Validation of the four-miRNA biomarker panel MiCaP for prediction of long-term prostate cancer outcome.

Improved prostate cancer prognostic biomarkers are urgently needed. We previously identified the four-miRNA prognostic biomarker panel MiCaP ((miR-23a-3p × miR-10b-5p)/(miR-133a-3p × miR-374b-5p)) for prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). Here, we identified an optimal numerical cut-off for MiCaP dichotomisation using a training cohort of 475 RP patients and tested this in an independent cohort of 281 RP patients (PCA281). Kaplan-Meier, uni- and multivariate Cox regression analyses were conducted for multiple endpoints: BCR, metastatic-(mPC) and castration-resistant prostate cancer (CRPC), prostate cancer-specific (PCSS) and overall survival (OS). Functional effects of the four MiCaP miRNAs were assessed by overexpression and inhibition experiments in prostate cancer cell lines. We found the numerical value 5.709 optimal for MiCaP dichotomisation. This was independently validated in PCA281, where a high MiCaP score significantly [and independent of the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) score] predicted BCR, progression to mPC and CRPC, and PCSS, but not OS. Harrell's C-index increased upon addition of MiCaP to CAPRA-S for all endpoints. Inhibition of miR-23a-3p and miR-10b-5p, and overexpression of miR-133a-3p and miR-374b-5p significantly reduced cell survival. Our results may promote future implementation of a MiCaP-based test for improved prostate cancer risk stratification.

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.

Novel DNA methylation biomarkers show high sensitivity and specificity for blood-based detection of colorectal cancer-a clinical biomarker discovery and validation study.

BACKGROUND: Early detection plays an essential role to reduce colorectal cancer (CRC) mortality. While current screening methods suffer from poor compliance, liquid biopsy-based strategies for cancer detection is rapidly gaining promise. Here, we describe the development of TriMeth, a minimal-invasive blood-based test for detection of early-stage colorectal cancer. The test is based on assessment of three tumour-specific DNA methylation markers in circulating cell-free DNA. RESULTS: A thorough multi-step biomarker discovery study based on DNA methylation profiles of more than 5000 tumours and blood cell populations identified CRC-specific DNA methylation markers. The DNA methylation patterns of biomarker candidates were validated by bisulfite sequencing and methylation-specific droplet digital PCR in CRC tumour tissue and peripheral blood leucocytes. The three best performing markers were first applied to plasma from 113 primarily early-stage CRC patients and 87 age- and gender-matched colonoscopy-verified controls. Based on this, the test scoring algorithm was locked, and then TriMeth was validated in an independent cohort comprising 143 CRC patients and 91 controls. Three DNA methylation markers, C9orf50, KCNQ5, and CLIP4, were identified, each capable of discriminating plasma from colorectal cancer patients and healthy individuals (areas under the curve 0.86, 0.91, and 0.88). When combined in the TriMeth test, an average sensitivity of 85% (218/256) was observed (stage I: 80% (33/41), stage II: 85% (121/143), stage III: 89% (49/55), and stage IV: 88% (15/17)) at 99% (176/178) specificity in two independent plasma cohorts. CONCLUSION: TriMeth enables detection of early-stage colorectal cancer with high sensitivity and specificity. The reported results underline the potential utility of DNA methylation-based detection of circulating tumour DNA in the clinical management of colorectal cancer.

Elevated miR-615-3p Expression Predicts Adverse Clinical Outcome and Promotes Proliferation and Migration of Prostate Cancer Cells.

miR-615-3p has previously been described as up-regulated in prostate cancer (PC) tissue samples compared with nonmalignant controls; however, its prognostic potential and functional role in PC remain largely unknown. In this study, we investigated the clinical and biological relevance of miR-615-3p in PC. The expression of miR-615-3p was measured in PC tissue specimens from 239 men who underwent radical prostatectomy (RP), and it was investigated if miR-615-3p could predict postoperative biochemical recurrence (BCR). These findings were subsequently validated in three independent RP cohorts (n = 222, n = 273, and n = 387) and functional overexpression studies conducted in PC cells (PC3M). High miR-615-3p expression was significantly associated with BCR in four independent PC patient cohorts (P < 0.05, log-rank test). In addition, high miR-615-3p expression was a significant predictor of PC-specific survival in univariate (hazard ratio, 3.75; P < 0.001) and multivariate (hazard ratio, 2.66; P = 0.008) analysis after adjustment for the Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) nomogram in a merged RP cohort (n = 734). Moreover, overexpression of miR-615-3p in PC cells (PC3M) significantly increased cell viability, proliferation, apoptosis, and migration. Together, our results suggest that miR-615-3p is a significant predictor of postoperative BCR and PC-specific survival and has oncogenic functions in PC cells.

