Sen Chen

Relapse of castration-resistant prostate cancer (CRPC) that occurs after androgen deprivation therapy of primary prostate cancer can be mediated by reactivation of the androgen receptor (AR). One important mechanism mediating this AR reactivation is intratumoral conversion of the weak adrenal androgens DHEA and androstenedione into the AR ligands testosterone and dihydrotestosterone. DHEA and androstenedione are synthesized by the adrenals through the sequential actions of the cytochrome P450 enzymes CYP11A1 and CYP17A1, so that CYP17A1 inhibitors such as abiraterone are effective therapies for CRPC. However, the significance of intratumoral CYP17A1 and de novo androgen synthesis from cholesterol in CRPC, and the mechanisms contributing to CYP17A1 inhibitor resistance/relapse, remain to be determined. We report that AR activity in castration-resistant VCaP tumor xenografts can be restored through CYP17A1-dependent de novo androgen synthesis, and that abiraterone treatment of these xenografts imposes selective pressure for increased intratumoral expression of CYP17A1, thereby generating a mechanism for development of resistance to CYP17A1 inhibitors. Supporting the clinical relevance of this mechanism, we found that intratumoral expression of CYP17A1 was markedly increased in tumor biopsies from CRPC patients after CYP17A1 inhibitor therapy. We further show that CRPC cells expressing a progesterone responsive T877A mutant AR are not CYP17A1 dependent, but that AR activity in these cells is still steroid dependent and mediated by upstream CYP11A1-dependent intraturmoral pregnenolone/progesterone synthesis. Together, our results indicate that CRPCs resistant to CYP17A1 inhibition may remain steroid dependent and therefore responsive to therapies that can further suppress de novo intratumoral steroid synthesis.

Fusion of the androgen receptor-regulated (AR-regulated) TMPRSS2 gene with ERG in prostate cancer (PCa) causes androgen-stimulated overexpression of ERG, an ETS transcription factor, but critical downstream effectors of ERG-mediating PCa development remain to be established. Expression of the SOX9 transcription factor correlated with TMPRSS2:ERG fusion in 3 independent PCa cohorts, and ERG-dependent expression of SOX9 was confirmed by RNAi in the fusion-positive VCaP cell line. SOX9 has been shown to mediate ductal morphogenesis in fetal prostate and maintain stem/progenitor cell pools in multiple adult tissues, and has also been linked to PCa and other cancers. SOX9 overexpression resulted in neoplasia in murine prostate and stimulated tumor invasion, similarly to ERG. Moreover, SOX9 depletion in VCaP cells markedly impaired invasion and growth in vitro and in vivo, establishing SOX9 as a critical downstream effector of ERG. Finally, we found that ERG regulated SOX9 indirectly by opening a cryptic AR-regulated enhancer in the SOX9 gene. Together, these results demonstrate that ERG redirects AR to a set of genes including SOX9 that are not normally androgen stimulated, and identify SOX9 as a critical downstream effector of ERG in TMPRSS2:ERG fusion-positive PCa.

Abstract Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100–400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70–90% and specificity~90–93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls ( p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.