Purpose: The lack of biomarkers that can distinguish aggressive from indolent prostate cancer has caused substantial overtreatment of clinically insignificant disease. Here, by genome-wide DNA methylome profiling, we sought to identify new biomarkers to improve the accuracy of prostate cancer diagnosis and prognosis.Experimental design: Eight novel candidate markers, COL4A6, CYBA, TCAF1 (FAM115A), HLF, LINC01341 (LOC149134), LRRC4, PROM1, and RHCG, were selected from Illumina Infinium HumanMethylation450 BeadChip analysis of 21 tumor (T) and 21 non-malignant (NM) prostate specimens. Diagnostic potential was further investigated by methylation-specific qPCR analysis of 80 NM vs. 228 T tissue samples. Prognostic potential was assessed by Kaplan-Meier, uni- and multivariate Cox regression analysis in 203 Danish radical prostatectomy (RP) patients (cohort 1), and validated in an independent cohort of 286 RP patients from Switzerland and the U.S. (cohort 2).Results: Hypermethylation of the 8 candidates was highly cancer-specific (area under the curves: 0.79-1.00). Furthermore, high methylation of the 2-gene panel RHCG-TCAF1 was predictive of biochemical recurrence (BCR) in cohort 1, independent of the established clinicopathological parameters Gleason score, pathological tumor stage, and pre-operative PSA (HR (95% confidence interval (CI)): 2.09 (1.26 - 3.46); P = 0.004), and this was successfully validated in cohort 2 (HR (95% CI): 1.81 (1.05 - 3.12); P = 0.032).Conclusion: Methylation of the RHCG-TCAF1 panel adds significant independent prognostic value to established prognostic parameters for prostate cancer and thus may help to guide treatment decisions in the future. Further investigation in large independent cohorts is necessary before translation into clinical utility.
Prostate cancer (PC) diagnosis is based on histological evaluation of prostate needle biopsies, which have high false negative rates. Here, we investigated if cancer-associated epigenetic field effects in histologically normal prostate tissue may be used to increase sensitivity for PC. We focused on nine genes (AOX1, CCDC181 (C1orf114), GABRE, GAS6, HAPLN3, KLF8, MOB3B, SLC18A2, and GSTP1) known to be hypermethylated in PC. Using quantitative methylation-specific PCR, we analysed 66 malignant and 134 non-malignant tissue samples from 107 patients, who underwent ultrasound-guided prostate biopsy (67 patients had at least one cancer-positive biopsy, 40 had exclusively cancer-negative biopsies). Hypermethylation was detectable for all genes in malignant needle biopsy samples (AUC: 0.80 to 0.98), confirming previous findings in prostatectomy specimens. Furthermore, we identified a four-gene methylation signature (AOX1xGSTP1xHAPLN3xSLC18A2) that distinguished histologically non-malignant biopsies from patients with vs. without PC in other biopsies (AUC = 0.65; sensitivity = 30.8%; specificity = 100%). This signature was validated in an independent patient set (59 PC, 36 adjacent non-malignant, and 9 normal prostate tissue samples) analysed on Illumina 450 K methylation arrays (AUC = 0.70; sensitivity = 40.6%; specificity = 100%). Our results suggest that a novel four-gene signature may be used to increase sensitivity for PC diagnosis through detection of epigenetic field effects in histologically non-malignant prostate tissue samples.
Background The current inability to predict whether a primary prostate cancer (PC) will progress to metastatic disease leads to overtreatment of indolent PCs as well as undertreatment of aggressive PCs. Here, we explored the transcriptional changes associated with metastatic progression of multifocal hormone-naive PC. Methods Using total RNA-sequencing, we analysed laser micro-dissected primary PC foci ( n = 23), adjacent normal prostate tissue samples ( n = 23) and lymph node metastases ( n = 9) from ten hormone-naive PC patients. Genes important for PC progression were identified using differential gene expression and clustering analysis. From these, two multi-gene-based expression signatures (models) were developed, and their prognostic potential was evaluated using Cox-regression and Kaplan–Meier analyses in three independent radical prostatectomy (RP) cohorts (>650 patients). Results We identified several novel PC-associated transcripts deregulated during PC progression, and these transcripts were used to develop two novel gene-expression-based prognostic models. The models showed independent prognostic potential in three RP cohorts ( n = 405, n = 107 and n = 91), using biochemical recurrence after RP as the primary clinical endpoint. Conclusions We identified several transcripts deregulated during PC progression and developed two new prognostic models for PC risk stratification, each of which showed independent prognostic value beyond routine clinicopathological factors in three independent RP cohorts.