A novel combined miRNA and methylation marker panel (miMe) for prediction of prostate cancer outcome after radical prostatectomy.

Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top-candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training). Using GLMnet, we trained a novel multimarker model (miMe) comprising nine miRNAs and three methylation markers that predicted postoperative biochemical recurrence (BCR) independently of the established clinicopathological CAPRA-S nomogram in Cox multivariate regression analysis in Cohort 1 (HR [95% CI]: 1.53 [1.26-1.84], p < 0.001). This result was successfully validated in two independent RP cohorts (Cohort 2, n = 159: HR [95% CI]: 1.35 [1.06-1.73], p = 0.015. TCGA, n = 350: HR [95% CI]: 1.34 [1.01-1.77], p = 0.04). Notably, in CAPRA-S low-risk patients, a high miMe score was associated with >6 times higher risk of BCR, suggesting that miMe may help identify PC patients at high risk of progression despite favorable clinicopathological factors postsurgery. Finally, miMe was a significant predictor of cancer-specific survival (p = 0.019, log-rank test) in a merged analysis of 357 RP patients. In conclusion, we trained, tested and validated a novel 12-marker panel (miMe) that showed significant independent prognostic value in three RP cohorts. In the future, combining miMe score with existing clinical nomograms may improve PC risk stratification and thus help guide treatment decisions.

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.

A five-microRNA model (pCaP) for predicting prostate cancer aggressiveness using cell-free urine.

Improved biomarkers for prostate cancer (PC) risk stratification are urgently needed. Here, we aimed to develop a novel multimarker model for prediction of biochemical recurrence (BCR) after curatively intended radical prostatectomy (RP), based on minimally invasive sampling of blood and urine. We initially measured the levels of 45 selected miRNAs by RT-qPCR in exosome enriched cell-free urine samples collected prior to RP from 215 PC patients (Cohort 1, training). We trained a novel logistic regression model (pCaP), comprising five urine miRNAs (miR-151a-5p, miR-204-5p, miR-222-3p, miR-23b-3p and miR-331-3p) and serum prostate-specific antigen (PSA), which significantly predicted time to BCR in Cohort 1 (univariate Cox regression analysis: HR = 3.12, p < 0.001). Next, using the same exact numeric cutoff for dichotomization as trained in Cohort 1, we tested and successfully validated the prognostic potential of pCaP in two additional cohorts, including 199 (Cohort 2, HR = 2.24, p = 0.002) and 205 (Cohort 3, HR = 2.15, p = 0.004) RP patients, respectively. pCaP remained a significant predictor of BCR, also after adjustment for pathological T-stage, surgical margin status and Gleason grade group (p < 0.05 in multivariate Cox regression analysis: HR = 2.72, 1.94 and 1.83 for Cohorts 1, 2 and 3, respectively). Additionally, pCaP scores correlated positively with the established clinical risk stratification nomogram CAPRA in all three PC cohorts (Pearson's rho: 0.45, 0.39 and 0.44). Together, our results suggest that the minimally invasive pCaP model could potentially be used in the future to improve PC risk stratification and to guide more personalized treatment decisions. Further clinical validation studies are warranted.

Independent Validation of a Diagnostic Noninvasive 3-MicroRNA Ratio Model (uCaP) for Prostate Cancer in Cell-Free Urine.

