Multi-Omics Profiling Exposes a Metabolic Void in Prostate Cancer Models That Drives Precursor Dependence and Clinical Progression

Castration-resistant prostate cancer (CRPC) survives androgen deprivation, a mechanism widely attributed to autonomous de novo steroidogenesis. Despite the clinical deployment of CYP17A1 inhibitors, the metabolic fidelity of the models underpinning this "tumor-as-gonad" dogma remains controversial. Here, integrating high-resolution liquid chromatography-mass spectrometry with transcriptomics across diverse prostate cancer models, we demonstrate that malignant cell lines universally lack autonomous steroidogenic capacity due to the transcriptional silencing of CYP17A1. Instead, these models operate as high-efficiency precursor "converters" by upregulating HSD3B1 and AKR1C3. Clinical stratification of 844 Prostate Adenocarcinoma patients corroborated this precursor-dependent phenotype. We identify a critical divergence: AR-High tumors rely on oxidative phosphorylation, whereas the transition to an AR-Low state is marked by extensive lineage plasticity. Strikingly, a neuroendocrine plasticity score inversely correlates with AR flux and independently predicts clinical progression (HR=2.41, p=0.024). Our findings redefine CRPC metabolism, dictating a therapeutic shift toward targeting downstream precursor conversion and adaptive lineage plasticity.