic), metachronous oligometastatic (≤5 lesions), metachronous polymetastatic (>5 lesions), or de novo metastatic (metastasis at diagnosis) disease. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We measured the frequency of driver mutations across metastatic classifications and the genomic associations with radiographic progression-free survival (rPFS) and time to castrate-resistant prostate cancer (CRPC). RESULTS AND LIMITATIONS: The frequency of driver mutations in TP53 (p = 0.01), WNT (p = 0.08), and cell cycle (p = 0.04) genes increased across the mCSPC spectrum. TP53 mutation was associated with shorter rPFS (26.7 vs 48.6 mo; p = 0.002), and time to CRPC (95.6 vs 155.8 mo; p = 0.02) in men with oligometastasis, and identified men with polymetastasis with better rPFS (TP53 wild-type, 42.7 mo; TP53 mutated, 18.5 mo; p = 0.01). Mutations in TP53 (incidence rate ratio [IRR] 1.45; p = 0.004) and DNA double-strand break repair (IRR 1.61; p < 0.001) were associated with a higher number of metastases. Mutations in TP53 were also independently associated with shorter rPFS (hazard ratio [HR] 1.59; p = 0.03) and the development of CRPC (HR 1.71; p = 0.01) on multivariable analysis. This study was limited by its retrospective nature, sample size, and the use of commercially available sequencing platforms, resulting in a limited predefined set of genes examined. CONCLUSIONS: Somatic mutational profiles reveal a spectrum of metastatic biology that helps in redefining oligometastasis beyond a simple binary state of lesion enumeration. PATIENT SUMMARY: Oligometastatic prostate cancer is typically defined as less than three to five metastatic lesions and evidence suggests that using radiation or surgery to treat these sites improves clinical outcomes. As of now, treatment decisions for oligometastasis are solely defined according to the number of lesions. However, this study suggests that tumor mutational profiles can provide a biological definition of oligometastasis and complement currently used numerical definitions.
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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) | 0.000 | 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".