BACKGROUND: Detection of prostate cancer (PC) based on serum prostate-specific antigen (PSA) testing leads to many unnecessary prostate biopsies, overdiagnosis, and overtreatment of clinically insignificant tumors. Thus, novel and more accurate molecular biomarkers are required. METHODS: Using reverse transcription quantitative PCR, we measured the concentrations of 45 preselected microRNAs (miRNAs) in extracellular vesicle-enriched cell-free urine samples from 4 independent patient cohorts from Spain and Denmark, including 758 patients with clinically localized PC, 289 noncancer controls with benign prostatic hyperplasia (BPH), and 233 patients undergoing initial transrectal ultrasound (TRUS)-guided prostate biopsy owing to PC suspicion (101 with benign and 132 with malignant outcome). Diagnostic potential was assessed by ROC and decision curve analysis. RESULTS: We identified and successfully validated 8 upregulated and 21 downregulated miRNAs in urine from PC patients. Furthermore, we validated a previously identified 3-miRNA diagnostic ratio model, uCaP (miR-222-3p*miR-24-3p/miR-30c-5p). High uCaP scores were distinctive of PC in urine samples from BPH vs PC patients in 3 independent cohorts [area under the curve (AUC) = 0.84, 0.71, 0.72]. Additionally, uCaP predicted TRUS biopsy results with greater accuracy than PSA (AUC uCaP = 0.644; AUC PSA = 0.527) for patients within the diagnostic gray zone (PSA ≤ 10 ng/mL). CONCLUSIONS: We successfully validated a urine-based diagnostic 3-miRNA signature for PC (uCaP) in 3 independent patient cohorts from 2 countries. In the future, the simple and noninvasive uCaP test may be used to help more accurately select patients for prostate biopsy. Prospective clinical validation is warranted.

Analysis of a gene panel for targeted sequencing of colorectal cancer samples.

Colorectal cancer (CRC) is a leading cause of death worldwide. Surgical intervention is a successful treatment for stage I patients, whereas other more advanced cases may require adjuvant chemotherapy. The selection of effective adjuvant treatments remains, however, challenging. Accurate patient stratification is necessary for the identification of the subset of patients likely responding to treatment, while sparing others from pernicious treatment. Targeted sequencing approaches may help in this regard, enabling rapid genetic investigation, and at the same time easily applicable in routine diagnosis. We propose a set of guidelines for the identification, including variant calling and filtering, of somatic mutations driving tumorigenesis in the absence of matched healthy tissue. We also discuss the inclusion criteria for the generation of our gene panel. Furthermore, we evaluate the prognostic impact of individual genes, using Cox regression models in the context of overall survival and disease-free survival. These analyses confirmed the role of commonly used biomarkers, and shed light on controversial genes such as CYP2C8. Applying those guidelines, we created a novel gene panel to investigate the onset and progression of CRC in 273 patients. Our comprehensive biomarker set includes 266 genes that may play a role in the progression through the different stages of the disease. Tracing the developmental state of the tumour, and its resistances, is instrumental in patient stratification and reliable decision making in precision clinical practice.

Diagnostic and Prognostic MicroRNA Biomarkers for Prostate Cancer in Cell-free Urine.

BACKGROUND: Widespread use of prostate-specific antigen (PSA) testing for prostate cancer (PC) detection has led to extensive overdiagnosis and overtreatment. Urine-based microRNA (miRNA) biomarkers could be useful in PC diagnosis and prognosis. OBJECTIVE: To train and validate urine-based microRNA (miRNA) biomarkers that may assist in PC diagnosis and prognosis. DESIGN, SETTING, AND PARTICIPANTS: We profiled the expression levels of 92 miRNAs via reverse transcriptase-poymerase chain reaction in cell-free urine samples from 29 patients with benign prostatic hyperplasia (BPH) and 215 patients with clinically localized PC (cohort 1). Our findings were validated in an independent cohort of 29 BPH patients and 220 patients with clinically localized PC (cohort 2). RESULTS AND LIMITATIONS: We identified and validated several deregulated miRNAs in urine samples from PC patients. In addition, we trained a novel diagnostic three-miRNA model (miR-222-3p*miR-24-3p/miR-30c-5p) that distinguished BPH and PC patients with an area under the curve (AUC) of 0.95 in cohort 1, and was successfully validated in cohort 2 (AUC 0.89). Furthermore, we trained a novel prognostic three-miRNA model (miR-125b-5p*let-7a-5p/miR-151-5p) that predicted time to biochemical recurrence after radical prostatectomy independently of routine clinicopathological parameters in cohort 1, and was successfully validated in cohort 2. CONCLUSIONS: Future clinical implementation of our novel diagnostic and prognostic three-miRNA signatures could help in primary diagnosis of PC and guide treatment decisions. Further validation studies are warranted. PATIENT SUMMARY: Using two large patient cohorts, we searched for novel prostate cancer biomarkers in urine. We found two new sets of microRNA biomarkers in urine that could accurately predict the presence of prostate cancer and the likelihood of recurrence after prostatectomy. Further studies are needed before an actual clinical test can be developed.

