Prognostic Value of Low-Pass Whole Genome Sequencing of Circulating Tumor DNA in Metastatic Castration-Resistant Prostate Cancer.

BACKGROUND: Multiple treatments are available for metastatic castration-resistant prostate cancer (mCRPC), including androgen receptor signaling inhibitors (ARSI) enzalutamide and abiraterone, but therapy resistance remains a major clinical obstacle. We examined the clinical utility of low-pass whole-genome sequencing (LPWGS) of circulating tumor DNA (ctDNA) for prognostication in mCRPC. METHODS: A total of 200 plasma samples from 143 mCRPC patients collected at the start of first-line ARSI treatment (baseline) and at treatment termination (n = 57, matched) were analyzed by LPWGS (median: 0.50X) to access ctDNA% and copy number alteration (CNA) patterns. The best confirmed prostate specific antigen (PSA) response (≥50% decline [PSA50]), PSA progression-free survival (PFS), and overall survival (OS) were used as endpoints. For external validation, we used plasma LPWGS data from an independent cohort of 70 mCRPC patients receiving first-line ARSI. RESULTS: Baseline ctDNA% ranged from ≤3.0% to 73% (median: 6.6%) and CNA burden from 0% to 82% (median: 13.1%) in the discovery cohort. High ctDNA% and high CNA burden at baseline was associated with poor PSA50 response (P = 0.0123/0.0081), poor PFS (P < 0.0001), and poor OS (P < 0.0001). ctDNA% and CNA burden was higher at PSA progression than at baseline in 32.7% and 42.3% of the patients. High ctDNA% and high CNA burden at baseline was also associated with poor PFS and OS (P ≤ 0.0272) in the validation cohort. CONCLUSIONS: LPWGS of ctDNA provides clinically relevant information about the tumor genome in mCRPC patients. Using LPWGS data, we show that high ctDNA% and CNA burden at baseline is associated with short PFS and OS in 2 independent cohorts.

Aberrant DOCK2, GRASP, HIF3A and PKFP Hypermethylation has Potential as a Prognostic Biomarker for Prostate Cancer.

Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types. We identified eight top candidate markers (cg12799885, DOCK2, FBXO30, GRASP, HIF3A, MOB3B, PFKP, and TPM4) that were specifically hypermethylated in PCa tissue samples and hypomethylated in other benign and malignant tissue types, including in peripheral blood cells. Potential as diagnostic and prognostic biomarkers was further assessed by the quantitative methylation specific PCR (qMSP) analysis of 37 nonmalignant and 197 PCa tissue samples from an independent population. Here, all eight hypermethylated candidates showed high sensitivity (75⁻94%) and specificity (84⁻100%) for PCa. Furthermore, DOCK2, GRASP, HIF3A and PKFP hypermethylation was significantly associated with biochemical recurrence (BCR) after radical prostatectomy (RP; 197 patients), independent of the routine clinicopathological variables. DOCK2 is the most promising single candidate marker (hazard ratio (HR) (95% confidence interval (CI)): 1.96 (1.24⁻3.10), adjusted p = 0.016; multivariate cox regression). Further validation studies are warranted and should investigate the potential value of these hypermethylation candidate markers for blood-based testing also.

Profiling of Circulating microRNAs in Prostate Cancer Reveals Diagnostic Biomarker Potential.

Early detection of prostate cancer (PC) is paramount as localized disease is generally curable, while metastatic PC is generally incurable. There is a need for improved, minimally invasive biomarkers as current diagnostic tools are inaccurate, leading to extensive overtreatment while still missing some clinically significant cancers. Consequently, we profiled the expression levels of 92 selected microRNAs by RT-qPCR in plasma samples from 753 patients, representing multiple stages of PC and non-cancer controls. First, we compared plasma miRNA levels in patients with benign prostatic hyperplasia (BPH) or localized prostate cancer (LPC), versus advanced prostate cancer (APC). We identified several dysregulated microRNAs with a large overlap of 59 up/down-regulated microRNAs between BPH versus APC and LPC versus APC. Besides identifying several novel PC-associated dysregulated microRNAs in plasma, we confirmed the previously reported upregulation of miR-375 and downregulation of miR-146a-5p. Next, by randomly splitting our dataset into a training and test set, we identified and successfully validated a novel four microRNA diagnostic ratio model, termed bCaP (miR-375*miR-33a-5p/miR-16-5p*miR-409-3p). Combined in a model with prostate specific antigen (PSA), digital rectal examination status, and age, bCaP predicted the outcomes of transrectal ultrasound (TRUS)-guided biopsies (negative vs. positive) with greater accuracy than PSA alone (Training: area under the curve (AUC), model = 0.84; AUC, PSA = 0.63. Test set: AUC, model = 0.67; AUC, PSA = 0.56). It may be possible in the future to use this simple and minimally invasive bCaP test in combination with existing clinical parameters for a more accurate selection of patients for prostate biopsy.