Verification of CRISPR editing and finding transgenic inserts by Xdrop indirect sequence capture followed by short- and long-read sequencing.

Validation of CRISPR-Cas9 editing typically explores the immediate vicinity of the gene editing site and distal off-target sequences, which has led to the conclusion that CRISPR-Cas9 editing is very specific. However, an increasing number of studies suggest that on-target unintended editing events like deletions and insertions are relatively frequent but unfortunately often missed in the validation of CRISPR-Cas9 editing. The deletions may be several kilobases-long and only affect one allele. The gold standard in molecular validation of gene editing is direct sequencing of relatively short PCR amplicons. This approach allows the detection of small editing events but fails in detecting large rearrangements, in particular when only one allele is affected. Detection of large rearrangements requires that an extended region is analyzed and the characterization of events may benefit from long-read sequencing. Here we implemented Xdrop™, a new microfluidic technology that allows targeted enrichment of long regions (~100 kb) using just a single standard PCR primer set. Sequencing of the enriched CRISPR-Cas9 gene-edited region in four cell lines on long- and short-read sequencing platforms unravelled unknown and unintended genome editing events. The analysis revealed accidental kilobases-large insertions in three of the cell lines, which remained undetected using standard procedures. We also applied the targeted enrichment approach to identify the integration site of a transgene in a mouse line. The results demonstrate the potential of this technology in gene editing validation as well as in more classic transgenics.

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 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.

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.

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.

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.

Two approaches for estimating the lower limit of quantitation (LLOQ) of microRNA levels assayed as exploratory biomarkers by RT-qPCR.

BACKGROUND: Circulating microRNAs are undergoing exploratory use as safety biomarkers in drug development. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is one common approach used to quantitate levels of microRNAs in samples that includes the use of a standard curve of calibrators fit to a regression model. Guidelines are needed for setting assay quantitation thresholds that are appropriate for this method and to biomarker pre-validation. RESULTS: In this report, we develop two workflows for determining a lower limit of quantitation (LLOQ) for RT-qPCR assays of microRNAs in exploratory studies. One workflow is based on an error threshold calculated by a logistic model of the calibration curve data. The second workflow is based on a threshold set by the sample blank, which is the no template control for RT-qPCR. The two workflows are used to set lower thresholds of reportable microRNA levels for an example dataset in which miR-208a levels in biofluids are quantitated in a cardiac injury model. LLOQ thresholds set by either workflow are effective in filtering out microRNA values with large uncertainty estimates. CONCLUSIONS: Two workflows for LLOQ determinations are presented in this report that provide methods that are easy to implement in investigational studies of microRNA safety biomarkers and offer choices in levels of conservatism in setting lower limits of acceptable values that facilitate interpretation of results.

Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.

MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

Assessing sample and miRNA profile quality in serum and plasma or other biofluids.

MicroRNAs (miRNAs) constitute a class of small cellular RNAs (typically 21-23nt) that function as post-transcriptional regulators of gene expression. Current estimates indicate that more than one third of the cellular transcriptome is regulated by miRNAs, although they are relatively few in number (less than 2000 human miRNAs). The high relative stability of miRNA in common clinical tissues and biofluids (e.g. plasma, serum, urine, saliva, etc.) and the ability of miRNA expression profiles to accurately classify discrete tissue types and disease states have positioned miRNA quantification as a promising new tool for a wide range of diagnostic applications. Furthermore miRNAs have been shown to be rapidly released from tissues into the circulation with the development of pathology. To facilitate discovery and clinical development of miRNA-based biomarkers, we developed a genome-wide Locked Nucleic Acid (LNA™)-based miRNA qPCR platform with unparalleled sensitivity and robustness. The platform allows high-throughput profiling of miRNAs from important clinical sources without the need for pre-amplification. Using this system, we have profiled thousands of biofluid samples including blood derived plasma and serum. An extensive quality control (QC) system has been implemented in order to secure technical excellence and reveal any unwanted bias coming from pre-analytical or analytical variables. We present our approaches to sample and RNA QC as well as data QC and normalization. Specifically we have developed normal reference ranges for circulating miRNAs in serum and plasma as well as a hemolysis indicator based on microRNA expression.

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.

A genome-wide screen reveals microRNAs in peripheral sensory neurons driving painful diabetic neuropathy.

ABSTRACT: Diabetes is a leading cause of peripheral neuropathy (diabetic peripheral neuropathy, DPN), and uncontrolled long-lasting hyperglycemia leads to severe complications. A major proportion of diabetics develop excruciating pain with a variable course. Mechanisms leading to painful DPN are not completely understood and treatment options limited. We hypothesized that epigenetic modulation at the level of microRNA (miRNA) expression triggered by metabolic imbalance and nerve damage regulates the course of pain development. We used clinically relevant preclinical models, genome-wide screening, in silico analyses, cellular assays, miRNA fluorescent in situ hybridization, in vivo molecular manipulations, and behavioral analyses in the current study. We identified miRNAs and their targets that critically impact on nociceptive hypersensitivity in painful DPN. Our analyses identify miR-33 and miR-380 expressed in nociceptive neurons as critical denominators of diabetic pain and miR-124-1 as a mediator of physiological nociception. Our comprehensive analyses on the putative mRNA targets for miR-33 or miR-124-1 identified a set of mRNAs that are regulated after miR-33 or miR-124-1 overexpression in dorsal root ganglia in vivo. Our results shed light on the regulation of DPN pathophysiology and implicate specific miRNAs as novel therapeutic targets for treating painful DPN.

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.

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.

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.

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.

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.

Quantitative RT-PCR for MicroRNAs in Biofluids.

MicroRNAs in biofluids hold great promise as minimally invasive diagnostic biomarkers for a wide range of diseases and biological processes. One of the most sensitive technologies for detection and measuring expression levels of microRNA is quantitative RT-PCR. However, quantification of microRNA in biofluid samples is challenging in many ways. Biofluids contain low levels of RNA and high levels of inhibitors of enzymatic processes like reverse transcription and PCR. Furthermore, biofluids are susceptible to many preanalytical variables. Here we describe procedures developed to address these challenges, which include highly sensitive and accurate microRNA detection methods, combined with optimized protocols for sample handling and preparation, and extensive quality control (QC) procedures.

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.

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.