Exosomal cargo including microRNA regulates sensory neuron to macrophage communication after nerve trauma.

Following peripheral axon injury, dysregulation of non-coding microRNAs (miRs) occurs in dorsal root ganglia (DRG) sensory neurons. Here we show that DRG neuron cell bodies release extracellular vesicles, including exosomes containing miRs, upon activity. We demonstrate that miR-21-5p is released in the exosomal fraction of cultured DRG following capsaicin activation of TRPV1 receptors. Pure sensory neuron-derived exosomes released by capsaicin are readily phagocytosed by macrophages in which an increase in miR-21-5p expression promotes a pro-inflammatory phenotype. After nerve injury in mice, miR-21-5p is upregulated in DRG neurons and both intrathecal delivery of a miR-21-5p antagomir and conditional deletion of miR-21 in sensory neurons reduce neuropathic hypersensitivity as well as the extent of inflammatory macrophage recruitment in the DRG. We suggest that upregulation and release of miR-21 contribute to sensory neuron-macrophage communication after damage to the peripheral nerve.

Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer.

Purpose: We investigated whether detection of ctDNA after resection of colorectal cancer identifies the patients with the highest risk of relapse and, furthermore, whether longitudinal ctDNA analysis allows early detection of relapse and informs about response to intervention.Experimental Design: In this longitudinal cohort study, we used massively parallel sequencing to identify somatic mutations and used these as ctDNA markers to detect minimal residual disease and to monitor changes in tumor burden during a 3-year follow-up period.Results: A total of 45 patients and 371 plasma samples were included. Longitudinal samples from 27 patients revealed ctDNA postoperatively in all relapsing patients (n = 14), but not in any of the nonrelapsing patients. ctDNA detected relapse with an average lead time of 9.4 months compared with CT imaging. Of 21 patients treated for localized disease, six had ctDNA detected within 3 months after surgery. All six later relapsed compared with four of the remaining patients [HR, 37.7; 95% confidence interval (CI), 4.2-335.5; P < 0.001]. The ability of a 3-month ctDNA analysis to predict relapse was confirmed in 23 liver metastasis patients (HR 4.9; 95% CI, 1.5-15.7; P = 0.007). Changes in ctDNA levels induced by relapse intervention (n = 19) showed good agreement with changes in tumor volume (κ = 0.41; Spearman ρ = 0.4).Conclusions: Postoperative ctDNA detection provides evidence of residual disease and identifies patients at very high risk of relapse. Longitudinal surveillance enables early detection of relapse and informs about response to intervention. These observations have implications for the postoperative management of colorectal cancer patients. Clin Cancer Res; 23(18); 5437-45. ©2017 AACR.

Genome-Wide Comparison of Next-Generation Sequencing and qPCR Platforms for microRNA Profiling in Serum.

This study compares next-generation sequencing (NGS) technologies that have been optimized specifically for biofluid samples, with more established qPCR-based methods for profiling microRNAs in biofluids. The same patient serum samples were analyzed by NGS and qPCR, and differences in the serum microRNA profile between HBV and HCV infected patients were investigated. While there was overall good agreement between NGS and qPCR, there were some differences between the platforms, highlighting the importance of validation.

miRNA profiling of circulating EpCAM(+) extracellular vesicles: promising biomarkers of colorectal cancer.