This project aims to develop new epigenetic biomarkers that can improve the accuracy of prostate cancer (PC) diagnosis and prognosis through a non/minimally-invasive molecular diagnostic test. Excessive use of prostate specific antigen (PSA) testing combined with the continued lack of accurate prognostic tools has led to overdiagnosis and overtreatment of many indolent prostate tumors. Hence, there is an urgent need for better PC biomarkers and for their translation into clinically useful tests. We have recently identified six novel genes that were hypermethylated in PC (C1orf114, HAPLN3, MOB3B, KLF8, GAS6, and AOX1) and, furthermore, developed and validated a three-gene DNA methylation signature that predicted time to PSA recurrence after radical prostatectomy (RP) in two large PC patient cohorts independently of clinicopathological parameters (Haldrup et al. 2013, J Clin Oncol). While our earlier work was based on analysis of post-operative tissue specimens, we now assess the feasibility of transferring these candidate markers to urine, plasma, or prostate needle biopsies. Using quantitative methylation-specific PCR (qMSP), we have determined the methylation level for each of the six candidate genes in histologically malignant vs. non-malignant prostate needle biopsies from a total of 49 patients referred to biopsy due to suspicion of PC. Ten random prostate biopsies were taken from each patient: 31 of the patients had PC in at least one biopsy, 18 patients had exclusively cancer-negative biopsies. For all six genes, the DNA methylation level was significantly higher in cancer-positive compared to cancer-negative biopsies (AUC: 0.95-1.00), confirming our previous results from RP specimens. Notably, for two of the genes (HAPLN3 and GAS6), we found a significantly (p<0.025) higher methylation level in histologically cancer-negative biopsies from patients with PC in at least one other biopsy compared to patients with exclusively cancer-negative biopsies, indicating the existence of a cancer field effect. A similar trend was observed for AOX1, but was not statistically significant (p=0.08) in this relatively small sample set. Detection of epigenetic field cancerization in histologically benign prostate needle biopsies may increase the sensitivity for PC detection and thereby predict the need for repeat biopsy in men with initial cancer-negative biopsies. We are currently investigating this further in a larger patient sample set. In addition, qMSP analyses of urine and plasma samples from patients with BPH, localized or advanced PC, respectively, are ongoing and the results will be presented at the conference. The development of novel and more accurate diagnostic and/or prognostic PC biomarkers, suitable for detection in non/minimally invasive samples, would be a major improvement to the clinical management of PC by allowing better and more personalized treatment strategies. Citation Format: Mia Moller, Christa Haldrup, Michael Borre, Soren Hoyer, Torben Orntoft, Karina D. Sorensen. Clinical utility of DNA methylation markers for prostate cancer detection and prognosis: Towards less-invasive molecular diagnostic tests. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1355. doi:10.1158/1538-7445.AM2014-1355
Prostate cancer (PC) is the fifth leading cause of cancer deaths among men worldwide and the second most common cancer form with an estimated 1.1 million diagnoses in 2012. Diagnosis is based on histological evaluation of needle biopsies by a trained pathologist. Despite the high number of diagnoses, PC is frequently missed in the initial set of biopsies. Thus, in more than 15% of patients with initial negative biopsies, PC is found in repeat biopsies. The aim of this project was to evaluate if DNA methylation-based cancer field effects can be detected in cancer-negative prostate biopsy samples for the nine genes HAPLN3, AOX1, GAS6, KLF8, MOB3B, CCDC181 (C1orf114), GABRE, SLC18A2, and GSTP1, and if this could be a potential novel diagnostic tool. Hypermethylation of these genes is known to be strongly associated with PC in prostatectomy specimens. First, we confirmed the presence of hypermethylation of all genes in malignant (n = 48) compared to non-malignant biopsy tissue samples (n = 40) using quantitative methylation specific PCR (pBonferroni≤0.00002 in Mann Whitney U test, AUC range 0.80-0.98 in ROC analysis). Next, non-malignant biopsy samples from men with (n = 39) or without (n = 40) cancer in other biopsies were compared. Here, the methylation status of no single gene showed a significant correlation to the presence of PC in other biopsies. However, PC is a heterogeneous disease and a panel of markers could lead to increased sensitivity for PC if each marker adds little but complementary information. Indeed, a 4-gene model (HAPLN3/GSTP1/AOX1/SLC18A2) was able to separate the 2 groups of non-malignant samples with an AUC of 0.65 in ROC analysis (PPV = 100%, NPV = 59.7%), indicating the existence of an epigenetic cancer field effect. In our sample set, this corresponds to 12 out of 39 samples that would be identified as originating from PC patients based on the molecular analysis although no signs of malignancy were identified by pathology. Finally, to investigate epigenetic field effects and heterogeneity on a genomewide scale, we have analyzed multiple cancer foci, adjacent non-malignant and distant non-malignant samples from radical prostatectomy specimens from each of 4 patients with multifocal PC using the Infinium HumanMethylation450 BeadChip (Illumina). The results will be presented at the conference. In summary, PC-specific hypermethylation of all nine genes was confirmed in diagnostic needle biopsies. Furthermore, DNA methylation based cancer field effects were detected for several of these genes, and a 4-gene model with potential to detect non-malignant samples from PC patients based on a DNA hypermethylation signature was identified. The results of our study suggest that detection of epigenetic field effects in cancer-negative prostate biopsy samples may be used to increase the sensitivity for PC detection. Citation Format: Mia Moller, Siri H. Strand, Christa Haldrup, Soren Hoyer, Michael Borre, Torben Orntoft, Karina D. Sorensen. Detection of prostate cancer associated DNA hypermethylation in diagnostic needle biopsies: Insight into field effects and heterogeneity. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3833. doi:10.1158/1538-7445.AM2015-3833
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.