Cancer cells secrete small membranous extracellular vesicles (EVs) into their microenvironment and circulation. These contain biomolecules, including proteins and microRNAs (miRNAs). Both circulating EVs and miRNAs have received much attention as biomarker candidates for non-invasive diagnostics. Here we describe a sensitive analytical method for isolation and subsequent miRNA profiling of epithelial-derived EVs from blood samples of patients with colorectal cancer (CRC). The epithelial-derived EVs were isolated by immunoaffinity-capture using the epithelial cell adhesion molecule (EpCAM) as marker. This approach mitigates some of the specificity issues observed in earlier studies of circulating miRNAs, in particular the negative influence of miRNAs released by erythrocytes, platelets and non-epithelial cells. By applying this method to 2 small-scale patient cohorts, we showed that blood plasma isolated from CRC patients prior to surgery contained elevated levels of 13 EpCAM(+)-EV miRNAs compared with healthy individuals. Upon surgical tumour removal, the plasma levels of 8 of these were reduced (miR-16-5p, miR-23a-3p, miR-23b-3p, miR-27a-3p, miR-27b-3p, miR-30b-5p, miR-30c-5p and miR-222-3p). These findings indicate that the miRNAs are of tumour origin and may have potential as non-invasive biomarkers for detection of CRC. This work describes a non-invasive blood-based method for sensitive detection of cancer with potential for clinical use in relation to diagnosis and screening. We used the method to study CRC; however, it is not restricted to this disease. It may in principle be used to study any cancer that release epithelial-derived EVs into circulation.

Novel diagnostic and prognostic classifiers for prostate cancer identified by genome-wide microRNA profiling.

PURPOSE: This study investigates the diagnostic and prognostic biomarker potential of miRNAs in prostate cancer (PC). RESULTS: We identified several new deregulated miRNAs between non-malignant (NM) and PC tissue samples and between more/less aggressive PC subgroups. We also developed and validated a novel 13-miRNA diagnostic classifier with high sensitivity and specificity for PC. Finally, we trained a new 3-miRNA prognostic classifier (miR-185-5p+miR-221-3p+miR-326) that predicted time to biochemical recurrence (BCR) independently of routine clinicopathological variables in a training radical prostatectomy (RP) cohort (n = 126) as well as in two independent validation cohorts (n = 110 and n = 99). EXPERIMENTAL DESIGN: After RT-qPCR-based profiling of 752 miRNAs in 13 NM and 134 PC tissue samples (cohort 1), we selected 93 top candidate diagnostic/prognostic miRNAs for validation in two independent patient sets (cohort 2: 19 NM and 138 PC; cohort 3: 28 NM and 113 PC samples). Diagnostic potential was assessed by ROC curve analysis and prognostic potential by Kaplan-Meier, uni- and multivariate Cox regression analyses. BCR after RP was used as endpoint. CONCLUSIONS: This is the first report of a miRNA signature with significant independent prognostic value demonstrated in three PC patient cohorts.

Profiling microRNAs by real-time PCR.

A variety of physiological processes are associated with changes in microRNA (miRNA) expression. Analysis of miRNA has been applied to study normal physiology as well as diseased states including cancer. One major challenge in miRNA research is to accurately and practically determine the expression level of miRNAs in various experimental systems. Many genome-wide miRNA expression profiling studies have relied on microarrays technology, and frequently differentially expressed miRNAs have subsequently been confirmed with real-time quantitative PCR studies. Here, we describe how different primer strategies for first-strand cDNA synthesis and PCR amplification can affect measurements of miRNA expression levels. Overcoming the small nature of miRNAs is a difficult task as the short sequence available does not allow for designing primers using standard PCR primer design guidelines. Finally, we demonstrate how to determine differentially expressed miRNAs using a locked nucleic acid-based real-time PCR approach.

Improved microRNA quantification in total RNA from clinical samples.

microRNAs are small regulatory RNAs that are currently emerging as new biomarkers for cancer and other diseases. In order for biomarkers to be useful in clinical settings, they should be accurately and reliably detected in clinical samples such as formalin fixed paraffin embedded (FFPE) sections and blood serum or plasma. These types of samples represent a challenge in terms of microRNA quantification. A newly developed method for microRNA qPCR using Locked Nucleic Acid (LNA)-enhanced primers enables accurate and reproducible quantification of microRNAs in scarce clinical samples. Here we show that LNA-based microRNA qPCR enables biomarker screening using very low amounts of total RNA from FFPE samples and the results are compared to microarray analysis data. We also present evidence that the addition of a small carrier RNA prior to total RNA extraction, improves microRNA quantification in blood plasma and laser capture microdissected (LCM) sections of FFPE samples.